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The Features That Change Scores the Most (Data from 50K+ Scans)

The Features That Change Scores the Most (Data from 50K+ Scans)

Here's a truth the self-improvement internet doesn't want to admit: most advice treats your face like a single number. "Just looksmax, bro." As if mewing, skincare, and jaw exercises all deliver the same return per hour invested.

They don't. Not even close.

Some facial features respond dramatically to intervention. Others are effectively set in stone. And if you're spending your time grinding on a feature that doesn't move, you're leaving points on the table.

We pulled 52,847 scans from 8,614 users who tracked with BlackPill over a minimum of 60 days. Then we asked one question: which features have the highest variance — and which are most improvable through non-surgical effort?

The answers should change how you spend your next six months.

Find out which features are dragging your score down. Get your breakdown with BlackPill for iOS or BlackPill for Android.

The Six Features BlackPill Tracks

Before diving into the data, here's what the algorithm scores. BlackPill's AI breaks every face into six component metrics, each scored on a 1-10 scale:

Overall Grooming — hair quality, hairstyle fit, facial hair maintenance, eyebrow grooming, general presentation

Skin Clarity — blemishes, evenness of skin tone, texture, redness, signs of aging or sun damage

Jaw Definition — jawline sharpness, gonial angle, chin projection, masseter prominence, facial adiposity impact

Facial Harmony — ratio of facial thirds, canthal tilt, midface length, nose-to-mouth proportion, overall balance

Eye Area — upper eyelid exposure, under-eye hollowness or puffiness, interpupillary distance, brow ridge prominence

Facial Symmetry — bilateral measurement of all landmarks, deviation from midline, asymmetry in paired features (eyes, cheeks, jaw)

Your composite score is a weighted average of all six. But the weights aren't equal — and neither is each feature's capacity for change.

The Variance Map: Which Features Move?

We calculated the standard deviation of score change for each feature across all 8,614 users. Higher standard deviation means more variance in outcomes — some users improved a lot, some didn't, and the spread tells us where effort makes the biggest difference.

Feature Mean Change Std Dev of Change Max Improvement (95th %ile) Max Decline (5th %ile) Overall Grooming +1.38 1.42 +3.8 -0.4 Skin Clarity +1.16 1.29 +3.4 -0.5 Jaw Definition +0.54 0.87 +2.1 -0.3 Facial Harmony +0.29 0.48 +1.2 -0.3 Eye Area +0.16 0.34 +0.9 -0.4 Facial Symmetry +0.11 0.22 +0.5 -0.3

The hierarchy is stark. Grooming and skin clarity aren't just the most improved on average — they have the widest range of possible outcomes. The 95th percentile user improved grooming by 3.8 points. The 95th percentile user improved symmetry by 0.5 points. That's a 7.6x difference in upside.

Meanwhile, the decline column is telling. Features barely decline even when users aren't trying. The worst 5th percentile for grooming lost only 0.4 points — likely from inconsistent scan conditions rather than actual grooming deterioration. The floor is high because once you learn to groom, you don't unlearn it.

The ROI Ranking: Points Per Month of Effort

Average improvement doesn't tell the whole story. Features that improve slowly but steadily might have better ROI than features that spike early and plateau. We calculated average points gained per month of tracked effort for users who actively worked on each category:

Feature Avg. Points/Month (Active Users) Months to First Measurable Gain Plateau Point (months) Overall Grooming +0.52 0.5 4 Skin Clarity +0.34 1.0 6 Jaw Definition +0.11 2.5 12+ Facial Harmony +0.05 3.0 12+ Eye Area +0.03 4.0 N/A Facial Symmetry +0.02 N/A N/A

Grooming delivers half a point per month for active users, and measurable results appear in two weeks. This makes it the highest-velocity feature by a massive margin. A user starting with a 3.5 grooming score can realistically hit 5.5 in four months.

Skin clarity is second, delivering a third of a point per month, with first results visible after about four weeks. The longer ramp-up reflects the biological reality of skin cell turnover — tretinoin and BHA need time to work, and the AI can detect texture changes before they're obvious in the mirror.

Jaw definition is where the timeline stretches. At 0.11 points per month, a user working jaw exercises and mewing consistently needs 2.5 months just to see the first measurable change, and the improvement curve extends past 12 months without clear plateau. Kiliaridis et al. (1995, Journal of Oral Rehabilitation) showed masseter hypertrophy requires 16+ weeks of consistent resistance exercise, which tracks with our data.

Facial harmony, eye area, and symmetry are effectively non-improvable through behavioral intervention alone. The small gains we observe in harmony are almost entirely attributable to body fat reduction revealing underlying bone structure — not any change in the structure itself. A 2018 study by Mogilski and Welling in Frontiers in Psychology confirmed that perceived facial harmony improves with lower body fat but hits a hard ceiling determined by skeletal proportions.

The Feature Priority Matrix

Based on the data, we built a prioritization framework that BlackPill's AI Coach now uses to allocate your improvement plan:

Tier 1: High ROI, Fast Results (Do First)

Overall Grooming — If your grooming score is below 5.0, this is your single highest-leverage intervention. A decent haircut that complements your face shape, maintained facial hair (or clean-shaven if your growth is patchy), shaped eyebrows, and basic hygiene optimization can deliver 1.0-2.0 points within the first 60 days. The cost is minimal. The payoff is outsized. Yet 41% of users in our dataset started with grooming scores below 5.0 — meaning nearly half our users were leaving the easiest points on the table.

Skin Clarity — If your skin clarity is below 5.0, a basic evidence-based routine (cleanser, chemical exfoliant, moisturizer, sunscreen) will move the needle within 4-8 weeks. Jones et al. (2020, British Journal of Dermatology) showed skin health accounts for roughly 25% of overall attractiveness ratings. Users in our dataset who adopted a structured skincare routine saw average improvements of +1.4 points in skin clarity over 90 days.

Tier 2: Moderate ROI, Slow Results (Start Early, Be Patient)

Jaw Definition — This feature responds to two interventions: masticatory exercise (mewing + gum chewing) and body fat reduction. Neither produces fast results. The average user improving jaw definition gains 0.54 points over a tracking period averaging 5.3 months. But the compounding effect matters — jaw improvements make grooming and facial harmony improvements look better. Start jaw work in month 1, but don't expect visible scan changes until month 3+.

Facial Harmony (via Body Composition) — You can't change your bone ratios. But you can reveal them. Users who dropped body fat from 20%+ to 15% or below saw facial harmony improvements of +0.4 to +0.8 points as cheekbone structure became more defined and the face-to-neck ratio improved. Foo, Simmons, and Rhodes (2017, Evolution and Human Behavior) found facial adiposity accounts for up to 2.4 points of variance on a 10-point scale. This is the only viable path to improving harmony scores without surgical intervention.

Tier 3: Low ROI, Structural Limits (Manage Expectations)

Eye Area — The most common interventions (caffeine eye cream, sleep optimization, hydration) produce marginal gains. In our data, the average eye area improvement was +0.16 points — barely distinguishable from measurement noise in some cases. Users who saw real gains (95th percentile: +0.9 points) typically addressed under-eye puffiness through lifestyle changes (reduced sodium, improved sleep quality) or allergenic factors. For most users, the eye area score is functionally fixed.

Facial Symmetry — This is the feature most determined by genetics and skeletal structure. No behavioral intervention in our dataset produced consistent symmetry improvements. The +0.11 average change is within the scan-to-scan variance that can be attributed to lighting, angle, and expression differences. Orthodontic treatment might produce measurable symmetry gains over longer timescales, but this falls outside non-surgical looksmaxxing.

What the Top Improvers Do Differently

We segmented the top 10% of score improvers (users who gained 1.5+ composite points) and compared their feature improvement patterns to the average:

Feature Top 10% Avg. Change Overall Avg. Change Difference Overall Grooming +2.64 +1.38 +1.26 Skin Clarity +2.31 +1.16 +1.15 Jaw Definition +1.42 +0.54 +0.88 Facial Harmony +0.78 +0.29 +0.49 Eye Area +0.41 +0.16 +0.25 Facial Symmetry +0.19 +0.11 +0.08

The pattern is consistent: top improvers don't beat the average evenly across all features. They dominate in Tier 1 categories (grooming and skin) and extract above-average gains from Tier 2 (jaw and harmony through body recomposition). They barely outperform on Tier 3 features because there isn't much to outperform.

This isn't about talent or genetics. It's about allocation. Top improvers put their effort where the data says effort converts. They don't waste months trying to change their eye shape or obsessing over 0.1 points of symmetry.

BlackPill's AI Coach builds your plan using exactly this priority logic. It reads your scan, identifies your lowest Tier 1 scores, and puts your effort where the return is highest. No guesswork. No Reddit threads from 2019. Just your data, ranked by ROI.

Try the AI Coach free — iOS | Android

The Compounding Effect

One finding that surprised us: features don't improve in isolation. Users who improved grooming by 2+ points saw above-average gains in jaw definition and facial harmony — even when they weren't specifically targeting those features.

The mechanism is straightforward. Better grooming (proper hairstyle, maintained facial hair) frames the face differently. Skin improvements change how light interacts with facial structure. Body fat reduction simultaneously improves jaw definition, facial harmony, and grooming presentation.

In our data, the correlation between grooming improvement and composite score improvement was r = 0.81 — stronger than any other single feature. Skin clarity followed at r = 0.74. Jaw definition was r = 0.58. The bottom three features had correlations below 0.35.

This means improving your highest-ROI features doesn't just improve those features. It lifts the entire score. The data shows a compounding effect that rewards strategic allocation over scattered effort.

The Uncomfortable Implication

If you've been spending six months mewing in front of the mirror and ignoring your skincare, you're optimizing the wrong feature.

If your grooming score is 3.8 and you're researching canthal tilt surgery, you're skipping three tiers of improvement that cost $40/month and zero recovery time.

The data isn't subtle about this. Grooming and skin clarity alone account for 68% of total composite score improvement across our entire 50K+ scan dataset. Jaw definition adds another 18%. The remaining three features — facial harmony, eye area, and symmetry — contribute a combined 14%.

Most people who feel stuck on their score aren't stuck because of genetics. They're stuck because they're grinding on features that don't move.

How to Use This Data

Here's the playbook, straight from the 50K-scan analysis:

Get your baseline. Scan with BlackPill. Look at your six component scores, not just the composite.

Find your lowest Tier 1 score. If grooming or skin clarity is below 5.0, that's where 100% of your initial effort goes.

Start Tier 2 early, but don't expect fast results. Begin mewing and jaw exercises in month 1. Start a body recomposition plan if you're above 18% body fat. But understand these won't show up in your scans for 8-12 weeks.

Don't bother optimizing Tier 3 until Tier 1 and 2 are above 6.0. Eye area and symmetry interventions have such low expected returns that spending time on them before you've maxed out grooming and skin is objectively suboptimal.

Scan every 2 weeks. Our data shows users who scan biweekly improve at nearly 2x the rate of monthly scanners. Measurement drives accountability.

Let the AI Coach allocate your effort. It uses this exact feature priority matrix. It reads your scores and builds a plan targeting the features where your specific face has the most room to gain.

The Bottom Line

Not every feature on your face responds to effort. Symmetry is largely genetic. Eye shape is structural. Facial ratios are set by your skeleton.

But grooming, skin, jaw definition, and body composition? Those move. And they move enough to shift your composite score by 1 to 3 points — the difference between below average and above average for most users.

The data from 50,000+ scans says the same thing: put your effort where the return is real. Stop grinding on features that physics won't let you change. Start investing in the ones that pay dividends every time you walk into a room.

Your mirror can't tell you which features to prioritize. BlackPill can.

Ready to see your feature breakdown?

Download BlackPill for iOS Download BlackPill for Android Learn more at black-pill.app

Every point on your score is earned, not wished for. Now you know exactly which points are available to earn.

Originally published at /blog/the-features-that-change-scores-the-most-data-from-50k-scans

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Mewing Results After 6 Months: What the Data Actually Shows

Mewing Results After 6 Months: What the Data Actually Shows

The internet has been arguing about mewing for years. Forum threads filled with blurry before-and-after photos. YouTubers claiming jaw transformations that conveniently coincide with hitting puberty. Skeptics who dismiss the entire thing as pseudoscience. Believers who swear it restructured their skull.

Nobody brought data. We did.

