The work, and what it changed.
Each study covers the decision that was on the table, what we built, and what held up after, including the parts that did not. If a number matters, we show how it was measured.
2.8x growth in 10 months, on measurement the whole company trusted.
A DTC brand stopped making budget calls off platform ROAS, rebuilt the measurement under one set of definitions, and moved spend it could finally defend.
Read the studyThe ~$100M loungewear category the data said was worth a real look.
Category and audience data kept pointing at an adjacency the roadmap had no view on. The analysis put a defensible range on the opportunity so the decision to enter was made on numbers rather than instinct.
Read the studyThe AI retention model whose first big call was sending fewer promos.
97% of the base never heard from the brand, while everyone got the same discounts. A next-best-action model picked each customer's action weekly, lifted net revenue +28% where it sent offers, and cut churn ~10%.
Read the studyFrom Google Sheets to thousands of orders a day, with cancellations down ~23%.
Complex fulfillment ran on semi-manual sheets that broke a little every day. We automated the backbone across NetSuite, Salesforce, and the 3PLs, and kept people on the steps where customers feel the difference.
Read the study20% more data revenue from the same data, once the selling had clean books.
The brand already sold its data, but nobody could see what was for sale, who was buying what, and what each feed earned. Clean views of the catalog and contracts surfaced underpriced deals, unbilled feeds, and where to expand next.
Read the studyMore studies are being written up. If the situation you are in looks like one of these, the fastest way to see the detail is to ask.
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Tell us what you are trying to figure out. If we can help, we will say how. If we are not the right fit, we will say that too, and point you somewhere better.