RecoSense

[recosense-blog]

Benefits of a 360-Degree Customer View

The 360-degree customer view is a single end-to-end picture of a customer’s journey as well as experience with a company. It stresses on customers having an experiential relationship with the company, rather than transactional. This holds the key in long-standing customer loyalty and positive endorsements.

The 360-degree view enables the company to collect all-round information about the customer and leverage it to provide the most efficient and personalized customer service.

Statistical Overview

86% Buyers Pay More for a Better Customer Experience

CRM Market is Expected to Reach $80 Billion by 2025

90% Marketers Believe an Unified Multi-Channel Customer View is Important

Only 20% Among them have a Customer View

Fewer than 10% of Companies have a 360-Customer View

Only 5% of those Companies are able to Leverage its Power

The 6 Essential Benefits of 360-Degree Customer View:

Single Source of Truth – Offering access to data and integrity is fundamental for your organization’s success as it provides a single source of truth concerning your customers.

Data Driven Triggers – With the help of data-driven triggered events, organizations are able to interact with customers automatically in real-time to influence their buying decisions.

Accurate Reporting – It facilitates a consistent and accurate reporting of various activities and results.

Reduces Cost – Integrating a 360-Degree Customer View enables you to deal with your low value customers in a different manner.

Cross-Channel Engagement – Simplifying the implementation of cross-channel campaigns across different systems yields relevant and consistent engagement among varying multiple-channels.

Personalization and Segmentation – Allowing dynamic personalization and segmentation of different campaigns by using a wide-array of real-time behavioral attributes of the customers makes for more effective and relevant results.

The business world has gone through a change over the years. Today, there is an additional focus on customer experience, one that was distant in the past. The customer-centric landscape has allowed the introduction of holistic strategies and concepts that reap maximum results.

At RecoSense, we understand the importance of the same and provide the requisite solution to your company in your bid to provide a 360-Degree Customer Experience.

[recosense-blog]

Content Recommendations on Media Websites

“Books/Movies/Shows like XYZ”. How many times have you Googled the above phrase to get suggestions on your next entertainment escapade? Probably often. There is a wealth of content available online, and no matter how many filters you apply, it is impossible to go through them all to find what suits your preferences. So naturally, we turn to friends, colleagues, or even technology for content recommendations.

They know what we have liked so far, so they can tell what we might like next!

What Are Recommender Systems?

A recommender system, or a recommendation engine, is an algorithm based on cutting-edge technology such as Artificial Intelligence (particularly Machine Learning), which utilizes Big Data and customer behavior to make relevant and customized recommendations. These suggestions could be based on factors like past viewership/readership, demographic information, and search history.

Typically, recommender systems operate on the following models:

Collaborative Filtering

Content-based Filtering

Demographic-based Filtering

Utility-based Filtering

Knowledge-based Filtering

Hybrid Filtering

Why Should Media Websites Invest in Content Recommender Systems?

On the surface, the role of content-based recommendation systems is obvious: to narrow down the selection pool and enhance the digital customer experience. Naturally, tailored content would birth better engagement (think of all the hours one spends binge-watching Netflix!)

However, it also adds more value to your media website in the following ways:

Better Retention: As consumers get to explore content that interests them, they are more likely to explore your collection rather than opt for your competitor.

Enhanced Engagement: As the media website continues to make relevant recommendations, it becomes easier to target them with fresh or recirculated content.

Build Loyalty: Customers appreciate businesses that value their time. Through relevant content recommendations, you save them from a long-drawn search process and cut right to what truly matters – content consumption.

Increase Sales: For media websites that run subscription services, content recommender systems can serve trigger cues that facilitate sales and upselling.

Scalability: Content recommender systems operate on customer data and match it up with automated metadata generation, making it easier to scale up or down depending on the number of users.

Recycle Content: Content-based recommendations not only add to the digital experience but also capture highly specific interests of the user, and recommend niche content that very few other users may have an interest in.

How Can Media Websites Deliver Content Recommendations?

So, how do we integrate content recommender systems on your media websites? Here are a few use cases to get you started:

Suggest the Next Article or Blog Post

The struggle is real – a user visits your website, consumes a specific content, and leaves never to come back! Encourage them to read your other posts by suggesting highly-relevant blog posts and articles to each visitor.

Suggest Similar Content Assets Across the Website

Media websites that are focused on demand generation can offer other types of relevant content such as case studies, videos, and white papers to their visitors. But who goes around looking for these, right? A suitable strategy, in this case, would be to recommend this content as additional resources for their area of interest.

Make Search More Efficient

On several occasions, users who make use of search bars are looking for specific content. Obviously, they would not enjoy sifting through tons of content to locate what they seek. Websites, to aid these users in this quest, can suggest the most relevant content for every individual as they search.

Allow Users to Bounce Back to Previously-Viewed Content

Adding a feature along the lines of a “Recently Viewed” tab can make it easier and more efficient for the visitors to locate the content that they may have engaged with recently. As a result, they can effortlessly pick up from where they left off.

Incorporate Dynamic CTAs

Your media website may promote certain content on the homepage or any other prominent location on the landing page. But what happens after the user has already consumed that content? You wouldn’t want to miss out on an opportunity to engage them with something else and waste it on continuing to promote the stale content! Through a content recommendation system, you can replace it with new and meaningful content that will guide them down your website’s rabbit hole!

Final Thoughts

Content recommendation systems offer a unique opportunity to add value to digital customer experience and user satisfaction. However, companies must also add creativity to their algorithms to help users discover other aspects of your website.

So go ahead, and get recommending!

[recosense-blog]

Best Magento Extensions to Increase Sales of Your Ecommerce Store

The digital era has ushered yet another massive upheaval in the area of shopping. Generations of shoppers worldwide have been given the privilege of shopping from the comfort of their homes, pushing their urge to shop till they drop! The recent years have shown an unprecedented boost in the number of e-commerce websites as more and more entrepreneurs bring their products on the web. Entrepreneurs can now avail resources to bring out their best on ecommerce websites to give a hassle-free, engaging, and rewarding shopping experience to customers. 

Magento is one such ecommerce platform that integrates individualized preferences to make the website user-friendly and boost sales significantly. Here is a list of some of the best Magento extensions you can try to increase the sales of your Ecommerce store:

Elasticsearch

As an ecommerce website, one of the most disappointing factors is your customer’s search result coming up blank. This can be rather difficult to overcome without the right tool. As a Magento extension, Elasticsearch can enhance the search results on your site by increasing the search relevance.

Why Elasticsearch?

Here’s what Elasticsearch can offer to you:

The extension works on both Magento 1 and 2

It ensures a quick autocomplete

Offers automatic suggestions to enhance the user experience

Helps simplify and manage indexation

Offers a lifetime upgrade

RetailSensePersonalized Merchandising

Ecommerce sales can be tricky without the necessary data to optimize the site. RetailSense closes this gap by relying on artificial intelligence (AI) to personalize search for customers shopping online. The analytics behind consumer behavior has proven to help minimize bounce rates significantly while shopping.

Why RetailSensePersonalised Merchandising?

Here’s why RetailSense is the ideal extension for those looking to increase sales

The extension makes use of AI algorithms to understand consumer behavior and intent.

It helps retailers in creating customized offers to customers, using collated data and insights.

It offers a personalized experience through suggestions for consumers across the web.

The extension helps reduce bounce rates by making the experience more relevant for consumers.

Single-Page Checkout Extension

Long and confusing checkout procedures can often drive people away from completing their shopping. It has been seen that almost 70% shoppers leave the shopping mid-way, if they come across a checkout process that is too perplexing.

Why the single-page checkout extension?

Single-page checkout extensions can help a lot of ecommerce sites improve their checkout procedures and increase the number of conversions.

The number of abandoned shopping carts will reduce significantly.

Your customer’s shopping experience can end amicably.

You can reduce the time taken for customers to fill out forms and details.

Facebook Pixel

Social media certainly has been a boon to ecommerce businesses, especially due to its ability to advertise products to individuals based on their search queries. Facebook Pixel remarkets products that were searched on an e-commerce site to the users on Facebook with the help of stored data, in a bid to keep the product in the users sight for long.

Why Facebook Pixel?

If you are as focused on social media for your sales, here’s what Facebook Pixel can offer you:

Ease of product configuration on Facebook by exporting products that you want to be promoted

The extension needs no additional procedure to begin collating data once installed

The extension keeps a track of the events on your e-commerce website and uses that information on Facebook to personalize the promotion.

Google Page Speed Optimizer

Ever since 2018, the page speed parameter has been one of the key Google-ranking parameters. With the page speed optimizer as a Magento Plugin, your eCommerce site can be made more user-friendly and Google-optimized. The better the speed of the site, the higher the chances of faster conversions.

Why Google page speed optimizer?

This Magento extension comes with advanced features that are beneficial in the following ways:

The extension will ensure an improvement in your page performance

Your page will score higher on page-speed insights for Google

You can ensure a clear code structure

The product pages on the site will be optimized automatically

Google Tag Manager

Google Tag Manager is the perfect extension to have for site tagging as well as data-driven sales. The extension helps analyze data and consumer behavior in order to improve the store performance as well as the rate of conversion.

Why Google Tag Manager?

Here’s how this extension can help you increase your Ecommerce store sales:

The extension ensures Ecommerce enhanced with Google Analytics

It helps in dynamic remarketing, increasing the exposure of products among buyers

Comes with the Facebook Pixel plugin

Offers 70+ tag types

Additional Extensions for Customer Satisfaction

Delivery Date, Nosto, Yotpo Reviews are some other extensions that you can look at for increasing sales of your products. These extensions aid in improving your customer’s user experience with your ecommerce store, hence, leading to better customer loyalty, brand image, and hence, better sales in the long run!

