It is a common fallacy that ecommerce personalization must and should treat everyone as completely unique individuals. Yes, I know we all think that we are completely unique people. But the reality of it is that we are more alike in or choices and preferences than we think. What is different about each of us though, are the patterns of how we behave – or the context in each moment. This is why providing a unique online shopping experience is both impractical and suboptimal for an ecommerce retailer. So, rather than focus on uniqueness, the goal of personalization should be to understand and deliver relevant content that best meets each visitor’s needs right now, in real time. To do this, we need to know intent. An intent-based approach to personalization is both elegant in its focus and powerful in implementation.
A user’s current intent is the best indicator of current needs. Intent is what the person is trying to achieve at that moment. Intent is expressed through behaviors of the user including the search terms they use to navigate to a site or in onsite search, the links they choose to click on, and which products or content items they engage with.
Personalize Experience for the Now, Not the Past
Many supposed personalization systems rely on customer profile data to deliver personalized content. These systems suppose that available user data such as demographics, home location, or past purchases are sufficient to predict what a person is likely to be interested in today. While profile data can tell you if the individual is more likely to purchase a certain brand, spend over a given amount, or what’s popular in their area; profile data cannot tell you what the person is looking for right now.
In addition, profile data is not particularly helpful when you have never seen the visitor before (anonymous visitors), the person is shopping for someone else (gifts), or when the person is buying something new and they deviate from past purchase behaviors (business traveler buying a vacation package). So when thinking about personalization strategies, be sure that you look for solutions that observes each user’s behavioral cues and takes advantage of onsite search terms to determine what the person is looking for right now. This step should be backed up by machine learning/data science that determines patterns in behavior and product affinities on a 24X7 basis. From there the system can infer what content are most likely to be interesting and then act in real-time to deliver the compelling content, in the moment.