There are numerous analytics tools available for e-commerce sites, from Google Analytics to more sophisticated and powerful offerings, and many organizations are severely underusing them. These tools make it possible to track a variety of valuable consumer statistics such as where they visited the site from, what geographic area they live in, and what types of products they have previously looked at or bought. This data can all be harnessed to offer the consumer a personalized experience that will help them find products they are interested in and encourage them to complete more purchases. Taking advantage of predictive analytics can increase conversion rates and profits substantially.
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Dynamic Landing Pages
Analytics provides a range of information about the customer that can be used to optimize the page they see when they visit a website. This includes what site they came from, what location they are in and demographic information. For example, if a visitor arrives at the site via a coupon link or other promotion, it is possible to create a pop-up or banner displaying the code and indicating that it has been applied. This can reduce confusion (is the coupon automatically applied? Do they need to type it in somewhere? Is it restricted based on location?) and encourage them to take advantage of the offer.
This information can also be used to personalize what products and offerings the customer sees when they first access the site. Analytics can customize these based on the statistics mentioned in the previous paragraph, as well as on data from previous site visits and purchases. If the consumer is greeted with products that interest them, they are more likely to stay on the site and to complete a purchase.
Customized Browsing Experience
Not every consumer needs to see the same thing when they visit a website. Location, for example, is a relevant factor, and using it can improve the customer’s experience and show them more relevant results. Automatically taking the visitor to the site appropriate for their country is one way of making use of this, but there are others. Do coupons vary depending on the city or specific store? Are certain products in stock at some locations but not others? Can this store hold a particular product for pick-up? Showing the customer only the products that are immediately available to them can decrease frustration and improve conversion rates.
Another common technique, as seen from Amazon and other large Internet retailers, is recommendations based on both their own purchases and those of other customers. Showing related products that other customers have bought can encourage the shopper to investigate those items as well. If the site has a large inventory, identifying what products are most relevant to a given customer can have a significant benefit.
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Personalized e-mail offerings are much more successful than generic ones. According to research by Experian, they have 29% higher open rates and 41% higher unique click rates. By tailoring e-mails to a customer’s demographics and preferences, it is much easier to engage their interest and induce them to click through to the website. Site browsing history and previous purchases are some ways to personalize these messages, but paying attention to location, time of year, and even time of week and day can also help increase engagement.
Predictive analytics comes down to determining what the customer is most likely to want, making it easy for them to find it, and providing incentives to purchase it. While that may seem daunting at times, there is a variety of easily available tools to help implement this. Even basic, easily available information can improve conversion, and for companies that want to drill deeper into consumer data, there are many solutions on the market to maximize results.