Darwin Analytics

[darwinanalytics]

3 easy steps to bring the lean start-up to content marketing

The lean start-up has a great point: there's no better way to learn than with experiments. They call it build-measure-learn, and it has been the working foundation of many successful start-ups.

The key to the lean start-up success is shorter feedback loops. The quicker you learn from mistakes and successes, the faster you'll achieve better results.

Can we bring the power of the lean start-up to content marketing, so you'll reach better results faster? Yes. Only three steps to take you there:

Lean start-up for content marketing

Define success To reach a goal, you first have to define it. Why are you investing in content marketing? Is it all about leads? Or do you care about engagement and reach?  The kind of goal you choose should depend on your overall strategy. For the lean start-up to work, you just have to pick one.

Build your hall of fame If you defined success, you have to illustrate what it looks like. What exactly are the pieces of content that helped you reach your goals? What kind of content converts? Or builds reach beyond your wildest expectations? Don't limit yourself to your own best practices. Look at what your colleagues are doing. Build your very own hall of fame with content success stories.  The goal of your hall of fame is to inspire and get inspired. Make it visual. Rather a Pinterest board than a boring excel file.

Get inspired  Success stories are the breeding ground of new successes. Walk through your virtual hall of fame before you write another piece of content. Get inspired by the things that worked well in the past, to build new content marketing successes in the future. And even more interesting: invite others to your hall of fame. Inspire new content marketing colleagues with all your best practices. 

The lean start-up is about learning faster. Every new piece of content is an  experiment. And every new experiment should be inspired by the results of previous experiments. 

How are you learning from your own successes and failures? Share with us on Twitter!

[darwinanalytics]

Launching our automated pdf reports

Darwin already has a nifty report feature that generates smart reports based on your goals. Smart, because Darwin will not just 'auto-fill' a template with your KPI's.

Learn from Darwin

We auto-analyze all your content across different channels, and we can tell you which pieces of content helped you reach your goals. That's not reporting, that's learning. 

Users asked: help us spread the knowledge

We got a lot of questions from users asking to make it easier to use Darwin smartness in their reporting. So we've worked with them to create a pdf export that does just that.

The content of a Darwin presentation

Darwin now translates all that Darwin smartness into a well-structured, easy-to-adapt pdf presentation you can use for reporting purposes. The presentation tells you:

How well you reached your goals

How each channel contributed

Which pieces of content had a significant impact

Score with Darwin

We hear users will use our automated pdf reports for two purposes:

Learning Because Darwin automatically detects your best practices, you can optimize your content marketing a lot faster.

Teaching Because Darwin proves how your content is linked to results, you can spend time teaching your colleagues or managers on how to improve those results.

If you'd like to find out how such a pdf report would like on your data, try it out during our free 14-day trial.

[darwinanalytics]

The vicious cycle that will trump your content marketing budget

Content marketing budgets are rising. Fast. It indicates high hopes for the results from these investments. And with high hopes come big disappointments. If you don't spend that budget wisely, you might enter the vicious cycle of decreasing budgets.

What the cycle of decreasing budgets looks like

You're budget is not big enough to spend money on Analytics.

Because you don't spend money on analytics, you can't prove the investments are paying off.

And because you can't prove content marketing ROI, the budgets will not increase.

What it feels like inside the cycle

When you're facing the question: 'why are we spending that money on content marketing?', it's already too late. Why? Because you'll need money to prove money.

How to get out

In french there's a beautiful proverb: reculer pour mieux sauter. Roughly translated it means: sometimes you need to cut back to be able to jump forward. 

You'll need to shift budgets away from operational work to Analytics. Only so you'll be able to answer the question of content marketing ROI, and justify increasing content marketing budgets.

How not to get in

That's the easy part. To prevent yourself from falling into the cycle of decreasing budgets, you'll need to preserve money to prove the money is working. 

Always, always ask yourself how you will justify the previous budget increase when you have to ask for new budget. When you can't answer that question, don't even spend the money.

[darwinanalytics]

How personalization leads to Frankenstein Marketing

Marketing automation lets you set up rules and triggers to feed specific content to a person based on their behavior or profile. But is this increasing individual relevance also interesting from a brand's perspective?

Are conversions the only that matters?

