Recommendation Engines: How B2C Brands Can Personalize User Experiences with AI

The application of personalization in marketing has undergone a major shift over the last few years. It all started with referring to users’ by their first names, wishing them on their birthdays or anniversaries, and celebrating transactional milestones. But, that sort of personalization - in today's market and world - doesn't work anymore. It's no longer a gamechanger.

Your users continue to grow smarter, more informed, and empowered. In fact, according to an Infosys report, 31% of surveyed users wished that their online shopping experience was more personalized than it currently is.

They require greater context. Greater relevance. Greater value for time, effort, and money spent. And, as a customer-centric brand, you need to work that much harder for their mindshare, screen-share, and eventually; wallet-share. This challenge assumes even greater significance during the current COVID-19 global pandemic and once it tides over.

Users now require hyper-personalized experiences, right from the first time that they land on your website or launch your mobile app. This is evidenced by a Deloitte study where 36% of surveyed users expressed an interest in purchasing personalized products or services.

Personalization is no longer limited to your marketing campaigns. Your digital or mobile marketing campaigns are merely pivotal cogs in your grander personalization wheel.

Laying the Foundation for Personalization

You need to integrate your personalization strategy into your multi-channel marketing automation approach to deliver 1:1 user experiences at scale - tailor-making experiences at an customized user level across various digital touchpoints such as websites, mobile apps, email, push notififications, SMS, and social media.

This needs to be powered in real-time by leveraging your users’ demographic, geo-location, device-related, and behavioural data along with their intent to search, click, add-to-cart, or complete transactions.

And, for this to happen you need your user data to be accurate and unified; sourced from both online and offline channels. Gaining a live 360-degree view of what individual users are doing across your website or mobile app is critical. Which is why, depending upon the scale and budgets that you operate at, you need to think beyond traditional Customer Relationship Management (CRM) tools.

Harnessing Personalization to Uplift Marketing Efficiency

Whether you are an e-commerce, online travel, OTT, fintech, edtech, etc. website or mobile app, a versatile personalization platform can help boost conversions by 8-13%.

Along the way, it gives you the chance to fuel greater user engagement, repeat purchase behaviour, loyalty, and retention.

Here’s how you can deliver data-driven user experiences backed by personalization:

1.  Personalize the navigational flow across your website:

Gone are the days when you could display the same website to all your first-time visitors and repeat users! It might be easier, but it’s certainly not going to help you drive higher conversions.

Tap into your user's past browsing behaviour and purchase history to customize how you want them to navigate across your website. The more customized your navigational journey, higher the chances of you directing them towards a conversion event, sooner.

You can also experiment with dynamic website elements such as graphics, banner images, custom text, and Calls to Action (CTAs) to further improve the persona-based website viewing and navigation experience.

Use Cases:

• E-Commerce: Create persona-based website home page viewing and navigation experiences based on gender, geo-location, or category of user (first-time anonymous visitor or repeat registered user)
• Travel: Show flight deals or travel packages based on the current weather, seasons, most-commonly-booked travel destinations, or Credit/Debit Card of choice

2. Individualize the search experience:

Once you’ve grabbed the attention of your users through personalization on the home page or specific landing pages across your website, you need to improve their search or browsing experience.

Using a niche personalization platform, you can instantly complete the search entry in progress or provide relevant product recommendations when your users are inputting a search query. This would be driven by past search terms recorded, intent to purchase, and most commonly made searches in a particular product category.

Your objective must be to reduce all possible points of friction in the customer journey that increase the chances of a user abandoning the potential purchase journey. Get this right and you place yourself in prime position to help the user complete a relevant purchase faster.

Use Cases:

• E-Commerce: Populate recommended products - in real-time - when your user is searching for a particular product category or specific item, along with similar search results
• Banking: Offer dynamic recommendations or re-directions towards the FAQ section when users’ make product or process-related search inputs or queries

3. Use predictive analytics to provide relevant recommendations:

Harness the capabilities of AI to do all the heavy-lifting by analyzing large sets of historical user data to generate highly personalized product or recommendations; that cater to individual users.

AI allows you to consider various behavioural parameters to accurately predict the probability of each user browsing, adding to cart, or purchasing a particular item or related products.

You can dive deeper to get insights into the propensity to search for, click on, add to wishlist or shopping cart, or purchase from various product categories and specific products - for individual users.

Based on these insights, your personalized recommendations can be displayed dynamically on your website or mobile app or be offered as timely, triggered communication across channels such as web messages, push notifications, or email.

You can optimize the marketing channels that you want to leverage in order to deliver these product recommendations; depending on past interactions of every customer to such campaigns.

When integrated with a robust multi-channel marketing strategy; you can choose from a mix of email, push notifications, web messages, SMS, etc. and at least 8 other effective channels of user engagement to deliver these contextual recommendations.

Use Cases:

• OTT: Provide video or audio content recommendations based on your users’ historical and real-time viewing/listening, watch list, favourite genres/artists, etc.
• Food Delivery: Recommend relevant restaurants or trending offers within a users’ geographic vicinity based on his/her preferred cuisines, frequency of app launch, most common time to place orders, etc.

4. Build and showcase a personalized boutique:

While highlighting contextual recommendations on the home page or product display page is a giant first step, why not take the ultimate personalization leap?

Create a personalized virtual storefront for individual users. Not only would this contain product or content recommendations with the highest probability of purchase or consumption, it would also continue to get dynamically updated based on customer eyeball data.

This means that this specially curated list of products, songs, videos, or articles, etc. would account for those recommendations that work and those that don’t, and refresh automatically - based on how many seconds a customer spends hovering over an item. These time-stamped signals loop back into the AI engine, making it smarter and more intuitive.

Leveraging these customer eyeball data-driven recommendations can in fact help you improve behavioural predictions by upto 20%.

Think of how Spotify or Netflix does this. Your playlists and watchlists continue to evolve based on every single session of content consumption.

Use Cases:

• E-Commerce: Develop a personalized boutique of highly customized product recommendations that a user is most likely to purchase. Drive traffic to this section through a banner ad on the home page
• OTT: Create customized playlists or watchlists based on historical and real-time consumption patterns to increase average session lengths. Make users keep coming back for more - to consume content that they love!

5. Reduce eventual paths to purchase or consumption:

Direct repeat website visitors towards conversion by highlighting the exact product that a user has viewed in his/her last recorded session - on a pre-decided section of your website, mobile site, or mobile app page.

This will help you increase top-of-mind recall and the chances of purchase or content consumption during the current active session.

Use Cases:

• E-Commerce: Highlight targeted offers on products based on past products viewed or items abandoned in carts on a specific space on your website home page
• EduTech: Remind repeat mobile app users to complete their pending courses by showing them a progress bar right where they are most likely to see it on app launch during their next session

Personalization is the Present and Future of Your Marketing Playbook

Read that again. And, let that sink in.

According to the Gartner Hype Cycle for Digital Marketing and Advertising, 2019; “innovation profiles like personalization engines are maturing rapidly as marketing leaders prioritize investments in this area”.

Delivering a truly omni-channel user experience is no longer a pipedream and scaling customer delight consistently is a function of your data-driven vision, creativity, and optimization.

Remember - the better you know and understand your users, the more effective your personalization strategy, powered by AI, will be.

And, there's no better time to re-evaluate your growth framework for the remainder of 2020 and beyond, as 1:1 personalization takes centre-stage during and post the COVID-19 era.