Like clockwork, “Your credit score has changed!” screams in your inbox once a week from one fintech app or another, and again on a monthly cycle from a bunch more. If you’re like most people, you use several apps — some for managing your credit cards, some for your bank accounts and some for other purposes.
All of these emails have your name (personalized) and credit score (also personalized), along with some sort of a call to action. Although the data is driving personalization of the target — you in this instance — and aggressively pitching a product (a new card with your name on it), the communications fall woefully short of personalizing what problem it is they could help you solve. They don’t know what is really important to you.
“To get past the obvious … and shed the creepiness of knowing more just for the sake of knowing more, the mortgage industry needs to employ data to personalize outcomes.”
Clearly, these companies know a lot about you, and it’s usually more based on how many boxes you check in your preferences to tailor a product they want to sell. There is no continuity, however, in taking you along a multistep journey to help you achieve more significant and complex outcomes than click-to-apply.
Mortgage originators who want to appeal to potential clients will want to take a lesson from these communications. It’s not just about knowing details about a potential borrower’s life. Originators will want to convince potential borrowers to opt in to sharing their data, then use this data to help borrowers achieve their homebuying goals.
Mortgage marketing has always had personalization at its core. Real estate agents could determine when a recently married renter couple in their community had decided to start a family and could seek opportunities to sell the couple their first home.
For decades, marketers painstakingly sorted through home purchase data and lien amounts from public records, then mailed postcards when rates dropped to offer rate-and-term or cash-out refinances. If your property was listed for sale, you received mail offers for new homes and mortgages as well as lower commissions on your current sale. The mortgage industry knew about personalized marketing and was rather effective in using consumer data to establish relevance and hopefully gain some business.
With the proliferation of customer relationship management platforms, data aggregators and other innovative marketing technology solutions, data that can drive personalization has exploded in type, scale and frequency. A good number of personalization engines were mainly fueled by digital exhaust like search engine data, tracking cookies and other social media trails — with derived consumer demographic and intent data.
This data, while fuzzy, still moved the needle on personalization, resulting in better targeting and timing of marketing. More recently, mortgage marketers are taking a page from the consumer and credit card lending industries. They are actively leveraging changes to credit scores, property values and even cash flows to help time the ideal offer that captures the consumer and monetizes the lead.
All of these developments have manifold increases in the amount of data a fintech app or lender has about a potential borrower. To get past the obvious (such as the weekly credit-score messages) and shed the creepiness of knowing more just for the sake of knowing more, the mortgage industry needs to employ data to personalize outcomes. Personalized targeting and messaging is good but pointless unless you are personalizing outcomes.
For the mortgage industry, unlike the credit card industry, getting a consumer to click “apply” is not the real purpose of data-driven personalization. The true outcome is to get the consumer into a home that fits their financial profile and aspirations.
So, how much personalization do you need to have in your communications about a weekly credit-score change? Will the notification of a 5- or 15-point VantageScore change in a weekly or monthly email really change a prospective homebuyer’s outlook on a mortgage? If they are on the cusp of a credit-score threshold, it might, but for the most part, a change of a few points should not make or break their ability to get a mortgage.
Instead, the industry’s personalization of communications must reflect the depth, complexity and layered nature of the product (a mortgage) being offered. Instead of stopping at bulk purchasing of credit-trigger leads for mass marketing, consumers can be invited to actively participate in the personalization of their journey. This happens by using a richer set of financial data and their explicit opt-in consent.
This explicit opt-in is key and requires consumers to manually perform an affirmative action to receive your messaging. Using shared data on their financial state, actions and objectives, you can provide a richer and more hyper-personalized communication strategy that allows you to meet them where they are both digitally and emotionally.
A data-driven and hyper-personalized communications strategy might need a multitiered approach to assist a consumer in overcoming the barriers that are impeding their progress toward homeownership. The first tier should include the fundamental triggers that tell you something about the change to the consumer’s financial state (e.g., their credit score has gone up or down).
The next tier should include the triggers that are matched to personas using the consumer’s self-selected goals and objectives. For example, the consumer might reveal that they’re a renter who needs to improve their credit and financial health to qualify for a mortgage.
The last tier should be about financial analytics that precisely disclose where a consumer is in their journey — downpayment amount, closing costs, debt-to-income ratio, desired properties and more. For example, first-person data can be collected from the credit history and financial accounts the consumer enrolls in a lender’s financial app. In turn, this may identify that the prospective homebuyer has insufficient funds currently saved for their downpayment and reserves, a 45% debt-to-income ratio and a 610 credit score.
The consumer can be placed on a personalized journey that guides them to use tools such as a home affordability calculator. They can then pinpoint the amount of money they should save for their downpayment and closing costs, or they can utilize an interactive credit simulator to see how their actions can impact their credit. Additionally, you can help to educate the client by explaining such things as the impact of debt-to-income ratio and payment history on a credit score.
The three tiers can be combined to form the hyper-personalized communications strategy. As the originator, you can know how to use each trigger to engage with the consumer within a richer context that provides meaningful value.
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Your knowledge that a consumer started spending less at a juice bar last month is less creepy and much cooler as you look at the broader change in their spending habits, which drives them closer toward their downpayment savings goal. But you’ll engage the consumer with this outcome-driven message, not just the juice-bar tidbit. This is the true North Star for hyper- personalized communications. ●