Our take:

Considering all of the benefits of magneto extensions in boosting sales remarkably, it is evident that choosing the right extension can take your ecommerce store to newer heights. Keeping your brand objective in mind, be sure to go through the various features of the extensions and choose one that is most ideal for your site.

[recosense-blog]

Most Amazing Magento Extension for Product Recommendation

If you are reading this, chances are product recommendations are a source of trouble for you. Running a retail business with a few thousand or more customers means catering to their personalization needs. When a customer lands on your retail website, they come with the mindset of finding a product in a few minutes. If this product search is completed after a long-haul, the customer loses interest and leaves.

To avoid a situation like this, you can offer personalized product recommendations to users in less time. However, the journey is often tedious as it is not easy to understand the user intent and behavior of every customer when you are working at scale. For this reason, Magento plugins are utilized for personalization and product recommendation.

RecoSense Magento Extension

To help you avoid losing users, sales, and revenue, RecoSense offers a free Magento extension. Using a native technology ‘Knowledge Graph IP,’ RecoSenseRecoSense extension understands users and their related product semantics.

RecoSense Magento plugin can help you improve your conversion by approximately 11%, increase the value of your orders by 5%, give a 3x boost to your lifetime value, and provides 1.4x kick to repeat purchases. All these improvisations and enhancements lead to better revenue – up to a 15% increase.

Features:

RecoSense plugin has four outstanding features. Not only these features offer a comprehensive package but also allow you to understand your customer better for long-term success.

Personalized Merchandising

The RecoSense extension tracks the behavior of your users to evaluate user intent. Based on artificial intelligence, this feature allows the retailer to send personalized recommendations to the user over the web, email, app, and push notifications. For example, sharing similar products, encouraging the user to complete cart transaction, or displaying bestsellers.

One of the amazing functions of personalized merchandising is cross-selling products and items. A deep understanding of user behavior on the website or mobile app can help in understanding cross-products that might interest the user.

User Insights

Insights are essential to understand users personally. RecoSense plugin achieves insights based on varying factors like life-time value, purchase frequency, user interest, etc.

Dynamic Engine for Offers

Dynamic offer engine is another valuable functionality that allows your team to promote offers specifically designed for a user segment or user. These offers are selected based on the cart value, order value, and similar features relevant to a user group.

Providing better-personalized services to a defined audience becomes easier with RecoSense.

Semantic Search

Understanding the semantics of every user search allows RecoSense plugin to offer relevant search results to the users. This means that the semantic search functionality takes into account various attributes, auto-correct, synonyms, brands, and additional personalization into consideration when delivering results.

For instance, RecoSense extension will show search results for ‘watch’ even when the customer mistakenly typed ‘wach.’

Pricing Structure

If you have 10,000 or fewer users, you can initially start with the free version of the RecoSense Magento plugin. With the increase in users, you can upgrade to higher packages, which can be checked through this link.

For Additional Support

If you wish to try RecoSense Magento extension and understand its functioning, it is best to start with a demo trial. To request a demo, head on over to our website and explore more.

[recosense-blog]

Lesser Known Magento Tools for Open Source Recommendation Engine in 2020

You may have wondered how Google displays advertisements about the products you like. Where is the link? Why you? What makes you so special? For every eCommerce platform, you are a prospective buyer. Their business can prosper with your increasing consumption. Amazon, Flipkart, Alibaba, and other eCommerce platforms are all relying on the same. 

In fact, apps, like Spotify, bank on this system to give you the best music experience. And, all this has an open-source recommendation system at its core. This system is bridging the gap between you and the sites. 

What is this open-source recommendation system? 

A recommendation system works using algorithms to filter data and make different clusters of it. This is to simplify the data fetching process. eCcommerce sites and various apps with an interactive set use this to provide a customized experience. 

For these sites and apps, you are at the center. They try to leverage from your shopping experience. To do this, they use recommendation systems. These open-source recommendation systems track your clicks and collect personalized data. Various online sites expand their product line, learn about trends, and attract new customers using these tools. 

Magento is a one of the most productive eCommerce platforms. A lot of companies are using this as their premise. Magento offers a flexible shopping cart system. It enriches the experience by providing services regarding look, content, and functionality. 

But there are some Magento tools people do not know much about. Yet, they can boost the production rate.

 Hidden Magento tools that you should know about? 

Your eCommerce business can thrive on a few pointers like 

 Flexible cart

 Themes to lure in customers

  Content

  Product range

  Offers

  Customization

The complete architectural setup of your website uses some backend tools to make these outputs more effective. These are 

1. Magento 2 Product Questions 

To create a better customer-centric eCommerce page, you can add a section where customers can pose their questions. Sometimes, people lack in-depth knowledge about a product. This tool can help them counter their concerns. 

 Customers can add product reviews 

 You can restrict customer group to add more questions

  It enables you to customize product form

 This can add Q&A on the product page

  Creates space for mass actions using Q&A

 2. Magento 2 Product Feed

 This creates a bridge between your product page and other major eCommerce sites like Amazon, Alibaba, and others. It helps in creating product feeds on other buying platforms. 

  Comes with ready-to-use feed templates

  Feed templates can be customized

  Data feed delivery is fast

  Automatically generates product feeds

  Easy integration of Google Analytics 

3. Magento 2 Import Export Product Review 

Use one click and get reviews on import and export using CSV.

  You can import review data quickly including rating, review, titles, and others

 The CSV file ensures easy download opportunity and quick finish of the process

  It can export reviews into a CSV file

  It can support multiple Magento 2 stores simultaneously 

4. Custom Order Number 

Magento 2 custom order number tool is an effective way to secure sensitive data. Using this, you can change the order increment ID. The professional system is also good to lure in more customers and ensure better productivity.

   Order number customization is easy with the tool

  The number pattern is flexible

  Billing document number and order number are perfectly in sync. 

  It can change order increment ID

  You can customize order number prefix

  This tool is compatible with Order History, PDF Invoice, and Order Labels

 5. Daily Deal 

Magento 2 Daily Deal extension can effectively attract customers and transform them into repeat customers. The technology helps site managers to launch exclusive deals and reach the exact audience to profit from it. It boosts sales, and enhances customer retention policies. 

   It helps in projecting daily deals on the page with a countdown timer

  You can configure various limited daily deals easily

  Creating four types of deal pages is easier with the tool

  It can back up the sidebar widgets and bolster floating deal slider

  If you configure it properly, it can automatically create deals

  Deal labels are customizable and easy to manage

  You can set up the tool to ensure daily deal blocks display at any place

 6. Magento 2 Refund Request

 The easy refunding process is important, as this ensures a better customer experience. Magento 2 Refund Request allows customers to launch a refund request on the account page.

   Enables an easy process to launch a request for refund 

  You can manage a refund request in the backend 

  A convenient grid helps in better understanding of funding request

  Eases the process of sending customers about admin’s decision regarding funding

  You can customize the refund request pop-up for customers and ease the process of submitting their inquiries

 7. Free Shipping Bar

 Magento 2 Free Shipping Bar extension has several options to spur customers' shopping cart size by tempting him with offers. This highlights how much your customers can benefit from spending more on the store.

   You can set displays with free shipping offer

  You can set an appropriate message on cart total

  It offers flexible design

  It can make the process of customizing messages easier

 8. Ajax Search

 Ajax Search houses all advanced techniques that a consumer needs to search online. A drop-down list will show search list options on the basis of your typing. This will boost the consumer experience.

  It has Search Autocomplete mode

  Starts searching instantly

  It can provide back up for up to 10,000 SKUs

  You will benefit from flexible search configuration options

  It shows maximum search result

  Its design is perfect for bolstering all languages

Conclusion:

With almost 12% of the global eCommerce site, Magento is fast-becoming a trusted site for various players. Merchants are benefiting from its applications, and reports are showing three times hike in their businesses. Such a growth deserves better structuring to bolster market reach. 

 Magento 2 is getting huge traction for its simplified user-setting. These eight are some lesser-known but deserving tools for better applauds

[recosense-blog]

How disruption in news media is creating better opportunities?

Disruption has gone a long way with the rapid use of technology as it has transformed the way the news is produced, delivered and consumed across the world. Consumers have now become participants and users rather being only the readers and viewers. The news media have adapted itself with the pace of this evolution. From the latest cricket score updates, interviews, budget, weather or opinion polls – disruption has changed the business models because of the rapid use of technology, social media, gadgets, automation of processes or innovation with respect to products and services.

Disruption in news media has also changed the way people think and react. It engages people to adapt to new ways of communication. It also leads to the formation of new ideas and expectations and requires a journalist to be innovative and creative. It requires businesses to stay updated and ahead of recent trends and be desirable and competitive for their audiences. This creates an impact on the stages of planning, executing and managing a communication strategy.

The big data analyzes the consumer interests, consumer behaviour and content marketing automation that play a key role in enticing the audience to actively participate through group discussions, forums, doing tweets or posts, leaving comments or feedback beneath the news section page.

About News Media Stagnation

News Media in the form of advertising became popular in the United States around 1880 as a $200 million dollar industry. Across 40 years, it became a $3 billion dollar industry. Till 2019, news media is a 240.7 billion dollars industry, with digital media accounting for exceedingly half of the advertisement spent, and print media decline by 18%. in the 19th century, this wasn’t the scenario. The news medium for advertising has changed dramatically as technology has gone more advanced, but digital is more promising towards educating users with the ready content in the right manner at the right time.

As per the 2018 Nielsen report, TV and radio are still active and at pace with 88% of media hours are spent watching TV and 92% of media hours are spent listening to radio per week. That is a consequential amount of time dedicated to those two traditional mediums, and it doesn’t appear to be slowing down any time soon.

This article throws light on the problems caused due to digital disruption and laying down effective solutions with remedial measures. It also talks about the benefits of digital disruption through digital transformation that has changed the journalism trend of advertising news from traditional to digital. The users will be able to learn about the opportunities brought by digital disruption in news media and how digital transformation has changed the way of engaging audience with rapidly available content at the right time instantly. It will also discuss how RecoSense can help News Media in disruption.

