Your data is sitting there telling you what to do.You just don't have anyone reading it every week.
We embedd as your growth analyst, reading the data daily and turning it into insights your team can act on.
The data to make a better decision already exists. It just isn't being read by anyone who knows what to look for.
Every Monday, someone pulls the MMP numbers, someone else the product analytics, someone else builds the cohort table. Hours of prep for twenty minutes of meeting, and often no clear output.
The cost shows up in a budget cycle that's already closed and a cohort you can no longer recover.
Reviews prepared manually from exports
Half a day every week pulling numbers from five tools into one spreadsheet. The data is stale before the meeting starts, and the prep eats the time that should have gone into deciding what to do about it.
Insight arrives too late to change the decision
By the time someone notices the retention curve shifted, the campaign has run for three weeks. The signal was in the data the whole time. Nobody was watching it closely enough to catch it.
A growth team without a dedicated analyst
Your growth team is running campaigns. Reading data deeply enough to catch anomalies is a second job they don't have time for, so it gets done shallowly, in a rush, or not at all.
No product analytics layer connecting acquisition source to what users actually do after install yet? There's not much to read every week until that's built. That's a different problem.
An analyst embedded in your growth team, reading your data so you don't have to.
This is the weekly rhythm. Not a one-time project. Clear output within the first two weeks. The data never goes unread.
Timeline
Engagements run on a monthly retainer, not a fixed scope. Cancel any time!
“Having someone like Muffaddal to guide us and bounce ideas off of has been an incredible asset. I’ve now worked with him across two successful companies where we scaled advertising spend to over $100K per day.”
Jose Avila
VP Growth Marketing
CalAI
The signals that matter, caught the week they appear. Not three weeks after.
A weekly insight summary
What changed, why it might have changed, and what (if anything) needs to happen. Delivered every Monday. Clear enough to forward to your CEO, specific enough to act on that day.
A monthly cohort deep dive
Retention curves, LTV trajectory, and payback period trends by acquisition cohort. The long-horizon view that weekly reviews miss, so slow-moving problems get caught before they reach the revenue line.
Proactive anomaly alerts
We watch for the signals you'd otherwise miss, retention drops, attribution shifts, channel efficiency changes, and flag them before they compound, not after they show up in CAC.
Campaign, budget, and on-demand analysis
A data read before major launches and budget decisions, plus answers to the mid-week questions when they arise. Not held until the next review cycle.
Dashboard upkeep and a running decision log
Your existing dashboards kept current as campaigns and sources evolve, and a record of what we found and what changed, so the reasoning behind each decision is there when you need to revisit it.
Before you reach out.
Monday morning, I go through your attribution data, product analytics, and revenue metrics. I write up what changed, flag anything unusual, and note what I think it means. You get a summary, usually one to two pages, that's specific enough to act on, plus availability through the week when questions come up. Beyond the weekly read, I take part in your decisions. I bring the data knowledge you should have about your own app, so you make better calls: how to hit your targets, which levers move which metric, what levels you need to reach to get there. I dwell in the data through the week to surface the opportunities you'd otherwise miss.
A junior analyst needs time to learn your stack, your business, and which signals matter, and they tend to run reports rather than read them for meaning. I bring pattern recognition from operating across many apps, so you get a useful read from week one instead of from month six.
Yes. Retainers run month to month. You can pause or cancel with one month's notice. No long-term commitment. The decision log and any dashboards I maintain stay yours, so pausing doesn't leave you with a gap you can't fill.
Either. If your measurement stack is already trustworthy, I can start reading it now. The analyst work is about turning attribution, product, and revenue data into decisions, not about building the pipes. If the underlying measurement is wrong, I'll tell you in the first couple of weeks, because analysis on top of broken data just produces confident wrong answers. In that case the fix is a scoped audit or rebuild first, then the ongoing analyst work on top, and the two connect directly.
Monthly retainer pricing depends on scope, how many data sources you have, how complex the analysis is, and how much on-demand work you expect. Email us your requirements and I will share the detail proposal with scope and timelines
Have someone read your data every week and tell you what it means.
Data nobody reads on a schedule surfaces problems weeks too late. Send me a note, and let's talk about what a weekly read would catch.