80% of shoppers are more likely to buy from a company that offers personalized experiences (Epsilon). That’s a significant percentage of users, isn’t it? Personalization is all about facilitating how well brands build in-person conversations with the end-user. We often see brands asking a couple of questions while using an app for the first time, for example, our age, interests, etc. Such personal information helps the brands precisely target the end-users with relevant information, ads, and product recommendations.
Especially in eCommerce, personalization plays an important role. Today, every eCommerce platform is a marketplace that enables sellers to list their products to reach the end consumer users. Hence, at the front end, personalization helps users to get what they want. In the backend, sellers get timely reminders to restock a particular product, maintain inventory, and forecast sales for the next season.
The holistic approach of serving both parties with much dedication and highly paced Machine Learning tech enabling companies like Amazon to position themselves as market leaders in this space. Eventually, every eCommerce platform got hold of such techniques and tactics to compete with market giants.
Here are the few personalization concepts of eCommerce that any organization can start with:
It all comes down to how well we understand a user as an individual, with selected interests and diverse choices. Hence, user profiling, otherwise known as persona building, lays a foundation for personalization. Knowing more about a user is always good. So brands should not leave any opportunity of collecting the personal information of the user. It would be a bad idea to ask everything in one go at the very onboarding phase itself. But, occasionally seeking answers for progressive profiling of the user pays off really well for precise personalization.
The rules of personalization also tend to change concerning brand choices. Every eCommerce platform delivers a different kind of experience. However, every brand tries to experiment with the content they show to the end-user. We often see these brands suggesting the products we search for on google on the top page and at times with additional discounts to speed up conversion.
Considering the massive amount of data related to customer touchpoints available today, brands were able to figure out the user behavior. These behaviors are often used to forecast the expected cart value, whether a user is discount-driven or not, and if a user is about to churn or convert. These futuristic insights are helping brand managers to come up with specific goal-oriented campaigns that could lead to more conversions.
Location and Language:
Lately, brands have realized “only English” is a barrier to entering the international markets and diverse nationalities like India. Each state is the size of a country, and many states have their distinct languages. So to expand the business into tier-II and tier-III cities in addition to personalization, localization of the website and product is a game-changer.
Today we see all big eCommerce companies have localized their business in all prime languages and, at times going ahead, celebrating local festivals with a sale.
Be it an NPS survey on your service/product recommendations or a study to figure out the pulse of the users; user responses are expected to be heard by the brands. Most of the users don’t spare their time to answer any kind of survey and tend to skip it most of the time. Few users spend their time providing valuable feedback to the companies anticipating improvements and changes in the process. There is also an expectation that brands respond promptly to all those suggestions in terms of engagement and service in such cases. Thus, the new beta version of the website can be A/B tested on those audiences who suggested such improvement—bearing in mind that only these people are the right set of audience to reach out for genuine opinions.
Every customer is different. Using the same data is not that hard to determine if a user is a night owl or an early hen. But most of their usage patterns are predictable based on their past usage data. Thus every user has their own most active usage interval, which indeed would be the right time to reach out or communicate personalized recommendations via push or in-app messaging.
Personalization is by far the most discussed yet less focused by brands. Some call A/B testing alone personalization, and few others think segmenting users for a campaign and personalization is just the same. With machine learning being implemented at ease and the standard processes for recommendation engines lining up, personalization is shaping up with time. So, personalization is much bigger than calling a user by their name. It is a way of personalizing the experiences so that the users feel connected to the brand. The more you know about a user, the more you can serve them. So, personalization is directly related to what businesses know about a user. Collecting such personal information without bothering users is an art yet to be mastered by many businesses.