A deep dive into how data, AI, and hyper-local insights are reshaping bank marketing, featuring Jim’s perspective on aligning product and sales.
Jim, can you briefly walk us through your fintech journey and how it’s shaped your approach to aligning product strategy with sales to drive customer-centric outcomes?
I’ve spent the past decade working closely with CMOs of leading banks to transform marketing into measurable, compliant business growth. In my previous role at Salesforce, I led financial-services product marketing. This meant every day I was driving pipeline and ARR (Annual Recurring Revenue) by translating AI and CRM capabilities into full-funnel go-to-market plays, executive storytelling, and sales enablement.
In my current role at Vericast as VP of Product and Growth Marketing, we partner with financial institutions (FIs) to help them use marketing data intelligence to grow deposits, loans, and most importantly, customer loyalty.
Why is it increasingly critical for financial institutions to understand nuanced consumer behaviour at the local level?
Demand, risk, and response aren’t uniform—they’re hyper-local. Two neigh boring communities can look similar from a distance but, when you dig into consumer behaviour, there are a lot of differences like rate sensitivities or home-equity availability. FIs need to consider how these change the “what”, “where”, and “when” of their outreach.
To better understand what makes each community different, look at detailed signals at the census-tract level. These signals can tell you a lot, including which products match to local need, how to best tune pricing and marketing creative to audience motivators, and what media tracts convert. Census-tract-level signals can also help you prove inclusive reach and meet Community Reinvestment Act and fair-lending expectations.
How can data-backed marketing strategies help FIs personalize their outreach and improve consumer engagement across different regions or demographics?
The customer experience is an institution’s most valuable asset. Strong data-backed marketing strategies can go a long way in making an FI stand out. Different types of data sets inform various marketing strategies and the best way to get started is by compliantly unifying everything you have, including core/CRM data, geographic data (for instance, aggregated data on sub-zip code geographies), and intent data. This gives you a holistic view of audience selection and product offers.
Prospect propensity and micro-geographical data can lead to highly personalized campaigns. Micro-geo data can inform marketers what messaging will resonate with a region and on which channels.
One of the best parts of data-backed marketing strategies is that they produce more data beyond just click rates. Teams can frequently optimize future campaigns based on the number of funded loans or new accounts that were a direct result of the strategy. When the strategy ultimately wraps, teams can feed results back into models to improve the next-best-offer (NBO) per market.
What are some key behavioural differences you’ve observed among consumers in different locations, and how should FIs adapt their marketing accordingly?
Adapting to regional differences requires shifting both the offering and the marketing. The product, message, incentive, and channel should be specifically chosen to best fit each market.
For instance, geographically, the Midwest stays more branch-centric, while coastal metros are mobile-first. Even then, that information isn’t the end-all-be-all; some markets chase rate/APY while others value speed or convenience. Marketing must keep all these factors in mind, and then some. Bilingual areas for instance will engage with language/cultural alignment while fraud-hit markets need security cues.
These subtle differences in messaging all ladder back to where a prospective customer is located and the everyday challenges they face. Tapping into census-tract data can help teams deploy message-matched direct mail and geo-targeted digital offerings.
How do localized consumer insights drive long-term brand loyalty and trust in the financial services sector?
Localized insights are what turn “marketing” into service. When you know a neighborhood’s equity levels, device habits, and financial stressors, you can create offers that resonate. Tapping into data-informed insights helps ensure offers are relevant and fair, access is inclusive, and that outreach is proactive in moments that matter (like fraud spikes or weather events that impact individual finances). When these factors are taken into consideration, customer trust begins to grow. Over time, those consistent, locally tuned experiences build loyalty far more effectively than a generic campaign could.
What role does technology play in enabling FIs to identify and act on hyper-local consumer trends?
Technology is the bridge between signals and action – and modern tech stacks are growing to support the full lifecycle of an FI’s marketing campaign. As FIs tap into emerging tools, siloed first-party data can be quickly unified with privacy-safe, third-party data and geo signals. Once combined and paired with census tract information, computational models can be used to find key information on neighborhood differences. Orchestration tools can then trigger message-matched outreach across channels (like direct mail, CTV/OTT, paid search, etc.) and paced to local demand and operational capacity. At the final stage, closed-loop measurement tools can tie marketing spend to how many funded loans or new accounts were a result of the campaign. This creates actionable insights that inform future campaigns or real-time shifts.
