Shopify shows revenue. Klaviyo shows email performance. Meta shows ROAS. None of them agree with your P&L, and none of them tell you which customers are actually profitable. Revenue operations connects the dots so growth decisions get made on real numbers, not platform-specific ones.
The Problem
Siloed data creates dangerous blind spots
DTC brands now run on a dozen platforms – Shopify, Klaviyo, Meta, Google, Attentive, Gorgias, a 3PL, a returns tool – each with its own dashboard and its own version of the truth. Shopify revenue doesn't match accounting revenue once returns, chargebacks, and gift cards hit. Meta's reported ROAS doesn't reconcile with Klaviyo's attributed revenue, and both platforms are happy to take credit for the same order. Without a unified data layer, budget decisions get made on numbers that contradict each other by design.
Contribution margin is a mystery for most DTC brands
Ask a DTC founder their contribution margin by channel and most hedge. Landed COGS shifts with freight and tariffs. Shipping cost varies by order size, carrier zone, and whether a promo waived it. Return rates differ by product and by acquisition source – a paid-social buyer returns at a different rate than an email-list repeat buyer. Discounting compresses margin unevenly across SKUs. Without real contribution margin by channel, 'profitable growth' is a guess dressed up as a metric.
Growth decisions run on lagging, incomplete metrics
Most brands set next month's ad budget off last month's blended ROAS and last week's top-line revenue. Neither metric says whether this month's buyers come back, whether the promo calendar is eating margin faster than it's adding volume, or whether the fastest-growing channel is quietly the least profitable one. Revenue operations replaces lagging, blended metrics with connected, channel-level ones that show which growth is worth funding before the quarter closes, not after.
How We Help
We start with a data infrastructure audit that maps every source, flags where connections are missing, and documents exactly where metrics conflict. We trace the customer journey from first ad impression through purchase, return, and repeat buy across every platform, so we know how data actually flows through the operation, not how the org chart says it should.
Strategy development designs a unified revenue operations framework: one source of truth for customer-level profitability, contribution margin models that account for every variable cost by channel and product, LTV projections by acquisition source, and a reporting cadence built for daily decisions rather than monthly board decks. This is the same discipline we bring to broader growth strategy work, applied specifically to the mess of DTC data.
Execution builds the infrastructure. We connect Shopify, ad platforms, email/SMS, CRM, returns, and fulfillment into one analytics layer, then build dashboards that show contribution margin by channel, LTV by acquisition source, and blended profitability that accounts for the full cost stack. This isn't a one-time data project – it's an operating system your marketing, finance, and ops teams use every week.
Measurement in RevOps is the product itself – we're building the measurement system, not just running reports through it. Done right, your team can finally answer what was previously unanswerable: true contribution margin by channel, which acquisition cohorts are actually profitable at 12 months, and where budget should shift to protect margin dollars instead of chasing top-line revenue.
What we deliver
- Data infrastructure audit – platform mapping, connection gaps, and metric reconciliation
- Revenue operations framework – unified data model, contribution margin methodology, LTV projections
- Analytics implementation – connected dashboards, automated reporting, and decision support tools
- Operating cadence – weekly/monthly reporting rhythms with decision frameworks
Most DTC brands think they have a growth problem. They actually have a visibility problem. When you can see true contribution margin by channel and LTV by cohort, the right growth decisions become obvious.
Our Methodology
Our 90-day RevOps sprint starts with data archaeology. Phase one maps every source, documents how each platform calculates its own metrics, and reconciles revenue, cost, and attribution data to establish a single baseline truth. This diagnostic phase routinely surfaces unit economics that look nothing like what the dashboards claimed.
Phase two builds the unified analytics layer: the data connections, the contribution margin models, LTV analytics by acquisition source, and the dashboards the team will actually open every week. Every metric ships with a documented definition so nobody argues about what a number means.
Phase three locks in the operating cadence – weekly performance reviews built around the right metrics, monthly strategic reviews with trend analysis, and decision frameworks that connect a number to an action. By day 90, the team runs on connected, accurate data and funds growth based on profitability, not vanity metrics.
How We Work
RevOps engagements typically run 3-6 months. The first 90 days cover data audit, framework design, and analytics implementation; the months after that optimize reporting, expand data connections, and embed the operating cadence into the team's actual workflow. We work directly with marketing, finance, and operations, since RevOps sits at the intersection of all three and breaks if any one of them is left out.
Our team pairs analytics work with DTC operating experience. You provide platform access, cost data, and business context; we handle data architecture, analytics development, and dashboard design. Custom integrations sometimes pull in your engineering team or an existing data partner.
Weekly check-ins during the build phase keep the analytics framework matched to how your team actually makes decisions. Monthly reviews after launch check data quality and reporting usage. Most brands start making visibly different growth calls within 60 days of getting connected revenue data.
- Data clarity – unified view of revenue, cost, and profitability across all channels
- Decision quality – growth decisions based on connected data instead of siloed dashboards
- Margin visibility – real-time contribution margin tracking that prevents unprofitable scaling
If your dtc / ecomm company needs revenue operations leadership, we should talk.
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Frequently asked questions
How much does revenue operations cost for DTC brands?
RevOps engagements typically run $10K-$30K a month, covering data audit, framework design, analytics implementation, and ongoing optimization. If you don't already have a data warehouse or BI tool, add that as a separate line item. The ROI shows up fast – brands consistently find they're over-funding an unprofitable channel and under-funding a profitable one the moment they can see connected data.
How long before RevOps produces actionable insights?
Initial data reconciliation and baseline metrics are usually ready in 30-45 days. Full dashboards with contribution margin and LTV data take 60-90 days to build and validate. The first useful insight often lands during the audit itself, when a channel that looked profitable turns out not to be once every cost is actually counted.
How does RevOps integrate with our existing analytics tools?
We build on top of what you already have wherever possible. If you run a data warehouse, we use it. If you're on Google Analytics or Triple Whale, we integrate that data alongside direct platform connections instead of replacing it. New tools only get added when there's a real capability gap – not by default.
What makes Winston Francois different from a data analytics agency?
A data analytics agency builds dashboards. We build decision-making systems tied to the specific calls DTC brands make every week – where to put budget, which products to push, when to discount, which channels to scale. Our DTC background means we know which metrics actually drive those calls and how to structure reporting around them instead of around vanity charts.
How do you measure ROI from a RevOps investment?
We track the financial impact of decisions made with connected data against what would have happened without it – budget reallocated away from losing programs, margin recovered by cutting unprofitable ones, revenue gained by scaling channels the data reveals as high-LTV. Most brands find at least 10-15% of marketing spend was misallocated once RevOps visibility is in place.
What type of DTC brand needs revenue operations?
Any brand over $3M in annual revenue running spend across multiple channels. If your team argues about which numbers are 'real,' or finance and marketing quote different revenue figures in the same meeting, that's a RevOps problem. Brands scaling aggressively are most exposed, since bad data compounds into bad decisions fastest at speed.
