There’s a Chinese proverb that says, “The best time to plant a tree was 20 years ago. The second best time is now.” That couldn’t be more true than in the case of data-driven marketing.

A few years ago, companies that were considered innovative and ahead of the curve began using consumer data generated by years of digital activity to redefine marketing as we knew it. Now, those companies are the ones that are on track for continued success. That leaves the rest playing catchup in order to create a solid marketing foundation for the future. 

Much of the financial industry is behind the data curve. 

For the past two years, incorporating AI, big data, and advanced analytics into marketing strategies has been ranked as the most important area of focus for financial institutions in the coming year.^1,2  Despite this general consensus, many financial institutions are missing out on the opportunities data provides. And the financial industry as a whole is falling behind.

While nearly half of technology industries are utilizing advanced analytics to drive their marketing, only 4% of financial services has made this shift.³ That’s an unfortunate statistic considering the financial industry has access to more useful data than most other industries. The problem is that the massive amounts of data are often too much for an institution with limited resources to properly sort through. 

The fact is, data can be messy — especially if you’re diving into it for the first time. But the opportunities it provides to not only attract but retain consumers makes it worth getting your hands a little dirty.

Today's consumer expects personalized marketing. 

Digitally-inclined consumers have been conditioned to only see advertising that’s not just relevant but speaks directly to them. So offering up ads or emails that fall short won’t capture their attention, let alone earn the click.

80% of consumers say they are more likely to purchase from a brand that offers personalized experiences.⁴ As technology capabilities have continued to increase, the definition of “personalized” has become more and more refined. An email with a person’s name in the subject line is good. An email with the person’s name and product recommendations based on their interests? That’s even better. And exactly what you need to build stronger relationships with both new and existing account holders.

Using customer segmentation also plays a key role in personalizing marketing. This involves grouping consumers by demographic, lifestyle, and behavioral characteristics. Then you can tailor your messaging and imagery to specific segments, driving a better marketing performance.

Brands who are using data-driven campaigns to tailor content to specific consumers are seeing the results. Figures from Salesforce reveal high performing businesses use data-targeting and segmentation 51% more often than underperforming businesses.⁵

The expectations of consumers have made data-driven marketing a necessity, not just a “nice to have.”

Here are the three ways to turn your data into a personalized marketing machine:

1. Be predictive-- not just descriptive. 

The simplest way to analyze data is by looking to the past to measure what happened. This is known as descriptive analytics, and while useful to a certain extent, it doesn’t warrant the same amount of influence on marketing decisions as the real-time analytics available today. 

Data that is processed through predictive modeling can be much more effective in not only creating personalized experiences for consumers by anticipating their needs but also informing business decisions. 

For example, a predictive algorithm would be able to accurately tell you how likely a consumer is to open a checking account (crucial to avoid wasting marketing dollars on unlikely prospects). It could also tell you whether those consumers have a high wealth predictor, or if a current account holder is likely to close their account with you soon based on a lack of engagement.

Predictive analytics helps you get in front of your audience rather than chase behind it and is a key component of a data-driven marketing strategy.

2. Be prescriptive-- not just predictive. 

Taking your marketing a step further means funneling your data through prescriptive analytics — where it not only predicts what will happen but prescribes recommendations to improve future results.

Through prescriptive modeling, you can continuously optimize your portfolio performance. As in the example above, predictive analytics may alert you to an account holder who will be closing their account soon. Prescriptive analytics would send that person relevant marketing to boost engagement and provide recommendations for products or services that would better fit their needs. This could include using a debit card or signing up for e-statements to earn a reward.

Allowing data to drive your marketing strategy and consumer relationships in a prescriptive manner will add value for your current account holders as well provide insight into a consumer’s needs and offering solutions that can best help them.

3. Find a partner who can help. 

As we said above, community financial institutions recognize the importance of AI and big data but are often at a disadvantage when it comes to aggregating that data and building useful algorithms from it. This takes time, manpower, the right technology and a lot of data. With limited resources, many community financial institutions just aren’t equipped to take on the task internally.

Outsourcing data to a third party can relieve these pain points while letting you take advantage of the research investment and operational scale that a company specializing in data-driven marketing provides.

Don’t wait another 20 years to plant your tree. As a community financial institution leader, you’re sitting on a data goldmine. From acquisition to cross-selling, using data to power personalized marketing programs will guarantee that you’re speaking to the right person, at the right time, with the right message. In doing so, you will deepen your relationships with consumers before (and well after) they begin.

Harnessing data is one piece of the digital marketing puzzle. See everything you need to create a successful digital marketing strategy here.

Allied & Kasasa work collaboratively with our customers to build 21st century growth strategies that meet the demands of the modern consumer.

This article was co-produced by Traci Mottweiler, Director of Growth Strategies at Allied Solutions and Keith Brannan, Chief Marketing Officer at Kasasa. 

About Allied Solutions

Allied Solutions, LLC is one of the largest providers of insurance, lending, and marketing products to financial institutions in the US. Allied Solutions uses technology-based products and services customized to meet the needs of 4,000 clients along with a portfolio of innovative products and services from a wide variety of providers. Allied Solutions maintains over 15 regional offices and service centers around the country and is a subsidiary of Securian Financial Group, Inc. Allied Solutions has tools and resources that can help you keep an eye on the potential areas of impact, protect against collateral losses, and stay on top of any new events, bulletins, and regulations as they happen.

^{1 Digital Banking Report Research. Dec. 2018. The Financial Brand.
2 https://thefinancialbrand.com/90673/financial-marketing-artificial-intelligence-martech-data-analytics/
3 http://assets.teradata.com/resourceCenter/downloads/WhitePapers/EB9996.pdf
4 https://www.slideshare.net/EpsilonMktg/the-power-of-me-the-impact-of-personalization-on-marketing-performance/1
5 https://www.huffpost.com/entry/state-of-marketing-2016-5_b_9569592}