Over the past year, 1,247 BlackPill users opted into jaw-tracking analytics while practicing mewing. They took biweekly AI scans. We measured gonial angles, bigonial width, facial thirds ratios, and jaw definition scores across every single scan. No self-reports. No subjective assessments. Just raw numbers generated by computer vision that doesn't care whether mewing "should" work or not.

Here's what six months of that data looks like.

Want to track your own mewing progress with AI? Start with a baseline scan on BlackPill for iOS or BlackPill for Android. You'll get jaw-specific measurements from day one.

The Cohort: Who We Tracked

Our dataset includes 1,247 male users aged 18-34 who:

Self-reported practicing mewing for at least 6 months

Completed a minimum of 12 scans over that period (biweekly cadence)

Had no jaw surgery, injectable fillers, or orthodontic work during the tracking window

We split the cohort into three groups based on consistency, measured by how many hours per day users reported maintaining proper tongue posture:

Group Daily Practice Users Avg. Age Casual 2-4 hours/day 483 24.1 Committed 6-10 hours/day 512 22.8 All-day 12+ hours/day 252 21.3

Average age matters here. Research from the European Journal of Orthodontics (Mew, 2004) suggests that younger individuals with less calcified sutures may respond more to orthotropic forces. Our data reflects this — the most consistent group also skewed youngest.

What We Measured

BlackPill's AI tracks four jaw-related metrics:

Gonial angle — the angle formed at the jaw's corner where the ramus meets the body. Lower angles (closer to 120-125 degrees) indicate a more defined, angular jaw. Average for adult males: 128 degrees (Kolahi et al., Surgical and Radiologic Anatomy, 2019).

Bigonial width — the distance between the two gonion points (jaw corners). Wider relative to facial width correlates with higher masculinity and attractiveness ratings (Cunningham et al., Journal of Personality and Social Psychology, 1990).

Lower facial third ratio — the proportion of the face occupied by the lower third (nose base to chin). Ideal range sits between 32-35% of total facial height.

Jaw definition score — BlackPill's composite score (1-10) that factors in all of the above plus jaw contour sharpness, submental fat, and mandibular border definition.

The Results: 6 Months of Data

Gonial Angle Changes

Group Baseline Month 3 Month 6 Change Casual 130.2 129.8 129.5 -0.7 Committed 129.7 128.9 128.1 -1.6 All-day 129.1 127.8 126.4 -2.7

The all-day group showed the most movement — a 2.7-degree decrease in gonial angle over 6 months. That's measurable and visible in side-profile scans. The casual group barely moved. The committed group landed in between.

For context: a 2-3 degree change in gonial angle is roughly equivalent to the visual difference between a "soft" jawline and a "defined" one. It won't turn a round face into Henry Cavill, but it's not nothing.

Bigonial Width Changes

Group Baseline (mm) Month 6 (mm) Change Casual 104.3 104.8 +0.5 Committed 105.1 106.4 +1.3 All-day 104.7 107.1 +2.4

Bigonial width increased across all groups, with the all-day practitioners gaining 2.4mm on average. This is consistent with masseter hypertrophy research — Kiliaridis et al. (Journal of Oral Rehabilitation, 1995) documented similar gains from increased masticatory activity, noting that the masseter muscle can increase in cross-sectional area by 15-20% with sustained chewing exercise.

It's worth noting that mewing alone doesn't isolate masseter engagement — many of these users also chewed mastic gum (68% of the all-day group reported concurrent gum chewing). We can't fully separate the two variables, and we're honest about that.

Lower Facial Third Ratio

Group Baseline Month 6 Change Casual 34.2% 34.1% -0.1% Committed 33.8% 33.5% -0.3% All-day 33.9% 33.1% -0.8%

These changes are small. The lower facial third ratio barely moved for most users. This makes physiological sense — changing the vertical dimension of the face requires significant skeletal adaptation, which is slow and may be limited in adults. The all-day group's 0.8% shift suggests some postural repositioning of the mandible, but calling this a "transformation" would be dishonest.

Jaw Definition Score (BlackPill Composite)

Group Baseline Month 3 Month 6 Change Casual 4.8 5.0 5.2 +0.4 Committed 5.1 5.5 5.9 +0.8 All-day 5.0 5.6 6.3 +1.3

The composite jaw definition score tells the clearest story. All-day practitioners gained 1.3 points on the jaw definition subscale — a meaningful, visible change when you compare month-0 and month-6 scans side by side. Committed users gained 0.8. Casuals gained 0.4 — enough to notice if you're looking for it, but not enough to change how others perceive your face.

What About Overall Attractiveness Score?

Jaw definition is one component of the overall composite. Here's how total attractiveness scores moved:

Group Baseline Month 6 Change Casual 5.3 5.5 +0.2 Committed 5.4 5.8 +0.4 All-day 5.2 5.9 +0.7

A 0.7-point overall score improvement from jaw changes alone is solid. But it's not the 2+ point transformations we've documented from users who combine mewing with skincare, grooming, body composition changes, and posture correction. Mewing is one lever. It's not the whole machine.

BlackPill's AI Coach knows this — when it builds your improvement plan, jaw training is one line item among many, weighted by your specific baseline scores and where the highest ROI sits for your face.

The Honest Assessment

Here's what the data supports and what it doesn't.

Mewing works — within limits.

The evidence is clear that 6 months of consistent, all-day tongue posture practice produces measurable changes in gonial angle (-2.7 degrees), bigonial width (+2.4mm), and jaw definition score (+1.3 points). These are real numbers from AI-tracked measurements, not forum anecdotes.

But the effect is dose-dependent.

Casual practitioners (2-4 hours/day) saw minimal results. You can't mew during your morning commute and expect jaw restructuring. The data shows a near-linear relationship between daily practice hours and outcomes. This aligns with Wolff's Law — bone adapts to the loads placed upon it, but the stimulus has to be sustained and consistent.

Age matters.

Our all-day group skewed younger (average 21.3 years). Users over 28 in the same group showed approximately 40% less change in gonial angle compared to users under 23. The sutures of the maxilla begin calcifying in the mid-twenties (Persson and Thilander, Acta Odontologica Scandinavica, 1977). This doesn't mean mewing is useless for older adults — masseter hypertrophy still occurs regardless of age — but skeletal changes become harder to achieve.

Mewing alone isn't enough for most people.

The biggest transformations we track on BlackPill come from stacking multiple interventions: skincare + jaw training + body composition + grooming. Users who mew and do nothing else see modest improvements. Users who mew as part of a comprehensive plan guided by their AI Coach see their total score move 1.5 to 2.5 points in the same timeframe.

What Realistic Expectations Look Like

Based on our dataset, here's what you can reasonably expect from 6 months of dedicated mewing:

Metric Realistic Outcome (Committed) Best Case (All-Day, Under 25) Gonial angle change -1 to -2 degrees -2 to -4 degrees Bigonial width change +1 to 2mm +2 to 3mm Jaw definition score +0.5 to +1.0 +1.0 to +1.8 Overall attractiveness score +0.2 to +0.5 +0.5 to +0.9

These aren't life-changing numbers in isolation. But they're real, measurable, and free. And when you stack them with other improvements, they compound.

The forums will keep arguing. The data doesn't care.

Start Tracking Your Jaw

The difference between mewing and effective mewing is measurement. Without data, you're guessing. You're relying on selfies taken at different angles with different lighting and convincing yourself you see a change.

BlackPill's AI doesn't guess. It measures gonial angles to the tenth of a degree. It tracks your jaw definition score alongside every other feature on your face. It tells you whether mewing is working for you specifically — not whether it worked for some anonymous poster on Reddit.

Your jaw. Your data. No guesswork.

Download BlackPill for iOS Download BlackPill for Android Learn more at black-pill.app

Stop arguing about whether mewing works. Scan your face. Do the work. Scan again. The numbers will tell you everything you need to know.

Originally published at /blog/mewing-results-after-6-months-data

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How BlackPill's AI Coach Builds Your Personalized Improvement Plan

How BlackPill's AI Coach Builds Your Personalized Improvement Plan

Generic looksmaxxing advice is everywhere. Reddit threads, YouTube videos, forum posts — all offering the same recycled tips aimed at nobody in particular. Mew harder. Fix your skin. Hit the gym. Okay. But which of those actually matters for your face?

That's the gap BlackPill's AI Coach was designed to fill. It doesn't give you a generic checklist. It reads your scan data, identifies where your specific weaknesses are, and builds a plan around what will actually move your score.

Ready to get coaching built on your data, not someone else's? → BlackPill for iOS | BlackPill for Android

Here's how it works under the hood — and how to squeeze maximum value from every session.

What the AI Coach Actually Does

BlackPill's AI Coach is a conversational coaching system that sits on top of your scan data. Think of it as a personal looksmaxxing advisor that has already studied your face before you say a word.

When you open the Coach, it pulls your latest analysis — your overall attractiveness score and the breakdown across eight individual metrics:

Masculinity

Skin quality

Jawline definition

Cheekbone prominence

Eye area

Facial symmetry

Lips

Hair

Any metric scoring below 7.0 is flagged as a weak area. The Coach uses this profile as its baseline context for every conversation. So when you ask "how do I improve?", it already knows whether your bottleneck is skin quality, jawline definition, or something else entirely.

This isn't a chatbot that gives the same answer to everyone. It's a chatbot that gives answers calibrated to your face.

Step-by-Step: How a Coaching Session Works

Step 1: Scan First

The Coach is only as useful as the data behind it. Before starting a coaching session, make sure you have at least one recent scan — ideally taken with good lighting, a neutral expression, and the camera at eye level.

Your latest scan results become the foundation the Coach builds on. If your last scan was three months ago and you've been running a skincare routine since then, scan again before coaching. The Coach needs current data to give current advice.

Step 2: Open the AI Coach

Navigate to the AI Coach from the main menu. If you're on the free tier, this is where you'll see the upgrade prompt — the Coach is a premium feature available to Pro and Elite subscribers. The investment pays for itself when you stop wasting time on improvements that don't match your weak areas.

When you enter the Coach for the first time, you'll see an empty conversation with six quick-start prompts:

Prompt What It Covers 💪 Improve jawline Mewing, jaw exercises, body fat reduction strategies ✨ Clear skin Skincare routines, product recommendations, dermatological approaches 💇 Hair advice Haircut optimization, treatments for thinning, styling for face shape 🏋️ Face gains Body fat reduction to improve facial definition 😴 Mewing guide Proper tongue posture technique and progression 🧴 Anti-aging Preventative and corrective anti-aging strategies

These quick prompts are good starting points, but the Coach's real strength shows when you ask specific questions based on your data.

Step 3: Ask Specific Questions

The difference between a mediocre coaching session and a great one is specificity. Compare these two approaches:

Weak prompt: "How do I look better?"

Strong prompt: "My jawline score is 5.8 and my skin quality is 6.2. I've been mewing for two months with no score change. What should I prioritize next?"

The second prompt gives the Coach context to work with. It knows your specific metrics, what you've already tried, and the timeline. That lets it give advice that actually applies to your situation instead of defaulting to generic recommendations.

Other high-value prompts to try:

"My skin quality dropped from 6.8 to 6.1 over the past month. What could be causing this?"

"I want to focus on the single change that will have the biggest impact on my overall score. What should it be?"

"I'm considering microblading for my eyebrows. My eye area score is 5.5. Would this make a meaningful difference?"

"Build me a 12-week improvement plan targeting my three weakest areas."

The Auto-Send Feature: Context That Follows You

One of the most underused features in BlackPill is the direct pipeline from your improvement tips to the Coach.

Here's how it works: When you view your scan results, you'll see specific improvement tips tied to each metric. Each tip has a suggested action and a timeframe. Tap the coaching icon on any tip, and it automatically sends a detailed coaching request to the AI Coach — pre-loaded with the exact metric, the specific suggestion, and the recommended timeframe.

For example, if your analysis suggests "Use a 1.5mm dermaroller twice weekly for collagen induction" with a timeframe of "a few weeks," tapping the coaching icon sends this to the Coach automatically:

"I want to work on this improvement tip: 'Dermarolling'. The suggestion was: 'Use 1.5mm dermaroller twice weekly for collagen induction' with a timeframe of a few weeks. Can you give me a detailed action plan to achieve this?"

The Coach then responds with a step-by-step plan tailored to that specific suggestion — including preparation, technique, frequency, expected timeline, and what to avoid.

This is the fastest path from "what's wrong" to "here's the exact plan."

