When One Missed Signal Leads to A Horrible Product Recommendation
Marketers need to be able to inform every message, campaign, and product recommendation with data about each customer's browsing patterns and personal preferences.
But without being able to stitch together customer activity across all channels, it becomes far too easy to miss a signal of intent and deliver a recommendation that's irrelevant - or, worse, that directly contradicts what your customer actually wants.
One of the most effective ways marketers can maximize customer lifetime revenue is through delivering contextually-relevant product recommendations. When you understand what each customer needs based on where they are in their unique lifecycle, it becomes possible to send the kinds of targeted communications that not only drive engagement, but that powerfully strengthen your relationships with your customers.
But it needs to be emphasized that this isn’t simply an “added plus” or a “nice-to-have” – because the consequences of delivering an incorrect recommendation are too severe to be taken lightly. According to CMO.com, 74% of customers react with frustration to a poor recommendation or an irrelevant message. One missed signal could be the key difference between driving a purchase and driving your customers away.
As part of our ongoing research on the strengths and weaknesses of today’s popular retailers, we created an account with a fitness site that’s popular for its selection of workout supplements, sports equipment, and newsletters offering body-building tips and tricks. It was important to me that this brand be able to demonstrate customer-centricity: Were they paying attention to the signals of intent I was sending with my actions, and were they actively trying to honor my preferences with their messages and recommendations?
To test this, I browsed a few supplements in the retailer’s “fat burners” category on their webpage. I wanted to see if the brand would be able to collect data about my browsing habits, and then use the data they’d collected to make recommendations for next steps or products that I might be interested in. Based on the preferences that I’d demonstrated in my browsing session, I assumed I’d receive something like a “Customers Have Also Bought” series of recommendations that would align.
Try to visualize my reaction when, the very next day, I checked my email and was met with a campaign from the retailer recommending their selection of weight-gainers. The recommendation wasn’t merely irrelevant – it completely contradicted the needs and preferences I’d demonstrated in my earlier sessions. Sending a poor recommendation is bad enough, but sending one that directly challenges a customer’s goals (in this case, weight-loss) is disastrous.
Were this a real browsing session, I definitely would have walked away in frustration. However, I decided to push further by pointedly continuing to demonstrate the same customer goal, while giving the brand a second chance to redeem themselves – I switched from web to mobile, and abandoned a bottle of dopamite tablets (meant for appetite suppression) in a shopping cart. If the brand was stitching together web and mobile data, perhaps the reiteration of weight-loss products might prompt a more relevant recommendation the second time around.
Not the case. Unfortunately, the emails that arrived in my inbox immediately following my abandoned cart were – in addition to a standard abandoned cart email – a series of offers promoting a line of protein powders. It was clear that the retailer wasn’t bothering to collect and respond to any of the behavioral data that I was sending them with my actions, which led them to make a huge mistake with their messaging and product recommendations.
When retailers don’t tie together the signals of intent that customers send across any and all channels of engagement, it’s impossible to be able to accurately understand what they want and then deliver what they need. Beyond merely being irrelevant or impersonal, a single missed signal is all it takes to deliver a recommendation that – in cases like mine – can end up being catastrophic to your relationship with your customer. According to Lee Resources, 91% of customers who are unhappy with a shopping experience will readily not do business with you again. And based on my experience with this retailer, it’s unlikely that I’m one of the 9% that’s willing to come back.
(This post originally appeared on the Zaius blog - visit us to learn more about our research project and to discover the benefits of a B2C CRM.)