Generated $375K YoY revenue (from a content infrastructure investment, not headcount), improved product performance 12% (directly improving OEM partner satisfaction and retention), and reduced development costs $150K through a scalable content system.
$375K
Incremental YoY revenue
The Learning Center lacked a content and SEO strategy grounded in real user behavior. Data across auto loans, insurance, and car buying lived in silos -- no team had a unified view of the customer journey. Content was not driving conversion because it wasn't aligned to actual decision-making moments.
USAA's car buying journey spans multiple products -- auto loans, auto insurance, and the TrueCar-powered car buying service -- but the teams managing these products operated independently. Each team had its own data, its own KPIs, and its own content strategy. The result was a fragmented customer experience: members researching car purchases encountered inconsistent information, disconnected product recommendations, and content that was written for search engines rather than for decision-making moments.
The Learning Center was the primary content surface for this journey, but it was functioning as a static repository rather than a dynamic decision support tool. Articles were published based on editorial intuition rather than behavioral data. The publishing process required engineering involvement for every article, which created a bottleneck that limited output and responsiveness to emerging topics.
My strategic insight was to treat the Learning Center as a data-driven decision system. If the content strategy was grounded in real user behavior -- what questions members were asking, what decisions they were facing, what information they needed at each stage of the car buying journey -- then the content would naturally align to conversion moments. And if the publishing process was redesigned as a template-driven system, the bottleneck would be eliminated and output could scale.
The Tableau dashboard was the enabling infrastructure. By connecting auto loan, insurance, and TrueCar data into a single view, my team could see the car buying journey as a whole rather than as three separate product experiences. That unified view revealed the decision moments that content needed to address -- and the A/B testing framework validated which content approaches drove the highest conversion.
A human-centered content and SEO strategy built from workshop insights, a unified Tableau dashboard connecting auto loan, insurance, and car buying data across three lines of business, and a template-driven content system that eliminated engineering dependency for article publishing -- scaling output from 8 to 24 articles in under a month.
I led human-centered design workshops to uncover real customer pain points and decision moments across the car buying journey
I built a unified Tableau dashboard connecting auto loan, insurance, and TrueCar car buying data across three lines of business
I partnered with a developer to create a template-driven content model, eliminating per-article engineering work
I implemented an A/B testing framework for OEM discount placement and value reveal timing
I scaled Learning Center output 3x (8 to 24 articles) without additional engineering resources
8% conversion rate increase. $375K incremental YoY revenue. 12% improvement in overall product performance. 10% uplift in user engagement from A/B testing. $150K in development costs eliminated. 20% increase in digital deposit growth.
A content system that requires engineering for every article isn't a content system -- it's a bottleneck. Redesigning it as a template-driven platform removed the constraint and made content a compounding asset instead of a one-time cost. The $150K in eliminated development costs is a direct measure of the bottleneck's previous cost.
Content would have continued requiring engineering involvement for every article -- a bottleneck that capped output and responsiveness.
The car buying journey would have remained fragmented across three product teams with no unified view of the customer decision path.
The $375K YoY revenue opportunity would have remained invisible without the Tableau dashboard connecting the three product lines.
The Tableau dashboard was not a reporting tool -- it was a decision support system. By connecting data from three separate product lines into a single view, it enabled my team to make content decisions based on the full customer journey rather than individual product performance. The A/B testing framework then validated those decisions at scale. Data leads to signal, signal leads to action -- that's the pattern.
"The content wasn't converting because it wasn't aligned to actual decision-making moments"
"The Tableau dashboard connected three separate product lines -- that's what revealed where the content gaps were"
"The template system eliminated engineering dependency -- content became a compounding asset instead of a one-time cost"
What the data says
“71% of consumers expect companies to deliver personalized interactions, and 76% get frustrated when this doesn't happen.”
The human-centered content strategy was designed to deliver personalized, relevant information at each stage of the car buying journey. The 8% conversion increase reflects the impact of content that matches user expectations rather than generic editorial content.
Source“84% of companies working to improve customer experience reported an increase in revenue as a result.”
The $375K revenue increase is consistent with the documented revenue impact of CX improvements. The Learning Center redesign was a CX investment -- making the car buying journey more informative and decision-supportive -- that produced measurable revenue outcomes.
SourceProprietary Framework Applied
"You have to market to three visits, not one. This is the part everyone misses."
Jon Taffer, Bar Rescue -- 40% return probability after Visit 1 · 42% after Visit 2 · 70%+ after Visit 3
return probability
The Red Napkin
Member starts researching cars (searches rates, reads buying guides)
SaaS Translation
Internal flag: this member is in the consideration phase. Trigger a personalized content sequence -- 'Here's what USAA members typically pay for a vehicle in your zip code.' Not a loan application push. A low-pressure, high-value data gift that signals the platform understands where the member is in their journey.
return probability
The Chicken Discount
Member returns to the car buying center after viewing 3-4 vehicles
SaaS Translation
Trigger: 'Based on what you've been looking at, here's a pre-qualification estimate -- no hard credit pull.' The pre-qual costs USAA almost nothing to generate but moves the member one step closer to purchase and creates a sense of progress. The Tableau dashboard made this possible by connecting auto loan, insurance, and TrueCar data into a single view.
return probability
The Free Cheesecake
Member returns with a specific vehicle in mind
SaaS Translation
Trigger: 'You're ready. Here's your rate lock -- good for 45 days. Lock it now and shop with confidence.' The rate lock is a low-cost commitment device that creates urgency and reciprocity simultaneously. The Learning Center content sequence was the journey that got members to this moment.
Framework Insight
The car buying journey spans 3-6 months. The Red Napkin framework maps each return visit to a progressively higher-commitment touchpoint -- from content consumption to pre-qual to rate lock. The $375K YoY revenue was the output of getting members to Visit 4: the loan application.
White Paper Thread: The Decision Layer
The Learning Center case study demonstrates the white paper's argument about data normalization as a prerequisite for content decision systems. The Tableau dashboard unified fragmented data sources into a single view, enabling content decisions based on the full customer journey. The A/B testing framework then validated those decisions empirically. The pattern -- normalize data, identify decision moments, test and optimize -- is the same pattern that appears across all 10 case studies.
Read the White Paper →Connective Tissue
The Learning Center A/B testing framework was the predecessor to the broader funnel optimization work. The OEM discount placement and value reveal timing tests informed the storefront and onboarding optimization that followed.
Read case study
Both cases use data normalization as the foundation for a content or decision system. At USAA, the Tableau dashboard unified auto loan, insurance, and car buying data; at iPROMOTEu, the ingestion framework unified vendor data. The architectural pattern is identical.
Read case study
See the prototype built from this experience
This work informed a real product
The Operating System
ibuildsystems.io
Four frameworks. One repeatable system. Applied across banking, fintech, government, and B2B SaaS to turn broken workflows into scalable revenue engines.