Offers and Promos:
Data analytics is very helpful for insights related to customized promotions and special offers. Every customer has unique tastes, preferences and needs. So, each customer will be interested in a personalized scheme. This can impact overall sales and profitability along with customer loyalty. While wish lists are great for the customer to curate the products he is interested in, the seller gets to see what the customer really likes and aspires to buy. So, he can customize offers based on that.
For example, a customer who has recently bought a certain brand of shampoo might be a potential target for a conditioner from the same brand and line. If his wish list has products you can give offers on, you can buy customer loyalty.
Customer experience Insights:
Data on inventory photos, color, objects in the photo, size, resolution, message combined with a database of the deployment data of time and place the content went live, what it was promoted with, who the audience were. Performance can be measured against these parameters to understand what works. The best customer experience can be charted out according to the study results.
Some photographs can look awesome on laptops but terrible on phones. Today, people shop from various platforms. So, your content needs to be feasible on all platforms. These also add to customer experience insights.
Study friction elements
A customer who comes to your site with the intention of looking at earphones searches for earphones first. Then, he likes to filter the list according to his budget and brand preferences. After this, he likes to sort the list according to price, reviews and customer feedback. After all this, if he decides to abandon a cart, he must encounter friction. Look at what causes this friction. And try to eliminate them as much as possible. For example, a cumbersome check out process that asks for too many details can irritate a customer. Or, not allowing a one time guest login can cost you. Not many people like giving details like birthdays and anniversary date for an online purchase. He will abandon the cart for these reasons.
You can get into the customer’s shoes when you see a replay of his session on your site. You can map his entire journey and get an idea of what he likes and dislikes about your site. You can mechanically track the number of seconds each customer spends on each page of your site to understand what captures customer attention. and then, based on that date, you can build better customer experience.