Challenge
An online store with a wide assortment of products was struggling with a relatively low conversion rate. Despite many visits to the Web, sales were unsatisfactory. The main reason was the lack of personalized communication with shoppers. They received generic newsletters and ads that did not hit their shopping preferences, resulting in low engagement and shopping cart abandonment.
Action
- Data analysis and segmentation
The store implemented iPresso monitoring code on the site, tracking user behavior in real time (products viewed, add to cart, purchase history, demographics). Accurate customer segments were created based on their preferences, purchase stage (new, returning, abandoning cart) and activity. - Personalization of product recommendations
Recommendations based on customers' history showed them products similar to those they had previously browsed - but also bestsellers in a given category, as the store was keen on effective up- and cross-selling. - Dynamic content on the site
Personalized pop-ups and recommendation frames appeared on the WWW. New customers saw promotions for their first purchase, returning customers saw offers tailored to previous purchases. - Personalized e-mail campaigns
Customers of different statuses (new, returning, long inactive) received automatic email sequences with personalized recommendations and incentives for future purchases.
Results
- The conversion rate increased by 28% compared to before the implementation of personalization.
- With recommendations of complementary products and personalized offers, customers were more likely to decide to buy more products, making the average order value increase by 15%.
- Precisely targeted email campaigns contributed to the recovery of potential transactions and reduced shopping cart abandonment by as much as 20%.
