Most wellness brands track vanity metrics across disconnected dashboards. The ones that scale profitably build measurement systems that connect every dollar spent to actual revenue. We build those systems.
The Problem
Every channel reports its own version of the truth
Your Meta dashboard says paid social drove 400 conversions. Google says search drove 350. Your email platform claims 200. Add them up and you've got more conversions than you actually had. Channel-level reporting double-counts, misattributes, and inflates performance because every platform wants credit. Without a unified measurement framework, you're making budget decisions based on numbers that don't add up.
Long purchase cycles make attribution nearly impossible
Wellness products often involve extended consideration periods. A consumer might see a podcast ad, read three blog posts, check reviews on Amazon, and buy six weeks later through your DTC site. Standard last-click attribution gives all credit to the final touchpoint and ignores the five interactions that built trust. In wellness, where purchase decisions are tied to personal health, the trust-building journey matters more than the last click.
Privacy changes broke your tracking infrastructure
iOS privacy changes, cookie deprecation, and evolving consent regulations have degraded the data quality most wellness brands depend on. Retargeting audiences shrunk. Conversion tracking became less accurate. Media mix models built on third-party data stopped working. Brands that haven't rebuilt their measurement stack for a privacy-first world are flying blind on channel allocation.
No connection between marketing metrics and business outcomes
Marketing teams report on impressions, clicks, CTR, and ROAS. Finance cares about customer acquisition cost, lifetime value, and gross margin contribution. The two teams speak different languages because there's no system connecting marketing activity to financial outcomes. This disconnect means marketing can't defend its budget and leadership can't tell whether growth is profitable.
How We Help
We start with a measurement audit that maps every data source, tracking implementation, and reporting workflow across your marketing stack. This reveals where data breaks — missing UTM parameters, misconfigured pixels, attribution windows that don't match your sales cycle, and gaps between platform reporting and actual revenue. Most wellness brands discover their data is less reliable than they thought.
The foundation is a unified data layer that connects marketing platform data with your e-commerce, CRM, and financial systems. We build a single source of truth for customer acquisition that resolves the double-counting problem and creates consistent metrics across channels. This isn't about building dashboards — it's about making sure the numbers in those dashboards are actually correct.
Our [growth strategy](/services/strategy/) team designs attribution models suited to wellness purchase behavior. For products with long consideration cycles, we implement multi-touch attribution and media mix modeling that account for the trust-building journey. For impulse-purchase categories, we use shorter attribution windows with incrementality testing. The model matches your actual customer journey, not a generic template.
We build marketing-to-revenue reporting that connects campaign performance to financial outcomes. Every channel gets measured on customer acquisition cost, contribution margin, and lifetime value — not just platform-reported ROAS. This gives marketing teams the language to communicate with finance and leadership in terms that matter to the business.
Our [measurement](/services/measurement/) framework includes experimentation infrastructure for ongoing optimization. We design holdout tests, geo-lift studies, and incrementality experiments that prove whether a channel is actually driving growth or just capturing demand that would have happened anyway. This is especially important for wellness brands spending heavily on brand awareness where the relationship between spend and revenue isn't linear.
[Creative](/services/creative/) performance analysis identifies which messages, formats, and concepts drive the best outcomes by audience segment. We connect creative testing to revenue data so you know which positioning resonates with your highest-value customers, not just which ads get the most clicks.
The outcome is a measurement system that tells you exactly where to spend more, where to cut, and how to allocate budget for maximum profitable growth.
What we deliver
- Measurement audit — tracking gaps, attribution issues, and data quality assessment across all channels
- Unified data layer — single source of truth connecting marketing, e-commerce, CRM, and finance data
- Attribution model — custom multi-touch or media mix model designed for wellness purchase behavior
- Marketing-to-revenue dashboard — channel performance measured by CAC, LTV, and contribution margin
The wellness brands that scale profitably don't have better marketing. They have better measurement. When you know what actually works, budget allocation stops being a debate and starts being math.
