This may be an over-simplification, but if I am shopping on-line to purchase vegan cookies and have consistently been buying vegan baked products from this shop, I’m probably not very interested in cured meats being recommended to me. By deepening awareness of customers’ experience, personalization could be used as a powerful tool for curating a highly-specialized customer experience. It is a valuable way to learn about buyer habits and current trends. It makes e-commerce more perceptive and sensitive to user needs.
So how can you integrate customer personalization successfully in your e-commerce design or website?
Customer collaboration and transparency is a key to practicing personalized e-commerce. Research shows that customers respond better to personalization when it’s descriptive and open regarding methodology.
According to a study from Harvard Business School’s Journal of Consumer Research, when consumers were shown messages next to advertisements, such as “recommended based on your prior views,” it was more likely that they would click on the site and purchase items than if there were no message present.
Moreover, experiments published by Harvard Business Review showed evidence that purchase interest may decline when consumers find out about their personal information flowing in a way they dislike. Personalization is most effective when elevating consumer experience is prioritized, as well as building user trust.
You might be wondering, how exactly is personalized marketing practiced? The equation has two parts, capturing data and personalizing it, which are done using several methods. Behavioral targeting is a process of gathering data on user behavior on a specific website. What are their browsing tendencies? Do they tend to look at new offerings or head straight to a certain product category? What were their past purchases? Psychographics plays a key role for behavioral targeting in helping to understand user values, interests, emotions, and more.
Demographics simply places users in categories by gender, age, and income. This practice can be more highly nuanced, as shown in our post on creation of user personas. Artificial intelligence (AI) machine learning is an integral personalization tool. There are an infinite number of factors that could be considered for personalized marketing. A1 is valuable for taking data beyond specifics and translating it to tangible steps for personalization. AI has an immediate impact since it can work while the user interacts with a website and make suggestions immediately.
Here are tips to understand the concepts better, plan a personalization strategy, and utilize it. It is extremely helpful to look at various ways personalization is used for e-commerce. The following examples highlight strategies being used across various media, desktops, apps, and email marketing. They also touch on their interaction with each other.