Managed Run + Measure

Keep your marketing and product data — and your AI — true

Managed Run + Measure is an optional, month-to-month engagement that keeps your governed marketing, ad-platform, and product metrics certified, your models evaluated, and your spend-and-model lift re-proven every quarter. It is usually added only after a project has proven its worth.

Ask about limited availability

Run Essentials starts around $5,000-$8,000/mo. Run + Activate usually lands around $8,000-$15,000/mo. Run + Measure — where evaluation and lift-proof work live — usually lands around $15,000-$25,000/mo. These are planning ranges, not a minimum-term commitment. See details

Keep your marketing and product data — and your AI — true

Optional support after the proof is real

  • Keep certified GTM and product metrics from drifting after the build ships
  • Monitor source changes, data-quality breaks, and metric caveats before they hit board decks or AI answers
  • Evaluate lead, churn, expansion, and spend models against the workflows they influence
  • Re-prove spend-and-model lift quarterly when the decision stakes justify it
  • Give leaders a recurring read on what dashboards, copilots, or board reports would get wrong this month

This is for you if...

  • A diagnostic or build project has already produced something worth keeping reliable
  • The team cannot afford metric drift between quarterly board, budget, or model-review cycles
  • Marketing, RevOps, product, finance, or data leaders need one owner watching the seams between systems
  • You want ongoing evaluation and lift proof without turning the original project into a lock-in retainer

This is not the starting point if...

  • The underlying metric definitions or source paths have not been certified yet — start with the AI-Ready Data Diagnostic, Data Foundation, or a focused diagnostic
  • You want generic dashboard maintenance instead of governance, monitoring, evaluation, and measurement judgment
  • You need a full managed-services vendor to run every analytics request, BI ticket, and ad-platform task
  • You are looking for a mandatory annual retainer — this is optional, month-to-month, and limited availability

What Managed Run + Measure covers

Certified metric governance

Quarterly recertification of the governed semantic layer for the marketing, ad-platform, product, and revenue metrics your dashboards, board reports, and AI answers depend on.

Drift and data-quality monitoring

A recurring check for source changes, broken pipelines, field ownership changes, silent logic drift, and caveats that should travel with the number.

Model retraining and evaluation

Lead, churn, expansion, lifecycle, or budget models are evaluated against real workflow behavior instead of being left as stale scores in a CRM field.

Holdout and lift readouts

When the stakes justify it, we help structure holdout, champion-challenger, or lift-readout cycles so the team can tell whether a model or spend decision actually changed behavior.

Monthly wrong-answer read

A practical review of what your AI, dashboard, or board packet would answer wrong this month — and which issues need repair, caveat, or retirement.

How the monthly operating rhythm works

1

Confirm

We start from a shipped diagnostic, semantic layer, model, or measurement system that already has owners and business value. No project proof, no retainer push.

2

Monitor

Each month, we check drift, data-quality signals, source-system changes, model behavior, and the caveats that matter before the next leadership readout.

3

Measure

Quarterly, we recertify critical metrics and re-read model or spend performance with the right evidence label: directional, decision-grade, or lift-backed.

4

Decide

The output is a short operating read: what stayed reliable, what changed, what your AI or board would get wrong, and what should be repaired next.

$5,000-$25,000 per month

Limited availability. Month-to-month, optional, and usually added only after a project has proven its worth.

Ask about Run + Measure

Start with proof, not a retainer

Most teams earn their way into Run + Measure

If we have not already helped prove a diagnostic, build, model, or measurement layer, the better first move is usually a scoped project. Managed Run + Measure exists to keep proven work reliable — not to sell indefinite support before the business case is clear.

See the service ladder

Client Outcomes

Mid-market SaaS Growth Team

Attribution confidence moved from roughly 60% to 95% before spend decisions changed

The value was not the dashboard alone. It was the recurring discipline of keeping channel, CRM, and revenue logic aligned enough that leadership could defend spend decisions.

Read case study

PLG SaaS Product Team

A warehouse-backed activation workflow shipped in 3 weeks and reduced churn 18%

A useful signal becomes more valuable when someone keeps watching whether it still reaches the right workflow, with the right caveat, at the right time.

Read case study

Still proving the first model or metric layer?

Use Data Foundation when source precedence and certified metric definitions are not ready yet. Use Data Activation when a trusted model or workflow needs to reach CRM, lifecycle, or product operations safely.

Explore Data Foundation

Common questions before adding Managed Run + Measure

Is Managed Run + Measure required after a project?

No. It is optional and month-to-month. Many teams finish a diagnostic or build and run it themselves. Managed Run + Measure is for situations where the metric layer, model, or measurement system is important enough that drift would create real operating risk.

Why is this limited availability?

The work requires context, judgment, and delivery capacity. We would rather keep the route by application than sell ongoing support faster than we can responsibly run it.

What is the difference between Run Essentials, Run + Activate, and Run + Measure?

Run Essentials is mostly governance and monitoring. Run + Activate includes workflow and destination support. Run + Measure is the lead tier: model evaluation, holdout or lift-readout design, quarterly metric recertification, and the recurring wrong-answer read.

Can we cancel?

Yes. The engagement is month-to-month and cancel-anytime. The point is to keep proven work reliable, not to create a permanent dependency.

What should we do if the build is not proven yet?

Start with the right project first. If leadership is unsure whether AI-ready data is even trustworthy, use the AI-Ready Data Diagnostic. If the semantic layer or warehouse logic is the blocker, use Data Foundation. If a score or workflow needs to reach the business, use Data Activation.
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