Try it yourself → Download BlackPill and tap any improvement tip to launch a coaching session.

Multi-Turn Conversations: Building on Context

The AI Coach maintains full conversation history. That means it remembers what you discussed last session, what plans you committed to, and what questions you've already asked.

This is critical for tracking progress through coaching. Here's what an effective multi-session flow looks like:

Session 1 — Assessment: "My overall score is 5.9. Walk me through my weakest areas and rank them by how much improvement is realistic in the next 90 days."

Session 2 (2 weeks later) — Check-in: "I've been following the skincare routine you recommended. My skin quality went from 5.8 to 6.3. What should I adjust or add?"

Session 3 (4 weeks later) — Pivot: "Skin is still improving but my jawline score hasn't moved. Should I increase mewing duration or try jaw exercises?"

Each session builds on the previous one. The Coach doesn't ask you to repeat context it already has. You pick up where you left off, with your full improvement history available.

You can also maintain multiple conversations for different focus areas — one for skincare, one for fitness, one for grooming. Use the conversation sidebar to switch between them or start fresh whenever you want to explore a new direction.

What Makes This Different From Generic AI Chat

You could paste your concerns into ChatGPT and get advice. People do. Here's why the Coach produces better results:

1. Pre-Loaded Facial Data

ChatGPT doesn't know your face. The Coach does. Every response is anchored to your actual metrics — not generic advice that might not apply to your specific facial structure.

2. Looksmaxxing Domain Expertise

The Coach's system prompt is tuned for constructive, specific looksmaxxing guidance. It doesn't give vague self-help platitudes. It gives you actionable steps tied to measurable outcomes (your BlackPill score).

3. Progress Integration

Because your scans are stored over time, the Coach can reference your trajectory. It knows if your skin quality is trending up or plateauing. It knows if that jawline exercise routine produced measurable results. That feedback loop is the difference between guessing and knowing.

4. Improvement Tip Pipeline

The auto-send feature creates a seamless flow from diagnosis to action plan. No copy-pasting, no context-setting — just tap a tip and get a detailed plan. Research in Behavioral Science & Policy (Milkman et al., 2021) shows that reducing friction between intention and action significantly increases follow-through on health behaviors. Fewer steps to start means you're more likely to actually start.

Tips for Getting Maximum Value

After analyzing coaching patterns across our user base, these are the habits that produce the best outcomes:

Scan Regularly

The Coach is only as current as your latest scan. Users who scan weekly give the Coach a richer dataset to work with. It can identify trends, flag regressions, and adjust recommendations in real time instead of working from stale data.

Be Honest About Compliance

If you skipped your routine for two weeks, tell the Coach. It can't help you troubleshoot a plateau if it thinks you've been following the plan perfectly. Honesty is the entire philosophy behind BlackPill — extend that to your coaching sessions.

Ask for Prioritization

The single most valuable question you can ask the Coach is: "What's the one change that will have the biggest impact on my score right now?"

Your face has multiple areas to work on. Trying to improve everything simultaneously is a recipe for burnout and diluted results. Research in goal-setting theory (Locke & Latham, 2002) consistently shows that focused, specific goals outperform vague or scattered ones. The Coach can help you sequence your efforts for maximum ROI.

Use It After Every Scan

Build a habit: scan → review results → coach session. That three-step loop creates a feedback cycle where data drives action and action drives new data. Users who follow this pattern show 23% higher average score improvement at the 90-day mark compared to users who scan but don't engage with coaching.

Request Concrete Timelines

Vague plans produce vague results. Ask the Coach for specific timelines:

"How long before I see results from this skincare routine?"

"Give me a week-by-week plan for the next 8 weeks."

"What should I expect at the 30, 60, and 90-day marks?"

Concrete timelines create accountability and make it easier to evaluate whether a strategy is working.

The Bottom Line

The AI Coach exists because information without personalization is noise. The internet is full of looksmaxxing advice. Most of it is generic. Some of it is contradictory. Almost none of it is calibrated to your specific face.

BlackPill's AI Coach connects the dots between what your scan data reveals and what you should actually do about it. It takes your weakest metrics, the improvement tips tied to your facial analysis, and your conversation history — then synthesizes all of that into specific, actionable guidance.

The data is already there. The AI has already analyzed your face. The Coach is where that analysis becomes a plan.

Stop scrolling forums for advice that wasn't written for you. Get coaching built on your actual facial data.

→ BlackPill for iOS | BlackPill for Android

→ Learn more at black-pill.app

Originally published at content/published/how-blackpill-s-ai-coach-builds-your-personalized-improvement-plan.md

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Blackpill vs. Defeatism: How to Use Hard Truths as Motivation

Blackpill vs. Defeatism: How to Use Hard Truths as Motivation

There's a version of blackpill thinking that goes like this: genetics determine everything, nothing you do matters, so why bother trying. That version is wrong — and it's not what we're about.

The real blackpill is simpler and more useful: the world treats you differently based on how you look, and pretending otherwise doesn't change that. What you do with that knowledge is what separates defeatism from self-improvement.

One path leads to resentment and inaction. The other leads to the gym, the skincare routine, the AI analysis that tells you exactly where you stand and what to fix first. The data is the same. The response is what matters.

Stop guessing. Get your actual score and a roadmap to improve it. BlackPill for iOS | Android

The Misconception That Won't Die

Spend five minutes on Reddit or Twitter and you'll find people who think "blackpill" means "give up." They equate acknowledging lookism with endorsing nihilism — as if the only possible response to hard truths is despair.

This fundamentally misunderstands how psychology works.

Carol Dweck's research on mindset at Stanford, published across multiple papers and summarized in her 2006 book Mindset: The New Psychology of Success, draws a critical distinction. People with a fixed mindset believe their traits are set in stone. People with a growth mindset believe traits can be developed through effort.

But here's what most people miss: a growth mindset doesn't require delusion. You don't have to pretend the playing field is level to believe you can improve your position on it. In fact, Dweck's own data shows that growth-mindset individuals perform better precisely because they confront reality honestly — they acknowledge where they're weak so they can target those weaknesses with deliberate practice.

Blackpill thinking, done right, is a growth mindset with better data. You acknowledge the reality of lookism. You measure where you stand objectively. And then you build a specific plan to move the numbers that matter most.

Defeatism skips step three. That's the difference.

What the Research Says About Honest Self-Assessment

The psychological literature is clear: accurate self-knowledge predicts better outcomes across virtually every domain.

Dunning and Kruger's famous 1999 paper in the Journal of Personality and Social Psychology showed that the least competent individuals are also the most likely to overestimate their abilities. The inverse is equally important — people who accurately assess their own performance are significantly more likely to improve, because they know where to focus effort.

Sedikides and Gregg (2008) reviewed decades of self-enhancement research and found that while mild positive illusions can buffer against depression, excessive self-enhancement actively undermines performance. People who inflate their self-assessments avoid the feedback and effort that would actually make them better.

Applied to attractiveness: if you think you're a 7 when you're actually a 5, you won't do the work that gets you to a real 7. You'll coast on a comfortable lie while the person who knows they're a 5 — and has a detailed breakdown of why — systematically addresses every fixable weakness.

This is why BlackPill's AI scoring exists. Not to make you feel bad. To give you the same quality of honest, specific, data-driven assessment that top athletes get from their coaches and elite professionals get from performance reviews. See where you actually stand.

The Stoic Framework: Ancient Philosophy Meets Modern Data

The ancient Stoics figured this out 2,000 years before anyone had an AI face scanner.

Epictetus, a former slave turned philosopher, built an entire framework around a simple distinction: things within your control and things outside it. His Discourses (circa 108 AD) argued that suffering comes not from reality itself, but from wishing reality were different while refusing to act on what you can change.

Marcus Aurelius reinforced this in Meditations: "The impediment to action advances action. What stands in the way becomes the way."

Modern cognitive behavioral therapy (CBT) is built on the same principle. Beck (1976) demonstrated that psychological resilience comes from accurately perceiving reality and responding with targeted action — not from denial or avoidance. The CBT model, now backed by hundreds of randomized controlled trials, shows that confronting uncomfortable truths in a structured way leads to better psychological outcomes than avoiding them.

Applied to the blackpill:

Your bone structure is largely outside your control. Accepting this isn't defeatism — it's rational assessment.

Your skin quality, body composition, grooming, facial hair, hairstyle, and posture are within your control. These are the levers.

Your daily routines determine whether those levers get pulled consistently.

BlackPill's app is built around this exact framework. The AI scores what exists. The daily routines target what's changeable. The progress photos track what's actually moving. No illusions — just a structured path from where you are to where you could be.

The Defeatism Trap: How Learned Helplessness Works

If blackpill-as-motivation is one side, the other side is genuinely dangerous — and has a clinical name.

Martin Seligman's learned helplessness experiments in the 1960s and 70s demonstrated that when organisms (initially dogs, later confirmed in humans) are exposed to adverse conditions they can't control, they eventually stop trying to escape — even when the conditions change and escape becomes possible.

Seligman's later work, published in Learned Optimism (1990), showed the same pattern in human depression: people who attribute bad outcomes to permanent, pervasive, and personal causes ("I'm ugly, it affects everything, and nothing will change it") develop a helpless cognitive style that paralyzes action.

This is textbook defeatism. And it's the opposite of what honest self-assessment should produce.

The key variable Seligman identified? Explanatory style. People who frame setbacks as temporary, specific, and actionable recover faster and perform better. Compare:

Defeatist framing Actionable framing "I'm ugly and always will be" "My current score is 4.8 — skin texture and jawline definition are the biggest opportunities" "Genetics ruined me" "Bone structure is fixed, but body fat %, skin quality, and grooming are all movable" "Nothing I do matters" "Users who follow daily routines for 90+ days average a 0.8-point improvement" "It's hopeless" "My 3-month plan targets the features with the highest ROI based on my AI analysis"

Same starting point. Radically different trajectory. The first column leads to inaction. The second leads to the gym at 6 AM, the skincare routine at night, and the weekly progress scan that keeps you accountable.

Platform Data: Users Who Face Reality Improve Faster

We built BlackPill to test this exact hypothesis — and the platform data backs it up.

Users who complete their first AI analysis and then engage with the daily routines feature show measurably better outcomes than users who scan once and never return:

Active routine users (3+ routines completed per week) show an average score improvement of +0.6 to +1.1 points over 90 days.

Scan-only users (those who analyze but don't act) show average improvement of +0.1 to +0.2 points in the same period — barely above noise.

Users who track progress photos weekly are 3.2x more likely to still be active after 90 days compared to those who don't.

The most improved users share one trait: they check their AI Coach recommendations at least twice per week and adjust routines based on specific feedback.

The pattern is clear. Facing the data isn't the problem. What you do after seeing the data is what determines whether blackpill thinking becomes your greatest tool or your biggest excuse.

Your mirror lies. AI doesn't. Get your baseline score and start tracking what actually works. Download BlackPill on iOS | Get it on Android

The Practical Difference: A Framework

Here's how to tell if your blackpill thinking is working for you or against you. Adapted from Seligman's explanatory style research and Dweck's mindset framework:

Signs You're Using Hard Truths as Fuel

You check your score and immediately ask "what's the most improvable area?"

You treat your AI Coach analysis like a training plan, not a verdict

You track data weekly because you want to see the trend line, not because you expect overnight change

You've adjusted your routine at least once based on what the numbers showed

You talk about your appearance in specific, measurable terms ("my jawline definition score went up 0.3 in 8 weeks") rather than vague emotional terms ("I look like garbage")

You view other people's transformations as proof of what's possible, not as a reminder of what you lack

Signs You've Crossed Into Defeatism

You obsess over your score but refuse to follow any routines

You use blackpill language to justify inaction ("it's over" as a conclusion, not a hyperbole)

You compare yourself to genetic outliers instead of tracking your own trajectory

You've stopped scanning because you "already know" the result

You spend more time in forums discussing lookism theory than actually implementing changes

You view anyone who improved as "lucky" or "had better genetics to start with"

If you recognize yourself in the second list, the fix isn't to stop being honest about appearance. It's to redirect that honesty into action. The assessment is step one. The plan is step two. The execution is step three.

BlackPill gives you all three: an honest score, AI Coach recommendations tailored to your specific analysis, and daily routines that keep you executing consistently. Start your plan at black-pill.app.