Of course, when using new tools, teams must keep embedded fair banking guardrails in mind. These rules help ensure personalization is compliant at scale.
What are the main challenges FIs face when trying to implement localized marketing strategies—such as inefficiency, complexity, or platform limitations—and how can these be overcome?
The short answer is that the blockers are real but they’re solvable. Here are some of the most common one’s FIs experience:
Data fragmentation: As a best practice, always unify data with privacy-safe geo/intent data. This creates a holistic view of the prospect which can then be normalized to census-tract/branch-radius. As an added tip, this data should be refreshed weekly so “local” stays live.
Platform/geography limits: Avoid proxy targeting which can create fair-banking risk. Instead, use deterministic geographic data. This is precise, verifiable data, like ZIP/tract allowlists which can be used across mail, CTV/OTT, and digital channels.
Operational complexity: Creative automation strategies are your friend. By embedding rules-based versioning into master templated creatives, teams can generate multiple offers personalized to a prospect. The final creative can be paired with a pre-launch checklist and capped variants that help teams roll out phased outreach.
Inefficient measurement: It’s important to optimize campaigns to funded loans/new accounts, not clicks, to truly track success. Teams should use a combined approach of holdouts, multi-touch attribution (MTA), and marketing mix modelling (MMM) to gain a strategic view of marketing performance. While holdouts establish a baseline, MTA can narrow in on individual customer journeys, allowing teams to optimize campaigns in real-time. MMM provides the long-term view of marketing’s impact on the business and bottom line. With these insights in hand, teams can reallocate weekly to tracts with the best customer acquisition cost (CAC), or payback.
Compliance and brand safety: Compliance can create major team hurdles if fair-banking reviews aren’t baked into processes from the get-go. This includes reviews pertaining to geographic distribution data and Regulation B discouragement. It’s critical that teams always document audience rationale and retain evidence files for regulatory purposes, like in preparation for a Community Reinvestment Act (CRA) exam.
How can FIs balance compliance and consistency with the need for localized, tailored messaging in highly regulated environments?
The best way to find this balance is with a “central brain, local hands” model. This is a hybrid marketing strategy that combines centralized control of brand strategy with localized execution.
At the center of it all, teams should establish a master narrative, approved claims library, and brand templates. Depending on the market and guardrails, each of these can be tuned to match product, rate band, verbiage, imagery, and timing. When tuning to specific markets, it’s best to use deterministic geo data which is verifiable. Be hyper-vigilant about avoiding proxy targeting which can ultimately create fair-banking risk.
One of the best ways to maintain compliance alongside hyper-local outreach is to run a pre-launch checklist for every localized campaign. Included, at minimum, on that list should be:
-
- Audience rationale
- Census-tract distribution vs. assessment areas
- Regulation B discouragement & UDAAP (Unfair, Deceptive, or Abusive Acts or Practices) review
- Additionally, if a pre-screen is used, FCRA (Fair Credit Reporting Act) steps need to be accounted
Remember, automate evidence files (approvals, creative versions, etc.) to help the team stay exam ready. While it sounds difficult, automating this information upfront relieves teams from having to scramble once a campaign wraps.
Looking ahead, how do you envision the future of marketing for FIs evolving in terms of personalization, automation, and local relevance?
I see personalization for FIs shifting from broad segments to intent- and micro-geo–driven journeys. As automation grows, propensity and journey orchestration will be able to trigger message-matched outreach across channels. This will also be paced to local demand and even operational capacity. The best part? Compliance guardrails will be embedded, easing the burden on teams.
What’s your advice for financial institutions aiming to use data and local insights to transform their marketing and drive growth?
Take it step-by-step and keep one approved narrative at the center of all marketing initiatives. Guardrails can be set up allowing product, messaging, and channels to differ depending on local needs. Under this approach, all marketing efforts should still measure to predictable CAC. This helps teams reallocate budget weekly to the tracts, products, and creatives that outperform.
From there, run a phased plan. This divides a campaign’s activities into distinct stages to systematically achieve goals, build momentum, and manage the process over time. This approach to personalization isn’t easy, especially for marketing teams already stretched thin, but it doesn’t have to feel impossible. The right partner can activate an FI’s data in a compliant ecosystem and deliver the right level of personalization for a campaign’s objectives.
Stay Ahead of the Financial Curve with Our Latest Fintech News Updates!
