Case Study Summary
The Client: A premium, PE-backed B2B corporate gifting firm.
Their Challenge: Test the effectiveness of their legacy marketing program and use that data to maintain, shift towards digital, or adopt a hybrid approach.
What Emerged: Data was available but untrustworthy. The set needed filtering, categorization, and meta-analysis to reveal clear buying signals.
Our Proposal: Separate what the business knew from what it assumed. Break up historical performance into cohorts, channel interactions, and attribution pathways to identify when the data was reliable and when it was not. Next, introduce scenario modeling across audiences, Contact-level purchases, and Company-level purchases to clarify repeat buyers across geographies, individuals, and corporate accounts. Cross-reference this information with their order history to establish clear patterns, then tie that information to the catalogue distribution dates.
Although a contract did not emerge from this proposal, it demonstrates key Signal Marketing insights that apply across industries:
1) Legacy channels often mask deeper structural issues.
2) Most marketing data is directional, not deterministic.
3) Channel strategy cannot exist without system design.
4) Seasonality amplifies risk.
The Takeaway: Growth is a product of systems built to clarify customer behaviors.
Case Study Narrative
A private equity-backed B2B company with $10–11 million in annual revenue needed a marketing experiment. Historically, 85% of their revenue was generated during one holiday window and relied on a direct mail catalogue. This consumed most of their marketing budget but had produced increasingly smaller ROI over the last few years.
The board approved $900,000 to measure this approach, establish a baseline, and use the findings to inform marketing efforts. The decision was straightforward on the surface: continue investing in catalogs, shift toward digital, or adopt a hybrid model. But a fundamental issue lay beneath that question - the company did not trust its own data.
The Emergent Challenge
What appeared to be a channel decision was, in reality, a measurement problem.
The catalog program was doing too much at once. It functioned as an acquisition engine, a retention mechanism, and a form of brand reinforcement all at once. Because of this overlap, the business could not isolate cause and effect. Revenue existed but attribution was obscured. In addition, the underlying data ecosystem lacked consistency. Internal reporting relied on a mix of manual attribution and historical assumptions, while external data sources introduced aggregation and structural differences. Lastly, acquisition efficiency had declined. New customer growth had dropped materially over several years, despite surface-level engagement metrics suggesting continued interest.
All of this was taking place in a high-stakes environment. With most revenue concentrated in a single seasonal window, there was limited opportunity to iterate.
Our Proposal: Design for Signal First
Instead of starting with channels, we would start with signal.
The first step was to separate what the business knew from what it assumed. Historicalperformance was delineated into cohorts, channel interactions, and attributionpathways to identify where the data was reliable and where it was not.
From there, instead of forcing a single version of the truth, we would introduce scenario modeling with multiple attribution points. Only then would we turn to the experiment itself.
From Test Plan to Decision System
The company’s original testing structure included:
- Print only
- Digital + print
- Digital only
- Control
We redesigned the experiment to ensure it could generate decision-grade insight, including stratified targeting, controlled exposure windows, and a clear KPI hierarchy. We also constructed a measurement system behind the test, ensuring results could be interpreted and acted upon with confidence.
Key Insights
Although a contract did not emerge from this proposal, it demonstrated key SignalMarketing insights that apply across B2B industries:
1) Legacy channels often mask deeper structural issues.
2) Most marketing data is directional, not deterministic.
3) Channel strategy cannot exist without system design.
4) Seasonality amplifies risk.
Signal & Scale Perspective
Growth is a product of systems built to clarify customer behaviors. Adding channels may be a solution, but without guardrails this effort only adds noise.
