Most portfolio companies have analytics tools installed but can't answer basic questions about customer acquisition costs, channel ROI, or cohort retention. We build the measurement infrastructure that turns dashboards into decisions and gives operating partners the visibility they need.

The Problem

Analytics tools are installed but nobody trusts the numbers

Portfolio companies accumulate analytics tools — Google Analytics, Mixpanel, Amplitude, HubSpot, Salesforce — but the data across systems doesn't reconcile. Marketing reports one set of numbers, sales reports another, and the board deck uses a third. When nobody trusts the data, decisions default to gut instinct and internal politics. For PE/VC-backed companies with aggressive growth targets, making decisions without reliable data is an expensive gamble.

Operating partners can't get consistent reporting across portfolio companies

Every portfolio company defines metrics differently. One measures CAC including all marketing spend, another only counts paid acquisition costs, and a third doesn't track CAC at all. This makes portfolio-level performance evaluation nearly impossible. Operating partners spend more time reconciling data than analyzing it. Without standardized metrics and reporting, the firm can't identify which portfolio companies need intervention or which growth strategies to replicate across the portfolio.

The team lacks the technical skills to build proper measurement infrastructure

Setting up proper event tracking, building data pipelines, creating attribution models, and designing dashboards that answer real business questions requires a mix of analytics engineering, data science, and marketing expertise. Most portfolio companies at the growth stage don't have this skill set internally. They rely on marketing generalists who can read dashboards but can't build the measurement foundation those dashboards need to be accurate.

Board reporting is manual, time-consuming, and tells a backward-looking story

Every board meeting, the marketing team spends a week pulling data from multiple tools, formatting it into slides, and trying to construct a narrative. The resulting deck is backward-looking and static — it tells you what happened but not why or what to do about it. For PE/VC portfolio companies, board reporting should be a strategic tool that informs investment decisions, not a compliance exercise that consumes a week of the marketing team's time every quarter.

How We Help

We start with a measurement audit that maps every data source, tracking implementation, and reporting workflow your portfolio company uses. We identify where data breaks — missing events, incorrect attribution, duplicate counting, broken integrations — and quantify the impact on decision quality. This audit gives leadership a clear picture of what the data can and cannot tell you today.

From the audit, we build a measurement plan that defines the metrics that matter for your specific business model and growth stage. For PE/VC portfolio companies, this always includes metrics that operating partners and board members need: customer acquisition cost by channel, lifetime value by cohort, payback period, retention curves, and revenue attribution. We define each metric precisely so there's one agreed-upon source of truth.

The technical implementation phase involves fixing tracking, building data pipelines, and creating dashboards. We set up proper event tracking in your product and marketing tools, build ETL processes that consolidate data from multiple sources, and create dashboards that update automatically. We work with your existing tool stack wherever possible — the goal is to make your current tools work properly, not to sell you new ones.

Attribution modeling is where most portfolio companies struggle the most. We build attribution frameworks appropriate to your business model — whether that's multi-touch for B2B SaaS, last-click for direct-to-consumer, or hybrid models for companies with both self-serve and sales-assisted motions. The attribution model feeds directly into CAC calculations and channel ROI analysis so marketing budget allocation is based on real contribution data.

For PE/VC firms, we develop portfolio-level reporting frameworks that standardize metrics across companies. This means defining common KPI definitions, building cross-portfolio dashboards, and creating the data infrastructure that lets operating partners compare performance apples-to-apples. We've found that this portfolio-level visibility alone often justifies the analytics investment because it surfaces performance patterns and intervention opportunities that were previously invisible.

We also automate board reporting. Instead of a week of manual data pulling, we build reporting templates that populate automatically from your data infrastructure. Marketing leaders get their time back, boards get more timely and accurate data, and operating partners can drill into specific areas of interest without waiting for the next board meeting.

Training and enablement ensure the analytics investment sustains. We teach your team how to use the dashboards, interpret the data, and maintain the measurement infrastructure. We document everything — metric definitions, data sources, dashboard logic, maintenance procedures — so the system doesn't break when our engagement ends.

What we deliver

Measurement audit with gap analysis and data quality assessment
KPI framework with standardized metric definitions and data sources
Dashboard infrastructure with automated reporting across key business metrics
Attribution model and channel ROI analysis framework

The biggest analytics problem in PE/VC portfolio companies isn't missing tools — it's missing trust in the numbers that are already being collected.

