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AI helps banks drive engagement

Consumer engagement expectations are changing. Marketing must act to augment and extend relationships and opportunities, writes Sarah Welch

Banks that move to deepen customer relationships with personalized treatments enjoy significant jumps in both retention and revenue.

 

Baseline marketing and engagement expectations are being set by the likes of Apple, Google, Netflix and Amazon, where artificial intelligence and machine learning allow platforms to adapt to the user. More consumer-facing tech providers take the entire context of all the things a user has done with the platform and identify the next best interaction that will achieve the business objective of sustaining long-term value of the relationship. Personalization has become so entrenched that consumers now do not just expect to be sold to, they expect to be wooed by the brand through communications that are specific to their needs and wants. Within banking however, marketing’s transition from branch to digital as the primary focus of engagement has proved too difficult for many providers.

 

Banks are failing to develop productive digital relationships: the percent of new customers originated via a digital channel are low and relationships are degrading.

 

Consider that in 2015 the average in-branch assistance time at a major US bank providing retail checking services was 23 minutes and 16 seconds. Sales and service representatives would build relationships through a series of micro-interactions (asking questions, paying compliments, talking about a financial topic) and adjusting to the customer’s specific needs.

 

Although banks sit on vast swathes of customer and market data, many marketing departments are too resource-stretched to fully capitalize on it, unable to gain an intimate understanding of the behavior and attributes of each of the microsegments of their customer bases.

 

But the advent of AI is changing the equation, and it’s why we’ve put it at the heart of our marketing optimization platform. Rather than “programming” experiences, marketers now can simply define sanity constraints for programs and then let machine learning platforms “discover” the optimal treatments across channels. The AI’s automation of time-and-labor-intensive work associated with pre-defining segment rules, trigger rules, or journey logic opens up the scope of the potential treatment variation to a level that just is not possible today (from incentive and condition levels, to value propositions, tones of voice, images, and sequencing within and across channels). More treatment variation increases the likelihood that a customer feels “understood” and engaged in a personally relevant way by the institution. This technology makes it possible to deliver the optimal treatment and sequence of treatments for each customer across channels. It’s fueled by a rich set of Curinos-built intelligence that has been tuned specifically for financial services, which means, in the time it would take to set up one campaign or journey today, they could be up and running with this technology. And its continuous learning core never stops – getting smarter and smarter over time and carrying intelligence about the customer forward. Essentially Amplero lets bank marketers listen to their customers, deepening the relationship by engaging with them in a way that speaks to them.

 

Systems like Amplero make it possible for FI marketers to operate much more like their colleagues at the tech giants, whose engagement methods consumers are increasingly becoming accustomed to, and which increasingly mimic physical sales and advisory services. By using our formula and technology banks are doubling incremental monthly revenue and retention is boosted more than five percent. In an increasingly competitive and noisy marketplace, adding depth to a relationship is a must.

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