No. If they were, you could just pour all your money in AdWords and optimize on conversions. But no big brand was built on conversions alone.

It might be hard to defend in today's world where everything should be measurable, but branding, despite the difficulties measuring it, still provides the feeding ground for long-term growth.

Personalization versus consistency

Hyper-targeting to improve conversions are great for short-term gain. But can there be more than one Coca-Cola? Or more than one Nike? 

The biggest danger with hyper-personalization is aligning all these messages with your brand's image. It'll be increasingly difficult to find out which message you are conveying as a brand, and even more so: which messages truly trigger your audience?

Algorithms taking over

Machines learn the behavior and interests of your audience. Content marketers feed one piece of content after another to the machines. And machines automatically match the right piece of content with the right audience based on conversion performance.

It sounds futuristic but it isn't. Marketing automation suites enable this way of work. I call it Frankenstein Marketing. It makes content marketers look like line workers. Condemned to brainless copywriting, all in favor of optimizing short-term gain.

Strike a balance

It doesn't have to be this way. But the way out needs visionary marketers capable of looking beyond short-term boosts of conversion rates.

I'm looking forward to a wave of marketers who care for brand strategy and consistency. Because when conversion optimization is commodity, the brand you're marketing will make the difference.

Your two cents? Share them with us on Twitter!

[darwinanalytics]

How do you motivate teams to create more content?

I had the pleasure of meeting with a few companies recently who openly shared their content marketing issues. One of the most recurring issues was the effort it takes to get a team to write more copy.

The mental hype cycle

The amount of copy created by teams seems to follow the famous hype cycle. At first, everyone's excited about the opportunity to produce content for the company. But after the initial high, people start to lose interest.

The question is: how do you reach the plateau of productivity?

Define success

Paint a picture of what content marketing success looks like for the company. Is it a 200% increase in leads through content marketing? Or 500 downloads from your whitepaper collection? Define success and make it SMART.

Gamify towards success

Can you link your content to results? Use that information! Make a ranking of the highest performing content to stimulate competition. Hand out a weekly reward to the person with the best performing content. 

Instant reward

Monthly reports on content marketing performance become outdated even before they're published. Go from weekly to daily reviews of the best performing content, and your content marketing results will quickly be soaring through the sky. 

Do you have other ways to motivate your team to create more content? Share with us on Twitter!

[darwinanalytics]

Things just got real. What the Darwin Analytics redesign means for your content marketing performance.

Over the past few months, we've been rebuilding Darwin Analytics from the ground up. The rising need to measure and improve content marketing performance with Darwin Analytics, called for a scalable architecture and a light-weight, snappy front-end.

I'll leave the technical details for our Tiger Team to explain in a blogpost. Let me just zoom in on what this huge rebuild means for your content marketing performance. 

We analyze all your content

And guess what we find out? Some content clearly works, and other clearly doesn't. Your Darwin Analytics dashboard shows what you should or shouldn't be posting to improve your content marketing performance.

We link your content to bottom-line results

Which content drives people to fill in forms on your website? Darwin links all of your content to the goals you configured in Google Analytics. Prove your content has impact on the metrics that matter with our report dashboard.

Only we know the total impact of your content

Your tweets are not just bringing you new followers. That's just half the picture. Tweets bring you better e-mail opening rates, or an increase in search traffic.

We bring all your metrics and content in one place. Use the analyze dashboard to see the total impact of every piece of content.

Improve your content marketing performance

Find out for yourself how Darwin Analytics can improve your content marketing ROI. Get your 14-day free trial. We'll guide you to every step and help you get the most out of your content marketing efforts. 

[darwinanalytics]

3 ways to optimize content marketing like an AdWords campaign

First off: why would you optimize content marketing like an AdWords campaign? Because AdWords is the most awesome example of data-driven marketing. The results are staggering. In fact so staggering that AdWords has quickly become one of the most popular ways of doing marketing.

AdWords has become so data-driven, that robots are taking over with Real-Time-Bidding. Sounds nowhere near to content marketing...

There's a lot of creative muscle involved in creating content marketing winners. But there is a way to bring the data-driven strength of AdWords to the creative genius in content marketing. 

Three steps to data-driven content marketing:

Tweak daily (at least!) AdWords wizards are constantly tweaking their campaigns. These shorter feedback loops give them a huge advantage, because they improve performance a lot faster. The same goes for your content marketing campaigns and calendars. Use the data from all your different channels to constantly optimize your overall performance.

