Getting from big data to customer loyalty

Despite your individuality, and the huge pool of information that we all implicitly and explicitly share with brands, chances are the retailers you’re loyal to, treat you like every other customer. 

The problem is, most medium and large retailers are besieged by the data produced by all our interactions with them. Big data promises insight, but only for those with the capabilities required to do anything about whatever they may learn.

Big enterprises tend to use data scientists to mine this information. But data scientists are expensive and can’t be scaled. Often it’s the same person crunching marketing and operational data, the middle man between the data and the decision-maker. This is unsustainable for most businesses.

SOME THINGS DON’T CHANGE

In industries where stable, repeatable patterns are already identified, technology provides (if you’re into efficiency) very exciting ways to manage this. For example, most online retailers’ customers fall into these segments: prospects, first-time buyers, active customers, defecting and lost customers – the age-old customer life cycle. Layering the customer’s latest behavioural information over this – the recent interactions, the value of the last transaction, and the frequency of engagement – is the most indicative, tested method of segmentation.

Emarsys technology plots these factors against the customer life cycle, alongside additional predictive algorithms, to automatically segment retailers’ customers in meaningful ways. We won some of our largest clients because their enterprise business intelligence tools just presented more questions than answers. They moved to us in favour of customer intelligence around the life cycle. They understand that the problem of big data is about focus – you need to know what you’re looking for.

STOP GUESSING – PREDICT

The result of technology processing the collected data is that instead of guesswork based on arbitrary demographics (after all, are you predictable based on yours?), marketers can take a scientifically smarter next step based on a mathematical likelihood of selling more to each particular customer. With customer intelligence, targeting options increase exponentially from sending to broad-brush segments to sending campaigns built specifically around each individual.

Emarsys technology plots these factors against the customer life cycle, alongside additional predictive algorithms, to automatically segment retailers’ customers in meaningful ways

DATA PARALYSIS STRIKES

No organisation has the human resources to send one-to-one campaigns without marketing automation, hence its recent rise, making it now a standard part of any serious marketer’s tool kit. But marketing automation has its roots in business-to-business and so the intelligence part being connected to the marketing automation part is rare, let alone with a focus on the life cycle.

BURSTING AT THE SEAMS

Experience will probably tell you that seams are often bad news in technology. Just as you’re winning when teams communicate well, you’re winning when your important technologies talk to each other. We work with online sellers specifically because the intelligence part of our system is built for them and talks to the automation part. So retailers can recover abandoned baskets instantly or react to any indication that, for example, their best customer is defecting. In short, influence more customers into buying more.

The learning alone from running your marketing campaigns around the customer life cycle and listening closer to what customers actually do can be incredible. We’ve seen customers remodel their businesses, rethink their messaging or simply remerchandise once they have access to predictive behavioural data on their customers.

One tactic that’s incredibly low effort is predictive recommendations – placing products each customer is algorithmically most likely to buy, everywhere they look such as social, e-mail, mobile or website. The sales impact from just this is striking, as shown in a case study from Ebebek, where predictive recommendations generated 320 per cent more revenue than manually selected products.

If your marketing team can’t use data to influence customers, you’ll become a laggard. Your biggest customer’s attention is a finite commodity. If you want to respect their loyalty and keep them buying, you need a technology built to do just that.

Join our webinar in conjunction with the Direct Marketing Association and we’ll show you how to provide the experience they deserve in every interaction.

Visit Emarsys.com/raconteur today to book your place