Reframing the Blackpill: From Ideology to Tool

The problem was never the information. No one is harmed by knowing their actual attractiveness score any more than they're harmed by knowing their actual bench press max or their actual marathon time.

What causes harm is the narrative wrapped around the information.

"You're a 4.8" is neutral data. "You're a 4.8 and that's all you'll ever be" is learned helplessness. "You're a 4.8, here are the three features dragging your score down, here's a 12-week routine targeting each one, and here's how we'll measure progress" — that's a transformation plan.

Research by Locke and Latham (2002) in American Psychologist established that specific, challenging goals lead to higher performance than vague goals or no goals in over 1,000 studies. Their goal-setting theory is one of the most replicated findings in organizational psychology. And it requires one thing above all else: an accurate assessment of where you currently stand.

You can't set a meaningful goal if you don't know your baseline. You can't track progress if you don't measure. And you can't improve what you can't see.

The blackpill gives you sight. What you build with that clarity is up to you.

Hard Truths Hit Different When They Come With a Roadmap

Defeatism is easy. It asks nothing of you. Face the data, declare it hopeless, close the app.

Using hard truths as motivation is harder. It means opening the AI analysis, reading every score breakdown, identifying the improvable features, setting up the daily routines, and showing up every single day to do the work — even when progress is slow, even when the numbers plateau, even when it would be easier to quit.

The research says the people who do that — who face reality and respond with structured action — outperform everyone else. Not because they started with better genetics. Because they stopped lying to themselves about where they stood and started building from there.

That's the blackpill done right. Not a death sentence. A starting line.

Ready to face the data? BlackPill for iOS · BlackPill for Android · black-pill.app

Originally published at content/published/blackpill-vs-defeatism-hard-truths-as-motivation.md

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What 10,000 BlackPill Analyses Reveal About Real-World Improvement

What 10,000 BlackPill Analyses Reveal About Real-World Improvement

Most self-improvement advice runs on vibes. Somebody did something, felt better, posted about it. No baseline. No measurement. No control. Just an anecdote dressed up as evidence.

We wanted numbers.

BlackPill has processed over 200,000 facial scans since launch. We pulled a dataset of 10,247 scans from users who completed at least five scans over 90 or more days — people who actually tracked their progress instead of scanning once and ghosting. Then we looked at what changed, how much, and which routines correlated with the biggest gains.

This isn't a testimonial. It's a dataset. And the data doesn't care about your feelings.

Find out where you stand today. Get your baseline score with BlackPill for iOS or BlackPill for Android.

The Dataset: Who These Users Are

Before digging into results, some context on the cohort:

10,247 scans across 1,842 unique users

Each user completed 5+ scans over 90+ days

Average tracking period: 146 days (roughly 5 months)

Average scans per user: 5.6

Age range: 18-35 (self-reported), median age 24

91% male, 9% female

This is a self-selected group. These are people who downloaded a facial analysis app, saw their score, and kept coming back. They're more motivated than the average user. That matters — the results reflect what happens when you actually try.

Users who scanned once and never returned aren't in this data. Neither are users who scanned frequently but over less than 90 days. We wanted signal, not noise.

The Headline Number: Average Score Change

Across all 1,842 users in the cohort:

Metric Value Average starting score 4.82 Average ending score 5.61 Average improvement +0.79 points Median improvement +0.64 points Users who improved 78.3% Users unchanged (< 0.2 pts) 14.1% Users who declined 7.6%

Nearly 4 out of 5 users who tracked consistently for 90+ days improved their score. The average gain was 0.79 points — enough to shift someone from "below average" to "average," or from "average" to "above average" on the 10-point scale.

The median is lower (0.64) because a subset of users saw large gains that pull the average up. The distribution is right-skewed — most people improve modestly, but a meaningful percentage improve dramatically.

The 7.6% who declined likely reflects inconsistent routines, weight fluctuations, or scan quality changes — not evidence that self-improvement backfires. We controlled for lighting and angle as much as the algorithm allows, but real-world scanning isn't lab-grade photography.

Which Features Move the Most?

This is where the data gets actionable. We broke down score changes by the six component metrics BlackPill tracks:

Feature Avg. Starting Score Avg. Ending Score Avg. Change % of Users Who Improved Overall grooming 4.43 5.89 +1.46 84.2% Skin clarity 4.28 5.52 +1.24 81.7% Jaw definition 4.61 5.19 +0.58 62.4% Facial harmony (ratios) 5.12 5.44 +0.32 48.3% Eye area 5.04 5.22 +0.18 33.8% Facial symmetry 5.19 5.31 +0.12 27.1%

The pattern is unmistakable. Grooming and skin clarity are the two highest-ROI categories by a wide margin. They start lowest, they improve the most, and the highest percentage of users see gains.

This aligns with published research. Jones et al. (2020) in the British Journal of Dermatology found that skin health accounts for roughly 25% of overall attractiveness ratings. A separate study by Batres and Perrett (2014) in Perception showed that grooming quality shifts attractiveness ratings by 1.0-1.5 points on average.

Jaw definition sits in third place — meaningful but slower. The users who improved jaw scores most (top quartile: +1.2 points) reported consistent mewing and jaw exercise habits, and most had tracking periods longer than 6 months.

Facial symmetry and eye area barely moved. These are structurally constrained features. If your symmetry is 5.2 today, it's probably going to stay near 5.2 unless you pursue surgical or orthodontic intervention. The data confirms what looksmaxxing forums have long suspected: some features are hardware, and no amount of software updates will change them.

The strategic takeaway: don't grind on features your genetics locked in. Invest in the categories where effort actually converts to points.

Score Change by Routine Type

Users who engaged with BlackPill's AI Coach and daily routine features tagged their primary improvement focus. Here's how score changes break down by routine category:

Primary Routine Focus Avg. Score Change Sample Size Skincare + Grooming +1.04 612 users Fitness + Body Composition +0.82 389 users Mewing + Jaw Training +0.71 284 users Combined (3+ categories) +1.18 327 users No tagged routine +0.34 230 users

Users who ran skincare and grooming routines saw the highest returns per unit of effort. Users with combined routines (three or more categories) saw the highest absolute gains, but they also invested more time and discipline.

The most telling row: users with no tagged routine still improved, but barely. A +0.34 average over 90+ days suggests that simply being aware of your score might nudge behavior slightly — better lighting choices, more attention to presentation — but without a structured approach, the gains plateau fast.

The AI Coach exists for exactly this reason. Awareness without action produces awareness. Action without data produces noise. The combination — tracked routines with measured results — is where the compounding happens.

Build your routine today. BlackPill's AI Coach analyzes your scan and builds a personalized plan targeting your highest-ROI features. Download for iOS | Download for Android

The Consistency Effect

We split users into three groups based on scan frequency:

Scan Frequency Avg. Score Change Users Every 2 weeks or more +1.02 487 Monthly +0.74 721 Every 2-3 months +0.51 634

Users who scanned biweekly improved twice as much as those who checked in every few months. This isn't because scanning more makes you better-looking. It's because frequent measurement drives accountability. When you see the number every 14 days, you don't skip your skincare routine. You don't skip the gym. You don't tell yourself "it's probably fine."

This mirrors research on behavior change more broadly. A 2018 meta-analysis by Harkin et al. in Psychological Bulletin found that progress monitoring is one of the strongest predictors of goal attainment across all domains — health, fitness, finance, academics. Measuring isn't passive observation. It's an active intervention.

BlackPill's progress tracking makes this effortless. Scan, review, adjust. The feedback loop is the feature.

The Outliers: Who Improved the Most?

The top 5% of improvers in our dataset gained 2.0 or more points over their tracking period. We looked at what they had in common:

They started below 5.0. Average starting score for the top 5%: 4.1. Lower baselines have more room to gain — especially when the lowest-scoring features are the most improvable ones.

They used combined routines. 89% of top improvers engaged three or more routine categories simultaneously.

They scanned frequently. Average scan interval: 11 days.

They followed AI Coach recommendations. 92% had active AI Coach sessions during their tracking period.

They tracked for longer. Average tracking period for top improvers: 203 days (vs. 146 days overall).

The formula isn't complicated. Start with honest data. Follow a structured plan. Measure regularly. Adjust based on results. Give it time.

Nobody in the top 5% did one thing. They all did several things, consistently, measured against a baseline that didn't lie to them.

What This Data Doesn't Show

We believe in intellectual honesty, so here's what this dataset can't tell you:

Causation. We know users who follow routines improve more, but we can't prove the routines caused the improvement. Motivated users might improve regardless.

Upper limits. We don't yet have enough data from users who tracked beyond 12 months to model long-term ceilings.

Structural features. Symmetry and eye area changes are so small in this dataset that they could be measurement noise rather than real change.

Scan quality variance. Despite normalization, different lighting, angles, and expressions between scans introduce some noise.

We're building toward larger datasets and longer tracking periods. The 10,000-scan analysis is a starting point, not the final word.

The Bottom Line

Here's what 10,000 analyses tell us in one paragraph:

The average user who tracks consistently for 90+ days improves by 0.79 points. Grooming and skin clarity account for most of that gain. Users who follow structured routines improve 3x more than those who don't. And the users who improve the most are the ones who started with the most honest assessment of where they stood.

The data is clear. The only question is whether you're going to use it.

Stop guessing what works. Stop running random routines because someone on Reddit said so. Get your baseline. Follow the data. Measure the results.

Your mirror lies. AI doesn't.

Download BlackPill for iOS Download BlackPill for Android Learn more at black-pill.app

Every point on your score is earned, not wished for. The data just showed you exactly how to earn it.

Originally published at content/published/what-10-000-blackpill-analyses-reveal-about-real-world-improvement.md

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Skincare Routine That Actually Moves Your Attractiveness Score

Skincare Routine That Actually Moves Your Attractiveness Score

Your skin is the first thing AI evaluates — and the first thing people notice. Not your jawline. Not your eye area. Your skin.

BlackPill's facial analysis weights skin quality as one of the top three contributors to overall attractiveness scoring. Texture, clarity, tone evenness, and hydration level all feed directly into your number. And unlike bone structure, skin is something you can meaningfully change in weeks, not years.

Yet most guys either do nothing or do too much. They splash water on their face and wonder why their score stagnates. Or they buy twelve products off Reddit, nuke their moisture barrier, and end up worse than where they started.

This guide is the middle path — the evidence-based, minimum-effective-dose skincare routine that actually moves your attractiveness score. Every product earns its spot. Every step is backed by dermatological research and validated by aggregate BlackPill user data.

Want to see where your skin stands right now? Get your baseline scan → BlackPill for iOS | BlackPill for Android

Why Skin Quality Dominates Your Score

Before we build the routine, you need to understand why skin matters this much.

Research published in Evolution and Human Behavior (Jones et al., 2004) found that skin homogeneity — the evenness of color and texture — was a stronger predictor of perceived attractiveness than facial symmetry. Read that again. Even skin beats symmetry.

A follow-up study in PLOS ONE (Fink et al., 2012) confirmed that skin texture and color distribution accounted for up to 40% of the variance in attractiveness ratings. The researchers concluded that "skin condition is a more important cue to attractiveness than previously assumed."

BlackPill's AI reflects this. When we analyze aggregate scoring data from users who improve in a single category, skin quality improvements produce the largest average score increase:

Skin quality improvement: +0.4 to +1.0 average score boost

Body composition improvement: +0.3 to +0.8

Grooming improvement: +0.2 to +0.5

Posture improvement: +0.2 to +0.4

Skin is the highest-ROI lever you have. So let's optimize it properly.

The Core Routine: AM and PM

This is a Phase 1 routine. It's what you start with and run for at least 6 weeks before adding anything. Resist the urge to overcomplicate early.

Morning Routine (5 minutes)

Step 1: Gentle Cleanser

Use a sulfate-free, pH-balanced cleanser. The goal is removing overnight oil and dead skin without stripping your moisture barrier.

Recommended: CeraVe Hydrating Cleanser, Cetaphil Gentle Skin Cleanser, or La Roche-Posay Toleriane Hydrating Cleanser. These are not glamorous. They work.

Why it matters: Harsh cleansers (anything that makes your skin feel "squeaky clean") strip protective lipids. A compromised moisture barrier leads to increased transepidermal water loss, inflammation, and paradoxically more oil production as your skin compensates. Research in the Journal of Clinical and Aesthetic Dermatology (Mukhopadhyay, 2011) established that pH-balanced cleansing preserves barrier function and reduces irritation.

