Frequently asked
Straight answers.
What mxdify is, who we work with, how we engage, and what we will not do. If your question is not here, book a 30-minute Growth Audit and ask it directly.
01
What mxdify is
What does mxdify do?
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What does mxdify do?
+mxdify builds growth infrastructure for digital health and SaaS companies: the measurement, CRM and revenue systems, and experimentation that let you grow efficiently. We build the systems and make the growth decisions from them.
What is mxdify?
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What is mxdify?
+mxdify is a growth infrastructure firm for digital health and B2B SaaS. We build the measurement stack, engineer the revenue systems, and run the go-to-market as one team — for a fraction of a senior full-time hire.
How is this different from a marketing agency?
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How is this different from a marketing agency?
+Agencies execute campaigns against a channel scope. mxdify owns the data layer and the growth strategy, then executes against it. Every decision is held to a warehouse-grade number, not a last-touch dashboard.
What is the Closed-Loop Growth System?
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What is the Closed-Loop Growth System?
+The Closed-Loop Growth System is mxdify's operating model for compounding growth. It connects measurement, strategy, and execution into a single loop: instrument the signals, size the opportunity, run disciplined experiments, systematize what works, and feed the results back into the next decision.
02
Who we work with
Who is mxdify for?
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Who is mxdify for?
+Funded, growth-stage digital health/telehealth and B2B SaaS companies that spend on growth but cannot clearly measure what works.
Who is a good fit for mxdify?
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Who is a good fit for mxdify?
+Series A through PE-backed digital health, telehealth, and B2B SaaS companies with real revenue, a product that works, and pressure to scale efficiently. Best-fit teams are past the 'do we have PMF' question and into 'why does our growth math not compound.'
Do you work with telehealth and regulated health brands?
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Do you work with telehealth and regulated health brands?
+Yes. We ship measurement, CRM, and paid programs for LegitScript-certified telehealth and pharmacy platforms inside Meta, Google, and TikTok health-ad policy. We know the compliance requirements because we have built through them, end-to-end.
Do you work with pre-revenue startups?
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Do you work with pre-revenue startups?
+Rarely. Most pre-revenue companies need a founder-led growth motion, not measurement infrastructure. We will occasionally take on a pre-revenue engagement in digital health where compliance and instrumentation must be right on day one.
Do you work outside digital health and SaaS?
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Do you work outside digital health and SaaS?
+Selectively. The core operating model applies to any subscription or high-consideration business. We take on adjacent verticals — financial services, consumer subscription, industrial IoT — when the engagement fits the three pillars.
03
How we engage
How does an engagement start?
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How does an engagement start?
+Every engagement starts with a 30-minute Growth Audit. You leave with two or three specific findings on attribution, paid efficiency, or funnel instrumentation, whether or not we ever work together.
How much does it cost?
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How much does it cost?
+Entry starts with the Growth Blueprint, a fixed-scope engagement with a one-time fee. After that, retainers start at $5,000 per month. See the full tiers on How We Engage.
How fast can we start?
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How fast can we start?
+Thirty-day onboarding. Week one is a full audit. Weeks two and three ship the priority instrumentation and system work. Week four is the first review with actual data.
How long does onboarding take?
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How long does onboarding take?
+Six weeks. Weeks one and two: instrumentation and warehouse. Weeks three and four: attribution and CRM. Weeks five and six: first experiments and reporting. You are operational at the end of week six.
How long is a typical engagement?
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How long is a typical engagement?
+Most clients run on a monthly retainer with a six-month minimum, then continue quarter-to-quarter. Some engagements are project-scoped — attribution rebuild, HubSpot rebuild, LegitScript-safe paid launch — and end when the work ships.
Where are you based?
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Where are you based?
+United States. We work remotely with clients nationally.
04
What we will and won't do
What CRMs do you build on?
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What CRMs do you build on?
+HubSpot, Salesforce, GoHighLevel, and custom.
Do you run paid ads?
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Do you run paid ads?
+Yes, but only as part of a measured system. We do not take on standalone media-buying scopes. If we cannot measure it in the warehouse and hold it to a payback number, we do not run it.
Do you build custom CRMs?
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Do you build custom CRMs?
+Occasionally. Most teams are better served by a properly rebuilt HubSpot or Salesforce instance. We build custom when the workflow genuinely does not fit an off-the-shelf tool.
Do you handle LegitScript-regulated telehealth advertising?
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Do you handle LegitScript-regulated telehealth advertising?
+Yes. We ship measurement, CRM, and paid programs for LegitScript-certified telehealth and pharmacy platforms inside Meta, Google, and TikTok health-ad policy. Compliance is a design constraint, not an afterthought.
Will you replace our in-house team?
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Will you replace our in-house team?
+No. We build the operating system and run it alongside your team, then transfer ownership. Most clients keep their marketer, PM, or ops lead and hire against our blueprint as they scale.
05
Growth methodology & measurement
What is the difference between a traditional growth agency and a growth system?
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What is the difference between a traditional growth agency and a growth system?