Link content to results AdWord ads are so loved because the reporting is so specific. "Hi Marketing Manager, this specific ad brought us 3 sales for a total of $2,000 and it only cost us $20." Bring the same level of detail to your content marketing performance: link the specific content pieces to results to illustrate the strength of what you do.

Report the hard numbers An AdWords report starts with total cost and ends with the revenue it generated. Those are hard numbers, and especially hard to argue with. Content Marketing should commit itself to the same standard of reporting if it wants to become a sustainable way of performing marketing.

These three steps are not impossible. But they do ask a lot of time. With Darwin Analytics, we do the hard work for you. So you can be the awesome data-driven content marketer, without losing your weekends. ;)

Get a free 14-day trial to find out for yourself.

[darwinanalytics]

Optimizing API-heavy page requests

At Darwin Analytics we rely on many external APIs. This includes the Google Analytics Management API. To get all the data we need we have to make a lot of requests to the Google Analytics API. However, making this many requests slows down the application significantly. This blogpost details how we dealt with it.

OAuth2

When a user decides to connect a Google Analytics account he is guided through the (in)famous OAuth2 flow. At the end of that flow, Google gives us access to read the Google Analytics accounts for that user.

Google Analytics uses the notion of accounts, properties and views. Every property belongs to one account and every view belongs to one property.

The Goal

The goal is to show the user a list of all his Google Analytics views, so they can choose which ones (one or more) to connect to the brand they track with Darwin Analytics.

The requests

To get a list of all the accounts of the user, we need to make a request to:

https://www.googleapis.com/analytics/v3/management/accounts

Every account has zero or more properties. The number of properties a specific account has is not returned in the first request. This means that we need to perform a separate request to:

.../accounts/{account-id}/webproperties

...for every account returned in the first request. First of all, keep in mind that when you have a Google Analytics account and you happen to delete a property, this property will still get returned by this request. Secondly, every property has a number that represents the amount of views that belong to that property. Remember: the accounts didn't have a property count attribute.

Moving on: we'd like to get all the views that belong to a property. We can do so with this request:

.../accounts/{account-id}/webproperties/{property-id}/profiles

We can decide not to perform a request if we know it is going to return zero views according to the profile's view count.

A real life scenario

Let's say a user has 3 accounts, and every account has 5 properties. Combining all the requests yields us a total of 1 + 3 + (3 * 5) = 19 requests. Most requests to the Google Analytics API took 70 to 90 milliseconds to complete on my development machine. Thus, even in the best case scenario, the requests will take at least 19 * 70 = 1330 milliseconds, or 1.3 seconds.

Unexpected problems

An additional issue that arose was a strange Google Analytics bug. Sometimes, a request returns an error without any reason. Performing an identical request again after several milliseconds sometimes does return the response we want.

Another problem is pagination. In the rare occasion a user has more than 1000 accounts, profiles or views, the Google Analytics API only returns 1000 entries at a time and requires you to make one or more additional requests. We don't have a client yet that has 1000 of any of these, but we still needed to add support for it. Just in case someone with that amount of profiles signed up.

Parallelism

This made us realize we needed to throw some parallelism in the mix.

Our application is made with PHP in the Laravel framework (4.1), the latest version. For debugging purposes, we use the Clockwork browser plugin which integrates with the Google Chrome DevTools. The Clockwork tool allows us to log certain things from the server side without messing up your HTML output like you would do console.log in the front-end. It also allows to track down time consuming parts of a request by logging it to the Clockwork timeline.

The screenshot below shows the timeline feature in the Google Chrome DevTools:

We use the GuzzlePHP HTTP Client to perform our requests to the Google Analytics API. This uses the PHP cURL extension but with an easy-to-use interface. By writing a Guzzle plugin I was able to log all requests to the Clockwork plugin. Every instance of a Guzzle Client gets a plugin attached to it which logs noteworthy events to the Clockwork plugin. The plugin logs status codes, tracks timing, etc.

To optimize the previously mentioned Google Analytics API problem, we made use of the Guzzle Multitransfer functionality. It's easy to use: create several Guzzle Request objects and passed them as an array to the Guzzle client's send() method. The client then performs a cURL multirequest. In doing so, we were able to retrieve all properties in under 90 milliseconds.

