In the highly competitive world of eCommerce, it’s become absolutely crucial to understand your customers. In fact, smooth customer experience has turned into one of the most important pillars of the whole field.
To provide your customer with the best experience possible, you need to have a clear picture of what they expect. And that’s where big data comes in handy.
It’s no secret that the success in eCommerce stands and falls with proper data collection. However, the numbers you can generate can turn out to be overwhelming.
That’s why a significantly rising number of companies are looking into solutions with proper customer intelligence. They base their operations on advanced analytics, such as predictive analytics and artificial intelligence.
This allows them to better understand and provide immediate solutions to individual customer needs and have the foresight to proactively address future behavior and expectation.
According to Walker (customer experience consulting company), the main three dimensions that help boost the customer experience are ease, speed, and personalization.
While an easy-to-use and fast front-end is more of a technical parameter of your website, for personalization using proper data analysis and Artificial Intelligence is the key.
Customers value companies that can give them real-time responses and forecast their future needs.
The best part is that you have tons of data to understand your customer properly. You just don’t use them on a full scale.
Let’s change that together!
As noted above, big data is a great achievement of humankind that is currently moving the needle in the world of eCommerce. But it can be messy and overwhelming for humans.
That’s why you should implement particular analyses generated by Artificial Intelligence platforms based on machine learning that are capable of real-time analysis, evaluation of historical data, and forecast.
The main advantages of advanced analytics are
One of the greatest ways to improve customer experience is to zoom in on particular customers and see their whole picture. The 360 Degree Customer View is a great way to perform the task.
The system gathers data from various points of the customer’s journey. On a single screen, you can see the person’s historical and present events, and thanks to advanced analytics and artificial intelligence, you can see a prediction of the customer’s future behavior.
This way, you can reach out to particular customers with detailed information about their preferences, or you can easily react to inquiries from their side.
The analyses can also generate a classification of the person in various modes. It can point out the average value they spend, the frequency of their purchases, and how important they are for your business compared to others.
Solvency is a metric that helps you find out how much money the customer is willing to pay for products on your eCommerce store. The amount is usually calculated from historical purchases but can be also influenced by real-time behavior and purchase forecasts.
By setting different levels of solvency, you can categorize your customers into relevant clusters and offer them more personalized content leading to a higher number of finalized purchases.
It’s always easier to maintain existing customers than to acquire new ones. But sometimes it happens that customers stop using your services. Sadly, it just occurs as it’s not realistic to keep all the people forever.
But it’s important to measure the rate of returning customers and the ones who churn because high levels of churn can indicate that the services you offer need improvements.
By keeping track of customer churns with the combination of machine learning and Artificial Intelligence, you can identify the possible cause of churn as well as customers that will be likely to leave.
With the analysis of churn you can:
RFM Insights (Recency, Frequency, Monetary) are a great way to make a breakdown of customers according to their historical behavior and loyalty towards your business.
This analysis evaluates how long it is since customers purchased something on your online store, how often they perform a transaction, and for what price. The combination of these metrics then helps you create a customer’s profile for further action.
With RFM insights, you can distinguish different groups of users that require a different approach from your side.
At Samba.ai, we work with 12 different categories of customers based on RFM insights.
■ Champions are paramount clients with the highest average of order value
■ Loyal Customers return to your shop frequently
■ Potential Loyalists have come back a few times but never spend much
■ New Customers would find it compelling if you'd reach out to them after their first purchase
■ Promising customers have bought something just once or twice but it was really expensive!
■ Needs Attention - careful! These clients have stopped returning to your shop. Motivate them to come back!
■ About to Sleep
■ At Risk - keep on returning to your shop. But their last purchase was long ago. Get in touch with them ASAP!
■ Hibernating are seasonal clients who come back to you only on special occasions, such as Black Friday or sales in January..
■ Lost are the ones who seem to have lost interest in your shop completely. But there is always a chance to get them back with proper motivation, such as sending them a voucher they wouldn't resist.
■ Cannot Lose Them - send them SMS or give them a call immediately because these are champions who stopped returning to your shop. Something must be done!
Each of the groups represents the value the customers have for your business and requires different actions from your side.
For instance, if your customers belong under At Risk, it means that the algorithm has concluded that they are likely to churn. This makes a great opportunity for a reach out to try to prevent the churn from happening. .
One of the greatest assets of Artificial Intelligence-based on machine learning is that it can help you predict the future. Of course not absolutely, with the ability to work with huge amounts of data based on historic and real-time behavior, it can help you forecast the behavior of your customers.
It can help you estimate the revenue trends in a given period of time, as well as the number of orders, the volume of marketing communication, and also the number of locations you distribute the emails to.
What’s more, with advanced AI algorithms, you can predict the needs of your supplies and the logistics of your goods.
Let's say that you use your online store for selling gardening supplies. With the first sunny days, many people emerge outside to barbecue for which they need charcoal that you have in your store.
With Forecast Insights, you can estimate how much of the charcoal would be needed, when is the highest demand, and where to ship. This will help you order the right amount from your suppliers.
The eCommerce business is a constantly evolving and extremely competitive field where every single customer matters. This means that customer experience is the real deal-breaker for upcoming years.
But thankfully, because of advanced analytical tools and AI algorithms capable of handling big data, it’s now very easy to get to know who your customers really are. Therefore, you can provide them with the best experience possible by analyzing the historical behavior, real-time events, as well as forecasts of their future needs.