Problems surfaced between traditional media and Digital Media

What digital disruptions have occurred in News Media?

The virtual reality is the biggest disruptor to be seen in the media and entertainment industry today. With technologies such as Facebook 360 and YouTube 360 permits millions of consumers to interact and experience with content from distant away through very natural and immersive human experiences. The rapid availability of low-cost 360 cameras combined with dynamic streaming technology will further emulate the content creation by permitting people to create and distribute VR experiences without any special equipment.

As per Jennifer Cooper, director of industry strategy in media and entertainment at Adobe:

“The biggest forces involved in disrupting media have resulted in the “tug of war” between linear, traditional and digital channels, and the consecutive monetization models can be put to use across linear and digital. The consumer expectations are propelling media companies to offer maximum digital content across all channels with access devices that continue to emerge. This leads to disruption in the audience measurement models and monetization”.

How News Media failed to adapt?

The news media failed to adapt to the changing times of digital technologies due to a lack of innovation and evolving from its present state to a new way of serving content paradigm.

The new media landscape has demeaned the traditional model of print journalism that the Times clasp to nostalgically.  Readers now no longer give privilege to the news the way the newspaper package it for them.

Both the newsroom and the business sides remain concentrated on print subscribers who now account for a small percentage of readers. While desktop readers are six times as many, yet monthly home page visits collapsed by nearly half between 2011 and 2013, one of several remarkable data points provided by the news report.

Solutions to Digital Disruption

Leveraging Digital Disruption and emerging technological shifts

Digital disruption has brought digital transformation (also DX or DT) through the development of technologies which has created value for the news media industry and its customers in the best possible manner. It helps the industry to innovate and adapt to the changing circumstances.

Digital transformation drives the cultural, organizational and operational change in the news media industry and its ecosystem through smart integration of digital technologies, processes and competencies throughout all levels and functions in a coherent manner. In advanced countries like Japan where digital transformation is focussed to impact all areas of life with the country’s Society 5.0 initiative, which goes away beyond the limited industry 4.0 vision in other countries.

One best shift through digital disruption can be seen actively in digital advertising that fundamentally changes the landscape for what comprises a feasible business model. For example, advertisers are willing to pay millions of dollars when it comes to YouTube videos and other content communication channels. This has given avenues for new digital technologies to transform how products are designed, the way consumer feedback is collected and examined, the way payments and funds are transferred and where and how people travel.

Emerging trends like podcasting, videos are not sufficient

Even millennials are using news media channels to voice their opinion, educate the masses about their emerging start-ups and promoting their businesses products and services. The use of regular videos and podcasts keep the individual in limelight and gain public recognition and become a face value of their business. With its regular use, the individuals are able to develop their own brand and publicize their businesses and gain more clientele from across the World. Not only this, news media is tiresomely involved in covering the LIVE highlights from across the World whether the news outburst is related to any flood, riots, damage or any issues cropping up in any segment.

Even though videos and podcasts are not sufficient to vocalise the news gathered from across the World. The news media is gearing up to bring a sea change in the distribution of content as podcasts still does not create enough content to attract the right type of audience that would sit down at a particular time such as 7 pm and watch CBS or NBC every night. The shorter content to listen via podcasts have given fumbling experience to many to check on their phones every few minutes to listen to the next episode which has not made the trend go for long. However, with the  introduction of smart speakers have given access to the shorter length sub-five-minutes podcasts to play have actually atomized the audio content. Now, content is readily accessible while brushing our teeth, sleeping or commuting have optimized every part of everyone’s day to day life.

Rapid emergence of AI and machine learning technologies

With the emerging technologies of AI and machine learning in the news media industry, the bulk data work is dedicated to audience understanding: the type of audience for which it has been designed to read, listen and watch the kind of media and entertainment content. Due to this, audience insight can easily be gathered that can inform anything from business strategy to marketing and content creation. The application of ML tools has turbo-charged the user experience as it can tag your image or text archive for a better search experience.  The recommender system brings in relevant content to readers, watchers, and listeners. As creators are involved in developing new content, installing recommender systems that can autosuggest the image assets for articles for example: displaying such image assets without any copyright limitations to such target image. sequence-to-sequence learning can easily translate your content in one language to another (for example: German to English) permitting your content to reach distinctive audience more quickly. Even, representation learning at the crux of neural networks permits to make use of more unstructured data such as image and text data, more simplified unlocking novel and exciting use cases.

Benefits of Disruption through digital technologies

The introduction of digital technologies have lead to the reduction in the circulation of mainstream newspapers and the art of consuming news, accumulating and writing more democratised, the need for journalists to be active on the digital platform becomes essential.

It is only that a few newspaper houses understand the relevance of the digital platform which has maximised the opportunities in order to reach a wider readership, thereby investing in the human capital for the best delivery.

The events watcher in the industry has observed that in this era of media disruption, organisations today must likewise confront with opportunities and threats implicit in a couple of emerging technologies. They must administer a multitude of data-driven, tech-centric tasks such as social media analysis, audience measurement, and cross-platform app implementations.

In the same way, disruption benefits can also be witnessed in the following segments:

Digital transformation with personalized user recommendations

Digital technologies have changed the way people engage with news media content in the right way, at the right medium and at the right time. Whether it is related to the interview of a favourite celebrity, breaking news, weather, political news issue or sports – every type of content is accessible straightaway to them through their devices. No matter the language, it is accessible in all regional languages categorising the content piece of their personal interest. This is actually known as personalisation. The news media have changed so much that it seeks the opinion of people on a political issue or tragic event that makes the issue more strong for the judiciary to take an action against it.

1. Increased re-engagement

Disruption has leveraged personalization to increase re-engagement with the use of push-notifications. Using push notifications strategically remind the users about their app. Push notifications should be used in the right manner whereby too many useless notifications can easily annoy app users. Even irrelevant push notifications fail to increase the engagement of users. In both cases, users could end up deleting their app. Therefore, it is recommended to use segmentation and customise the message according to individual users. This will permit you to build different content strategies as per the type of profile you want to target. Also, incorporate the users’ demographics (such as age, location, gender, etc.), favorites, or recently viewed items for example. This data will generate powerful and customized messages that will make the customers feel special as it will be a one-on-one conversation. This will particularly induce them to re-open their app and check out on the latest offerings.

2. Making News participatory using social media

The way users have changed the tools for getting the information, newsroom too has changed the tools to present the news and gather it. Facebook and Twitter have become heavily social media channels for making the news participatory among users. In this digital age where information can be disseminated quickly, there’s no far much better tool to do it almost the same way that Twitter, Facebook or the news website does. It is clearly understood that no one is going to wait until 5 p.m newscast to watch the breaking news story that happened at 2 p.m.

Even Live streaming has also emerged as the latest example of how users have started expecting a personalized experience while viewing the content online.  Hulu, Roku, and Netflix have changed the ways to engage the audience and offer them a niche personalized version of what they want and when they want.

As per James P. Mahon, news reporter at Chattanooga, Tennessee’s WDEF News 12, “During breaking news and extreme weather situations, we can bring emergency press conference info straight to the viewers who need it.” This lead to informing the users about the immediate happening occurred at the time when they are busy watching other news.

3. New ways of growing subscriptions – A massive shift in Journalism

Disruptions of news media are in the league of distributing meaningful content to the audience and monetize it in a better manner. The users are more keen to pay for direct access to premium, high-quality content instead of settling for free programming that used to be subsidised by advertising. Various publishers continue to fight for attention by creating compelling content just as the value of these efforts reduces; no matter changes the game.

The quantity game has become more of the quality game, and only the best content administrator, whether media companies or marketers who have achieved subscribed users will proper in the attention economy.

The lower capital costs of digital publishing with free access for readers helped drive the demand from users and established digital as the basic distribution platform. Digital content production volume was greatly influenced by search engine algorithms. The model was expectedly elastic-creating more content, hence building wider audiences and earning more revenue.

NYTimes.com is known to be good for deeper engagement for its subscription business. According to Jeff Bezos in an interview on Washington Post business: “We attempt to be customer-centric, which in the case of The Post means reader-centric.”

Moreover, the Ponyster Institute has indicated the shift as the “service era” of journalism, where the journalism is paid for the readers, by readers. The Atlantic’s How to survive the media apocalypse, later on, endorses this journey forward, suggesting that digital media should welcome the rise in reader subscriptions and effectively hinge on monetization strategies.

4. Leverage real-time, viral, and brag-worthy news

With the deployment of powerful algorithms – artificial intelligence, machine learning, and google algorithms optimize the real-time, viral and brag-worthy news to be on the top of the page before the user visits the website or app. It has effectively given competition to many news segments to be updated from all categories with the latest updates or breaking news to be displayed or showcased through videos on the main page.

With traditional news media have only confined to print have compensated the loss endorsed towards digital media through digital technologies. The digital transformation has been able to gain wide viewership access with a high engagement rate.  It has not only personalised the news content but to due consistent emergence in technologies have successfully been able to deliver the updated news in the niche segment to a particular user in the right way, at the right time, at the right device.

How RecoSense can help News Media?

RecoSense with the deployment of AI assist digital publishers in personalising their user experience with an expandable search and intelligence delivery platform. It helps users to access content with respect to their personalities, topics and categories of search without any direct input. Furthermore, RecoSense can help News Media in the following ways:

Automated Metadata Generation for video and text articles.

Delivering personalized suggestions to every user through the home page, category page, content detail page, In-video suggestions etc.

Delivering  highly significant search queries

Increase in audience engagement through multiple ways of In-video suggestions via video player plugin.

Making them understand the reactions and behaviors of your user segments to the contents displayed in front of them through Analytics and User Insights.

Makes the users engaged with personalised notifications through push notifications, emails of the live updates, movies or genres.