$client->setBaseUrl('https://www.googleapis.com/analytics/v3/management'); foreach ($accounts as &$account) { $requests[] = $client->get("accounts/{$account->id}/webproperties"); } $responses = $client->send($request);

We use the same trick to get all the views. The total time to retrieve all views takes the same amount of time as the longest of it's individual request. In theory, we should be able to retrieve a list of all the user's views in around 210 milliseconds. In reality, this takes about 240+ milliseconds on a slow development virtual machine, if none of the Google Analytics API requests return an error. The total time requesting the Google Analytics API does not increase as the amount of accounts or properties go up as long as the JSON returned doesn't get ridiculously long or as long as we don't need to do pagination.

Lessons learned

Use a debug tool with a timeline. It doesn't matter which one. We prefer Clockwork because it is clean and it does the trick.

Track which API requests take a while to complete, and try to group similar calls to perform those requests in parallel.

The user doesn't like waiting, so optimize.

[darwinanalytics]

Fixing the Google Chrome 'Aw Snap' error

Only kick-ass developers work at Darwin. And instead of keeping our knowledge to ourselves, we'll be sharing our development adventures on our blog. First in this series: a blogpost by Thomas Tuts, our Front-End Engineer. 

Out of nowhere, a mysterious error blindsided us that only seemed to rear its ugly head in Google Chrome 32. This is the story of how we beat it — with lots of patience, perseverence and pizza.

How it all started

On a (probably rainy, knowing Belgium) Thursday morning a client notified us that our app no longer worked on his install of Google Chrome. Indeed, we were instantly able to reproduce the crash — two of the three views in our app were no longer responsive and simply showed an 'Aw Snap' page, courtesy of Google Chrome.

Now, you might or might not know this, but the devious 'Aw Snap' is a victim of its own simplicity; it simply tells you what went wrong, but not exactly what, or how to fix it. This is pretty frustrating as a developer, since it means you're kind of looking for a needle in a haystack.

The crashes created no usable logs, so we had to get logs from the source — Google Chrome. After some cursory research, the best approach seemed to be debugging the actual Chrome binary to see what exactly went wrong. Doing so didn't yield a lot of interesting results (at least for someone not well-versed in Chrome internals, i.e. me). All we could make out from the logs was that the renderer was crashing for some unknown reason.

The War Room

Since it became more and more likely that this wasn't a bug we'd be able to solve in an hour, we decided to huddle up in a War Room. In total there were three developers: two back-end engineers and one front-end engineer (myself). The major problem with the app is that it's currently being ported; the old codebase was extremely bloated and unmaintainable (legacy code that was built before any of us got here).

The first step was reproducing the error on a local environment. To do so, we used Vagrant (which was already set up, but not fully configured yet). After some Vagrantfile fiddling, we managed to get it up and running. Lo and behold, the same crash happened on our local environment. This was A Good Thing™.

We managed to narrow down the error to the following two lines of code:

var focusPeriodStart = moment.unix(funnelStartDate).format('YYYY-MM-DD'); var focusPeriodStop = moment.unix(funnelStopDate).format('YYYY-MM-DD');

The funnelStartDate and funnelStopDate variables were genuine UNIX timestamps that didn't seem to indicate any bug-worthy behaviour, yet they were clearly the culprits of the crashes. After changing the code to calculate the date from the UNIX timestamp with vanilla JavaScript, we managed to completely eliminate the error:

focusPeriodStart = new Date(funnelStartDate * 1000); focusPeriodStop = new Date(funnelStopDate * 1000); focusPeriodStart = moment(focusPeriodStart).format('YYYY-MM-DD'); focusPeriodStop = moment(focusPeriodStop).format('YYYY-MM-DD');

To be honest, we're still not 100% sure what the exact cause of the crash was, and we probably never will be. Apparently, some people online thought the call stack size of Google Chrome got reduced in the v32 update. This would explain why the crash only started happening on Thursday - v32 was released roughly the evening before.

Lessons learned

When an ugly bug shows up, don't try to take it on alone. Ask other people to help out. Among other things, you'll be able to act as a sounding board for eachother.

