5 Omnichannel Personalization Strategies That Increase Response Rates
By Nicole Volpe, Contributor at The Financial Brand
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Need to Know:
- Treat data signals as hypotheses, not conclusions. A burst of Home Depot transactions might look like a HELOC opportunity — unless the member rents. Suncoast requires corroboration from multiple data points before acting.
- Bad personalization backfires badly. Gartner found poorly timed personalization makes consumers 3.2x more likely to regret a purchase and 44% less likely to buy again. The downside risk of sloppy targeting is real.
- AI should amplify humans, not replace them. Suncoast will “never become an AI-first organization.” With 84% of banking professionals saying human oversight is essential for trust, they’re betting on smarter people, not autonomous machines.
For Darlene Johnson, Chief Strategy and Transformation Officer at Suncoast Credit Union, the word “campaign” sums up everything that’s wrong with how financial institutions typically use accountholder data — because it puts selling a product ahead of meeting a member’s needs. “The word campaign gives me chills up the back of my neck,” Johnson said.
Research suggests that she is onto something. A broad-based study in 2025 by Gartner, spanning both professionals and consumers, found that poorly timed personalization created negative experiences for 53% of respondents, making them 3.2 times more likely to regret a purchase and 44% less likely to buy again.
Suncoast — Florida’s largest credit union and one of the ten largest in the United States by membership and assets — has spent years learning how to use data in ways that strengthen member relationships. Serving more than one million members across roughly 40 Florida counties, the Tampa-based institution was first chartered in 1934 as Hillsborough County Teachers Credit Union and maintains a mission of empowering members to enjoy healthy financial lives.
To support its data strategy, Suncoast works with financial data platform provider MX to help it unlock actionable data-based insights. MX also provides Suncoast with personal financial management tools that help members act on recommended steps, including budgeting, automatic transaction categorization, and a unified view of financial accounts.
In an interview with The Financial Brand, Johnson described Suncoast’s disciplined approach to data-driven engagement, which centers effective personalization as the primary goal and growth as the natural byproduct. What follows are five lessons — plus one bonus takeaway — that other financial institutions can apply to their own data strategies.
Want more insights like these? Check out MX’s content hub: Data in Action
Lesson 1: Context Matters
At scale, personalization can easily devolve into its opposite, something that leaves the member feeling that the institution actually doesn’t know them very well at all. Consider the example of the member who makes a series of purchases at Home Depot. A burst of home-improvement transactions might look like a home-equity opportunity. But if the member’s account shows regular rent and renter’s insurance payments, or if they already have a home-equity line, the “personalized” offer can just as easily suggest that the provider is out of touch.
Johnson advises institutions to treat each data signal as a hypothesis. Marketers should require corroboration from multiple data points. And, when they do take action, they should develop messaging that invites a conversation. In practice, this may involve establishing thresholds for action and building decision trees that require multiple validating signals. Before surfacing a home-equity loan offer, first ensure the member has home equity but no existing HELOC, and then analyze capacity signals like deposit frequency or cash on hand to confirm the recommendation.
The idea is to strive for “segment of one” marketing that gives each member a unique experience. It requires steering away from product-driven campaigns and moving toward journey-based orchestration, where personalization aims to serve the member’s needs rather than the marketer’s campaign calendar.
Lesson 2: The Downside Risk Is Real
Personalization can be a double-edged sword. According to the Gartner study cited above, 48% of personalized communications are perceived as irrelevant or intrusive by their recipient. Meanwhile, a BCG study of 5,000 global consumers revealed that while more than 80% want personalization, two-thirds report experiencing it in ways that felt inappropriate or inaccurate — which can lead them to disengage, unsubscribe, or not return to a site.
This is especially true when the messaging or user experience implies the institution has drawn an inaccurate conclusion about a member’s needs. Johnson offers the example of a provider that assumes an accountholder’s transaction with a check-cashing outlet means they are under financial pressure. In fact, the reality could be far more mundane — the accountholder may have been traveling and simply had limited options to get cash.
The risk is that the accountholder sees through the tactic — connecting the dots between the visit to the check-casher and the offer they received. They may conclude the institution’s presumption of financial trouble is invasive or lazy. “If you use data without fully understanding the data, or if the data isn’t accurate, then you can start to get into offensive territory,” Johnson said.