Our Methodology

Our analytics engagements follow a 90-day sprint structure. The first 30 days focus on audit and strategy: we map every data source, identify tracking gaps, define the KPI framework, and present a measurement plan to leadership. We also fix any quick wins — broken tracking, misconfigured events, obvious data quality issues — that can improve data accuracy immediately.

Days 30-60 focus on technical implementation. We build the data infrastructure: event tracking, data pipelines, dashboards, and attribution models. We work in iterative sprints, delivering usable dashboards weekly rather than waiting 60 days for a big reveal. Each dashboard is reviewed with stakeholders to ensure it answers the questions they actually need answered.

Days 60-90 focus on optimization and enablement. We refine dashboards based on real usage, build automated board reporting, and train the team on maintenance and interpretation. By day 90, the portfolio company has a fully operational measurement system, the team knows how to use it, and operating partners have the visibility they need to make informed decisions.

How We Work

Analytics engagements begin with a 2-week measurement audit. We inventory every data source, test tracking accuracy, and identify gaps. We present findings and a prioritized implementation plan to leadership and operating partners.

Weeks 3-8 focus on technical implementation. Our team includes an analytics engineer who builds the data infrastructure, a data analyst who designs dashboards and reporting, and a strategy lead who ensures the measurement framework connects to business objectives. This team works alongside your marketing and product teams, not in isolation.

From month 3, we shift to optimization and training. Weekly syncs review dashboard usage, identify new data needs, and ensure the team is getting value from the measurement system. Monthly reviews with operating partners assess whether the analytics infrastructure is providing the visibility needed for portfolio-level decision making.

Clients should expect an initial period of discomfort. The audit will reveal that some numbers leadership has been relying on are wrong. That's the point — better to know now and fix it than to continue making decisions on bad data. We present findings honestly and focus on solutions rather than blame.

Data accuracy and decision confidence improvement
Marketing budget optimization through attribution clarity
Board reporting automation and operating partner visibility

If your pe/vc portfolio companies company needs data, reporting & analytics leadership, we should talk.

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Frequently asked questions

How much does data, reporting, and analytics cost for PE/VC portfolio companies?

Analytics infrastructure engagements typically range from $20,000 to $60,000 for the initial 90-day buildout, with optional ongoing retainers of $8,000 to $15,000 per month for continued optimization and support. That's a fraction of the cost of hiring a full analytics team and delivers faster results because we bring specialized expertise from day one. Portfolio-level reporting frameworks for PE/VC firms are priced based on the number of portfolio companies included.

How long before we see results from data and analytics?

Quick wins — fixing broken tracking, correcting metric calculations, building initial dashboards — typically deliver value within the first 2-3 weeks. The full measurement infrastructure takes 60-90 days to build. The real payoff comes when teams start making better decisions based on accurate data, which usually becomes visible in improved marketing efficiency within the first quarter of using the new system.

How does the data and analytics team integrate with our existing portfolio company staff?

We work directly with your marketing, product, and engineering teams. Our analytics engineer coordinates with your developers on tracking implementation. Our analyst works with your marketing team on dashboard requirements and reporting needs. We use your existing tools and communication channels. The goal is knowledge transfer — we build the system and teach your team to run it.

What makes Winston Francois different from a traditional data and analytics agency?

Most analytics agencies focus on building dashboards. We focus on building decision-making capability. We understand what PE/VC operating partners need to see, how board reporting should work, and which metrics actually drive investment decisions. We also build for sustainability — your team owns and maintains the system after we leave, rather than depending on an external vendor for every report.

How do you measure ROI from a data and analytics engagement?

We measure the business impact of better data: marketing budget reallocation from low-performing to high-performing channels, reduction in time spent on manual reporting, improvement in data-informed decision making, and the portfolio-level visibility that enables better capital allocation. We also track practical metrics like dashboard adoption rates, report automation coverage, and data accuracy improvements.

What type of PE/VC portfolio company is the right fit for this service?

The best fit is a portfolio company that has analytics tools installed but can't answer fundamental questions about customer acquisition costs, channel ROI, or retention accurately. Companies spending meaningful amounts on marketing without clear attribution are leaving money on the table. We also work well with PE/VC firms that want standardized reporting across their portfolio to improve operating partner decision making.