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If you don’t personalise, you lose!

 Many of the eCommerce sites are still on the rising pressure to personalize their brands or products. This may include referring to the name tags consisting of the receiver's name in their email campaigns, sending abandoned cart emails or recommending products depending on previous purchases. 

More than half of the consumers believe personalization would be more likely to gain consumer loyalty. As personalization brings more value proposition and does well around each customer segment, it's a way for brands to inspect the offers, messages, and experiences they deliver as per every visitor's unique profile. 

Personalization is used for making a more subtle, organic and authentic relationship with the customers by presenting them the relevant content for which they are searching for over the web. It brings more perceived supposition in order to induce the interest of internet surfers making them convert into final customers.  

Personalization is most suited for retail/eCommerce companies who are always stressing on the need using data analytics and the audience to fulfill the individual needs of a consumer. Like brands, if you don't personalize to what your customers are saying or looking for, you won't be able to serve your customer closely by recommending him/her a particular product or service without crossing the creepy line. 

Personalization doesn't mean that you are inhibiting the personal space of a particular customer rather looking into the tiniest details of each customer's experience that can influence their purchase decisions. 

There's no doubt that personalization influences conversion rates. Personalization can be done through email or the websites as the numbers reported to be 65% and 61% respectively.

 Personalizing your email campaigns is a methodical way to scale up your open and click-through rates and can have a measurable impact on your revenue and ROI. Various research studies have revealed emails with personalized subject lines have a 26% likelihood of getting opened up than those without personalization and Rich Relevance has discovered that the revenue gets scaled up at 5.7 times higher via emails that use personalization tactics. 

On the contrary, website personalization is a straight away tactic on the homepage by offering the Internet surfers or prospective buyers: 

·         Deals recommended for you

·         And products inspired by your Wish List 

This way, the retailers advocate their power of conversions across the board which brings them almost guaranteed results. 77% of the marketers believe that employing personalization has given them spontaneous results while 60% of them still struggle with implementing it.

 Although many companies don't personalize, so let us know the outcomes to what happens if you don't personalize: 

without personalized emails, you will lose 6X higher transaction rates.

without personalized emails, you will lose click-through-rates by as much as 14% and conversions by 10%.

you won’t be able to change the internet surfers’ next call-to-action i.e. leading them into the next step of the procedure.

you won’t be able to demonstrate your services through personalized videos via emails that could have lead to the increase of your email’s click-through rate.

you will see a 26% fall in open rates.

you will see 5.7 times fall in revenues.

80% of the brands without tailoring products are most likely to lose their customer’s loyalty.

in-house marketers witness 19% downwards in sales if they don’t personalize their web experiences.

Brands without AI capabilities fail to provide the consumers with the appropriate products in real-time.

you won’t be able to discover who, when, where, and how to reach buyers and prospective buyers using AI and machine learning.

you won’t be able to tap 95% of purchasing decisions that take place in the subconscious mind of your prospective buyers.

96% of marketers will lose their advancement in customer relationships.

More than 90% of the bounce rate will happen means more than 90% of the customers will leave your website and make a purchase somewhere else.

93% of companies will witness a fall in conversion rates if they don’t personalize.

78% of shoppers won’t likely to buy again.

71% of shoppers won’t be keen on buying again if they don’t get targeted offers based on their location.

Around 75% of potential customers will be frustrated with irrelevant products that are not specific to them.

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How can agencies help their eCommerce customers with personalization? - RecoSense Blogs

It might not be possible for all agencies to implement personalization for their e-commerce customers with their present set of employees and staff. This is where RecoSense comes in. We have partnered with agencies to make personalization a possibility for their eCommerce customers.

Personalization is showing individualized offers, products, discounts, and content to your customers and visitors based on several parameters.

Personalization in eCommerce can have a huge impact on your business. It helps drive more engagement, revenue, repeat purchases, and increases customer satisfaction.

Personalization ensures whatever you are presenting to your site visitor or customer is highly suited and relevant to them. Seventy-four percent of people hate being shown irrelevant content on the internet.

This can be attributed to the shrinking attention span or the demand for better customer services and experiences.

[recosense-blog]

5 personalisation tips for small eCommerce businesses to boost sales

eCommerce personalization can go a milestone in building up a relationship with prospective buyers. It personalizes with every customer by giving them individualized offers, product recommendations and relevant content subject to their previous activity, demographics and other personal data.

As per the latest eCommerce personalization trends, every customer wants more instead of less personalization. According to the market statistics,

74% of customers get disappointed when showing them irrelevant content.

90% of customers believe personalization is meant for the future.

48% of customers like to spend more when their experience is personalized

Personalization is just a way beyond greeting the customer only by their name when they visit your website. Just follow the simple 5-easy-to go steps for making personalization more effective to your businesses:

(1) Provide Tailor made content

Provide every Internet user with meaningful information relevant to their searches. Make use of Artificial Intelligence and continuous machine learning for showing the products and offers that are essential for every customer group irrespective of their profile. AI helps in drawing customer data subject to their likes, dislikes, trends and behaviour and your own customer focused recommendations, personalized search and merchandising that lead to highly effective improvements in online conversion rates. When you know what the buyers are searching for, provide them with relevant content which helps them to make up their mind. Once the purchase is finalized, provide tutorials and instructions to the customers for making the most of their products.

(2) Make the buyers move throughout the buying process

With personalization, you can track every customer through every step of their buying process. You would get to know when to greet the customer by the name when to share with them about more product information which interests them and which products to recommend.

(3) Offer them better product recommendations

These are based on buyers’ previous purchase history. Show them the previous products under different categories, prices, and sellers which induce them to take a look at and prepare their minds for final purchase.

AI-based personalized e-commerce platforms gather behavioural data of each single website visitor with respect to views, searches, purchases and even time of day or amount spent. Analyze the data and identify relationships that help clustering the data as per different customer segments. Classify the users into first time visitors, special cart promotion to VIP customers or offer 25% off during a seasonal duration for all customers who have not purchased in the last 6 months.

(4) Handle the data and deliver a personalized experience across all users

Analyze the large volumes of customer data in real-time using Big data and predict the frequency of every visitor to convert depending on historical interactions of visitors and customers on your website. Provide touch base to every customer and work on segmenting the buyers according to their wishes, wants, tastes, income and any other descriptor you can think of.

(5) Work on maximizing the segmentation benefit

Make use of pop-ups that encourage the users to sign up for your mailing list, loyalty program or newsletter. This will increase your contact list and help you in setting email marketing campaigns for boosting sales.

Offer free-shipment: Free shipment generates customer loyalty and increases future sales.

Reduce the shopping cart abandonment in the following ways :

Create a user-friendly interface to ease out the navigation and check out process.

Send shopping cart abandonment emails

Increase the trust of the prospective buyers by showing them trust symbols and valid SSL certificate

Show them price match guarantee

Give them guest checkout option

Positive customer reviews that build trust through ratings, customer testimonials and reviews which builds the market reputation and creates an impact on other customers to buy from you.

Set automated email marketing campaigns to prospective buyers navigating on their current activity inducing them to take further action such as encouraging cart abandonment users to revisit the site and complete the transaction.

Provide excellent customer service via social media, live chat, email, phone or customer service centre or helpdesk for resolving the immediate queries of the customers.

Reward your loyal customers via loyalty programs, reward points, discount coupons or free shipment that encourages maximum sales.

Sell your products in any innovative way by churning out new innovative marketing ideas to boost up the sales.

[recosense-blog]

How an AI-Driven Magento Plugin Can Help eCommerce Companies Grow Revenues

Artificial Intelligence is powering a better world with advanced solutions and intuitive applications. Everything from manufacturing to e-commerce is getting intelligent and smart, thanks to artificial intelligence. AI has found several use cases across industries, leading to digital transformation — which many companies are now experimenting and implementing.

Especially in the eCommerce space, AI can do wonders for businesses by enabling better insight into customer behavior and a corresponding shift in personalizing their user experience. AI is rapidly becoming a promising technology for online stores are striving to compete in an overcrowded market and differentiate the experience they offer their customers.

The eCommerce industry is set to gross $700 B by 2022, according to Statista. Let’s look at how artificial intelligence can be one of the driving forces behind the growth and expansion of the industry.

Use Cases of an AI-Enabled Magento Plugin For Online Retail Stores

Core technology and retail automation companies are now coming up with innovative solutions for online stores that could enhance the quality of experience they offer their customers, enabling them to earn more revenue and keep customers coming back to them.

RetailSense is one such AI-based Magento plug-in. Let’s look at a few ways such a plugin can be beneficial for an eCommerce business.

Learn buyer intent

The buyer might not be mentioning all they need when coming to your website. AI can help you learn about the buyer’s purpose in-depth by looking at various parameters, including their past purchases, cart items, unfinished transactions, browsing behavior, and more. By learning about the detailed buyer’s intent, you can enable a smart plugin to make decisions concerning product displays, recommendations, and pricing.

Personalized merchandising

Merchandising on an online retail store is no more accessible than it is in a physical store. To make things simpler for you, an AI-powered plug-in can help you optimize merchandising on various pages of your website to drive more revenue through relevant product suggestions. These might include similar products, popular products in the same category, frequently bought together, previous purchases, and so on.

Customized product suggestions

Automated and personalized product recommendations are responsible for driving 35 percent of Amazon’s revenue. AI-powered real-time product recommendations can weigh in on multiple factors such as buyer intent, behavior, lifestyle, search queries, past purchases, and current interest to show highly relevant product recommendations. Since AI has its foundations dug deep into big data, the technology is well-positioned to make hyper-personalized product recommendations that speak to a customer’s needs and interests. By enabling such an intuitive functionality in your online eCommerce store, you can encourage customers to return to your site, gain higher visitor retention, offer a better customer experience, and leverage browsing habits to generate more revenue.

