
Without a shared measurement standard, one portfolio company's efficient channel mix never reaches the next. We build the performance marketing assessment, measurement framework, and cross-portfolio learning system that turns isolated ad spend into a shared advantage.
Ad spend efficiency varies wildly with no visibility into why
Two portfolio companies in similar categories can post very different acquisition costs, and without a standardized measurement approach nobody at the firm level can tell whether that gap is a market difference, a team capability gap, or broken tracking. Operating partners end up comparing dashboard numbers built by different teams using different definitions, which makes the comparison close to meaningless. This gets worse the more platforms lean on modeled data instead of direct tracking, since each company's dashboard now reflects a different mix of first-party and estimated numbers.
Each portfolio company reinvents performance marketing from zero
A company that just solved a channel efficiency problem or found a working audience segment has no structured way to pass that learning to a sister portfolio company facing the same problem six months later. Every company relearns the same lesson on its own budget and timeline, which means the fund pays for the same mistake multiple times across the portfolio instead of once.
Portfolio companies lack the marketing leadership to run this well
Most portfolio companies at this stage cannot justify a full-time performance marketing leader, so paid acquisition ends up managed by a generalist marketer or an agency with no accountability to the fund's return timeline. Spend looks active on a dashboard but is not being managed against the incrementality and efficiency standard the investment thesis actually requires.
No standardized way to benchmark or prioritize portfolio support
Operating partners are stretched across every company in the portfolio and need a way to know which companies most urgently need marketing support versus which are performing fine on their own. Without a consistent scoring approach applied the same way everywhere, that prioritization becomes a guess based on who escalates loudest, not on which company's marketing gap is actually costing the fund the most.
We start with a performance marketing maturity assessment applied consistently across the companies you want evaluated – not a generic audit, but a scored review of channel mix, attribution accuracy, creative testing discipline, and team capability against a common standard. That standard is what makes the results comparable across the portfolio instead of a one-off opinion about a single company.
Measurement gets fixed before spend gets optimized. Most portfolio companies are still making channel decisions off platform-reported numbers that overstate performance, a gap that has only widened as browser tracking restrictions and platform-side modeling have replaced direct attribution over the past several years. We rebuild attribution using server-side tracking and incrementality testing so decisions are based on what a channel actually contributed, not what the ad platform claims credit for.
Once measurement is trustworthy, we build the standardized framework that lets you compare acquisition cost, return on spend, and channel efficiency across portfolio companies on the same terms. This is the piece most funds are missing – not a lack of data, but a lack of a shared definition for what that data means from one company to the next.
The shared learnings layer is where the compounding value shows up. When one portfolio company finds a channel, an audience segment, or a creative approach that works, we test whether it transfers to other companies with a similar customer profile, rather than letting that insight stay locked inside one team's dashboard. This does not mean copying tactics blindly across dissimilar businesses – it means having a structured way to test transferable learnings instead of no way at all.
For companies approaching an exit, we build performance marketing organizations with documented processes and a team that can operate independently, because a marketing function that only works while an outside operator is running it is a diligence flag, not a value creation story.
The fund is not short on performance marketing data – every portfolio company has a dashboard. What it is short on is a shared definition of what that data means, which is why the same channel efficiency lesson gets relearned at full price by every company in the portfolio instead of once.
Our 90-day sprint for portfolio performance marketing starts with a two-week attribution audit at each participating company – reviewing the current tracking setup, identifying where platform-reported numbers diverge from actual incremental performance, and scoring the company against the maturity framework used across the rest of the portfolio.
Weeks three through eight focus on rebuilding the measurement foundation and restructuring channel mix based on what the corrected data actually shows. This is also when we run the first cross-portfolio comparison, surfacing which companies are outperforming on efficiency and which specific tactics might be worth testing elsewhere in the portfolio.
From week nine on, we run structured optimization cycles at the company level while feeding results back into the shared benchmarking framework at the portfolio level. The goal by the end of the sprint is not just improved efficiency at one company – it is a repeatable process the operating team can apply the next time a portfolio company needs the same evaluation.
The first 30 days are the attribution audit and maturity assessment, run the same way across every company in scope so results are directly comparable. You get a scored report per company plus a portfolio-level view of where the biggest efficiency gaps sit.
Days 31 through 60 are measurement rebuild and channel restructuring at the priority companies identified in the assessment, with weekly reporting so the operating team sees progress against the corrected numbers, not the inflated platform-reported ones.
Days 61 through 90 shift into the shared learnings phase – testing tactics that worked at one company against similar companies in the portfolio, and documenting the framework so the operating team can run the same assessment on new portfolio additions going forward. Engagements typically run three to six months depending on how many companies are in scope and how much of the measurement foundation needs to be rebuilt from scratch.
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We apply the same maturity assessment and attribution rebuild process to every company in scope, using a common definition for channel efficiency, acquisition cost, and incrementality rather than accepting each company's own dashboard definitions. That consistency is what makes cross-portfolio comparison possible in the first place. Without a shared standard, comparing one company's reported numbers to another's is comparing two different measurement systems, not two different performance levels.
The transfer only works if there is a structured process behind it, not an informal email when someone remembers a relevant result. We document what worked at one company in a form that specifies the customer profile and market conditions it applied to, then test whether it transfers to a similar company rather than assuming it will. Some tactics transfer cleanly, others do not, and the point of the process is to find out quickly instead of guessing.
It scores each company on channel mix and dependency, the accuracy of its attribution and measurement setup, the discipline of its creative testing process, and the capability of the team currently running acquisition. Each category gets scored against defined criteria rather than a subjective impression, which is what lets an operating partner compare scores across the portfolio with confidence. The output is a prioritized list of what to fix first at each company, not just a health rating.
We rebuild attribution using server-side tracking and first-party data collection, then layer in incrementality testing such as holdout experiments to verify what a channel is actually contributing rather than relying on what the ad platform reports. This typically restores a meaningful share of the visibility lost as browser restrictions and platform-side modeling have replaced direct tracking. The result is a measurement foundation the operating team can actually trust when making budget decisions.
Cost scales with the number of companies in scope and how much of the measurement foundation needs to be rebuilt versus optimized. Engagements are typically structured per company with a discount for multiple portfolio companies engaged together, since the assessment framework and much of the attribution rebuild process is reusable across similar businesses. This is generally far less than each company independently hiring a performance marketing director, which runs well into six figures per hire before results even start.
An agency hired independently by each company has no visibility into what is working elsewhere in your portfolio and no incentive to standardize measurement in a way that helps the fund compare results. We work at the portfolio level specifically so that the maturity framework, the measurement standard, and the learnings process are consistent across every company, which is the entire source of the compounding value. A single-company agency relationship cannot produce that by design.
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