Six kinds of work
Each project starts with a written scope and a fixed price. The prices below are where most projects start; the scope sets the final figure.
- From
- $6,500
- Typical length
- 3 weeks
Data audit
inventory, cross-system joins, one clean customer table
We list every source your reports depend on, test how well they agree, and fix the joins that break most often.
Most reporting problems start upstream. The CRM counts a customer once per contact, billing counts one per invoice address, and the two never agree on how many customers you have. We find those mismatches before anyone builds a forecast on top of them.
What we check
- Duplicates and orphaned records
- Fields that changed meaning over time, like a “region” that was a state until 2021 and a sales territory after
- Gaps: days, stores or products with no rows at all
- Refresh times: which report is a day old and which is a week old
What you keep
The checks are plain SQL that runs in your warehouse every night. When one fails, it emails the owner of that source, not us.
What you keep
- A map of every data source, its owner and its refresh time
- Row-level checks that run every night
- One customer table that matches sales, billing and support
- A written list of what we could not fix, and why
- From
- $8,000
- Typical length
- 4 to 6 weeks
Reporting
defined metrics, one dashboard, a Monday email
One dashboard with fifteen numbers at most, each with a written definition, an owner and the query behind it.
Most companies we meet have forty dashboards and three definitions of revenue. We start by writing down what each number means, then build the smallest report that answers the questions asked in your weekly meeting.
How we build it
- Interview the five to ten people who use the numbers
- Write one definition per metric, next to the query that computes it
- Build the dashboard in Looker Studio, Power BI, Metabase or Tableau, whichever you have
- Retire the reports nobody opened in the last ninety days
What you keep
- A metric glossary signed off by your finance lead
- One dashboard in the tool you already pay for
- A Monday email with the five numbers that moved most
- Training for the person who will maintain it
- From
- $12,000
- Typical length
- 6 to 8 weeks
Demand forecasting
weekly forecasts, stock levels, staffing plans
Forecasts by product and location with a range around every number, so buyers can see how sure the model is.
We forecast whatever drives your costs: units, orders, calls or staff hours. Each forecast comes with a back-test, so you can see how the model would have done last year before you trust it this year.
What we model
- Seasonality and holidays, including the ones that move every year
- Promotions and price changes, if you have the history
- Stock-outs, which hide real demand in your sales data
- New products, using the closest existing ones as a guide
When we say no
With less than eighteen months of history, a forecasting model rarely beats a well-kept spreadsheet. We tell you that in the first week and bill for the first week only.
What you keep
- A weekly forecast by product and location, 13 weeks ahead
- An 80% range around every number
- A back-test against the last two years
- A plain Python job that reruns every Monday
- From
- $14,000
- Typical length
- 6 to 10 weeks
Pricing
price tests, discount rules, gross margin
We estimate how demand responds to price for each product group, then set prices and discount limits from that.
Most price lists were set once and adjusted by feel. We use your order history to estimate how volume moves when price moves, then set prices where margin is highest without losing the customers you want to keep.
What we usually find
- Discounts given to customers who would have paid full price
- Products priced below cost once shipping and returns are counted
- Price steps that push customers down to the cheaper tier
What you keep
- Price response estimates by product group
- Recommended prices, each with its effect on margin
- Discount rules your sales team can apply without asking
- A test plan for the changes we are least sure about
- From
- $5,500
- Typical length
- from 2 weeks per test
Experiments
A/B tests, sample sizes, honest readouts
We design tests that can answer the question, size them before launch and report the result even when it is flat.
Half the tests we are asked to review were too small to detect the effect they were looking for. We fix the sample size and the stop date before launch, so nobody ends a test early because the first week looked good.
What we test
- Prices, offers and free-shipping thresholds
- Checkout and sign-up changes
- Email timing and content
- Sales scripts, by randomizing which reps use them
What you keep
- A one-page plan per test: question, metric, sample size, stop date
- Randomization checks on day one
- A readout with the effect, its range and what we would do next
- A log of every test you have run
- From
- $10,000
- Typical length
- 5 to 7 weeks
Customer analysis
segments, churn, lifetime value, who to call first
Segments built from what customers buy and how often, plus a churn score your account managers can use every week.
Segments only help if someone treats each one differently. We build them from order history, not demographics, and agree with your team which action goes with each segment before we hand them over.
Questions we answer
- Which channel brings the customers who stay longest
- What the last three orders of a customer who left look like
- How much you can spend to win back a lapsed account
What you keep
- Four to six segments with a plain description of each
- A churn score for every active account, refreshed weekly
- Lifetime value by acquisition channel
- The twenty accounts most at risk, in your inbox every Monday