Marketing textbooks usually talk about Segmentation, Targeting and Positioning (STP). In today’s time segmentation does not mean a group or a category – but means individuals. Not that the textbooks are outdated in anyway, but today’s times call for specialized targeting and positioning – we also know it as hyper-personalization. As a kid we all remember going to our favorite mom and pop store round the corner of the lane where the shop owner would have more than a mere transactional relationship with us and our families. The shopkeeper recommends products that we either bought in past or knows what new products we would be interested in, based on his familiarity with our household preferences and members.
Now we see the same on some of the e-commerce websites. This is an outcome of organizations investing in artificial intelligence (AI) & automating it to provide optimized buying experience by prioritizing individual requirements. These requirements are gauged by shopper’s web browsing behavior, in-app behavior, use of devices, engagement data, past purchase data, searches, watchlists and shopping carts. Hyper-personalization means that every shopper gets a unique experience right from the time they log into the site or app. For a retailer, the short-term benefits are increase in revenue, higher conversion rates and long term are increased customer lifetime value, reduction in churn, and increase in net promoter scores.
Let us understand this with an example. With the approaching Christmas time everyone is shopping for Santa dresses, decorative items, gifts, lights, Christmas trees amongst others. Now everyone searching for these items will be ideally put under one segment and a common marketing strategy would be used to target them followed by a usual product positioning if we go by the old way of segmentation. But let’s take the case where someone had already purchased a Santa dress last year, probably they may just need the tree or decorative items and vice versa. Unless the affinity and expectations of each shopper is captured individually, we cannot call it hyper-personalization, or a retailer cannot suggest the right products. For this, the path of the customer clicks needs to be followed and not just what’s in their cart currently. Because personalization needs to sail through so many possible combinations of items, and their attributes, a fully powered artificial intelligence needs to be in place to capture a customer’s journey right from the first click till the customer leaves the website irrespective of the fact that he/she buys the product or not.
For offering a great personalized experience to its customer (and for the customers to be wowed), ecommerce platform provider and retailers need to invest in a robust AI engine and also have their back-end operations synchronized.
Using AI Engine to power hyper-personalization – The AI engine needs to first get the historic purchase, search and click through data of the customer. Based on this the predictive capabilities of the AI engine, makes recommendations. Since all this data may not be available on the ecommerce platform it is imperative that the integration between various tools used by the platform providers and individual retailers is seamless. Unless the retailers have visibility into behavior cues, past purchases, and ways to identify individual data, returning users, and what’s available in their cart, personalization cannot be achieved. Visibility of just not enough – there must be an analytical engine on top of all the gathered data to understand the customer sentiment and predict purchases. AI-engines should also be able to understand and analyze factors such as price, and product availability including website latency due to which a customer decides to hop off from one website to the other.
Integrated business functions across the retail organizations on the platform – Though this is not new, but the power of personalization lies in how well an organization is integrated at two levels. First, at the backend with suppliers’ data, available inventory of various attributes like size, color, type and second, at the front end with data related to the customer behavior before and during purchase. Retailers need to know what path the customer followed to reach the final purchasing process, and what could have been the possible reasons for choosing the competitor’s product vs. theirs. Individual retailers must have an integrated function with its suppliers, inventory, CRM systems (to understand buying behaviors of the visitors) and the data flow should be seamless.
Personalization needs to be at every stage in the ecommerce customer journey. Many ecommerce platform providers are offering this service not only on the online, but offline too. So next time do not be surprised when you see a product recommendation by your favorite ecommerce site while you were still thinking of buying it.