The Organizations
River City FCU is a credit union based in San Antonio, Texas, serving the residents of Bexar County. Its vision is to help all households and businesses access affordable, value-based financial products and services.
Subconscious AI delivers insights powered by an advanced AI market research platform that incorporates behavioral science and causal modeling to build digital twins of your customers, helping you understand purchase drivers and make marketing and product decisions.
Clearocity provides research and advisory services using a hybrid human-AI model to help organizations overcome challenges and improve their ability to achieve their mission faster.
Background
While credit unions are not-for-profit entities, maintaining financial strength is essential to providing members a secure, stable organization to manage their money.
With that in mind, River City Credit Union hired Michelle Seay Baker, APR, Founder of Clearocity and Subconscious AI Advisory Partner, to conduct research and data analysis to inform a strategic marketing plan and improve the organization's ability to achieve its mission.
Upon engaging with River City FCU, Michelle recognized an immediate need to optimize an important auto loan campaign. Equipped with Subconscious AI, she was able to deliver insights to the leadership team quickly and launch an improved version of the campaign within weeks.
Objectives
- Improve ad campaign performance by 25% in terms of "Result Rate," the percentage of link clicks to the promotion landing page by the end of the initial test cycle.
- Determine the campaign incentive dollar amount that would generate the most interest in applying for an auto loan while still being affordable for the credit union.
- Find out which campaign slogan would generate the most clicks in Facebook/Instagram ads, then apply it to other marketing tactics and channels to improve overall campaign results.
Methodologies and Tools
Testing methods: Discrete choice survey with digital twins and A/B testing
Respondents: 140 AI-generated digital twins infused with human behavioral data
Tools: Subconscious AI causal research platform and Facebook/Instagram Ads Manager
Hybrid Human-AI Advisory: Clearocity Growth Architect and Fractional CMO Michelle Seay Baker
Process
Step 1: Test incentive levels and messaging in Subconscious AI with digital twins.
Step 2: Conduct comparative tests on messages in Facebook/Instagram with humans.
Key Findings
Objective 1: Improve Ad Campaign Performance
Hypothesis: Previously, the credit union hadn't done quantitative research or A/B testing to optimize its marketing campaigns in recent years. By hiring a consultant to enhance its use of AI, research, and data, the credit union sought to improve campaign performance through the Subconscious AI platform and A/B testing in Facebook/Instagram.
Finding: Confirmed. The Facebook/Instagram campaign achieved a .74 Result Rate, a 42% increase compared to the previous campaign's .52 Result Rate.
The optimized campaign lifted the Result Rate from .52 (no testing) to .74 (with testing), a 42% improvement.
Resulting action: Armed with evidence that Subconscious and A/B testing improve campaign metrics, the credit union will use a similar approach for its next campaign to improve results even further.
Objective 2: Find the Right Cash-Back Incentive
Hypothesis: Credit union staff had observed other credit unions offering $300 cash-back incentives for auto loans and wanted to confirm that this amount would strike a balance between attracting enough applicants and not giving away too much cash.
Finding: Confirmed. In Subconscious, the $300 incentive proved to be the right amount to balance incentivizing applicants without giving away unnecessary cash.
The relative effect of cash-back incentive levels on consumer choice for credit union auto loans. The $300 range hits the sweet spot.
Resulting action: The credit union decided to proceed with the $300 cash-back incentive for the auto loan campaign.
Objective 3: Identify the Best-Performing Slogan
Hypothesis: The slogan a staff member suggested was good, but the team believed it could perform better by adding dollar amounts and emphasizing member benefits rather than just catchy copy.
Finding: Confirmed. Although the top slogans varied slightly from the Subconscious ranking due to their similarity, the one originally suggested was clearly the worst-performing ad.
Subconscious slogan rankings closely tracked real-world Facebook CTR. The staff-suggested slogan ranked worst in both.
Resulting action: Armed with data, the marketing staff avoided the poor-performing slogan and chose the best one to optimize other materials like direct mail and email blasts. Going forward, if a slogan performs much worse in Subconscious AI, the team will avoid using it in tests, reducing A/B testing costs and improving overall campaign performance.
Key Outcomes
By utilizing an advisor equipped with a discrete-choice AI tool that leverages behavioral science to uncover and prioritize consumer preferences, River City FCU's leaders were able to make informed decisions about campaign offers and slogans, significantly enhancing performance compared to their last campaign. Leaders were able to:
- Confirm the cash-back sweet spot for their campaign offer.
- Predict the worst-performing slogan to avoid across other marketing channels.
- Improve overall campaign performance compared to a past campaign by 42%.
- Save $40,000 in estimated testing costs by using Subconscious AI instead of hiring an agency for a conjoint analysis study.
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