Why Retail Recommendation Engines Need More Than Buzzword Tech
Pairing customers with the right products isn’t as easy as it might seem. Recommendation engines have come a long way over the years, and most deliver satisfactory upsells. The perfect method of steering paying customers toward additional complementary products they actually want has proven difficult to nail down. This is critical to help ecommerce retailers to increase their profit.
Most companies depend on collecting personal user data through cookies, browsing history, and past customer purchases. And even then the recommendations are not guaranteed to convert—most retailers have poor cross-sell performance, leaving money on the table. And retailers can see this when they compare their cross-sell performance in-store versus online.
The next wave of tech behemoths are turning to highbrow technologies like AI and machine learning to improve their success rate. However, incorporating buzzword tech is no surefire solution to perfect cross-sell product recommendations either.
Anthony Ng Monica is the CEO of Swogo, the world’s first automated bundle solution for e-commerce retailers to increase margin. Hundreds of retail leaders in over 30 countries around the world drive profitable growth with Swogo. Swogo takes a unique approach that focuses on understanding a retailer’s product assortment - Swogo Product Graph combined with machine learning and AI algorithms surpassing billions of recommendations per year.