Dynamic offers and discounts

Customizing offers and discounts for various customer segments can help you appeal to them based on multiple conditions. An AI-powered engine can help you lay down offers for a well-defined audience, segmented as idle visitors, loyal customers, and so on. Artificial intelligence can also be used to create personalized discounts based on the total cart value. Dynamic offers can be free products, free shipping, or discounts on specific products.

Intuitive search functionality

Product searches lie at the heart of any eCommerce store. But, converting search queries to sales takes more than displaying the products by the specific keyword. AI-powered searches can be more fine-tuned to an individual’s inclinations. Artificial intelligence can take into account customer browsing patterns, social media footprint, last purchase, etc. by pulling this information. AI can leverage more than the search query to display intuitive and more sensible product recommendations. This, in turn, drives higher purchase values, better experience, and, ultimately, more profit for your e-commerce business.

User analytics and insights

The role of artificial intelligence in eCommerce borders around taking data and offering insights on deep analysis. 61 percent of marketers already consider AI as a part of their data strategy, says MeMSQL. AI can switch on predictive analytics for any eCommerce business, which can be its biggest blessing. User analytics and insights can be used in an eCommerce business throughout several operations. Businesses can gain granular intelligence, analyze customer segments, and profile and rearrange customers with newer insights. Artificial intelligence in eCommerce can also help companies reduce the need for human expertise, lading to cot optimization.

Benefits of an AI Magento Plugin for eCommerce Companies

AI-powered plug-ins such as RetailSense can mean so much for an eCommerce business, including:

Increased conversion rates

By personalizing the entire customer experience, you can attract visitors by displaying relevant products and appealing to their interests. Customer-centric search functionality, product displays, and so on work to attract visitors to your website and convert them into loyal customers.

Improved average order values

Customized product recommendations and in-depth insight into buyer behavior can help you increase the cart value for each customer by providing relevant suggestions that spark buyer interest.

Higher total number of orders

Bring customers back with personalized offers and discounts. Higher perceived value for a customer means repeat orders. AI can help you roll out deals and discounts to bring back dominant customers.

More revenue

PointSource found that the presence of AI brings customers not only to shop frequently but also to spend at least 34% more in order value. All of the previous impacts can be summed up to prove AI, when used appropriately, can drive better revenue for your eCommerce business.

Conclusion

RetailSense is a smart recommendation engine, AI-powered search feature, analytics tool, dynamic offer engine, all rolled into one. Its intelligent capabilities can help you build a differentiated offering in the overcrowded eCommerce space.

With AI-powered RetailSense, you can grow your online store and thrive in your business. Learn more about the plug-in that makes it all happen for you.

[recosense-blog]

Top Trends in Cognitive Computing

As we have arrived in the third decade of computing –the cognitive decade–and it will bring on a fundamental change in the manner humans work with machines. There will be a breakthrough in the way the computers used to function earlier, as with the onset of cognitive computing, various software developers and engineers are bridging the gap between the way the computer functions and the way a human brain thinks. The result is intuitive and interactive however which improves over time and can help humans in expanding their limits of capabilities, increasing knowledge and making well-informed decisions.

Cognitive Computing is a new technology that permits people to communicate with computers using a natural language. Earlier, people used to code or format their text in a manner for the system to understand. For example: if they wish to search something, they used to input the keywords. Natural language processing permits the users to ask questions or speak in sentences while communicating with their systems in the same manner as we talk to another person.

How Cognitive computing works?

Cognitive computing systems are a consistent flow of learning techniques. These techniques employ different processes such as data mining, recognition of patterns and language processing. Although, cognitive computing is witnessing a dramatic change as companies are now engaged in developing Artificial Intelligence(AI) and are competing in the market to get a foothold. Cognitive computing can assist us in realising the accurate AI as it helps in imitating the activity of the human brain. These systems can be useful in developing an automated system for solving complex problems by itself.

IBM is the forerunner of Cognitive computing technology.  The company has made a billion-dollar investment in big data analytics and is now on the verge to spend near to one-third of its R&D budget in the development of cognitive computing technology.

Pillars of Cognitive Computing

The three main pillars of Cognitive Computing are:

Machine Learning

Big Data Analytics

Cloud Computing

Machine Learning

Machine Learning is making the algorithms put to use. The objective of the algorithm is to examine the data and estimate the trends. Normally, there is a set of training data that feeds the information.

You are required to examine this data on several data parameters to determine its efficiency. However, a self-learning feature is necessary for Cognitive Computing. From there itself, Machine Learning comes into the picture.

Big Data Analytics

The processing of huge amounts of information is the function of the human brain. Understanding the relation of any question is essential. Machines can make it happen faster once you feed the data in it.

But there are two forms of data – Organized and Unorganized. Here, Big Data Analytics plays a role in processing the huge data for you and finding the relevant one you need.

Cloud Computing

If you have huge data to process, you need to have high computing power. The demand is continuously changing in cognitive computing. However, scalability becomes a big factor.

From there Cloud Computing comes in the limelight which helps in providing you with scalable resources. This type of environment works great for Cognitive Computing.

Phenomenal Trends Seen in Cognitive Computing

Chatbots

The simulation of human behaviour by computer programs are known as Chatbots. It employs the feature of Natural Language Processing (NLP).

NLP is used for taking inputs from a human. The chatbots are the intelligent feature used by Cognitive Computing. It can analyse the situation and answer you accordingly.

For example, Chatbots such as Google Assistant, Alexa, Siri are all intelligent bots using cloud-based natural language processing. The cloud capacity permits the business to store user based relevant information and offer tailor-made solutions, products, and messages subject to the behaviour and user preferences. These chatbots optimize the cloud computing potential to offer personalised context significant customer experiences.

Sentiment Analysis

Sentiment Analysis is associated with determining various forms of emotion. Emotions are a normal thing in a human which comes out naturally. But you need to train a machine by feeding a set of data conversations.

Sentimental analysis can be put to use by many companies for splitting up the social media conversation. You can examine individual posts, likes, replies, comments, etc. very spontaneously.

Face Detection

The image processing that detects your upper face is known as face detection. The cognitive system is put to use to analyse the eye colours, lips, contours, etc. to scan a face. Once a facial image has been generated, one can easily recognize the face.

Normally, 2D images are used for face detection. However, it can also be performed for 3D models. Primarily, the face detection is helpful in any security surveillance system.

Risk Management

Examining the possibility of unforeseen risks via current trends prediction is all about risk management. This feature does analyze data, instincts, behaviour, etc. It is a mixture of both art and science.

Cognitive Computing supports you to amass data and trends. Depending on this collection, it can create actionable insights. Moreover, an analyst would be a better person to contact for any further details in this regard.

Fraud Detection

Identifying any abnormal transaction results in fraud detection. In order to study the frauds happened, you need to go through the historical data for identifying the reason. From there, cognitive computing plays a vital role.

Trends by Industry

The top cognitive computing trends are clearly witnessed in the following segments:

(1) Cognitive Computing in OTT

Cognitive Computing capabilities are also harnessed to produce Over-the-Top-Content for delivering video-based content in the form of web series and movies. The cognitive technologies allow the learning and classifying the information from different organized and unstructured data may at times be cumbersome. But the substance administration can potentially be benefitted from AI innovation as feeling, image and voice recognition has involved media innovation buyers to increasingly depend on AI apparatuses to cluster and search for substance files. So that, AI can provide support in substance labelling (which is a costly affair). With the fundamentals of metadata, go through the substance administration structure which ends up having more precision in this way which empowers monetization avenues. Artificial intelligence, coined as “cognitive computing intelligence” in media industry claims to track the user client habits of utilization.

Now, OTT is no more confined with Android-backed Smartphone, instead, manufacturers are developing Android TV sets along with apps to necessarily assist the users in delivering Omnichannel experiences throughout the devices.

(2) Cognitive Computing in News Industry

To allow natural human interaction to flow with cognitive computing tools, the IBM Watson platform has assemblage various capabilities such as:

Speech and Image recognition

In-depth text understanding

Detecting emotion and expression

Translation tools

Relation extraction

When a user wants to read, listen or hear news – with the already embedded cognitive abilities in the device can present the news in the form of text, image or voice according to the user preferences.

The latest news update, forums, weather forecast, sports, politics, business, finance –are all under the cognitive controls backed by four API categories:

Language: An API combination, but not restricted to, categorizing natural language text, entity extraction, conversations, converting documents, extracting semantic concept, language translation, retrieval of passage and ranking, relationship extraction, tone analysis and much more.

Speech: An API combination for speech to text conversion and text to speech conversion which includes the potential to train with your own language models.

Vision: APIs to search new perspectives, gather relevant value and take actionable insights from images.

Data Insights: News is a pre-enriched content that comes with a natural language processing which allows the highly-targeted search and trend analysis.

(3) Cognitive Computing in Retail

Cognitive computing permits enterprises to increase human expertise vigorously. The cognitive computing technologies enable consumers to assist the retail industry to discover new opportunities and make rational shopping decisions.

The technologies also provide interactive, adaptive and contextual systems for making and permit retailers for creating quality tailor-made experiences for individual customers. The following are some rapid trends that are transforming the retail industry:

IBM Watson Commerce

IBM Watson Commerce is a software program for managing the business processes of both retail and online merchandisers. It also focuses on enhancing the customer involvement initiatives. The software program put Insights Assistant to use which help merchandisers to recognize abnormal situations in their marketplaces and advocate suitable actions.

Predictive Analysis

Predictive analysis helps online retailers anticipate what the customers would like to buy in advance. This would help them to predict the customers buying choices such as knowing the highest amount for a certain item the customer is willing to pay. It assists them in optimizing their customer service. Their analytical tools search at the several determinants that can assist in generating the desired involvement from the client such as clicking an online product promotion or subscribing to a newsletter.

Voice  Assistants

It is amazing to know the engagement of activated voice digital assistants revolutionising the retail sector. These devices permit the customers to make orders of their preferred product choices and get them delivered within a few hours at their homes.