Our Methodology
Our 90-day analytics sprint begins with a full measurement audit. Phase one maps every data source, identifies tracking gaps, and documents the current state of attribution and reporting. We interview marketing, finance, and operations teams to understand how decisions are currently made and where data falls short.
Phase two builds the measurement infrastructure — unified data layer, attribution models, and marketing-to-revenue reporting. We implement tracking fixes, connect data sources, and build the dashboards that will drive ongoing optimization. Initial reports run against historical data so your team can see how the new measurement framework changes what you thought you knew about channel performance.
Phase three launches the experimentation program and trains your team on the new measurement system. We run initial incrementality tests, establish baseline metrics, and set up the cadence for ongoing optimization. By day 90, you have a measurement system that answers the question every wellness CEO asks: where should we spend the next dollar?
How We Work
The first 30 days are diagnostic. We audit your tracking implementation, data pipelines, and reporting workflows. We assess every marketing platform, analytics tool, and data warehouse connection. The output is a clear picture of what's working, what's broken, and what needs to be built.
Days 31-60 focus on infrastructure. We build the unified data layer, implement attribution models, and create marketing-to-revenue reporting. Your marketing team participates in weekly working sessions to ensure the new system reflects how they actually work and what decisions they need to make.
Month three operationalizes the system. We launch dashboards, run initial experiments, and establish the optimization cadence. Team training ensures your analysts and marketers can use the system independently. Weekly reviews shift from build-mode to optimization-mode.
Our team pairs a measurement strategist with a data engineer. The strategist designs attribution models, reporting frameworks, and experimentation programs. The engineer builds data pipelines, implements tracking, and maintains the unified data layer.
- Accurate attribution — unified measurement resolves double-counting and misattribution across channels
- Budget confidence — clear connection between marketing spend and revenue enables evidence-based allocation
- Experimentation capability — incrementality testing proves which channels actually drive incremental growth
If your health & wellness company needs marketing analytics leadership, we should talk.
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Frequently asked questions
What marketing platforms and tools do you integrate with?
We work with all major marketing platforms — Meta, Google, TikTok, Amazon, Shopify, email platforms, and CRM systems. We also integrate with data warehouses like BigQuery, Snowflake, and Redshift. The specific integration scope depends on your stack. We design the data architecture to be tool-agnostic so you're not locked into any particular vendor.
How long before we see actionable insights from the new measurement system?
Initial insights from the measurement audit surface within 2-3 weeks — most brands discover immediate optimization opportunities just from identifying tracking gaps. The full measurement system produces actionable channel allocation recommendations by day 60. Experimentation results that prove incrementality require 60-90 days of testing depending on traffic volume and channel mix.
Do we need a data warehouse before starting?
Not necessarily. If you don't have one, we can set up a lightweight data warehouse as part of the engagement. If you have an existing data infrastructure, we build on top of it. The measurement system needs a central place to unify data from multiple sources, but the complexity of that infrastructure depends on your scale and the number of data sources involved.
How do you handle attribution in a post-cookie world?
We use a combination of first-party data, server-side tracking, media mix modeling, and incrementality testing. The specific approach depends on your channels and data availability. The key is not relying on any single attribution method. We build layered measurement that cross-validates findings across multiple methodologies so you can trust the results even as tracking continues to degrade.
What is the difference between this and hiring a BI analyst?
A BI analyst builds dashboards and reports. We build the measurement strategy, data architecture, and attribution methodology that make those dashboards meaningful. Most wellness brands don't need more dashboards — they need better data inputs and clearer decision frameworks. We build both the infrastructure and the strategic layer on top.
How do you measure the ROI of marketing analytics itself?
We track budget reallocation value — the revenue impact of shifting spend from underperforming channels to proven performers. Most wellness brands find that accurate measurement enables them to reallocate a significant portion of their marketing budget more effectively within the first quarter. We also track decision speed, as teams with clear data make optimization decisions faster than teams debating which numbers to trust.
