I've had the privilege of working with financial services companies for years (think as far back as analyzing consumer demand for features and functionality to include on their mobile websites!). Fast forward a number of years, and I was working with a financial services brand struggling to optimize its credit card rewards program. With a suite of benefits—cashback, travel perks, and exclusive discounts—they debated endlessly over which combination would drive the highest engagement. That’s when I introduced TURF analysis. The moment we ran the first simulation, the insights were clear—adjusting just a few key offerings could expand their reach significantly while maintaining efficiency. That was the moment I became a firm believer in the power of TURF. 

Now, as a Senior Customer Success Manager at Suzy, I help financial brands use TURF to maximize growth, optimize products, and refine campaigns with data-driven confidence. In this blog, I’ll share how TURF can be a game-changer for financial services, from fine-tuning credit card rewards to enhancing digital banking experiences. Let’s dive in.

What is TURF and How Does Suzy’s TURF Simulator Work?

Before diving into real-world applications, let’s take a moment to understand what TURF is and how Suzy’s TURF simulator enables brands to manipulate their data at advanced levels.

TURF stands for Total Unduplicated Reach and Frequency. It’s a methodology that helps brands identify an optimal combination of items, like flavors, features, products, and more, that will reach the most consumers and maximize ROI. TURF is all about optimization and prioritization, and calculates reach and frequency for different combinations of items. 

• Reach refers to the percentage of respondents who would be interested in a given combination, and it’s visualized with the bars and percentages on the waterfall chart.
  
  • Cumulative reach refers to the percentage of respondents who selected at least one of the items in the combination.
  • Incremental reach is part of the cumulative reach, and refers to the net new percentage of respondents who were reached with the inclusion of the attribute.  
• Frequency can be defined in different ways across market research tools, but Suzy’s definition for frequency refers to the average number of items selected by a respondent, which can be considered a sales predictor of how many units a person might purchase or be interested in purchasing. 

Suzy’s TURF offering allows brands to explore additional business scenarios through a simulator to answer discovery questions like: 

• If I know we have to deliver on these 3 features, which features would increase consumer reach even more? 
• If I know these services are desirable but expensive to offer, which services are our next best options to retain our customers and attract new ones?
• If I were to filter my data by customer segments or specific demographics, how do reach and frequency change from group to group?

With the TURF Simulator, brands have flexibility to toggle different settings to gain insights into different combinations of offerings or messaging through the following functionality: 

• Ability to reposition items: Reposition certain items so that they are included in the reach and frequency calculations of the rest of your items 
• Ability to exclude items: Ensure certain items are not included in the reach and frequency calculations of the rest of your items
• Ability to filter by groups: Understand how reach and frequency changes amongst the tested items based on typing tool segments and demographics 

How TURF Can Empower the Financial Services Industry

Suzy’s TURF simulator empowers financial institutions to optimize product offerings, refine rewards programs, and enhance marketing strategies by identifying the most impactful feature combinations. Below are real-world use cases demonstrating how TURF helps financial brands drive innovation and reach more customers.

1. Unlocking the Ideal Credit Card Rewards Program

Challenge: Offering the perfect mix of credit card rewards is one of the most critical challenges financial services brands face.

How Suzy’s TURF simulator helps:

• Feature Repositioning: The TURF simulator allows brands to prioritize essential rewards (e.g., cashback on groceries and gas) while testing additional perks that maximize reach without cannibalizing existing products​.
• Exclusion Capabilities: A company may already offer travel perks on one card and wants to see if adding dining rewards would expand reach without affecting their high-value travel cardholders​.
• Filtering by Groups: The simulator enables brands to segment customer types (e.g., high spenders vs. budget-conscious consumers) and determine which reward combinations appeal most to each​.

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2. Optimizing Bundled Financial Products

Challenge: Financial brands aim to deepen customer relationships by bundling financial products, such as checking and savings accounts, loans, or credit cards.

How Suzy’s TURF simulator helps:

• Scenario Modeling: Brands can toggle different combinations of products to see which bundle offers the greatest reach across customer segments​.
• Segment-Based Testing: The simulator allows companies to assess bundle adoption among different demographics, such as new homeowners vs. young professionals​.

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3. Enhancing Digital Banking Experiences

Challenge: With digital banking adoption at an all-time high, financial services brands must continuously evolve their app features to meet customer expectations.

How Suzy’s TURF simulator helps:

• Feature Optimization: TURF enables brands to determine which digital banking features (e.g., AI-driven budgeting tools, P2P payments) drive the highest user engagement​.
• Dynamic Filtering: Companies can see how preferences shift by age group or financial behavior (e.g., frequent online shoppers vs. high savers)​.

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4. Testing Targeted Marketing Campaigns

Challenge: Marketing in financial services requires messaging that resonates across diverse customer segments.

How Suzy’s TURF simulator helps:

• Messaging Combination Analysis: The TURF simulator allows financial brands to test co-branded credit card messaging with different value propositions (e.g., travel rewards, statement credits, exclusive discounts)​.
• Frequency Metrics Adjustments: Marketers can measure message impact by frequency, ensuring optimal exposure levels for different audiences​.

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5. Refining Loan Products for Niche Audiences

Challenge: As financial services brands cater to increasingly diverse customer needs, optimizing loan product features is crucial.

How Suzy’s TURF simulator helps:

• Feature Prioritization: TURF helps lenders test various loan terms, interest rates, and incentives (e.g., flexible repayment options) to determine which features drive maximum reach​.
• Demographic Filtering: Brands can refine loan offerings for niche groups, such as gig workers, small business owners, or first-time homebuyers​.

With TURF, your brand can uncover which features drive the most impact, how to optimize bundled offerings and rewards programs and even fine-tune your messaging for different customer segments.

Ready to unlock smarter growth in financial services? Talk to our team today!