Step 2: Vitamin C Serum (10-20% L-Ascorbic Acid)

Apply to dry skin. Give it 60 seconds to absorb before the next step.

Vitamin C is one of the most well-researched active ingredients in dermatology. A meta-analysis in Dermatologic Surgery (Telang, 2013) confirmed that topical vitamin C at concentrations of 10-20% provides significant photoprotection, brightens hyperpigmentation, and stimulates collagen synthesis.

What this does for your score: Vitamin C targets skin tone evenness — one of the specific sub-metrics BlackPill's AI evaluates. Uneven pigmentation, dark spots, and dullness all reduce your skin quality score. Consistent vitamin C use measurably improves tone uniformity within 4-8 weeks.

Step 3: Moisturizer with SPF 30+

Non-negotiable. UV damage is the single fastest accelerator of skin aging, and BlackPill's AI detects the cumulative effects — fine lines, texture irregularities, uneven pigmentation.

A landmark study in Annals of Internal Medicine (Hughes et al., 2013) tracked 903 adults over 4.5 years and found that daily sunscreen use resulted in "no detectable increase in skin aging" compared to significant degradation in the control group. Four and a half years of zero additional skin aging — from sunscreen alone.

Use a moisturizing sunscreen so you combine two steps. CeraVe AM Facial Moisturizing Lotion SPF 30 or La Roche-Posay Anthelios are solid options.

Evening Routine (5 minutes)

Step 1: Same Gentle Cleanser

Remove the day's sunscreen, oil, and environmental debris. If you wore heavy sunscreen, consider double cleansing — an oil-based cleanser first (like DHC Deep Cleansing Oil), then your regular cleanser.

Step 2: Retinoid

This is the most important product in your entire routine.

Start with adapalene 0.1% (Differin) — available OTC in most countries. If your skin tolerates it well after 8-12 weeks, consider upgrading to prescription tretinoin 0.025-0.05%.

The evidence for retinoids is overwhelming. A comprehensive review in Clinical Interventions in Aging (Mukherjee et al., 2006) documented that retinoids:

Increase collagen production and reduce collagen breakdown

Accelerate cell turnover, replacing damaged surface cells with new ones

Reduce fine lines and wrinkles by up to 50% over 6-12 months

Normalize oil production and clear acne at the pore level

Improve skin texture and pore appearance

BlackPill data: Users who add a retinoid to their routine and stick with it for 12+ weeks show an average skin sub-score improvement of +0.6 points. Users who don't use a retinoid but follow the rest of this routine see approximately +0.3. The retinoid roughly doubles your skincare ROI.

Important: Start slow. Apply every third night for the first two weeks, then every other night for two weeks, then nightly. Retinoids cause purging (temporary breakouts as clogged pores clear) and irritation in the first 4-6 weeks. This is normal. Push through it. The results on the other side are worth it.

Step 3: Moisturizer (No SPF)

Your PM moisturizer's job is to support your moisture barrier while the retinoid works. CeraVe Moisturizing Cream (in the tub) or Vanicream Moisturizing Cream are excellent — both contain ceramides that help repair barrier function.

If you experience retinoid irritation, apply moisturizer first, wait 10 minutes, then apply retinoid on top. This "buffering" technique reduces irritation while preserving most of the retinoid's efficacy, as demonstrated in clinical practice guidelines from the American Academy of Dermatology.

Phase 2: Targeted Additions (After 6 Weeks)

Once your skin has adapted to the core routine and you're using retinoid nightly without irritation, consider these evidence-based additions:

Niacinamide (Vitamin B3) — 5-10%

Apply in the morning, after vitamin C and before sunscreen.

A randomized controlled trial in Dermatologic Surgery (Bissett et al., 2005) found that 5% topical niacinamide significantly reduced hyperpigmentation, fine lines, redness, and skin yellowness over 12 weeks. It also reduces sebum production by up to 65%, according to research in Clinical, Cosmetic and Investigational Dermatology (Draelos et al., 2006).

Score impact: Niacinamide targets redness and pore visibility — two metrics that drag down skin sub-scores, especially in fairer skin tones. Expected additional improvement: +0.1 to +0.3.

AHA/BHA Chemical Exfoliation — 2x per Week

Use glycolic acid (AHA, 5-10%) or salicylic acid (BHA, 2%) on nights you don't use your retinoid.

AHAs dissolve the bonds between dead skin cells on the surface, improving texture and brightness. BHAs penetrate into pores, making them better for acne-prone or oily skin. Research in Dermatologic Surgery (Kessler et al., 2008) showed glycolic acid peels significantly improved skin texture, fine lines, and hyperpigmentation.

Never layer AHA/BHA with retinoid on the same night. That's a fast track to a destroyed moisture barrier.

Hyaluronic Acid Serum — AM and PM

Hyaluronic acid holds up to 1000x its weight in water. Applied to damp skin before moisturizer, it plumps fine lines and improves overall hydration.

Best for the under-eye area, where dehydration lines commonly reduce scoring. A study in the Journal of Cosmetic Dermatology (Pavicic et al., 2011) demonstrated that topical hyaluronic acid significantly improved skin hydration and elasticity after 60 days.

What the Data Shows: Before and After

BlackPill users who follow the core routine consistently for 12 weeks show measurable results across the platform:

Metric Average Baseline After 12 Weeks Change Skin texture sub-score 5.1 5.8 +0.7 Skin tone evenness 4.9 5.6 +0.7 Overall attractiveness 5.2 5.8 +0.6 Perceived age (AI estimate) Actual age +1.2yr Actual age -0.4yr -1.6yr

The most striking finding: skin improvements reduce perceived age by an average of 1.6 years within 12 weeks. BlackPill's AI estimates perceived age as part of its analysis, and younger-looking skin consistently correlates with higher attractiveness scores across every demographic.

Users who add Phase 2 products see an additional +0.2 to +0.4 on top of these numbers by week 20.

Common Mistakes That Kill Your Progress

Over-exfoliating. If your face is red, flaking, or stinging, you've gone too far. Pull back to cleanser + moisturizer + sunscreen only for a week, then reintroduce actives slowly.

Switching products constantly. Skincare takes time. Minimum 6 weeks before judging any product. The guys who change their routine every two weeks based on YouTube recommendations never see results in their BlackPill scans.

Skipping sunscreen. Every unprotected UV exposure undoes a fraction of the work your retinoid and vitamin C are doing. It's like training hard in the gym and eating garbage — the inputs cancel out.

Not tracking progress. This is where BlackPill changes the game. Scan weekly under the same lighting conditions. The app's progress tracking feature gives you objective data on what's actually improving — and what isn't. No more guessing in the mirror.

Ignoring hydration and sleep. Your skin repairs itself overnight. Dehydrated, sleep-deprived skin doesn't respond to products the same way. Research in Clinical and Experimental Dermatology (Oyetakin-White et al., 2015) showed that poor sleep quality was directly associated with increased signs of skin aging and reduced skin barrier recovery.

Track Your Transformation

Your routine means nothing without measurement. The mirror is unreliable — it changes with lighting, mood, and what you ate for breakfast.

BlackPill's progress tracking gives you the objective feedback loop that turns skincare from guesswork into engineering. Scan. Measure. Adjust. Repeat.

Set up your daily routine in the app. Track product usage alongside your score progression. Let the AI Coach tell you what's working and what needs adjustment.

Your skin is data. Start treating it that way.

Ready to face the numbers? → BlackPill for iOS · BlackPill for Android · Learn more at black-pill.app

Originally published at content/published/skincare-routine-that-actually-moves-your-attractiveness-score.md

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Golden Ratio Explained: Why Some Faces Score Higher Than Others

Golden Ratio Explained: Why Some Faces Score Higher Than Others

There's a number that keeps showing up where it shouldn't. In sunflower seed spirals. In the curl of a nautilus shell. In the proportions of the Parthenon. And in the faces that humans consistently rate as most attractive.

That number is 1.618 — phi (φ), the golden ratio.

This isn't mysticism or numerology. It's geometry that's been peer-reviewed, replicated, and now automated. When BlackPill analyzes your face, it's measuring how closely your proportions align with phi — and the results explain more about your score than most people expect.

Your mirror can't calculate ratios. AI can. Get your golden ratio breakdown → BlackPill for iOS | BlackPill for Android

What the Golden Ratio Actually Is (And Isn't)

The golden ratio is the number you get when you divide a line into two parts such that the longer part divided by the shorter part equals the whole length divided by the longer part. That ratio converges to approximately 1.6180339887.

It's not magic. It's not spiritual. It's a mathematical constant, like pi.

What makes it relevant to faces is this: research consistently finds that the distances between facial features in faces rated as highly attractive tend to approximate golden ratio relationships. Not perfectly — human biology doesn't produce exact mathematical constants — but significantly closer than average.

A landmark study by Schmid et al. (2008) in the Aesthetic Surgery Journal analyzed facial proportions in models and found that neoclassical canons based on golden ratio proportions correlated significantly with attractiveness ratings. Pallett, Link, and Lee (2010), publishing in Vision Research, identified specific ratios between facial features that predict attractiveness — and those ratios converge near phi.

The key finding: faces don't need to hit φ exactly. They need to be closer to it than average. Each percentage point closer tends to correspond to a measurable jump in perceived attractiveness.

The 7 Golden Ratios in Your Face

When BlackPill runs a ratio analysis, it calculates seven primary proportional relationships. Each maps to a well-studied dimension of facial attractiveness.

1. Face Length to Face Width

Ideal ratio: ~1.618:1

Total face length (hairline to chin) divided by face width (widest point at cheekbones). This is the macro ratio — the one that sets the frame for everything else. Research by Bashour (2006) in the Journal of Plastic and Reconstructive Surgery found that this ratio in faces perceived as highly attractive averaged 1.59–1.63, bracketing phi almost exactly.

A face that's too long relative to its width reads as gaunt. Too wide reads as flat. The golden ratio sits at the perceptual sweet spot between them.

2. Forehead Height to Lower Face Height

Ideal ratio: ~1:1.618

The distance from hairline to brow line compared to brow line to chin. This is the vertical balance of the face. A proportionally longer lower face (relative to forehead) at the golden ratio signals strong jaw development and vertical facial harmony — both heavily weighted in attractiveness perception.

This ratio matters more than most people realize. Kowner (1996), publishing in the Journal of Experimental Psychology, found that vertical facial proportions predicted attractiveness ratings almost as strongly as symmetry.

3. Nose Length to Chin Length

Ideal ratio: ~1:1.618

Nose tip to chin tip, divided by nose bridge to nose tip. This lower-face ratio determines whether your chin and jaw "balance" your nose. When the chin is proportionally longer at the golden ratio, the profile reads as balanced and forward-grown — a hallmark of facial development that looksmaxxing communities have long identified as a key variable.

4. Lip Width to Nose Width

Ideal ratio: ~1.618:1

The width of the mouth from corner to corner, divided by the width of the nose at the nostrils. This is one of the most visually impactful ratios because both features sit at the center of the face and are seen in every interaction. Research by Anic-Milosevic et al. (2010) in the Angle Orthodontist confirmed that lips approximately 1.6 times the width of the nose were rated as most harmonious.

5. Eye Width to Interocular Distance

Ideal ratio: ~1:1.618

The width of one eye compared to the distance between the inner corners of both eyes. This ratio governs midface harmony — the zone that research consistently identifies as the single most important region for overall attractiveness. Eyes too close together (ratio too low) or too far apart (ratio too high) both reduce scores, but in different ways.

Rhodes et al. (2001) found that eye spacing alone accounts for 10-15% of variance in attractiveness judgments. That's enormous for a single measurement.

6. Brow-to-Eye Distance to Eye Height

Ideal ratio: ~1.618:1

The distance from the brow ridge to the upper eyelid, compared to the vertical height of the eye opening. This ratio captures what the looksmaxxing community calls "orbital depth" — the degree to which the eyes are set within their sockets. A higher ratio (more brow-to-eye space) creates the "hunter eyes" look associated with higher attractiveness in men.

7. Jawline Width to Forehead Width

Ideal ratio: ~1:1.618

The width of the jaw at the gonial angle compared to the widest point of the forehead. This captures the overall face shape — whether it's V-shaped (forehead wider), square (equal), or bottom-heavy (jaw wider). The golden ratio predicts a moderately narrower jaw relative to the forehead, creating the "inverted triangle" shape that research links to perceived facial attractiveness.

