In part three of our enhancing your customer engagement series, we look at tailoring customer experiences with personality scores for products and content.

Understanding the elements that encourage consumers to make a purchase is like striking gold for any online business. We know human behaviour can be irrational and at times, downright difficult to understand. Ever been left scratching your head about high shopping cart abandonment rates or wondering why certain promotions work better than others? We get it and you’re definitely not alone.

With this in mind, Woven has looked at a number of approaches and models that help to improve customer experience (CX) by tailoring a site to specific user personality traits. While increasing the probability of purchase, this also helps to demystify behaviour commonly taking place on a merchant’s site.

Why now?

In the last decade, we’ve seen an exponential rise in the number of people choosing ecommerce as a means of purchase. A factor at play is that 52 per cent of digital consumers believe they’re able to customise content based on their user profile, leading to a more seamless and successful CX. We know that proactive sites that are taking into account customer personalities are increasing the probability of purchase.

The reasons for making a purchase and how a customer makes that purchase can be distinguished by a number of different needs. That said, there are two main drivers:

Goal-oriented: the customer has a purchase plan already in place and their search has one aim -to obtain information about the product to be purchased, its cost, convenience and availability.

Pleasure-seeking: the user adopts an ‘exploration-oriented’ search. There’s no purchase plan in place yet but they’ll make it as they go, by browsing and exploring different solutions.

Whenever motivations driving a user to purchase are related to personality traits, sellers should consider how to tailor their content to a personality model such as the big five.

What does this all mean?

Recent studies indicate there is a significant connection between personality and people’s tastes and interests. Our personalities influence the human decision making process and interests. How? By drawing on the patterns presented among customer’s different personalities and behaviours. The great news for online retailers is that a personality-based recommender can be designed to provide a personalised online experience. As a result, brands are likely to reap the rewards with higher profits.

User decisions are influenced by emotions and at least partially by the content brand’s choose. It’s important to weave in emotions and strong calls to actions on your website. A recommender system can also introduce a psychological dimension to your products and their categorisation based not only on attributes such as their price and physical parameters, but also on the impact they may have on a consumer at any particular time or in any situation.

How to make it happen

Making content on your site leverage a personal model requires the extraction of information so that you can define various user personalities. While in the offline world, you may use a lengthy questionnaire that won’t work for an online exchange. We’ve based this series to date on how you can start building your customer’s profile. Essentially, you need to start collecting a combination of explicit data (questionnaires for example) and implicit (clicks, purchases, abandoned carts and so on) information.

Once you’ve started to build a profile about your customers, you can use a context-aware recommender system that can determine and suggest products and services specific to that user’s interests. It’s worth noting that personality scores can be used for more than recommending products and services - they can dictate which blogs are recommended to customers, the banner ads displayed that are likely to be most interesting to them and even the promotions that are likely to appeal to people and encourage them to complete a purchase. This sees the recommendation process taking into account the user interests and preferences as well as their personality profile.

To make the recommendation system work, it can make use of a neural network such as IBM Watson, which can receive input of the explicit and implicit data we have collected (we hope you’ve started rolling out the recommendations from part one and part two of this series to date). It can all get rather complicated in terms of user-modelling and concept matching but what you’re after is a personality score (or rank). This is then used in combination with the results coming from the different interactions of the website with your products, blogs and/or services. The score allows us to re-rank or even filter research results. It also allows us to suggest personalised services or products of potential interest for a specific consumer.

At the end of the day, we’re aiming to adapt the type of recommendations of products and services available within the ecommerce platform to the user personality profile and as a result, improve the relevance and motivations that lead people to make a purchase.

If you’re an ecommerce executive, we highly recommend you doing your homework in terms of studying online consumer behaviour and understanding different personality types that consumers have. From there, you can then aim to give your customers a positive online experience that ultimately, ends in a  successful purchase and a fulfilling CX.

 Note: this is part 3 of 4 in our enhancing customer engagement series that our brains trust has put together. You can read part 2 here or if you’ve already done so, come back for part 4, which will be available soon.

Need help with creating tailored customer experiences? Contact Woven today.