Generative Data Intelligence

Transform the Banking Customer Experience through Hyper-Personalization (Anoop Melethil)

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Traditionally marketing functions in banks were accountable for building brand awareness and, to some degree, generating revenue. As post-pandemic trends show, functional areas of customer acquisition, digital cross-selling, and upselling now form an integral part of marketing’s digital-first strategy. 52% of
Financial Services marketers think
social selling is critical, and 38% say revenue generation is crucial. After all, B2B marketing campaigns integral to revenue growth are essential to deciphering changing customer needs.

From a B2B marketer’s perspective, once the target personas are mapped with their real-world conditions, the campaigns (with precise positioning and messaging hooks) – or hyper-personalization – begin to deliver.

The case for hyper-personalization only grows stronger.

Personalization has moved far beyond addressing a customer by name in mailers to providing real-time product alerts based on customer needs, propensity, and circumstances. Banks are competing with the likes of Amazon, which, through their AI-based engines, can suggest product recommendations based on order history, what similar customer personas have ordered and what might be beneficial to the customer.

Brands like Netflix and others have raised expectations so much that customers attach similar personalization expectations from B2B providers, including Financial Services. Consider a

survey finding
: only 31 % of consumers believe their primary financial institution offers relevant products or creates new offerings.

Fueling this customer dissatisfaction is a plain fact. Banks, with their mountains of customer behavior data and the available analytics firepower, are yet to offer game-changing value.

(Only) Data Doesn’t Do

While a single data source is inarguably required, the data platform ecosystem is equally important. When this is in place, banks can utilize the single view, map it to customer personas, drive campaigns with specific outcomes, and monitor results that loop back for campaign success. The
JD Power survey
brings this point front and center when reporting that 78% of customers would continue using their bank if they received personalized support, but only 44% are delivering it.

Creating a single source of truth is easier said than done. Very few FIs have demonstrated success in the area. While promising use cases emerge, investments in banking technology must also keep pace. When creating the 360-degree customer view, there are indications that the financial services industry is examining advanced options across data storage, access, and analyses.

For one, banks are adopting various ways to achieve their objectives through data warehousing, MCIF, CRM, and Data Lakes. Adding to the complexities of choice, data also flows via numerous channels. For leading banks and FIs, the situation points to one approach: Use first-party data responsibly, so that customer engagement grows multifold.

From Data to  Journeys – Banks hold a clear edge, but…

The next stage involves analyzing customer data to understand customer journeys.

Compared to Fintechs, banks have a decisive edge here. Holding long-term customer relationships, they are in a better position to understand their customer’s journey stages and can tailor products as required. While this is good in theory, the situation comes with the familiar caveat: If only the banks could harness the customer data across their various systems.

When done correctly, banks can provide niche offerings quickly. A lending solution with a low initial load. Done. The child moving toward graduation needs a customized loan. Done.  

Additionally, a crucial insight that guides technology investments is how the various dynamic factors intermingle, such as the growth in customer base, the shift in demographics, and millennial banking mindsets.

In all of this, one point is crucial. With the availability of the correct data in a single place of access, the ability of technology to support new-age bankers is unlimited.

It is a cheerless fact that many well-intentioned personalization initiatives fail. Especially at the campaign level, more support is needed. This happens because of inconsistencies when data is gathered across external channels. Case in point. A

McKinsey report
posits that only 8% of banks can apply predictive insights from their ML models to campaigns.

Use Data, Without Losing Trust.

In the customer journey to heighten personalization, trust plays a vital role. In today’s sensitive environment of privacy norms and consumer protection acts, personal data collection has to happen only by consent. Therefore, banks must inform how the data will be used and for what duration. After all, being more transparent about data usage reinforces the customer’s respect – an entity valuable as gold today!

The Future of Hyper-Personalization in Banking

In sum, offering data-driven frictionless, consistent experiences across the customer journey should be high on the Marketing Leaders’ agenda. Said another way, personalization initiatives need to scale. And to do that, banks must invest in automated, intelligent models that integrate customer data across the entire lifecycle.

Not only that. To analyze for actionable insights means customer details are captured through website behavior and combined with information gleaned from their purchase-behavior ecosystem. After that, deciphering their purchase intent, history, and geo-location will help bankers offer the right product at the prescient times.

For marketing, owning the personalization mandate is a worthwhile one. It is like hitting multiple targets in a single shot – areas like data-driven marketing, e-commerce, and CRM will no longer exist in silos. As personalization irons out the friction from the customer journey, banks will accelerate to topline growth.

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