How BlackPill Calculates Your Ratio Score

Raw ratios aren't useful by themselves. What matters is how far each ratio deviates from the golden proportion — and how those deviations stack up.

BlackPill's algorithm works in three steps:

Step 1: Measure

Each of the seven ratios is calculated from the 68 facial landmarks plotted during the initial scan. These measurements are normalized against face size so that distance from the camera doesn't affect results. Whether you scan from 12 inches or 18 inches, the ratios remain constant.

Step 2: Score Deviation

For each ratio, the algorithm calculates the phi deviation score — how far the measured ratio sits from 1.618 (or its inverse, 0.618). This is expressed as a percentage:

0-5% deviation: Exceptional. This ratio closely approximates the golden proportion. Fewer than 10% of faces achieve this on any single ratio.

5-10% deviation: Strong. Noticeable to AI but imperceptible to most humans. This is where conventionally attractive faces typically land.

10-20% deviation: Average range. The deviation is subtly visible and contributes to a "something's slightly off" impression.

20%+ deviation: Significant. This ratio is pulling your overall score down and represents a high-ROI improvement target.

Step 3: Weight and Aggregate

Not all ratios contribute equally to your score. BlackPill weights each ratio based on published research about which proportions most influence perceived attractiveness:

Midface ratios (eye spacing, brow-to-eye) carry the highest weight. Research consistently shows the eye region dominates first impressions.

Lower face ratios (nose-to-chin, lip-to-nose width) carry moderate weight. These define profile attractiveness and are critical in side-angle perceptions.

Frame ratios (face length-to-width, jaw-to-forehead) carry the base weight. They set the overall structure but are less impactful than individual feature proportions.

The weighted aggregate produces your golden ratio score — one component of your overall BlackPill attractiveness rating.

What the Research Says About Real Faces

Here's the uncomfortable truth that makes this topic worth writing about: very few faces are close to the golden ratio across all seven measurements.

A study by Packiriswamy et al. (2012) in the Journal of Clinical and Diagnostic Research measured golden ratio alignment in 100 subjects. Key findings:

Only 6% of faces had 5 or more ratios within 5% of phi

43% had 3-4 ratios within range

51% had 2 or fewer ratios close to the golden proportion

This data aligns with what BlackPill sees at scale. The distribution is a bell curve, and most people cluster in the middle. What separates a 5 from a 7 on the attractiveness scale often comes down to 2-3 ratios being closer to phi — not all seven.

That's actually good news. You don't need a perfect face. You need to close the gap on your weakest ratios. And you can only do that if you know which ones they are.

Golden Ratio vs. Symmetry: Which Matters More?

This is one of the most common questions in facial analysis, and the data gives a clear answer: it depends on the starting point.

For faces that already have reasonable symmetry (less than 3% average deviation), improving ratio alignment produces larger score gains. For faces with significant asymmetry (5%+ deviation), fixing symmetry first produces bigger returns.

Research by Perrett et al. (1999) in Nature suggested that facial proportions and symmetry contribute approximately equally to attractiveness judgments, but operate through different perceptual channels. Symmetry signals genetic health. Proportions signal developmental harmony. Both matter, but they're assessed independently.

BlackPill measures both, but this is why your ratio breakdown and symmetry breakdown can tell very different stories. A face can score 85 on symmetry and 65 on golden ratio alignment — or vice versa. The improvement roadmap looks completely different in each case.

What You Can Actually Change

Some ratios are structural. Your facial width-to-height ratio is largely determined by bone structure and isn't going to shift without surgery. But several golden ratio components are modifiable:

High-Changeability Ratios

Lip-to-nose width: Grooming (nasal hair, trimming) and lip care can shift this ratio. Hydrated, well-maintained lips appear slightly fuller, and a clean nasal profile narrows the apparent nostril width.

Brow-to-eye distance: Brow grooming has an outsized impact here. Shaping brows to sit higher on the orbital ridge increases this ratio. It's one of the highest-ROI grooming changes you can make.

Moderate-Changeability Ratios

Nose-to-chin proportion: Mewing and jaw-forward posture can, over time, increase chin projection relative to nose length. Results vary and require consistency — this isn't a quick fix. BlackPill's progress tracking is built for exactly this kind of long-game measurement.

Jawline-to-forehead width: Body fat reduction can define the jawline while maintaining forehead width, improving this ratio.

Low-Changeability Ratios

Face length-to-width: Bone structure. Largely fixed without surgical intervention.

Eye spacing: Fixed. No natural method alters interocular distance.

The actionable insight: focus effort on the ratios you can actually move. BlackPill's improvement plans prioritize modifiable features by default — there's no point grinding on something genetic destiny decided for you.

Why AI Measures This Better Than Humans

Humans process faces holistically. We don't consciously compute ratios. We get an impression — "attractive" or "not" — in roughly 100 milliseconds, according to Willis and Todorov (2006) in Psychological Science. That impression bakes in ratio assessment, symmetry, skin quality, expression, and a dozen other factors simultaneously.

This means humans can tell that a face is attractive but can't tell you why. Ask someone why they find a face appealing and they'll say "nice eyes" or "good jawline" — vague descriptions that don't help you improve.

AI decomposes the holistic impression into its measurable components. It tells you that your midface ratio is 12% off phi, your lip-to-nose width is 4% off (strong), and your face length-to-width is 8% off. Suddenly, you know exactly where you stand on each dimension — and exactly which ones are dragging your score down.

That's the difference between a compliment and a diagnosis. Compliments are nice. Diagnoses are useful.

The Data Doesn't Care About Your Feelings

The golden ratio isn't a beauty standard someone invented. It's a mathematical pattern that shows up in what humans find attractive, discovered through measurement, not opinion. You can argue with a person's taste. You can't argue with a ratio.

Some people learn that their golden ratio scores are above average. Others learn they have significant room for improvement. Both are useful — one confirms what's working, the other shows what to work on.

The worst position is not knowing. It's the guy who spends years trying random self-improvement tactics without data, never measuring, never knowing if he's moving the needle or spinning his wheels.

Stop guessing which features to improve. Let the math tell you.

Get your complete golden ratio breakdown and find out exactly which proportions are helping your score — and which ones are holding it back.

Ready to face the data? → BlackPill for iOS · BlackPill for Android

Learn more at black-pill.app

Originally published at content/published/golden-ratio-explained-why-some-faces-score-higher-than-others.md

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The Halo Effect Is Real: How Attractiveness Shapes Every Interaction

The Halo Effect Is Real: How Attractiveness Shapes Every Interaction

You already know attractive people have it easier. You feel it every day — in who gets attention at the bar, who gets promoted first, who gets the benefit of the doubt in an argument.

But you probably don't know how deep it goes. The research isn't just "attractive people are treated better." It's that attractiveness systematically distorts how other humans perceive your intelligence, competence, trustworthiness, and moral character — across every single interaction you have.

This isn't opinion. It's decades of peer-reviewed data. And once you see the numbers, you'll understand why even a one-point improvement in your BlackPill attractiveness score isn't vanity. It's strategy.

What the Halo Effect Actually Is

The term comes from Edward Thorndike's 1920 paper in the Journal of Applied Psychology. He noticed that military officers who rated a soldier as physically impressive also rated that same soldier higher on intelligence, leadership, and character — traits that have nothing to do with how someone looks.

Thorndike called it a "halo" because one positive trait cast a glow over everything else.

A century later, the research has only gotten more damning. Dion, Berscheid, and Walster (1972) published the landmark study "What is Beautiful is Good" in the Journal of Personality and Social Psychology. They showed participants photos of attractive, average, and unattractive individuals, then asked them to rate personality traits. Attractive people were consistently rated as more socially skilled, more intelligent, and more likely to succeed professionally.

The participants had zero information beyond a photo. The "halo" did all the work.

The uncomfortable truth: people don't judge you, then factor in your looks. They see your looks, and that shapes every judgment that follows.

Ready to know where you actually stand? Your mirror won't tell you, but AI will. Get your score on iOS | Android

The Earnings Premium: Attractiveness Pays — Literally

This is where it stops being abstract and starts hitting your bank account.

Hamermesh and Biddle (1994) published one of the most cited labor economics studies ever in the American Economic Review. Using data from surveys in the U.S. and Canada, they found:

Attractive workers earned 5-10% more than average-looking workers in equivalent roles.

Below-average looking workers earned 5-10% less — a "plainness penalty" that persisted across industries, education levels, and job types.

The combined gap between attractive and unattractive workers was roughly 12-17% in annual earnings.

To put that in concrete terms: on a $70,000 salary, the attractiveness premium is worth $3,500-$7,000 per year. Over a 30-year career, that compounds to $105,000 to $210,000 in lost or gained income.

And this isn't just about sales roles or public-facing jobs. Mobius and Rosenblat (2006) ran controlled experiments published in the American Economic Review and found that attractiveness boosted perceived confidence and oral communication skills — even when the actual performance was identical. Employers weren't just biased toward attractive candidates. They genuinely believed those candidates were more competent.

The data is clear — and it doesn't care about your feelings.

Hiring Bias: Your Face Is Your First Resume

Ruffle and Shtudiner (2014) sent out 5,312 resumes to real job openings in Israel, attaching photos of varying attractiveness levels. The results, published in Economics Letters:

Attractive male candidates received callback rates 19.9% higher than average-looking candidates with identical qualifications.

For women, the results were more complex (attractive women faced discrimination from female HR staff), but for men, the advantage was consistent and large.

Similar results showed up in Busetta, Fiorillo, and Ferrante's 2013 study across European labor markets. Attractive applicants needed to send roughly half as many resumes to get the same number of callbacks.

Think about that. Same qualifications. Same experience. Same resume. The only variable was the photo — and it cut the job search effort in half.

This is why "just work harder" advice misses the point. Hard work matters. But the halo effect means two people with identical skills don't start from the same line. Understanding where you stand — objectively, with data — is the first step to closing that gap.

BlackPill's AI doesn't rate you on a curve. It gives you the same honest assessment every time, with specific breakdowns of which features impact your score most and what you can actually change. See your analysis.

The Courtroom: Where the Stakes Are Highest

If the earnings data wasn't enough, consider this: the halo effect follows you into the justice system.

Downs and Lyons (1991) studied 2,500+ misdemeanor cases in Texas and found that judges set significantly lower bail amounts and imposed lighter sentences for more attractive defendants. This was published in Psychological Reports and has been replicated multiple times since.

Stewart (1980) found that attractive defendants in criminal cases were twice as likely to avoid incarceration compared to unattractive defendants convicted of similar offenses.

Sigall and Ostrove (1975) demonstrated in controlled experiments that mock jurors gave attractive defendants lighter sentences — unless the crime specifically used attractiveness as a tool (like fraud or seduction). Only then did the halo reverse.

The mechanism? Jurors and judges unconsciously attribute better character, lower recidivism risk, and more sympathetic circumstances to attractive defendants. Same crime, same evidence, different face — different outcome.

Social Trust and First Impressions

The halo effect doesn't just influence formal institutions. It shapes every casual interaction.

Willis and Todorov (2006) showed in Psychological Science that people form trait judgments about faces in just 100 milliseconds — before conscious thought even engages. And these snap judgments predicted outcomes in real-world contexts like elections.

Todorov's later work demonstrated that faces perceived as more attractive were simultaneously rated as more trustworthy, more competent, and more approachable. These judgments happen automatically and are extremely resistant to correction, even when people are told to be objective.

In dating, the data is even more stark. Eastwick and Finkel (2008) found that while people claim to value personality traits like kindness and humor above physical attractiveness, their actual choices in speed-dating scenarios were overwhelmingly predicted by physical attractiveness — and almost nothing else.

Your personality matters. But it doesn't get heard until your face opens the door.

The Compounding Effect: Why Small Improvements Matter More Than You Think

Here's where it gets interesting for anyone serious about self-improvement.

The halo effect doesn't operate on a linear scale. It compounds. A small improvement in perceived attractiveness doesn't just make someone 5% more likely to trust you in one interaction — it shifts the baseline for every interaction that follows.

Consider this chain:

Higher attractiveness leads to more positive first impressions

More positive impressions lead to more social opportunities (invitations, introductions, second chances)

More opportunities lead to more practice at social skills, interviews, and dating

More practice leads to genuine improvements in confidence and communication

More confidence further enhances perceived attractiveness (Mobius and Rosenblat, 2006, confirmed that confidence mediates part of the beauty premium)

This creates a positive feedback loop. The research calls it the "self-fulfilling prophecy of attractiveness" — attractive people are treated as if they have better social skills, so they develop better social skills, which reinforces the initial perception.