Direct Purchase via Social Media

Social media platforms such as Facebook, Twitter, Instagram and Pinterest are also navigating the online shopping sales by offering several purchase options. For example: when you see a product suggestion on your social media platform, upon clicking on the product’s image, an application combined with cognitive capabilities will navigate you to the product page. This will help to drive instant traffic on an e-commerce website and enhance the chances of a customer buying a specific product.

Personalized Recommendations

Online retailers use cognitive technology to offer their clients instant personalized recommendations in the form of mobile notifications or e-mail newsletters regarding products they should consider to purchase. This will help the retailers to develop complex insights into their product and generating customer base for a particular product.

Demand Forecasting

To sustain the immediate demand from their customers, online retailers make estimations regarding future demands with the help of demand forecasting. There are a couple of demand forecasting tools that are based on cognitive technology and machine learning will help the online retailers facilitate the precision of deriving probabilities of future demand.

Price Optimization

It becomes difficult for online retailers to accurately determine the price fluctuations responsiveness in their respective markets. This is due to factors such as competitor pricing, supply constraints and complex predictions of customer demands. To face this situation, online retailers can put price optimization tools to use subject to the cognitive technologies for making predictions on how their clients will respond to the price fluctuations of different products or services. These tools help the online retail industry to fulfil their objective of maximizing profit.

[recosense-blog]

Top Trends of Data Engineering in OTT

Subscription-based on-demand content and media platforms have risen in demand over the years as they offer more flexibility and better entertainment to users. As OTT platforms replace traditional TV sets, they are becoming the preferred medium for consuming content, be it around entertainment, news, sports streaming, or education.

In India, the growth of OTT players is astounding. According to a report by the Boston Consulting Group, the Indian OTT market will grow ten times to reach $5 Bn by 2023 from $500 Mn in 2018.

As television programming undergoes a renaissance, the promise of more and better data allures advertisers. Data and analytics stay as the key to television’s profitability. Advertisers now have more access to data due to OTT platforms, while content providers and networks leverage data to guide programming decisions.

The Need for Data Engineering in OTT Content

The growing abundance of data available to marketers, advertisers, and content providers makes it necessary to have systems in place to analyze, process, and transform this data into something meaningful.

To offer better personalization, content discovery and push the continuous development and transformation of underlying systems, it is critical for OTT platforms to use data to its full potential.

How OTT Players are Leveraging Data and Engineering it?

Data to drive content

For homes that have a subscription service, OTT players are using data to guide viewers to the right content. The most famous example of data-driven viewership is Netflix’s House of Cards. The content is designed to be a hit considering platform data such as ratings, preferences, user viewing habits, and so on.

Netflix’s data pipeline is fed with data from millions of set-top boxes and online accounts, which the company processes and stores using the Hadoop ecosystem and leverages Amazon’s AWS platform for cloud computing resources. Data from A/B testing has led Netflix to insights that have given tangible results such as up to 30 percent increase in a particular content’s viewership.

Personalization for loyal viewing and revenue

Alluring and retaining the generation of cord-cutters and cord-nevers takes more than great content. These viewers expect tailored services in the form of personalization, served based on their preferences and choices.

Personalization is not just about the content. Everything from subscription plans to metadata, frontends, and recommendations can be personalized for greater impact and viewership, which ultimately drive revenue.

Enhancing user experience

All OTT players sit on a huge pile of relevant data about their viewers and their behaviors. By putting this data through a cleaning process and leveraging insights for improving the recommendation engine or personalization feeds, OTT players are enhancing the user experience.

By knowing what will keep users coming back for more, companies are making personalized recommendations and accurate predictions for cross-selling or upselling opportunities.

Having a more nuanced and sophisticated view of the customer can help companies keep track of this trend in data analytics and OTT media suggestions.

Personalized Emails and Push Notifications

Customer-specific data collected by means of AI and ML, and churned with the help of analytics, helps OTT players recommend shows, series, and movies to viewers through personalized push notifications and emails.

Since both of these marketing media are proven to have exceptional RoI, OTT companies can now use them to make relevant recommendations on the basis of viewer interest and viewing behavior.

Furthermore, the push notifications and emails can be timed for when the user is more likely to access the OTT media site or mobile app- for greater impact and conversion.

Personalized digital advertising

Programmatic media promises data harnessing for advertisers, using set-top box data to inform OTT players about viewers and their behavior in consuming content. Building on the viewer’s inclination for customized viewing experiences, programmatic television can deliver unique advertisements, even though viewers are watching the same programming.

According to eMarketer, only 5-10 percent of the TV inventory is available and addressable for programmatic. Even then, the market looks massive and promising. Programmatic advertising is all about the efficient spending of dollars by careful targeting and retargeting.

This is why data and analytics look vital for personalized digital advertising.

Omnichannel advertising

Companies are now working with entertainment players to measure audience metrics across platforms and channels. By aggregating viewers and their behavior, companies get a more holistic view of their audience, offering advertisers opportunities to execute an omnichannel advertising plan.

By augmenting data such as viewing history, demographics, political inclination, and so on, companies can now offer in-depth insights to advertisers for improved ad delivery and execution.

Converging OTT with E-commerce

OTT ad spending has skyrocketed, and providers are maximizing their investments in correlating viewership with consumer purchasing behavior. The convergence of OTT with e-commerce, driven by analytics and personalized advertising is opening up better and more avenues for profit for providers.

AI and ML-based content creation and recommendation

The cutting-edge technologies of artificial intelligence and machine learning are also playing a strong role in facilitating content discovery, creation, and recommendation in the OTT arena.

A personalization approach backed by these sophisticated technologies can help companies make leaps of progress in regions such as India where people in the regional market have their own sensibilities and entertainment preferences, besides language inclinations.

Data Engineering for Better Viewership and Viewer Retention

Data available to OTT players needs to be churned and utilized for insights so that effective decision-making can be practiced. When that happens, data utilization will be the driving fuel behind the success of OTT players and their expansion.

At RecoSense, we use artificial intelligence to build deeper insights across touch points for OTT players and digital media providers. Learn more about how we do it here.

[recosense-blog]

Why OTT Platforms are focusing more on regional content?

OTT, or over-the-top is a productized practice of streaming content to consumers directly over the Internet. It represents the future of entertainment, which is fast unfolding in India as well as around the globe. As a result of audience’s growing appetite for content, OTT players are witnessing high demand for movies and original content even in regional languages around the world.

These countries include Europe, China, Middle East, and India. Since India is a multilingual country, the opportunity to present content in multiple languages can prove to be a hot opportunity for OTT players in the country.

India’s internet users are expected to grow by double digits to reach 627 Mn in 2019, driven by accelerated internet growth in rural areas. Internet usage in the country has hiked over half a Mn for the first time at 566 Mn people, also driven by rural internet usage and growth. Internet users in rural India have reached 251 Mn and this number is expected to hit 290 Mn by the end of 2019.

Multi-Lingual OTT Content

The inclusion of regional content on OTT platforms has paved the way for mass-market adoption instead of the initial niche offering that these were once. As over-the-top platforms in India reach the scale, the need for local content will increase along with it.  As per research points to around 500 Mn OTT platform users within the next three years, out of which at least 90 percent will be non-English speaking users, and at least half will be non-Hindi speaking users.

India already has a proliferation of OTT players, as unlike the West, broadcasters in India went into OTT directly and quicker. The number of OTT players in the country has grown from nine in 2012 to thirty-two in 2018. With a large number of players competing for audience attention, getting differentiated is the key to success. This means players need to diversify content strategy across segments.

The effect can be seen as ALT Balaji is set to foray into Bhojpuri originals, Zee Studios producing premium original content for all digital platforms, ad Netflix has announced 17 new originals for the Asian market and ~5 Billion and ~6 Billion have been allocated annually for Indian content, industry reports reveal.

As OTT players up their investment in regional language production, they hope to acquire regional and local audiences. Many OTT players says that they are seeing a lot of consumption from smaller towns, and therefore are preparing for the next wave of regional content. The trend is clear- if an OTT player needs to sink in a larger audience, it will have to dabble into regional content.  

Regional Content on OTT Platforms Beyond India

Data from Digital TV Research reveals that despite a large number of OTT subscriptions, there is more room for growth in both Eastern and Western Europe. Western Europe Subscription Video On Demand (SVOD) revenues are expected to increase from USD 2.8 Bn in 2016 to USD 6.5 Bn in 2022.

Eastern Europe will see a more accelerated growth as Amazon and Netflix penetrate the market, with revenues x4 from USD 552 Mn to USD 2.23 Bn.

The OTT market is divided into two parts in Europe- the Anglo-Saxons and Scandinavians have directly adopted it while the Latin countries struggle to establish it. Culturally speaking, Latin countries are less accustomed to English than Scandinavian and Anglo-Saxon countries.

Europe’s diverse population with varied language preferences acts as both an opportunity and a challenge for OTT service providers. Therefore, OTT players will need to embrace French and German languages which are the most popular ones in which OTT video content is offered in Europe.

A Deloitte report suggests that OTT players have set aside a budget of ₹3,300 crore to invest in original content in Hindi and other regional languages prevalent in India, Bangladesh and the Middle East.  A Bengali OTT platform says they identified the opportunity to make Bengali content a key market with an audience size spanning all three of those nations.

In China, the video streaming giant, iQIYI boasts of a large volume of Chinese language content it either commissioned or produced.  As the market for English video content gets saturated, if OTT players have to maintain expansion and growth rates, they will have to shift toward regional content and deliver people what they expect and demand.

Regional content is the pathway to boosting subscribers and offering original content in languages people are well-versed with in developing and developed nations. Trends already show that viewers are thirsty for content in their regional dialects and the next couple of years might see a significant expansion in regional video content streaming, magazines, and series.

