The significance of AI and ML in Effective Product Recommendations

By December 15, 2020 January 7th, 2021 eCommerce Trends, Email Marketing

Product Recommendation

The right recommendations increase sales. Make sure they’re on target with Artificial Intelligence (AI) and Machine Learning (ML).

“Using marketing automation without AI is like dancing without music,” Niraj Ranjan Rout, Hiver’s Founder, observed. “Sure, it works, but it won’t create the same magic.”

This level of magic is what the latest generation of customers are expecting in terms of personalization.

Just as Amazon’s recommendations for books and products or Netflix’s recommendations for movies are tailored for them, they expect their marketing messages to reflect their taste and personality. That’s where AI and ML come into play.

Show your customers what they want 

As explained in a Martech Today article, “consumers tell us what they want — and how, where and when they want it.”  But you need to have the technology in place to read and automatically act on those signals.

AI & ML enable marketers to deliver on those expectations because it can anticipate not just what customers would want to hear about but when and how they’d want to receive that communication.

That’s why you need to give your eCommerce the Big Data advantage that makes companies like Amazon so successful. This is what Remarkety’s solution enables you to do.

Recommendations boost sales and revenue

Accenture  found that  91% of consumers say they are more inclined  to shop where they get  relevant offers and recommendations. They also are more likely to return.

Sales and revenue  will rise with AI-enhanced marketing, according to  the McKinsey Global Institute Study’s Artificial Intelligence, The Next Digital Frontier’s report. It offered several case studies as proof.

Among them is Stitch Fix, the personal shopping service that can figure out what a customer wants even if they fail to describe it. Its algorithm reviews the images they favor on Pinterest to get a sense of their taste.

“Insights-based selling, including personalized promotions, optimized assortment, and tailored displays, could increase sales by 1 to 5 percent,” the report says.  Even more impressive is the potential 30 percent growth in sales that can result from “this kind of personalization, combined with dynamic pricing.” for internet sales.

“Shoppers that clicked a recommendation were nearly twice as likely to come back to the site; 37% of shoppers that clicked a recommendation during their first visit returned, compared to just 19% for shoppers that didn’t click a recommendation during their first visit,” reports Salesforce.

The conversion rate for the online shopper who responds to a recommendation is 70% higher per session than for those shopping without the recommendation, according to eMarketer. The benefit holds even on return sessions to the extent of a 55% greater conversion.

The average order value (AOV) is also boosted by recommendation. As per Salesforce: “Purchases where a recommendation was clicked saw a 10% higher AOV, and the per-visit spend of a shopper who clicks a recommendation is five times higher.”

Ready to see if it can work for you? Try it for free or book a demo.

Making product recommendations work for your business

Anyone who has shopped on Amazon or ordered online from the likes of Target and Walmart has received emails with the message, “We thought these may be of interest.”  They’re drawing on their vast amount of data on millions of customer transactions and selections to predict what is likely to draw your attention.

Smaller businesses don’t have that kind of Big Data to draw on. But Remarkety puts its power within their reach.

Remarkety leverages data both from the individual customer and the customer’s  segment, drawing on  browsing and purchase history to deliver different options for relevant recommendations to your customer. One size does not fit all, and neither do recommendation messages.

The following are different types of messages Remarkety can make work for you:

  • Complementary product recommendations triggered by a purchase; like the eye liner that matches the eye shadow, the bowl in the same pattern as the platter purchased, etc. Even if they didn’t add the item on at the time of the original order, they may decide they want to complete the look after they receive the item.
  • Best sellers from customer’s favorite category: for the customer who has demonstrated an interest in pet items, for example, this can show what other pet owners are buying now. This is selling on the basis of segmentation.
  • What’s new or trending now among their product categories or those that are related. For example, someone who has shown interest in candles may be interested in scented versions, as well as other scented products. That combines data on the customers with more generalized data to deliver a product recommendation that they would find interesting rather than spammy.

Remarkety’s recommendations are always relevant because it tracks what customers have already bought and not suggest anything already ordered. It also will always limit suggestions to products that are currently available, so that you will not get customers interested in an item, only to become disappointed when they can’t buy it.

With Remarkety’s advanced recommendation ability, your business can tap into the power of AI to achieve a level of personalized insight that is normally beyond the reach of small business resources. Retailers that implement it enjoy  increased average order value, boosted revenue, and customers who keep coming back.

Ready to see if it can work for you? Try it for free or book a demo.