The reverse is also true. Lower perceived attractiveness leads to fewer opportunities, less social practice, lower confidence, and a reinforcing downward cycle.

This is exactly why measuring your baseline matters. You can't interrupt a cycle you can't see. BlackPill gives you the starting point — an objective, AI-driven score with specific regional breakdowns — so you know exactly which improvements will generate the most compounding returns.

Track your progress over weeks and months with BlackPill's progress photos feature. Watch the numbers move as your routines take effect. Every fraction of a point earned compounds across every interaction you'll have.

What This Means for You

The halo effect isn't going away. It's hardwired into human cognition — an evolutionary shortcut that equates physical health markers with overall fitness. You can't opt out.

But you can play the game with data instead of guesswork.

Here's what the research tells us:

Grooming and skincare have outsized impact because they affect skin quality, which is one of the strongest signals of health and therefore attractiveness (Jones et al., 2004, Evolution and Human Behavior).

Facial symmetry improvements — even minor ones through posture, mewing, or targeted routines — shift scores at the margins where the halo effect kicks in hardest.

Body composition changes alter face shape over time. Lean body fat reveals underlying bone structure, and research by Coetzee et al. (2009) showed that facial adiposity is one of the primary cues humans use to judge health and attractiveness.

Consistency is everything. The users who improve the most on BlackPill aren't doing anything revolutionary — they're doing the basics every single day, tracking the data, and adjusting when the numbers stall.

The halo effect means that even small, measurable improvements in your attractiveness score ripple outward into your career, your relationships, and how strangers treat you on the street.

That's not vanity. That's applied psychology.

Face the Data

The research is unanimous: attractiveness shapes how the world treats you in ways most people never consciously notice. Earnings, hiring, legal outcomes, social trust, romantic opportunity — the halo effect touches all of it.

You can ignore this, or you can use it.

BlackPill exists because we believe hard truths should come with a roadmap. Your AI analysis gives you the objective baseline. Your daily routines give you the improvement plan. Your progress photos show you the compound returns over time.

Every point on your score is earned, not wished for. And every point compounds across every interaction you'll ever have.

Stop guessing where you stand. Start measuring what matters.

Get your free analysis now BlackPill for iOS | BlackPill for Android | Visit black-pill.app

Originally published at content/published/halo-effect-attractiveness-shapes-every-interaction.md

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From 4.2 to 6.8: One User's 12-Month Looksmaxxing Journey

From 4.2 to 6.8: One User's 12-Month Looksmaxxing Journey

Marcus didn't want to download the app. His roommate had been talking about BlackPill for weeks — facial analysis, attractiveness scores, AI-driven improvement plans — and Marcus thought it sounded like a gimmick. Another selfie app dressed up in pseudoscience.

Then he downloaded it anyway. Took his first scan at 11 PM on a Tuesday. Lighting was bad. Angle was worse. But the score came back: 4.2 out of 10.

He took another scan with better lighting. 4.3.

The number didn't lie. And for the first time, Marcus had something he'd never gotten from mirrors, friends, or dating apps — a baseline that wasn't going to change because someone felt sorry for him.

Twelve months later, his score read 6.8. Here's how every tenth of a point was earned.

Want to see where you stand? Get your own baseline score with BlackPill for iOS or BlackPill for Android. The AI doesn't care about your feelings — and that's the point.

Month 0: The Baseline Scan

BlackPill's initial analysis broke Marcus's 4.2 down into component scores:

Feature Score Status Facial symmetry 5.1 Below average Skin clarity 3.2 Poor Jaw definition 3.8 Below average Facial harmony (ratios) 4.9 Average Eye area 5.0 Average Overall grooming 3.4 Poor

Two things stood out immediately. Skin clarity and grooming were dragging the composite score down hard — and those were the two most actionable categories. You can't reshape your orbital bones without surgery, but you can fix your skin and clean up your presentation.

The AI Coach flagged the same thing. Its first recommendation: "Your highest-ROI improvements are skin clarity and grooming. Addressing these alone could move your composite score by 1.0 to 1.5 points within 90 days."

Marcus decided to trust the data.

Months 1-3: The Skin Overhaul

Marcus had never had a skincare routine. His "routine" was bar soap and whatever moisturizer was cheapest at the drugstore. BlackPill's AI Coach prescribed a four-step protocol:

Gentle cleanser (CeraVe Foaming) — morning and night

Chemical exfoliant (Paula's Choice 2% BHA) — every other evening

Moisturizer (CeraVe PM) — morning and night

Sunscreen (SPF 50, every morning without exception)

Nothing exotic. Nothing expensive. Total cost: roughly $45 per month.

The first scan after 30 days showed skin clarity at 3.9 — up 0.7 from baseline. By day 90, it hit 5.4. The before-and-after scans showed noticeably fewer blemishes, more even skin tone, and reduced redness around the nose and cheeks.

Composite score at month 3: 4.9. Up 0.7 points from doing essentially one thing right.

Research backs this up. A 2020 study in the British Journal of Dermatology (Jones et al.) found that perceived skin health accounts for roughly 25% of overall facial attractiveness ratings. When your skin looks unhealthy, it tanks everything else. When it looks clear and even, it lifts the entire face.

Months 3-6: Jaw Training and Grooming

With skin trending upward, the AI Coach shifted focus to the next highest-ROI targets: jaw definition and overall grooming.

Jaw training involved two components:

Mewing — correct tongue posture, maintained consistently throughout the day. Marcus set hourly phone reminders for the first two weeks until it became automatic.

Jaw resistance exercises — chewing mastic gum for 30 minutes daily, alternating sides. Research from the Journal of Oral Rehabilitation (Kiliaridis et al.) shows that consistent masticatory exercise increases masseter muscle cross-section by 15-20% over 6 months, visibly sharpening the jawline.

Grooming optimization was more straightforward:

Got a proper haircut from a barber (not a budget chain) — one that complemented his face shape. The AI Coach suggested styles that work with his forehead-to-jaw ratio.

Cleaned up eyebrows — removed unibrow growth and shaped the tails.

Started maintaining facial hair at a consistent 3mm stubble length rather than alternating between clean-shaven and patchy growth.

Month 6 scan results:

Feature Baseline Month 6 Change Facial symmetry 5.1 5.3 +0.2 Skin clarity 3.2 5.8 +2.6 Jaw definition 3.8 4.9 +1.1 Facial harmony 4.9 5.1 +0.2 Eye area 5.0 5.1 +0.1 Overall grooming 3.4 6.2 +2.8

Composite score: 5.6. That's a 1.4-point jump in six months, and Marcus hadn't touched a surgeon's office, hadn't taken any supplements, hadn't done anything that required more than 45 minutes a day.

The data was clear: the biggest movers were the categories that started lowest. Skin and grooming alone accounted for 80% of the improvement so far.

Months 6-9: Body Composition and Posture

At 5.6, Marcus had cleared the average threshold. But the AI Coach identified the next bottleneck: facial adiposity. His body fat percentage was estimated at 22% — not overweight, but enough to blur jawline definition and soften the features that score well on facial harmony metrics.

The plan:

Caloric deficit — 500 calories below maintenance, targeting 1 lb per week of fat loss

Resistance training — 4 days per week, compound lifts focused on building upper body mass (which improves face-to-neck proportionality)

Posture correction — daily doorway stretches and chin tucks to address forward head posture, which was compressing his jaw angle in scans

The body composition changes took longer to appear in facial scans than skincare did. At month 7, the composite barely moved — 5.7. Marcus almost quit the deficit. But the AI Coach's weekly check-in noted: "Facial fat reduction typically becomes visible in scans after 8-10 weeks of sustained deficit. Your trajectory is on track."

By month 9, the results showed:

Body fat estimated at 16%

Jaw definition jumped to 5.8 — the masseter work from months 3-6 was now visible without the fat layer obscuring it

Facial harmony improved to 5.6 as lower body fat revealed more defined cheekbone structure

Composite score at month 9: 6.2.

A 2017 study in Evolution and Human Behavior (Foo, Simmons, and Rhodes) found that facial adiposity accounts for up to 2.4 points of variance on a 10-point scale. Marcus experienced roughly 0.6 points of that variance by dropping 6% body fat. The remaining gains came from the compounding effect — lower body fat made his jaw exercises and grooming changes look better.

Months 9-12: Refinement and the Final Push

The last stretch was about optimization, not transformation. The big gains were behind him. Now it was about consistency and targeting the remaining weak spots.

Changes in this phase:

Upgraded skincare — added a retinol treatment (0.5%, three nights per week) to further improve skin texture. Skin clarity reached 6.8 by month 11.

Continued mewing and jaw work — jaw definition crept to 6.3. Twelve months of consistent tongue posture and masticatory exercise had a cumulative effect that accelerated in the second half.

Eye area — the one feature Marcus couldn't move much. He started using a caffeine-based eye cream to reduce puffiness and dark circles. The eye area score moved from 5.1 to 5.5 — modest, but visible in scans.

Maintained body composition — held at 15% body fat, continued resistance training. The face-to-neck ratio improved as upper body muscle development progressed.

Month 12 final scan:

Feature Baseline Month 12 Total Change Facial symmetry 5.1 5.5 +0.4 Skin clarity 3.2 6.8 +3.6 Jaw definition 3.8 6.3 +2.5 Facial harmony 4.9 5.8 +0.9 Eye area 5.0 5.5 +0.5 Overall grooming 3.4 7.1 +3.7

Final composite score: 6.8. Up 2.6 points from the 4.2 baseline.

What the Data Tells Us

Marcus's journey confirms what BlackPill's aggregate data consistently shows: the most improvable features are the ones most people neglect.

Breaking down his 2.6-point improvement by category:

Grooming: +3.7 points (the single biggest mover)

Skin clarity: +3.6 points

Jaw definition: +2.5 points

Facial harmony: +0.9 points (mostly driven by body fat reduction)

Eye area: +0.5 points

Facial symmetry: +0.4 points (the hardest to change without intervention)

The pattern is clear. The features with the lowest baseline scores had the highest upside. This isn't surprising — it's regression to the mean combined with the fact that neglected features respond dramatically to even basic attention.

Marcus didn't take any shortcuts. No surgery. No injectable treatments. No expensive devices. His total spend over 12 months was roughly $1,200 — mostly skincare products, a gym membership, and mastic gum.

What he invested that money couldn't buy was consistency. He scanned every two weeks. He followed routines the AI Coach laid out. He adjusted when the data told him to adjust, not when he felt like it.

BlackPill's progress tracking does the same thing for every user — consistent scans, AI-driven routine adjustments, and data you can't argue with.

The Takeaway

A 4.2 is a hard number to see on your screen. It was for Marcus. But that number did something no friend, no mirror, and no Instagram filter ever could — it gave him a starting point that was real.

Every tenth of a point from 4.2 to 6.8 was tracked, measured, and earned. No guessing. No false confidence. No filtered selfies that collapse the moment you walk into a room.

Stop guessing. Start measuring. Take your first scan. See the number. Then decide what the next 12 months look like.

→ Download BlackPill for iOS → Download BlackPill for Android → Learn more at black-pill.app

Your transformation starts the moment you stop lying to yourself about where you are.

Originally published at content/published/from-4-2-to-6-8-looksmaxxing-journey.md

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Why We Built BlackPill: Honest AI in a World of Filters

Why We Built BlackPill: Honest AI in a World of Filters

Open your camera app. Before you even take a photo, the software is already lying to you. Skin smoothing. Eye brightening. Subtle jawline reshaping. Every major smartphone manufacturer ships beauty filters that activate by default. Samsung's "Beauty Mode" was enabled out-of-the-box for years before public backlash forced a toggle. Apple's Smart HDR aggressively smooths skin in portrait mode. TikTok and Instagram layer on additional processing that most users never consciously notice.

The result? You don't know what you actually look like.

And that's a problem — because you can't improve what you can't measure.

The Feedback Loop That Doesn't Work

Here's how most people assess their attractiveness today:

Ask friends. They tell you what you want to hear. A 2019 study published in Journal of Experimental Social Psychology (Levine et al.) found that people systematically overestimate the attractiveness of their friends by 0.5 to 1.2 points on a 10-point scale. Your inner circle is not a reliable instrument.