[recosense-blog]

How AI is shaping the future of eCommerce Landscape

In this hyper-competitive business world, technology is being incorporated in the businesses more than ever just to grow at a rapid pace. If you are new to AI then you might not be aware of how AI is shaping the future of eCommerce business and more. So, let’s dig deeper into the topic. This article will help you find out what exactly AI is and how AI is shaping the future of giant eCommerce Landscape.

Most of the eCommerce giants are incorporating AI in their business strategies to boost their ROI. Coming to the eCommerce and lifestyle business, AI has changed its entire game. No matter what the outcome is, AI has provided some great ways to engage with their shoppers and retain them in this hyper-competitive space with its special hyper-targeting features.

How AI is transforming eCommerce Landscape

AI is transforming the relationship between technology and people. Apart from that AI has been shaping the future of eCommerce by its powerful features. The future of Artificial intelligence promises a definite new era of disruption and productivity. Here human ingenuity is always enhanced by speed and precision.

The prime example of AI shaping eCommerce landscape is the survey result from statista. In 2017, the retail eCommerce sales worldwide have reached $2.29 trillion and it’s expected to grow up to the $3.74 trillion by the end of 2020. That means E-commerce is growing continuously by 20% every year.

Personalization can encourage users to return

These days, people love to have some personalized touch to the eCommerce product. Usually, personalization in the eCommerce industry is not a new aspect, but it’s emerging with the help of AI.

You can find many retailers use collaborative filters to provide customers with good recommendations. These filters are based on their most viewed history, best sellers, popularity and other parameters.

Although these collaborative filters only gather data from one channel such as mobile applications, online store, etc. But AI helps you to seamlessly enhance your customer experience across all the platforms.

Almost all the eCommerce sites these days are having these special features mainly to attract users and help them buy their desired product with ease.

Even in a niche product market place like that for medical devices, Pinkblue is leveraging AI based platform to predict and display the personalized and similar products. As AI predict data and display relevant results. It’s also showing popular product in the brand to help their users.

Machine Learning provides better search results:

As AI is becoming incredibly important, brands are now turning towards it and incorporating machine learning to quickly enhance their search results.

Machine learning can help shoppers to sort out the search results by relevance. You can see machine learning in lots of eCommerce tech giants.

Many eCommerce portals using machine learning to get the most relevant search results for customers. Now, with these actionable user insights, most of the companies will love to have this tech on their eCommerce platform because its best suited for their customers. This could definitely improve their sales and enhance their customer experience as well.

Artificial Neural Networks For Campaigning

Most of the eCommerce sites use AI neural networks just to recreate how the human brain behaves. With the help of these networks, retailers can simply collect data and make changes to their ad campaigns to make them work.

With the help of neural networks, you can carefully understand the pattern of the users and even predict the trends and other aspects which are useful.

AI has improved Visual Search:

Shoppers can now say goodbye to the old way of text-based search. Previously when a user wants to have to look at the objects, then they have to undergo text-based search but with AI it is changed.

Thanks to AI, now shoppers can just upload an image and find the related products what the customers are looking for with ease. The visual search capabilities have improved a lot by AI, particularly in mobile platforms. If you are regular online shopper then you will love to check out the items with the filters such as — shape, size, color, brand and fabric as well. Visual search often gives the advantage to the users and it also gets accurate outcomes.

These special filters will help the shopper to find the exact products they are looking for within a few seconds.

These days shoppers don’t even have to do shopping to explore new products they love. This is another advantage of the AI in eCommerce platforms and this can definitely enhance their digital sales.

Voice search – The innovation which leads customers to search more:

People love to use voice search to find out the products they want to buy. Usually, most of the people these days love to use voice search because they are tired with boring ways of typing the keyword of searching for their favourite product.

Nearly 50% of all searches will be voice searches by 2020 so that’s a huge figure when it comes to the voice search. That’s why incorporating voice search to the eCommerce landscape is a huge plus. All the voice searches will make use of Artificial intelligence to quickly recognize what users are trying to search for and recognize their voices and phrases as well.

Apart from that, virtual shopping assistant voice searches can help shoppers to have an interactive real-time conversation with an e-commerce platform. This special feature can give a great experience for shoppers and will increase customer retention as well. According to creative strategies, 97% of mobile users are using AI-voice assistants.

Recently, Google Home has made it possible for users to make online shopping by using voice-based search technology. So, shoppers can simply place orders through their voice with the device integration with the help of Alexa technology.

Ex: Voice search is a go-to option for e-commerce businesses. There are literally hell lots of examples when it comes to voice search. Take a look at the “Google Assistant”, Apple Siri, windows Cortana all these are voice search engines which helps you shop with ease.

Online Personal Assistant:

With the latest AI innovations, shoppers can now take advantage of personal fashion assistant. This personal assistant will give personalized recommendations on the basis of their past searches and usage pattern. AI technology is helpful to curate products without manual work. So, users love the virtual assistants.

Sometimes these virtual assistants will also send push notifications and alerts for the price of the product which the user is searching for and it also helps the eCommerce business to get higher conversion rate. With the help of online personal assistant you can also check out the product recommendations and more. So definitely say AI is crucial for eCommerce.

Conclusion:

AI has been a hot new trend in eCommerce industry which is why most of the eCommerce giants are striving to implement it on their business. If you’re striving to get succeeded with your eCommerce site, Artificial intelligence will help you to find out real and sustainable benefits.

Apart from that, RetailSense can help you out in this fast paced digital world. With RetailSense top notch AI based platform, you can create the best user experience and powerful analytics help you observe the key stats for your business and helps users to move forward. Not only that, you can even use personalized retargeting

The fast pace at which AI is gaining traction in the e-commerce industry heralds a promising future. And, with RetailSense, you can change the way how you communicate with your customers and enhance your products. This is how AI is shaping the future of eCommerce industry.  For more interesting updates please keep reading our blog and follow us on Linked In.

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What Kind of Content is Trending Among Millennials on Digital Platforms

According to a study by eMarketer, 64.8 Mn millennials are expected to watch digital video at least once in a month. This figure is expected to rise year over year across the globe. Research studies are increasingly suggesting that millennials are moving away from traditional TV and learning more against digital media platforms. The same research pointed out that video consumption numbers are steadily growing from 64.2 Mn in 2018 to 64.8 Mn in 2019, and 65.1 Mn by 2020.

But, what are they necessarily into? Let’s delve into types of content millennials appreciate on digital platforms

News: Millennials follow different style of watching videos and reading articles online compared to the generation X and baby boomers. The most popular type of content is News and millennials prefer to watch online videos to stay up to date in this competitive world. 94 % of millennials in US are more comfortable using smart phone for all their content browsing needs. The content consumption again differs from male to female but the most challenging part is to enable millennials to find what the content they are looking for. Incorporating user persona will help to target the customers and to deliver the personalized content.

Entertainment: Many on demand streaming platforms launched in recent and focuses on non English content exclusively original shows, movies, live events, TV series and entertainment content etc. Digital platform helps millennials to watch the content as per the convenient time and the content what they are interested. In US millennials prefer to watch the live events and other entertainment content like comedy shows etc in weekends.

Sports: Millennials watch sports? Yes millennials watch sports but the content crave for millennial is different from the traditional way, millennials also like to watch sports documentary movies digitally to know the history of real show. 65% of US millennials say they binge-watch blocks of videos at least once a week. The number of millennials watching the NFL increased compared to previous seasons. Sony India’s, SonyLIV  is also not behind by providing live streaming of football tournaments like the UEFA Champions League, La Liga, Serie A, Ligue 1, UEFA Europa League etc. If we connect and engage millennials with relevant sports content digitally to have a cohort of sports fans in hands.

Apart from these categories millennials like to watch entrepreneur content, fiction content and product related videos etc on digital platform.

Live Streaming Content

According to the Recording Industry Association of America, 75 percent of the music industry’s revenue comes from streaming. It is also expected that the role of video streaming will continue to expand in the music industry. Before live streaming, even sports fans had only two choices for live viewing: either buy expensive tickets to attend events or watch limited sportcasts on TV. Now, with over-the-top sports, fans have convenient and affordable access to local and international sports events.

With live video and viewers poised to stream, share, and engage with sports worldwide, content providers can enhance the overall experience with contests, special promotions, fantasy experiences, continuous interaction, and more.

Live streaming allows for media delivery by scaling to millions of users without compromising on the quality viewers expect. It’s no surprise that live streaming content is enabling music, sports, and event live content delivery through popular demand. The proliferation of digital media platforms has led millennials to ditch the traditional television and find what they love to watch, over the Internet.

But, are they effectively able to find all the media they would like to consume?

The challenge of discovering the right content is real.

Over half of the consumers, 55 percent, are searching for a new movie to watch at least one every week. And 83 percent of consumers are searching for their favorite kind of content a few times each month. But, nearly two-thirds of users are struggling to find something that sparks their interest. These statistics come from a new report from PwC- which surveyed 1,000 digital media consumers between the ages of 18 to 64 and asked about the challenges they face in discovering the content of their interest.

The survey reported that 79 percent of consumers had watched a movie or TV show solely based on the recommendations of their content service, and 90 percent said they liked what was recommended to them.

If entertainment and media companies are to win the digital race, they need to focus on a critical pillar- content discovery. AI and analytics can help media companies make relevant content discoverable for their target audience. Content recommendation and personalization are key components of a successful media distribution strategy.

MediaSense is a product that employs artificial intelligence to personalize the experience for consumers and recommend content to them based on many factors. By doing so, you can enhance the experience of your consumers and make them stick around longer while offering content that interests them.

