Be sure to analyze all angles when considering shopper loyalty.
With a global turnover of $27 trillion projected by 2020, it’s no wonder why CRO (conversion rate optimization) is possibly the most measured action of ecommerce retailers. And since the average conversion rate for ecommerce continues to hover at 1.33 percent, according to Compass, any added advantage that leads to understanding shopper behavior can increase those conversions significantly.
Advanced behavioral analytics offers businesses this added advantage by collecting, storing, enriching and analyzing raw user data over time. This makes it possible for patterns to be revealed that lead to better insights of shopper loyalty, which businesses can use to drive higher engagement and reduce churn.
Here are six behavioral analysis tips that can help retailers get more insight into shopper behavior:
1. Analyze cart abandonment to encourage shoppers to purchase
The moment a shopper adds an item to their cart is the moment that makes or breaks them as a customer. Either they continue to purchase the item or they abandon their cart. The more a retail site understands about the process that led a shopper to abandon their cart, the greater the likelihood to drive higher conversions.
For example, shoppers may tend to add items to their cart a few days after abandoning, perhaps as a response to an email marketing campaign they received. Additional large groups of purchases a number of days after cart abandonment can reveal more insights into customer behavior and encourage further optimization.
2. Identify which retail items are the most popular
Beyond cart abandonment, a high-level report of the top 10 items shoppers add to their cart can give insight into the types of items shoppers are interested in purchasing, especially in comparison with items they may simply be browsing (i.e. luxury items they wish they could purchase). Businesses can also learn a lot about shopper behavior by analyzing the retention rate of shoppers who tend to purchase the most popular items. Retailers may find, for example, that loyalty is higher among shoppers who purchase luxury items.
3. Learn to spot the difference between lookers and browsers
While certain items might be popular because shoppers tend to purchase them, others may be popular because shoppers may tend to continuously view them. Shoppers may be likely to continuously view items that cost over a certain amount of money before purchasing them, since this is part of the consideration stage of the customer journey. Other shoppers may view items over a certain amount and never purchase them, since they are cautious shoppers, and the items are over their budget, for the time-being.
4. Examine shopper retention from a different angle
Retail businesses are constantly measuring shopper retention to learn what drives shoppers to repeatedly return to purchase on their site. Beyond simple cohort analysis of campaigns, for example, retailers can also examine retention of shoppers according to shopper type (VIP, first-time purchasers, occasional purchaser) or according to a particular behavioral segment.
For example, focusing on the “frequent shoppers” segment according to the different times they registered to the website can shed deep insight into shopper behavior, helping retailers optimize these shopper registrations in the future.
5. Path analysis of shoppers
What was the most popular path of shoppers? Did they mostly browse within one department or move between different departments? Did they add items to their cart after browsing each department, or did they wait until they were finished to add items to their cart and immediately purchase? Understanding the past behavior of shoppers allows retailers to offer effective next-best offers at the right time and increase loyalty and engagement in the future.
6. Examine the exit events of shoppers
Similar to understanding what drives shoppers to purchase, retailers also need to know what drives shoppers to churn or leave the site temporarily. Was it a better offer from another retailer? Was the offer delivered at the wrong time or to the wrong shopper segment? The ability to examine the last three steps shoppers took before exiting the site, for example, can offer deep insights into why shoppers didn’t complete their purchase. With these insights, retailers can adjust their offers or prices in response to their shopper behavior.
A golden opportunity not to be missed
Shopper behavior is dynamic, and it is crucial for retailers to be able to constantly monitor it from all angles. The ability to see sudden changes in behavior at a certain time for a specific campaign, and adjust accordingly, can mean a significant increase in revenue, and often, an edge over the competition. Behavioral analysis enables retailers to keep their finger on the pulse of their shoppers so they won’t miss this golden opportunity.
Guy Greenberg is the Co-Founder & President at http://www.cooladata.com/, a leading behavioral analytics platform. Before founding Cooladata, he was the co-founder and CEO of Gilon Business Insight, which was acquired by Ness Technologies in 2010. At Ness Technologies, Guy served as Senior Vice President for Global BI and Big Data, where he worked with some of the largest corporations in the world. With over 20 years of experience in big data and startups, he is an active angel investor and adviser of several Big Data startups. http://www.cooladata.com/
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