When it comes to sales, understanding the customer is paramount. The target population is hardly ever homogenous and the one-size-fits-all approach does not work at all. Yet, an experienced shop clerk can oftentimes tell what goods the particular customer is likely to purchase and, moreover, knows how to convince them to do so. Thanks to advanced profiling, behavioural analytics and Artificial Intelligence, this becomes possible for online merchants too. Adaptive segmentation is the key.
A good salesperson observes individuals stepping into the store – their body language, gestures, the way they navigate between racks, select items, react to certain parts of the display – and knows exactly what kind of pitch will make them buy. In that sense, bricks-and-mortar merchants have had, until recently, a cognitive advantage over those trading online. Fortunately for the latter, developed economies are driven mostly by Millennials and Gen Zs – ecommerce loyalists and self-focused individuals. This, in turn, is good for internet retailers and at the very same time fosters the need for better, more accurate research and analytical tools – ones capable of systematizing the diversified and continuously evolving consumer market, and keeping up with the pace of changes. Eyes, ears and intuition of a top-class sales clerk in the complex digital world. Solutions that bring ultra practical insights, enabling actionable customer segmentation.
Actionability is the (not so) new black
Actionable customer segmentation can be a powerful growth driver for any ecommerce player. “Actionable”, in this context, means real-time, adaptive and easily implementable. A clear, direct link between each segmentation insight and a quickly deployable action is a must. In order to win customers, merchants need the ability to create unique, bespoke shopping experiences for every single person they serve (i.e. offer exposition, incentive programmes, retention measures, etc.).
Not enough and uncertain – the shortcomings of conventional segmentation
Most businesses still rely on conventional segmentation models based on demographic features, such as gender, age, place of residence, etc. This approach is outdated. Such parameters are too general to be used for purchase propensities modelling, let alone making accurate predictions. Knowing that an individual is a married male Millennial with MA degree, living in a big city does not really help to predict whether or not will he buy a particular item. Moreover, as information about demographics is usually declarative, the merchant cannot even be sure if the said male Millennial is really who he claims to be.
The “How” that makes the “Who”
Adding behavioural aspects into the equation is a step in the right direction. By “behavioural aspects” I mean both – explicit and implicit. Explicit refers to previous purchase history, search history, etc. Implicit refers to the way a given user is interacting with the “shopfront” – the unique behavioural fingerprint they leave behind them. Behavioural data, however, usually means big data, so drawing any serious conclusions requires in-depth analysis carried out in the blink of an eye. This is where Artificial Intelligence (AI) steps in.
The digital shop clerk
The true power of AI is that it allows for identifying correlations where they are not obvious, thus generating nontrivial insights for business owners in real-time. Moreover, there are no fixed rules in this approach, which makes segmentation adaptive – the system continuously learns and gets more effective with each analysed customer. In other words, the customer is not assigned to this or another demographics-based segment but provided with the most likely-to-convert shopping experience.
Time to look ahead
At the end of the day, adaptive segmentation levels the cognitive playing field between ecommerce and bricks-and-mortar commerce. A shop clerk has indeed a chance to observe all the non-verbal communication (which accounts for more than 70% of all human communication) but thanks to advanced profiling and custom AI-based models, online merchants can finally take advantage of similar insights. This, combined with the general well-established e-commercialisation trend and ever increasing capabilities of online shopping experience solutions, clearly defines the future of commerce.
If you want to discover how Nethone solutions help online merchants carry out actionable customer segmentation and if you want to boost sales by giving your customers truly individual shopping experience simply contact our team.
At Nethone, Hubert is responsible for creating and operationalizing the company’s go-to-market strategy, coordination of key business development projects and building relationships with all stakeholders.