Get rid of an old, bloated codebase as soon as you can. Eventually, some mysterious bug will turn up. When it does, it'll be insanely hard to debug; especially if you're not familiar with the codebase at all.

Trust yourself and your team. Things were pretty rough, but I was absolutely sure that we'd get to the bottom of it. I have complete faith in my team and its ability to quickly cope with difficult situations. The hiring process at our company is pretty rigid, so you can be damn sure you're surrounded with some of the most talented people you'll have the pleasure of working with.

When in doubt, order pizza. Obviously, it doesn't have to be pizza — just be sure to take a break now and then to stretch your legs. Distract yourself for a little while, and you'll find that you and your team will come up with a solid plan of attack.

[darwinanalytics]

Three ways to become a data-driven marketer

Interesting graph by our friends at Adobe. Marketers want to be more data-driven, but they feel like they're not doing a great job. Here are three ways to fix this:

Hire a consultant Get someone with a lot of expertise in digital marketing measurement. The upside: great consultants can build you a report about basically everything. And on the off chance that they can't - you must be asking weird questions - they'll be able to build you a report about the reason they can't build a report. The downside: well, you're depending on outside knowledge for a critical part of your business. Even consultants will tell you that's not a great idea.

Become a data-nerd There's a huge amount of courses out there to teach you about digital marketing analytics. The upside: you'll soon become the go-to person when it comes to marketing metrics and insights, and you'll be able to drive better, data-driven decisions. The downside: you'll soon be doing nothing else but working with metrics. Weren't you a marketer instead of an accountant?

Get a better analytics tool Maybe, just maybe, it's not you who's the problem. It's your analytics tool. If these tools you use are so hard to understand and so difficult to get insights from, should you be the one studying? We don't think that's fair. 

Marketing analytics tools are built for data-nerds

These tools are great if your goal is to turn marketers into accountants. But if your goal is to become a data-driven marketer, you'll need a different approach.

The fact is: You don't need an analytics tool with millions of graphs and metrics and pivot tables.

You need a smart analytics tool. One that provides you with insights instead of metrics. Overview instead of confusion. With:

All your marketing channels in one dashboard. 

Automated reports about how channels contribute to conversions.

Automated reports on your content performance.

And we've built this.

Because we love marketers. And we want to help you become data-driven. Not by turning you into an accountant, but by providing you with a smarter analytics tool.

Excited? Learn more.

[darwinanalytics]

Three reasons to ask for more data in Facebook reporting

Check the data source of any Facebook report, and you'll hear a lot about Facebook Insights. In fact: you'll only hear about Facebook Insights. And that's a shame.

You could find out a lot more if you were not just looking at Facebook data, but if you start pulling in some external sources. 

Three things you will find out if you stop looking at Facebook as a silo:

Facebook impact on other social media channels Combine your Facebook data with Twitter data for instance, and you might find out how retweets are having an impact on the amount of new fans. These correlations can get really powerful if you take other channels into account as well:

Facebook impact on your website You can use Facebook Insights to see how many people clicked your link. But how are these people behaving on your website? Are they converting or bouncing?  You'll need to combine all your Facebook Insights skills with your Google Analytics expertise to find out. But there's a huge amount of knowledge to gain: maybe Facebook is not that big in driving traffic, but the quality of that traffic might be impressive. 

Beyond conversion attribution Simply put: conversion attribution is about deciding which channel brings in the most conversions. The problem is: with people using multiple devices and browsers, tracking their behavior has become really difficult.  Because of this, Google Analytics doesn't always know when a conversion on your website originated on Facebook. But by combining Facebook and Google Analytics data, you will discover patterns in this behavior. You might see that a spike in new Facebook fans translates to a spike in conversions on your website.

Looking at Facebook as a data silo is really dangerous. You're making business decisions about your Facebook page without a complete overview on the facts. 

If you'd like to know what the complete picture looks like, ping us for a demo. Darwin Analytics tracks all your online marketing channels, to provide you with real insights instead of just metrics.

[darwinanalytics]

How to really know if a tweet was successful?

Of course favorites and retweets are awesome. But does it really mean your tweet was a success? Judging by the amount of brands tweeting lolcats, I guess not.