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Omnichannel Personalization in Retail

As the online businesses have already carved its foothold with its extensive online presence, there are many challenges and avenues retailers are confronting with. The quick retail transformation and e-Commerce industry have supported common retailers to make their online presence. e-Commerce businesses and retailers are confronting pressures to get accommodated with a technique that focuses on a solitary medium is no longer sufficient to attract the growing demands of the consumers.

eCommerce Industry and retail are rising exponentially and so are the expectations of the customers. Since the Consumers are consistently living with the brand across their buying lifecycle and they expect a sense of having a personalised experience that is on the top of all channel frontiers. It can be a social media, website, mobile and so on.

Here, the OmniChannel Personalisation seizes the limelight

Omnichannel is a way out of multi-channel strategies which focuses to offer the customer with an effortless, seamless and a high-driven quality of shopping experience. This takes place within and between channels of contact, irrespective of whether the customer keens to shop from a desktop, web or Smartphone or at a brick and mortar.

How to Achieve Omnichannel Personalization?

Web and Email Personalization

Email marketing is known to be a continuous driven communication channel which the companies opt to interact with their customers. It has transformed over time, with various technological developments in the market.

Web channels and email can be directly linked to promoting messages that powerfully deliver proposals of items that are accustomed to the interests of every single client. This includes knowledge gathered from email and web actions.

Personalized Mobile Apps

It is a prime concern to implement specific personalisation techniques that employ the topography to enhance the experience for the customers who are always in a hurry and reveal Geo-centric offers. The recognisers assembled for email and web can be utilised to organize the portable channel, allowing sharing of information inside and crosswire throughout channels for continuous engagement.

In-Store Personalization

With a set-up of strong portable technique, extending personalisation in-store is a consecutive characteristic stage. Coming up with lucrative deals, partners with tablets for procuring clients and advanced presentations is the succinct methodology to take care of the personalization into the physical sphere.

Catching in-store, information for buying can be more worrisome on the fact that POS frameworks are consistently not in a cohesive state with online channels.  It returns to mention an identical customer identifier accomplished in various channels.

Customer interaction centre

Contact centre point usually appears at the consecutive stage, drawing on the telephone and web-based client benefit operators in with the general mishmash involving offers and item perspective proposals relevant to every customer.

Omnichannel retail keeps on progressing, fuelled by shifts in buyer desires and conduct for more of tailor-made experiences that are genuine inside each and every step a client collaborates.

Organisations can start reciprocating on this desire by determining the channels that are most purposeful to their consumers, least demanding to materialise and begin a staged omnichannel personalisation approach that will gradually interpret a continuous guarantee for the client experience.

Omnichannel Product Recommendations

Make efforts to develop touch points for your customers in the following manner:

Personalise every Feature of your Website

Attract customer attention by combining personalised product recommendations, offers and content across your website which includes home pages, landing and category pages, product pages.

Personalise Mobile Users with Engagement

Outstretch the personalisation to buyers simultaneously with contextually significant product recommendations on apps and mobile sites for covering complete omnichannel aspects.

Create ubiquitous experiences across mobile devices and sessions to increase engagements and conversion rates.

Personalise In-store Experiences

Facilitate in-store associates with extensive customer data on the latest purchases, browsing history and buying intent to make product recommendations on an individual basis.

Increase fulfillment of omnichannel strategies like buying online pick-up-in-store, ship-to-store and returns with personalised recommendations during conversations with in-store associates.

Personalise your Call Centre Communications

Combine estimated recommendations into sales, customer service calls or returns by motivating representatives with enriched customer data.

Highlight significant products subject to preferences, web browsing and latest purchases.

Give engaging experiences for each buyer based on their individual needs.

Effects of OmniChannel Personalisation

Conversions

Tailor-made omnichannel experience such as product recommendations, rapid web-based promotion and content subject to consumer behaviour, statistics, social communications, in-store behaviour, click-stream information, setting, climate and area increment regulatory transformation. Personalization can disclose 5 to 8 times the return on initial capital investment made in promotional expenses.

Higher Order Value

Support your clients on their buying venture and increment usual request by giving them incentives with strategies. For instance, computer-based product recommendations, focused interest-based offers, effective marketing and launching of  the shopping cart movement.

Higher Lifetime Value for Customer

Retailers who ingeniously contextualise and tailor-made offers to customers can prompt more repetitive business.

Enhanced Data Assemblage

In-store information assemblage is resulting in an increasingly essential element of the omnichannel methodology of retailers. It provides the clients with an extensive tailor-made shopping background,  offering deals staff the efficiency to manufacture relevant customer profiles, and allowing retailers to administer the in-store investigation they must differentiate clients and increment deals.

As on the web and discontinued efforts sustain with retail advertisers, blending needs to be wrapped up which specifies clear mindfulness of the relevance of in-store information assemblage and how the clients react on the questions asked by the retailer.

Improved Customer Relationships

The more you know about the preferences of your customer, the more you will be able to establish relationships and induce their retention rates. The features of customers’ behaviours and choices will help deliver user experiences on a personalised level and enhance engagement.

Predictive personalisation

Depending upon the customer interests, purchase repetitions and several other factors, it can be estimated which customer may formulate purchase and the medium of a channel of purchase.

Integrated Analytics

The analytics of the omnichannel customer allows the retailers to draw out an incentive from information with a particular end goal to know who their customers are and what they expect from most of their brands.

Increase in Brand Love

In this shifting of channel economy, mark moving, client dependency is widely significant and can be attained only due to the intense, discerning customer strategy that involves completely tailor-made and contextualised offers.

Personalization is one of the most relevant characteristics for customer allegiance.

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Learn How to Optimize Product Discovery for eCommerce using AI

Product management in e-commerce has its roots deep down in discovery. Enabling products discovery generally differs across websites, but the essence is to help the customer find what they are looking for, sooner and automating the user insights without explicit questions. Luckily, optimizing product discovery also increases the chances of conversion. Therefore, it is important that your e-commerce portal be intuitive and intelligent enough to facilitate efficient product discovery for each customer.

A study by ClickTale revealed that shoppers spent more time attempting to find their product on e-commerce websites that were not optimized for product discovery, but left because they were unable to find it. On the contrary, e-commerce websites with strong user insight make the customer stick around to make a purchase despite spending less time on the site. The study said small retailers tracked a longer time on site (around 200 seconds) than large retailers (around 70 seconds). But, the bounce rate for small retailers was higher at 34 percent in comparison to that for large retailers (9.4%). Quicker and efficient product discovery also becomes a positive customer experience, leading to retention.

Here’s why this study matters:

These numbers prove that large retailers are beating small retailer in the game of optimizing product discovery, and thus reaping benefits in terms of revenue and conversions. Due to substandard customer experience, customers are abandoning their purchases midway from small retailers.

Convinced? Let’s get to optimizing product discovery for your e-commerce audience!

Optimize the Home Page

This is what customers first see when they land on your website. Make sure you are leveraging the home page to ease product discovery, using one or more of these elements:

Promotions – These are your current discounts and ongoing, time-sensitive offers. Use intelligence-infused solutions that help you personalize offers for customers at various buying stages such as first-time users, first-time buyers, repeat buyers, and so on.

Personalized elements – These might include the ‘Recently viewed’ or ‘You might like’ sections. Where the user is logged in, or where their browsing history is saved via cookies, pull products based on the customer’s past purchases or cart additions. You can even leverage customer data such as their gender or location to personalize recommendations on those factors.

Popular products – These are the products you can show to people who are in their initial journey with your website. A display of the fast-selling products can help customers choose between two brands.

New arrivals – If fashion is one of your e-commerce offerings, it makes a lot of sense to show what’s new. Most customers would love to buy something that’s fresh and so these product displays are compelling.

Educational content – Your homepage can be the right place to ease the customer deeper into their buying journey with you. To do so, you can offer informative content such as product reviews and ratings so that customers who are not yet ready to make a purchase can still find something of use.

Streamline the Navigation

Product navigation is a critical component of the shopping experience for buyers who know what kind of product they want but have not yet made a decision. Otherwise, they might have used the search feature. If you are looking for a new couch and are not hung up on a type, color, brand, or size, you will want to explore. And that is exactly the reason why product navigation needs to be quick and seamless. Flyout navigation menus work great here. They offer a way to start with a broad idea and then subsequently narrow down your desired product as you go.

Strategize the Filterable Product Attributes

Now, you need to focus buyers on getting what they want. If you don’t help them make a purchase soon, they might abandon and go back.

There are two ways to do this:

Make use of rich product attributes that cover every aspect your customer would want to customize and filter. And, make sure you allow the customer to filter as well as sort by these attributes. A few of the factors can be height, weight, color, availability, reviews, brand, cost, and so on.

Optimize the filtering and sorting experience for your customer. Avoid reloading the page for every added filter. This only decelerates decision making and increases buyer frustration. Use checkboxes to allow the customer to add multiple filters at once and see consolidated results.  

Faster, Accurate, Personalized Search Results

For powerful discovery, enable auto-correct, search by attributes, brands, and auto-suggestion capabilities in the search bar. Building a strong user persona for aiding personalization also helps make the search inputs more effective. Aim to feature relevant products immediately from a product search. For instance, if the buyer searches for ‘black shoes’, the search should direct them to the ‘shoes’ subcategory with ‘black’ pre-selected as the color attribute. Leverage Error 404 pages to display hot and popular items in the same category the user was looking in. An error can turn the user off, but you can leverage it as an opportunity to drive sales.

Secondary Product Discovery

For customers who recently bought a mobile phone, for instance, you can make secondary product recommendations such as screen-protection glasses or mobile holders. Upsell using personalized secondary product recommendations. If a pair of pants were frequently bought with a shirt the buyer selected, make the recommendation under the ‘Complete the Look’ feature. These specific steps can highly optimize product discovery for your audience and help them swish through the shopping experience, coming back to you for more!

Using an intelligent personalization, recommendation, and visualization platform can help you leverage AI and analytics to their full potential. Experience increased conversions, lifetime value, order value, revenue, and repeat purchases with a data intelligent SaaS platform for e-commerce product discovery, such as RetailSense.