GTM Advisory, Implementation and Technology
We turn growth decisions into execution. We connect market strategy, customer acquisition and revenue operations, and develop, build and operate the data and technology they need.
We Engineer Systems for Growth.
Who you target, how you acquire customers and how you manage revenue affect one another. Focus on the area you need, while keeping its connections to the others in view.
You are entering a market, defining an offer or deciding which customers to prioritize.
You want to reach more of the right customers, enter their consideration and turn interest into sales opportunities.
You want reliable sales data, clear handoffs between teams or less manual work.
We combine data science, business intelligence and product development to assess sales forecast reliability, organize market research and automate repetitive work. We configure Harvester, Kastelan and Luna around these needs.
Entirely synthetic data
Twelve months of illustrative sales, a simple baseline and a three-month forecast. Historical evaluation is separate from the future scenario.
Monthly sales count
Each of the last four historical months was evaluated using only the months preceding it.
Mean absolute error (sales)
Not a client result or product performance claim. This small synthetic comparison does not establish which model to use with real data.
The shaded scenario band adds ±4, ±6 and ±8 to the point forecasts. It is not a probability, confidence or statistical prediction interval.
The illustrative model is an ordinary least-squares linear trend. The baseline repeats the previous month’s sales. Mean absolute error is the average absolute difference between a prediction and its observation.
| Month | Synthetic observation | Linear model | Previous-month baseline |
|---|---|---|---|
| 1 | 41 | - | - |
| 2 | 46 | - | - |
| 3 | 44 | - | - |
| 4 | 48 | - | - |
| 5 | 47 | - | - |
| 6 | 53 | - | - |
| 7 | 49 | - | - |
| 8 | 55 | - | - |
| 9 | 52 | - | - |
| 10 | 58 | - | - |
| 11 | 54 | - | - |
| 12 | 61 | - | - |
| 13 | - | 60.44 | 61.00 |
| 14 | - | 61.94 | 61.00 |
| 15 | - | 63.45 | 61.00 |
Align CRM stages, offer history and close dates. Keep missing records visible as a limitation of the analysis.
Use BI to inspect stage transitions. Where the data supports modelling, compare forecasts with a simple baseline and track error.
Give the sales owner a follow-up priority. Define automated tasks separately from actions that require human approval.
Gathers data from public and permitted sources for market and customer research. Produces records your team can review with their source and collection time.
Carries out defined research and operational tasks. Turns repetitive work into a workflow with agreed permissions and approval points.
Interprets data and findings, making options, uncertainty and missing information visible. Helps your team assess its next decision.
One team can take responsibility from understanding the need through implementation and operation. The starting point depends on your existing work; you do not need to buy all four phases from scratch.
How we workReview the objective, current operations and data to identify priorities and assumptions to test.
Situation review and prioritiesPlan the work, channels, data and team responsibilities together.
Execution and measurement planSet up the required content, funnel, CRM flows, integrations and measurement.
Working flow + control pointsReview results with the team, improve operations and record decisions.
Decision cadence + learning recordFit is assessed through company stage and the problem you are ready to solve, not through a long industry list.
Explore engagement conditionsSource reviews and practice notes on market strategy, customer acquisition and commercial technology. We examine what an approach proposes, where it applies and which questions it leaves open.
All insights
April Dunford’s work shows that positioning is not a creative slogan. It is a decision system that defines what customers compare a product with and why its value matters.
How can Brian Balfour’s Four Fits inform a channel investment? We distinguish the framework’s context from Hornpiper’s application advice.
Elena Verna proposes building repeatable growth foundations into product infrastructure. Hornpiper asks a further question: which work can we automate, with which controls?
Let’s discuss your goals, your current situation and where we could work together.
The introductory call explores the opportunity to work together. Detailed diagnosis and solution design are scoped separately.