+A traditional growth agency executes campaigns against a channel scope and reports channel-level metrics. A growth system installs the underlying instrumentation, revenue systems, and experimentation cadence so every campaign is measured against warehouse-grade revenue and every win compounds.
- Agency: channel-scoped deliverables (media, creative, landing pages).
- Growth system: identity graph, event schema, warehouse of record, pre-registered experiments, standing playbooks.
- Agency: reads on tool-reported conversions. Growth system: reads on contribution margin and payback period.
How does growth instrumentation directly impact contribution margin and unit economics?
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How does growth instrumentation directly impact contribution margin and unit economics?
+Instrumentation exposes the true cost per acquired customer and the true revenue per cohort, which are the two inputs to contribution margin. Without it, tool-reported CAC understates real CAC (each channel over-credits itself) and LTV drifts against out-of-date cohort assumptions.
- Blended CAC is computed against real revenue in the warehouse, not summed from channel tools.
- LTV is refreshed on the same cadence as revenue, segmented by acquisition source.
- Payback period is computed per cohort against contribution margin, so finance trusts the number.
- Budget reallocates against warehouse-grade CAC:LTV, not against tool-reported ROAS.
What does a statistically rigorous A/B testing workflow look like for a growth-stage funnel?
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What does a statistically rigorous A/B testing workflow look like for a growth-stage funnel?
+A rigorous workflow pre-registers the hypothesis, powers the test against a minimum detectable effect the business would actually act on, verifies instrumentation before opening allocation, and calls the result strictly against the pre-registered primary metric.
- Hypothesis: change, mechanism, primary metric, expected lift, guardrails, all written before design.
- Sample size: computed from baseline rate, MDE, 80%+ power, 5% two-sided significance.
- Randomization: user-based, persistent across sessions, chosen to prevent cross-variant spillover.
- Readout: pre-registered stopping rule. No peeking. Guardrails monitored throughout.
- Losers: revised hypothesis on the same surface. Winners: promoted to scale.
Why do standard marketing attribution models fail for DTC health and funded SaaS brands?
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Why do standard marketing attribution models fail for DTC health and funded SaaS brands?
+Standard attribution (last-click, last-touch, or platform-reported) assumes short, single-device journeys with unrestricted tracking. DTC health and funded SaaS violate every one of those assumptions.
- Long consideration cycles cross devices and sessions. Last-touch under-credits the true acquisition path.
- Health-ad policy and consent restrictions strip conversion signal at the source. Platforms model the gap and often over-credit themselves.
- PLG SaaS trials convert asynchronously and often across accounts, breaking cookie-based attribution.
- Warehouse-grade closed-loop attribution stitches paid exposure, on-site behavior, and downstream revenue against a single identity, then reconciles against real revenue.
How do you calculate a right-sized experiment cycle based on traffic volume and statistical power?
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How do you calculate a right-sized experiment cycle based on traffic volume and statistical power?
+The cycle length equals the required sample size divided by the traffic assigned to the experiment. The required sample size is a function of the baseline conversion rate, the minimum detectable effect, the desired power, and the significance level.
- Choose the minimum detectable effect based on operational significance, not aspiration.
- Compute required sample size at 80%+ power and 5% two-sided significance against the baseline rate.
- Divide by weekly experiment traffic to get cycle length. Rescope if the cycle exceeds a reasonable window.
- If traffic will not support a meaningful MDE in a reasonable cycle, the surface is wrong for A/B testing and should be tested via holdout or geo-experiment instead.
What does growth infrastructure look like for a telehealth or digital health company?
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What does growth infrastructure look like for a telehealth or digital health company?
+For a telehealth or digital health company, growth infrastructure is designed around PHI segregation, consent capture, and health-ad-policy compliance from day one, not retrofitted around them later.
- Server-side event capture with PHI stripped at source. Downstream tools see hashed identifiers and non-PHI properties only.
- Consent captured at the collection layer and enforced downstream.
- LegitScript-compatible tagging, ad-account structure, and creative review pipeline.
- Warehouse-grade closed-loop attribution wired to order margin so paid programs are measured against real economics inside the compliance envelope.
- Lifecycle orchestration triggered from warehouse events so patient communication uses the same source of truth as measurement.
How do you run compliant paid acquisition for telehealth and DTC health?
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How do you run compliant paid acquisition for telehealth and DTC health?
+Compliant paid acquisition for telehealth and DTC health treats platform policy and pharmacy licensing as design constraints on the whole system, not as content checks at the end of a creative brief.
- LegitScript certification and platform pre-approval (Meta, Google, TikTok) completed before spend scales.
- Ad accounts structured for the health vertical (special-category audiences, restricted targeting, region policy).
- Creative pipeline built to health-ad-policy language rules. No condition targeting, no promises of outcomes.
- PHI-free conversion signal fed back to platforms via server-side APIs, so learning happens without leaking regulated data.
- Measurement reconciled in the warehouse against order margin, so scaling decisions never depend on platform-reported ROAS alone.
Newsletter
Field notes on measurement, experimentation, and growth for health and SaaS. No fluff.
Occasional dispatches from real engagements — attribution, revenue engineering, digital-health growth. Sent when there is something worth reading, not on a drip schedule.