In a business context, a real successful tweet is about more than just making people laugh. Here are 3 ways to find out if a tweet was truly successful:

Did it build you a bigger audience? Having an audience ensures you of people receiving your messages. The reason you use Facebook, Twitter and a mailinglist is because you can communicate about new products and services to this presumably interested audience.  A true successful tweets brings in new audience members. These could be Twitter followers, but also Facebook fans or mailinglist subscribers.  To discover the true impact of a tweet, you'll need to combine the data about your tweet performance with data from Facebook and your mailinglist.

Did it educate your audience about your offering? These tweets you are sending out our tiny drops of marketing, educating the client tweet by tweet about the products and services you offer, and the kind of company you are. Getting twitter followers to your website and having them browse around for a while, is an import metric for twitter success. The more pages these twitter visitors consume, the more appealing your offering proves to be. 

Did it convert your audience? In the end, the goal always is getting people to *buy or apply*. People following you and consuming your content are merely steps in the process.  So what you really should do to measure twitter success, is combining your twitter data with your conversion data. You'll soon find out which twitter content is generating true leads on your website.

Not all tweets are created equal

"Are you saying all that engagement is meaningless?" you ask. Yes and no.

In the short run, you might be happy with engagement alone. But it won't last long if this engagement is not translating into one of the above. Engagement is what it is: a valuable means to an end. 

Find out how successful your tweets really are: ask us for a demo. Darwin Analytics combines data from all your online marketing channels, to provide you real insights instead of just metrics.

[darwinanalytics]

Report from the first Darwin Analytics Evolution event

There were two main reasons for us to host our first Evolution event. First, we wanted to thank our customers. Many of them signed up when Darwin Analytics was still finding its' way, and the feedback from these customers helped a great deal in building a top-notch product.

Secondly, we wanted to start a new chapter with our customers. Leaving behind us a year of mainly searching and experimenting, we're now starting a year of expanding on top of what we have already built. 

Below, you'll find the presentation about the past, present and future of Darwin. 

Darwin Analytics Event from DarwinAnalytics

  Finally, some great pictures  and tweets to remember a great evening. Thanks all!

Check out the cool t-shirt the guys from @DarwinAnalytics made. I'm sure you'll like it @garyvee. pic.twitter.com/cCWudzFebS

— Filip Verbrigghe (@filipverbrigghe)

August 30, 2013

I am the ROI of my mother. @anthonybosschem is on fire. #darwinanalytics @ Darwin Analytics http://t.co/v7kjYUPUlQ

— Sofie Verhalle (@lamazone)

August 29, 2013

Thanks again @anthonybosschem and co for the book and certificate.Tough we @mobilevikingsbe are ;-) http://t.co/phrh8RLBoy

— Dorien Aerts (@theonehitwonder)

August 29, 2013

@DarwinAnalytics knows how to 'work with' customers in stead of 'using' them. There's a big difference. #latertweet Proficiat gasten!

— Pieter-Jan Pauwels (@PJPauwels)

August 30, 2013

PS: If you'd like one of our 'I am the ROI of your mother'-shirts: become a customer or bring on a customer, and we'll send you one! :)

[darwinanalytics]

A brand new Darwin Analytics release: report, analyze and compare

Darwin Analytics gives marketeers and marketing managers the possibility to gain overview on all their online marketing channels. Here's how it looks:

A complete report, in two clicks

Reporting is key in a data-driven organization. Learning from the past enables you to experiment smarter in the future. So it shouldn't take too long to build or receive a report. 

At Darwin, we believe it should be two clicks. You select the timeframe you're interested in, and Darwin does the rest:

- Darwin shows you how your marketing goals are evolving for all your marketing channels. From your website to AdWords and from your mailingtool to Facebook, we cover it all. Darwin even explains why these channels performed as they did:

- Of course you'd love to know which of the content you posted is responsible for these results. No problem. Darwin automatically analyzes all the content you post, and presents you the content that lead to remarkable results.

Below you can see two Darwin tweets that lead to extraordinary results. The first one brought us more requests for trials, the second one a lot more engagement and impressions:

Discover cross-channel impact 

If you like to dig deeper, the analyze view will be your cup of tea. Discover if remarkable events on Twitter had an impact on one of your other marketing channels, or how more awareness on Facebook is leading to more engagement as well:

Why are you using a channel?

