Services

Work built around a decision

I help teams answer questions that sit between marketing, customer behavior, and data systems. I start by pinning down the decision, then check whether the data you have can support it. A model or dashboard comes later, if it helps.

Who this fits. Businesses that run Google or Meta ads and keep a CRM, POS, or sales log, when the ad reports stop at leads, the platforms claim more sales than you made, or a budget decision is coming and nobody trusts the numbers behind it. I also help with forecasts, prospect ranking, and turning spreadsheets into reports. Each section below lists the questions I work on and what you get at the end.

The terms. The first consultation is free. After it, I quote the price up front, based on what you've asked for, before any work starts. I reply to new inquiries within a day, and client data stays confidential. How an engagement runs has the details.

On this page: Campaign and revenue measurement · Channel budgets and demand forecasts · Prospect and demand analysis · Reporting and document search · How an engagement runs · Sample readout

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Campaign and revenue measurement

Questions I work on

• Which campaigns bring in paying customers, not just clicks?
• Where do prospects drop off between the ad, the lead, the visit, and the purchase?
• Does a high acquisition cost pay off in later customer value?
• Why do the ad platforms together claim more sales than we actually made?
• What should we start tracking now so next quarter's comparison works?

What you get

I join campaign, lead, visit, offer, and sales data wherever the identifiers allow it, and we agree on the definitions first: what counts as a lead, a verified visit, a conversion, and attributable revenue. When the identifiers don't exist yet, I help set them up, from dated flyers to personal offer codes. If your forms don't save the campaign tag yet, the first readout starts from what you already keep, such as lead source fields in the CRM, weekly spend, and closed sales. It's rougher, and it says so, and the tags we add at the same time let the next readout count each sale against its ad.

Whatever the business, the chain looks like this:

1. The adA Google or Meta campaign, or a dated flyer
2. The leadA form, call, or offer code, tagged with the campaign
3. The recordYour CRM, POS, or sales log keeps the tag
4. The saleA closed account or paid bill, joined by the same tag
5. The readoutWhich campaigns brought paying customers, each sale counted once

I've tied leads to closed sales in two settings. For a cafe and lounge, Google and Meta lead campaigns collected phone numbers, and a personal offer code linked each lead to the visit and the bill. For a wholesale supplier, I built the CRM that records every sales call through to the closed account. If your leads arrive through web forms, I'd set it up with the campaign tag or ad click ID saved with each form, which carries onto the CRM record and joins to the closed sale. It's the same join with a different key. With closed sales on the record, I can check what each ad platform claims against the sales that actually happened, so one sale isn't counted twice.

I've worked in Google Ads, Meta Ads and the Meta pixel, Google Analytics, and BigQuery, including BigQuery connectors for the ad platforms, and I report in Looker, Tableau, Power BI, or a spreadsheet, whichever your team already reads.

Typical deliverables are a measurement map, a clean analysis table, a campaign comparison, a funnel report, and a plain-language summary of what the numbers say and what to do next. The sample readout shows the format on a made-up business. When you need to know what a campaign added on its own, I design a fair comparison that can show it, such as holdout days when the campaign or event doesn't run.

For a cafe and lounge client, this work cut the ad spend behind each dollar of tracked sales by about 70% on lead campaigns.

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Channel budgets and demand forecasts

Questions I work on

• How much does each channel add to sales once the others are accounted for?
• How long does a campaign's effect linger after it stops, and where does more spend stop paying?
• Which days are best to run a campaign, and when should it start and stop?
• How many visits or orders should we expect next week, and can we staff for them?

What you get

From your spend and sales history, I estimate what each channel adds to sales. Most channels give only one data point a week, so each channel gets a likely low and high estimate instead of one falsely exact number. Technically, these are Bayesian marketing mix models. At Ringer Sciences, teams used my marketing mix and forecasting models to set channel budgets, and the forecasts were about 18% more accurate. For smaller businesses, I forecast visits by hour as a likely low-to-high range, so the owners know how much food, stock, and staff a given spend will need.

Typical deliverables are channel contribution estimates with likely ranges, a budget scenario table, and a forecast your team can refresh.

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Prospect and demand analysis

Questions I work on

• Which prospects should the sales team call first?
• Which audience, offer, event, or product deserves a small test?
• Which basket combinations lift the average ticket?
• What should we compare before spending more?

What you get

I score or rank prospects from your existing records, and I can train a model when the data supports one. For a wholesale supplier's sales team, I built a lead CRM with a model that ranks leads, and closing rate per call rose about 50%. For demand questions, I combine sales, audience, platform, and local-market data, including public posts from local forums and community groups, and turn the finding into a test you can run.

Typical deliverables are a ranked contact list, a demand brief, a test design with a defined outcome, and a follow-up analysis.

Read how local demand analysis pointed a cafe to language-exchange nights. Foot traffic doubled within one quarter of the launch. The same method works on public reviews: for an in-development historical strategy game, I ran a player and market study on more than 200,000 Steam reviews.

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Reporting and document search

Questions I work on

• Can analysts find the right passage in old reports without opening every file?
• Can an AI tool write up the findings without getting the numbers wrong?
• Can messy spreadsheets become a reliable reporting input?
• Which rows failed validation, and where did they come from?

What you get

For document search, every answer shows the passages it came from, so people can check it, and I test the system against real questions before anyone relies on it. For reporting, I import, join, standardize, and validate the source files. Rejected rows stay visible with their source and a reason, so nothing disappears during cleaning.

Typical deliverables are a working search tool, a set of real questions to test it against, clean database tables with their validation rules, a recurring report or dashboard, and documentation.

Read about the search assistant behind about 40% less research time, the hospital marketing dashboards, or inspect the spreadsheet consolidator.

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How an engagement usually runs

Most projects run in this order:

1. In a free first consultation, agree on the decision and who will use the answer.
2. Look at the data you have and how records connect.
3. Write down the measures, the comparisons, and what the data can't tell us yet.
4. Build the smallest report, model, or workflow that answers the question.
5. Walk through the result with the people who will act on it.

The first three steps end in a written plan: the measures, the comparisons, and what the data can't answer yet. That plan is where we decide together whether the build is worth doing.

To start, I usually need read access to the ad accounts or an export from them, the sales, CRM, or POS records for the same period, and time with the person who will act on the result, once at the start and again at the readout. Read access is enough for measurement, so nothing in your ad accounts changes. If your forms need the campaign tag added, that's a small change for whoever manages your website.

Pricing. The first consultation is free. After it, I quote a price up front for the work you've asked for, so the cost is settled before anything starts. The effort depends on data quality, access, and the comparison you need, so each quote comes from the request rather than a price list. If the first project turns up a recurring need, the work can continue as implementation, or as ongoing reporting on a retainer.

Your data. Client data stays confidential. I've worked with a hospital client and know the HIPAA rules for health data, and I hold every client's data to the same standard.

Replies. I reply to new inquiries within a day.