Lesson 3: Establish a Single Source of Truth
A single source of truth (SSOT) is often defined as a centralized, authoritative repository or view of data that ensures everyone in an organization bases decisions on the same, consistent information, rather than conflicting local copies. In practice, however, an institution can have multiple SSOTs, depending on the domain — and their effectiveness is as dependent on governance as on database configuration.
According to PwC, designing a trust-based architecture and workflows is critical: building a reliable data inventory and backbone for decision-making with clear ownership, standards, and controls. Within that scope, the truth can be conditional, because it depends on explicit assumptions (e.g., product definitions or time windows) that are documented and consistently applied.
Suncoast’s data lives in multiple places — core system, loan origination platform, digital channels — and those systems can all be accurate while still disagreeing in ways that might produce bad targeting. “If I want to use the data to market a product,” Johnson said, “I need to ensure I’m taking it from the source of truth that I know to be both relevant and accurate.” In offering a loan product, the data that’s on an institution’s core system may not be the applicable source of truth; the SSOT is more likely its loan origination system.
Conversely, if a financial institution pulls customer data from the wrong system for the use case, it risks sending an offer that is mistimed or contradicts something they already know about their accountholder.
Lesson 4: AI Is a Choice Not a Destiny
Though Suncoast feels the gravity pull of AI like all businesses, it has specifically adopted a posture of moderation with respect to the technology, placing heavy emphasis on human-in-the-loop applications. “Suncoast will never become an AI-first organization,” Johnson said. “I believe we’re going to be smarter human beings with the ability to better connect with our members through the use of AI, but not allow AI to do it for us.” For Johnson, AI can surface patterns and opportunities at scale, but can’t yet navigate the nuance or the empathy required when defining someone’s financial needs.
A new global study by Moody’s, canvassing 600 risk and compliance professionals, supports Suncoast’s policy. The study shows AI adoption surging to 53% in banking and fintech (up from 30% in 2023), while also revealing that 84% see human oversight as essential for trust and accountability. More pointedly, while some 91% of respondents recognize AI’s role, only 30% see clear benefits in practice due to concerns like errors, privacy, and transparency — and making “human-in-the-loop” a must. Even among the largest players, safeguards like training and governance ensure people guide inputs, review outputs, and own decisions.
Lesson 5: Prioritize Member Well-Being
Customers who believe their financial institution cares about their financial health are three times more likely to be “very satisfied” and three times more likely to recommend their primary institution, according to a study by the Financial Health Network. They’re also five times more likely to purchase additional products and services.
Suncoast’s data strategy subjects each initiative to a simple test: Will this make a member’s financial life measurably healthier? If the answer is no — if the primary goal is, for example, to drive balance-sheet or revenue growth — the institution won’t move forward. “Suncoast isn’t in the industry to just get bigger,” Johnson said. “We think the value we bring to our communities can help our members become more financially healthy, so that’s what we focus on.”
Bonus Lesson: Innovation Is a Team Sport
Johnson is quick to credit partnerships for enabling Suncoast’s data strategy. The credit union’s collaboration with MX exemplifies how a vendor relationship can accelerate capability-building without requiring institutions to solve every problem in-house.
“Strong partnerships enable better data outcomes than any vendor relationship alone,” Johnson said.
Where to Start
If you’re looking to apply these lessons to your own institution’s data-driven engagement or marketing, you can begin by evaluating the status quo:
- First, ensure your personalization efforts are aligned with your mission: From Johnson’s perspective, the pivotal question — for every institution — should be whether such initiatives aim to measurably improve member financial health or whether they solely serve growth targets. Whether you agree or not, ensure your personalization strategy aligns with your institution’s big-picture outlook.
- Next, inventory your sources of truth and trigger criteria: What drives personalization — product ownership, income estimates, life-stage indicators? What is your governance model, especially when it comes to resolving data conflicts?
- Finally, what’s your posture on AI? Where does your organization currently use AI? Are you certain you are aware of all use cases? What role does human review play, in general and especially in high-stakes relationship moments?
The institutions that win at personalization won’t be those with the most data or the most sophisticated AI. They’ll be the ones that use data with discipline, context, and an unwavering focus on mission. As Johnson puts it: “If you do the right thing by the consumer, you’re going to grow.”
