Customer loyalty was a top theme at the National Retail Federation's recent Big Show in the US, where thousands of retailers gathered to discuss trends and learn from the industry's top names. This theme frequently overlapped with another important topic that is linked to loyalty: a strong focus on customers and on personalising the retail experience, according to Brendan O'Kane, CEO for OtherLevels.
Customer-centricity was at the heart of a presentation from large Canadian grocery-store chain Metro and Dunnhumby, which specialises in helping companies personalise their loyalty programmes. In their presentation, the executives pointed out that the average Canadian has 14 loyalty memberships. In the US, that average number is about 18 memberships per household.
So, how does a retailer like Metro stand out from the pack? By using data gathered through customer interactions across all channels to personalise marketing messages and strengthen engagement with its most loyal customers.
Of course, fine-tuning all sorts of marketing messages - in print, on television and on desktop-based Web - is important to any retailer's overall strategy. But, to build top engagement with its highest-value customers, the retailer will need to put a strong emphasis on mobile.
That's because, as techniques such as action analytics, A/B split testing and retargeting for mobile record how loyalty members interact with messages, they also generate data. And that data can tell the retailer a lot about a customer's preferences, painting a detailed picture of individual loyalty members.
In order to get to know their mobile-toting loyalty members better, retailers can employ this three-step technique:
For example, a fictional grocery chain with a mobile app-enabled loyalty programme might run an A/B split test to see what kind of push notifications drive higher conversion rates.
From previous analysis of a particular loyalty member's interaction, the chain knows the segment it's targeting regularly buys large amounts of eggs, sugary breakfast cereals and, say, Sunny Farm brand milk. These loyalty members fit the profile of moms with big families. So the chain deploys the following:
Message A had a 40% open rate and a 20% conversion rate. For every 100,000 messages sent, 8,000 led to a redemption.
Message B had 30% open rate and a 30% conversion rate. For every 100,000 messages sent, 9,000 led to a redemption. Though it had a lower open rate, message B yields better ROI because it had a higher redemption (9% vs.8%).
Using what it learned from these results, the chain further fine-tunes the message and re-deploys to customers who ignored the message and those who opened it but didn't convert. After these tests, the chain knows this customer segment much better than it did before. And that knowledge leads to ever-more personalised messages that can drive engagement and ROI.
For any retailer with a loyalty programme, action analytics is critical to tailoring messages that speak to what customers really want and building stronger relationships that last.
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