Transactional–Influence Marketing Model
Balance measurable conversion with harder-to-measure market influence
- Difficulty
- Moderate
- Time to result
- ~months to results
- Steps
- 6
- Confidence
- 94%
This model treats marketing as a spectrum with transactional activity at one side, influence at the other, and an overlap where an activity does both. Teams first classify their programs by how they create value rather than forcing every channel into a direct-response model. They retain reliable conversion metrics but supplement them with directional evidence such as geographic holdouts, influenced demand, buyer research, and changes in market behavior. Allocation decisions then account for both immediate transactions and the longer path through which buyers form preferences. As search, social platforms, privacy changes, and AI weaken deterministic attribution, the portfolio should shift toward influence and the overlap—especially creative, use-case-led stories that show how customers win—without pretending the estimated ROI is exact.
Origin
Extracted from Marketing Against The Grain during Kipp Bodnar and Kieran Flanagan's discussion of distribution and attribution becoming harder.
Core principles
- 01Marketing creates both transactions and influence
- 02Direct conversion captures only part of a channel's value
- 03Influence grows more important as attribution becomes less reliable
- 04Directional evidence can support decisions without claiming exact ROI
- 05Customer success stories connect influence to real value
How to run it
- 1
Map the marketing portfolio
Place each activity in the transactional circle, the influence circle, or their overlap based on how it contributes to customer acquisition.
Pro tip Classify the mechanism, not the channel label; one channel may contain multiple activity types.
Watch out Do not classify an activity as transactional solely because the platform reports clicks.
- 2
Capture reliable transactions
Measure direct conversions where the customer path remains observable and the metric is decision-useful.
Pro tip Treat reported ROI as directional when the path includes multiple channels.
Watch out Do not present modeled attribution as an exact accounting identity.
- 3
Estimate influence
Use buyer studies, geographic holdouts, incrementality tests, or influenced-demand models to estimate effects that direct attribution misses.
Pro tip Match the method's cost and precision to the size of the decision.
Watch out Complex testing can consume more time than the added accuracy is worth.
- 4
Compare investments directionally
Use the combined evidence to determine which activities appear stronger or weaker relative to alternatives.
Pro tip Express uncertainty explicitly with ranges and assumptions.
Watch out Do not reject influential channels merely because their effects are difficult to attribute.
- 5
Create use-case influence
Tell vivid stories about specific customer problems, product use cases, and resulting wins so buyers can understand and remember the value.
Pro tip Build stories around customer outcomes rather than generic product claims.
Watch out Influence without relevance can generate attention that never supports demand.
- 6
Rebalance continuously
Adjust the mix as algorithms, buyer behavior, measurement quality, and channel economics evolve.
Pro tip Reserve resources for new distribution experiments during periods of disruption.
Watch out A portfolio optimized for yesterday's attribution environment can become increasingly ineffective.
In the wild
A B2B company sees weak direct-response attribution from social and plans to reduce spending. Buyer research shows that social is the channel with the greatest influence on enterprise buyers. The company reclassifies social as primarily influential, tracks directional evidence alongside direct conversions, and invests in customer-focused content rather than judging the channel only by last-click revenue.
→ The company preserves a channel that materially shapes buyer preference despite weak direct attribution.
A team spends heavily on video advertising but cannot connect every exposure to a conversion. It uses geographic holdouts to estimate incremental demand, documents the assumptions, and compares the result directionally with other investments. It stops short of claiming an exact return and limits additional testing once greater precision would no longer change the budget decision.
→ The team makes a defensible allocation without confusing modeled influence with exact ROI.
Common mistakes
Optimizing only for reported ROI
Last-click or directly measurable returns can systematically undervalue activities that influence buyers earlier or indirectly.
Treating modeled ROI as exact
Influence models contain assumptions even when they use sophisticated tests. They should guide relative decisions, not manufacture certainty.
Measuring beyond decision value
Additional testing is wasteful once better accuracy is unlikely to change the allocation decision.
Is it for you?
Best for
Marketing leaders operating across a mix of measurable acquisition channels and less measurable channels that shape buyer preference.
Not ideal for
Organizations seeking exact person-level attribution or guaranteed short-term revenue from every marketing activity.
From the transcript
“The entirety of marketing is basically transactional, influence, and there's that overlap in between, right?”
“I think what we're saying is over time, that is gonna move back. So it's like the inverse where it's like heavily in the middle…”
“if you want to grow, you are going to have to do highly influenced-based plays, right?”
From the episode
Why It’s SO Much Harder To Grow A Startup In 2023… (#133)