When Amazon introduced product recommendations over a decade ago, they successfully tapped into a growing consumer expectation for a personalised shopping experience and certainly set the bar for other retailers. Today, recommendations form an essential strategy for any ecommerce brand hoping to grow revenue, providing a personal shopper based on the customer’s browsing and buying patterns.
Product recommendations are an effective way to re-ignite the interest of a shopper, but chasing a customer too vigorously might put them off your brand completely. So understanding how to use them in a way that will drive value is crucial.
Making the sale
Browse recovery emails use techniques similar to basket abandonment messages, encouraging shoppers who left your website without adding products to the basket to come back. These emails should be used to remind consumers what they were looking at or make relevant recommendations for similar products. It’s not simply about selling, but selling smarter.
Delivering one-to-one recommendations
You should be using all the customer data available to drive higher levels of personalisation. Leverage contact, order and browse behaviour information to ensure the customer feels understood and recognised. This data can be used in line with multiple filtering options, including “customers who bought this, bought that,” “you might like” and “recommended products from your preferred brand.”
Do you want to move low average order value customers into a higher tier? Adjust the filters to show high-margin items within a shopper’s area of interest. Have a product customers buy again and again? Sell out faster with an “almost out-of-stock” email. By showing similar products and additional options, consumers may even end up purchasing more than they had intended.
Tracking progress
With so much data being generated and captured, it has never been easier to track results and get a better understanding of what’s working and what isn’t. Simply implementing a recommendations functionality is not enough in the long-run. Why rely on instinct when there is so much data available to provide concrete insight? Make sure you have reporting that shows what is effective and split by rule, popular products and traffic trends.
The information needs to be kept at the contact level, i.e. the individual email, to positively impact segmentations and workflows going forward. Use these insights for changes to make your recommendation strategy as effective as possible.
For years, businesses have talked about the value of keeping customers vs. acquiring new ones. Recommendations and browse abandonment fit snugly into that strategy. The latest techniques are quite simple and cost-effective to implement, restricting them no longer to ecommerce giants but making them an easily accessible option for retailers of all sizes looking to grow revenue. It’s time to give it a try.
By Saima Alibhai, Practice Manager, Professional Services at Bronto Software
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