Every channel has its own merits. The question is: which channel are you using for what reason? We managed to build a view that answers this question perfectly. 

In one glance, you'll discover which channel is contributing to a specific marketing goal. Whenever you're launching a new campaign, you'll know which channel you should use. 

Questions, feedback, demo?

We love, love, love questions, feedback and - of course - demo requests. For any of those: get in touch, or leave your feedback in the comment box below.

Thanks for reading!

[darwinanalytics]

Sneak preview: automated reports on all your online marketing

We have a dream. To give you an overview on all your online marketing channels. To minimize the confusion triggered by too much, or unimportant metrics. And to make it easy for you to discover which of your marketing efforts worked, and which didn't.

Our dream is rapidly becoming reality. And we would like to give you a sneak preview on our progress.

Last week was a great marketing week for Darwin. This is how our dashboard looks:

A 23% increase in our goal (website leads). Twitter performed a little worse than normal. Darwin tells me I reached more people, but not the ones who are interested in becoming a customer.

AdWords on the other hand, did a lot better. We boosted our remarketing efforts thanks to some advice from Dries. The results are great: more people saw our ads, and those people were more likely to convert. A bigger and better audience, so to speak.

This feature is live in beta, and I think it's one of the best things we have ever built. It's easy and intuitive, and provides me with a great overview on all our marketing efforts. I honestly can't wait to show you how we are making this view even more powerful.

If you'd like to see a live demo of this feature, just let us know. You can reach us via Twitter, or the contact form on our website.

[darwinanalytics]

Party Time

We are throwing a party to say 'thank you' to our customers, make some pretty interesting announcements and hand out gifts. 

The exclusive invites will be sent out over the coming days. If the party is going to be half as much fun as it is planning it, our invitees will be in for a fun night. :)

[darwinanalytics]

Working at Darwin, what's that like?

When writing a job offering, we include all the big ideals: 'only work with the best people in the field', 'get top-notch working gear', 'get a monthly mentoring budget to hire someone to learn from', 'use free friday afternoons to work on your own projects', ... But big ideals only take you so far.

To really give you an idea of what it's like working at Darwin, I just asked the people working here to describe it. I didn't want to do any editing, so all typo's are the responsibility of the people quoted ;).

Improve yourself

As a young designer, I am grateful to get so much trust and responsibility at Darwin. Because Anthony really pushes you to make your own decisions and ensures that you are responsible for your own quality, you get the chance to build something you can be proud of. Your voice is heard! Not only will your skills be put to full use, you also get the chance to gain new ones or to expand the ones you already have. My co-workers and the people in the Darwin network are talented, which makes it a good learning environment. I'm proud to be part of this and help build it from the ground up.

Miet, user experience designer

Participation & transparency 

I only begun working 'for' Darwin Analytics recently. Yet it doesn't feel like I am working 'for' someone. Instead you get the opportunity to see a startup unfolding before your eyes and gradually help to build it along the way. Participation and transparancy are key values and they just fit me like a glove.

Dimitri, software engineer

Understand why you are building this software

Working for Darwin, for me, is: a team with an awesome sense of humor; having a chief that actually listens to his engineers; cool teammates who want to be the best in whatever they do; understanding why I'm building this software, and knowing why it benefits people.

Dieter, freelance software engineer

'Awesomeness'

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{

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        array('work' => 'required|min:7.6')

    ));

    if (!$validator->fails()) {

        return 'Awesomeness';

    }

         return false;

});

- Andreas, interim CTO

Pythonesque humor

Why I really enjoy working with the Darwin Analytics team: No need to endlessly push for even the tiniest bit of innovation within a corporate dinosaur: it's innovate or die!; A 'get things done' mentality with a good deal of pythonesque humor mixed in to keep the mood high up there; A clear vision of where to go, yet highly valuing and encouraging any employee's input

Peter, data scientist

This is where work gets done

Don’t let the relaxed atmosphere and the friendly people over at the Darwin office confuse you. This is where work gets done.

Working with the talented Darwin team boils down to improving an awesome product, and knowing that your input makes a difference.

- Mathias, freelance javascript wizard

If this sounds like a place you would like to work: check out our job page. We're currently looking for an experienced software engineer, and we're always on the lookout for (ux) designers and data scientists.

E-mail: anthony - at - darwinanalytics - dot - com.