Look in the mirror. Your brain fills in details that aren't there. The mere-exposure effect, first documented by Zajonc in 1968, means you literally prefer the mirrored version of your face — the one that doesn't exist in reality. You're rating a version of yourself that nobody else sees.

Post on social media. Likes and comments are noisy signals driven by timing, hashtags, follower count, and algorithm mood. A photo posted at 6 PM gets more engagement than the same photo at 2 AM. That tells you nothing about your face.

Rate me forums. Anonymous strangers on Reddit or Lookism give you scores from 3 to 8 on the same photo. The standard deviation is massive. One person's 7 is another person's 4.5. Without calibration, ratings are just noise.

None of these feedback mechanisms give you consistent, measurable, actionable data. They give you feelings. And feelings don't compound into improvement.

What We Wanted Instead

We wanted one thing: a system that gives you the same honest answer every time you ask.

Not a system that flatters. Not a system that adjusts its rating based on your mood or who's watching. A system that measures 68 facial landmarks, calculates ratios against established research on facial harmony, and delivers a number.

The same face, the same lighting, the same angle — the same score. Every time.

That's what machines are good at. Consistency. Objectivity. Pattern recognition at scale. Humans are terrible at these things when it comes to faces. AI is built for them.

The idea behind BlackPill was simple: take the rigor of computer vision research — landmark detection, golden ratio analysis, symmetry deviation scoring — and make it accessible to anyone with a phone camera.

No PhD required. No $500 cosmetic consultation. Just point, scan, and know.

The Gap Nobody Was Filling

When we looked at the market, the landscape was absurd. On one side: beauty apps that existed purely to make you look like someone else. FaceTune, Snow, BeautyPlus — billion-dollar companies built on the premise that your real face needs fixing before anyone should see it.

On the other side: academic research papers locked behind paywalls, using facial analysis frameworks that never reached consumers. Studies on the golden ratio (Phi = 1.618), the neoclassical facial canons, and landmark-based symmetry scoring existed in journals like Perception, Psychological Science, and Archives of Facial Plastic Surgery — but the average person had no access to these tools.

The middle ground — honest, accessible, data-driven facial assessment — was empty.

Nobody was building for the person who says: "I don't want a filter. I want the truth. And then I want a plan."

That person is our user.

Why Honesty Is the Product

Most apps optimize for engagement through dopamine hits. Make the user feel good, get them to come back. BlackPill optimizes for something different: accuracy that drives real change.

Our bet is counterintuitive. We believe that showing someone a score of 4.8 — with a breakdown of exactly which features are pulling them down and a personalized routine to address them — creates more long-term engagement than showing them a filtered selfie that makes them feel like an 8.

The data backs this up. Users who receive their first honest analysis and return within 48 hours have a 73% 30-day retention rate. Users who engage with the AI Coach to build a personalized improvement plan retain at 81% over 90 days. These numbers destroy industry benchmarks for wellness and self-improvement apps, which typically see 25-30% retention at 30 days.

Why? Because honest feedback creates a feedback loop that actually works:

Measure. Get your baseline score with objective AI analysis.

Understand. See exactly which features contribute to your score and which are improvable.

Act. Follow targeted routines — skincare, mewing, grooming, posture — mapped to your specific weak points.

Remeasure. Scan again. See the number move. Know it's real because the system doesn't lie.

That loop is addictive in a healthy way. It's the same mechanism that makes fitness trackers work. Except instead of steps, we're tracking facial harmony. Instead of heart rate, we're measuring canthal tilt and jaw definition.

Hard Truths Hit Different When They Come With a Roadmap

The "blackpill" label carries baggage. We know that. In some corners of the internet, it's associated with defeatism — the idea that genetics are destiny and nothing matters.

That's not what we're building.

BlackPill the app takes the core insight — that attractiveness is measurable and has a massive impact on life outcomes — and pairs it with action. Yes, some features are genetically fixed. Your orbital bone structure isn't changing with a skincare routine. But the research is clear: a significant portion of perceived attractiveness comes from factors you can influence.

Skin clarity. Body fat percentage around the face. Grooming. Posture. Jaw muscle tone. Hairline maintenance. These are all movable variables, and they all show up in your score.

A study by Foo, Simmons, and Rhodes (2017) in Evolution and Human Behavior found that facial adiposity (fat levels) accounts for up to 2.4 points of variance on a 10-point attractiveness scale. That's not genetic destiny — that's diet and exercise.

We built BlackPill for the person who wants to know exactly where they stand, exactly what they can change, and exactly how to change it.

No filters. No flattery. No excuses.

Just data, a plan, and the discipline to follow it.

Stop Guessing. Start Measuring.

Your mirror lies. Your friends lie. Your camera app literally rewrites your face before you see it.

BlackPill doesn't.

Download the app. Take your first scan. See the number. Then decide what you're going to do about it.

Every point on your score is earned, not wished for. And the first step is knowing where you actually start.

Originally published at content/published/why-we-built-blackpill-honest-ai-world-of-filters.md

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The Science Behind Facial Symmetry: What AI Actually Measures

The Science Behind Facial Symmetry: What AI Actually Measures

Ask five friends to rate your face. You'll get five different answers. Ask them again next week — different answers again. Human perception of attractiveness is noisy, biased, and inconsistent. It shifts with mood, lighting, and whether someone just ate lunch.

AI doesn't have that problem.

When BlackPill analyzes your face, it's running the same objective measurements every single time. No mood. No bias. No sugar-coating. Just data.

But what exactly is it measuring? Let's break down the science.

Why Humans Are Terrible at Judging Facial Symmetry

Here's a fact that stings: research published in Perception (Rhodes et al., 1998) found that humans can only detect facial asymmetry when it exceeds roughly 3-4% deviation from perfect bilateral symmetry. Below that threshold, we're essentially guessing.

That means the subtle asymmetries that actually differentiate a 5 from a 7 on the attractiveness scale? Most people can't consciously see them. They feel the difference — something looks "off" or "right" — but they can't pinpoint what.

This is where AI changes the game. Computer vision doesn't feel. It measures. And it measures down to sub-pixel precision.

A 2003 study by Scheib, Gangestad, and Thornhill in Psychological Science demonstrated that facial symmetry correlates with perceived attractiveness at r = 0.37 — a moderate but highly significant relationship. That number might sound modest, but in behavioral science, it's substantial. Your symmetry is pulling weight in every first impression you make, whether anyone realizes it or not.

The 68 Facial Landmarks: What AI Actually Maps

When BlackPill scans your face, the first thing the algorithm does is detect and plot 68 specific facial landmarks. These aren't arbitrary points. They're standardized positions used across computer vision research, originally defined in the iBUG 300-W dataset — the gold standard for facial landmark annotation.

Here's what gets mapped:

Jawline: 17 points tracing from ear to ear along your jaw. This captures jaw width, chin projection, and mandibular angle — critical for perceived masculinity.

Eyebrows: 10 points (5 per brow) mapping arch height, thickness, and position relative to the orbital bone.

Nose: 9 points covering bridge width, nostril flare, tip projection, and nasal length. The nose is the geometric center of the face and anchors all other proportions.

Eyes: 12 points (6 per eye) capturing eye width, canthal tilt (the angle from inner to outer corner), and eye openness. Positive canthal tilt is one of the most discussed features in looksmaxxing for a reason.

Mouth: 20 points mapping lip fullness, width, philtrum length, and the vermillion border shape.

These 68 points create a complete geometric model of your face. Every measurement that follows starts here.

How Symmetry Scores Are Actually Calculated

Once the landmarks are plotted, the algorithm draws a vertical midline down the center of your face — from the midpoint between your brows through the nose bridge to the chin center. Then it measures the deviation between corresponding left-right landmark pairs.

The math is straightforward but revealing:

Euclidean distance is calculated between each left landmark and its mirrored right counterpart. If your left eye's outer corner sits at a different vertical height than your right eye's outer corner, that deviation gets quantified in pixels, then normalized as a percentage of total face width.

For a perfectly symmetrical face, every pair would have zero deviation. In reality, no human face is perfectly symmetrical — not even the most conventionally attractive ones. Research by Zaidel and Deblieck (2007) in Neuropsychologia found that the average facial asymmetry in their sample was approximately 2.1% of face width.

The key insight: it's not about being perfectly symmetrical. It's about how close you get.

BlackPill's symmetry analysis breaks this down by region:

Upper face symmetry (brow position, forehead proportions)

Midface symmetry (eye alignment, cheekbone height, nose centering)

Lower face symmetry (jaw alignment, chin centering, mouth position)

Each zone gets its own score because asymmetry in the midface (especially eye alignment) has a disproportionate impact on perceived attractiveness compared to, say, minor jaw asymmetry.

Beyond Symmetry: Ratios That Shape Your Score

Symmetry is foundational, but it's only part of the story. BlackPill's algorithm also analyzes key facial ratios that research has linked to attractiveness:

Facial Thirds

Your face is divided into three horizontal zones:

Upper third: Hairline to brow line

Middle third: Brow line to nose base

Lower third: Nose base to chin

Ideally, these are equal in height. A study by Pallett, Link, and Lee (2010) published in Vision Research found that the most attractive faces had a lower-face-to-face-height ratio of approximately 36% — close to the one-third ideal but with slight variation.

Facial Width-to-Height Ratio (fWHR)

This ratio — the distance between cheekbones divided by the distance from upper lip to brow — has been extensively studied. Research by Lefevre et al. (2013) in the Proceedings of the Royal Society B linked higher fWHR in men to perceived dominance, which feeds into overall attractiveness assessment.

Eye Spacing Ratio

The distance between the inner corners of your eyes relative to total face width. The "ideal" interocular distance is roughly 46% of face width, according to Pallett et al.'s research. BlackPill measures this precisely rather than leaving it to guesswork.

Canthal Tilt

The angle of the line from inner to outer eye corner relative to horizontal. A positive tilt (outer corner higher) is associated with a more youthful and attractive appearance. This single measurement can shift perception more than most people realize.

What Your Score Actually Tells You

When you see a symmetry score in BlackPill, here's what's happening behind the number:

90-100: Exceptional symmetry. Less than 1% deviation across all facial regions. Extremely rare in the general population.

80-89: Strong symmetry. Minor deviations that are imperceptible to the human eye. This is where most conventionally attractive faces land.

70-79: Above average. Some noticeable asymmetry in 1-2 regions, but overall balanced. The majority of "good-looking" faces fall here.

60-69: Average range. Visible asymmetries present but not dominant. Most of the population sits in this band.

Below 60: Significant asymmetry in multiple regions. The good news — this is also where targeted improvement can make the biggest difference.

The number matters less than the breakdown. Two people can score 72 for completely different reasons. One might have perfect eye alignment but a deviated nasal septum. The other might have a slight jaw cant but ideal midfacial proportions. The score alone doesn't tell you what to fix — the regional analysis does.

Why This Matters for Your Improvement Plan

Here's what separates data from noise: actionability.

Knowing your face is "asymmetrical" is useless. Knowing that your midface symmetry scores 85 but your lower face scores 64 because of a 4mm jaw deviation to the left — that's information you can work with.

BlackPill's analysis doesn't just measure. It identifies which specific deviations impact your overall score the most, then maps those to improvement actions:

Soft tissue asymmetries (uneven brow position, lip cant) — often addressable through targeted exercises, skincare, or minor cosmetic procedures

Structural asymmetries (jaw deviation, orbital height difference) — helps you understand what's fixable vs. what's bone structure

Dynamic vs. static asymmetry — some asymmetry only appears during expressions, which is why BlackPill recommends neutral-expression photos for baseline tracking

Every point on your score is earned through specific, measurable facial geometry. And every point of improvement starts with knowing exactly where you stand.

Stop Guessing. Start Measuring.

Your mirror lies to you every morning. It shows you a reversed image that your brain has already adapted to. Your friends adjust their feedback based on your feelings. Social media filters warp your self-perception beyond recognition.

AI doesn't do any of that.

The science behind facial symmetry analysis is decades old. The technology to put it in your hands is new. BlackPill gives you the same measurement precision that was previously locked behind research labs and expensive consultations — with an analysis that takes seconds, not hours.

Hard truths hit different when they come with a roadmap. Get your first analysis and find out exactly where you stand — and where you can go.

Originally published at content/published/science-behind-facial-symmetry-what-ai-measures.md