A Strong Track Record, Built on Proximity

A Swiss AI services boutique had built something rare in its space: an exceptional track record of getting customers' AI-based use cases into production, exactly where most organisations stall. Their go-to-market approach was cross-industry, relationship-driven, and deeply rooted in a strong home-market network across business and academia, including years in national innovation programmes that built deep, hands-on AI experience.

To unlock the next growth phase, the board appointed a new CEO and made it a strategic priority to enter a new market, one where they had limited traction but saw significant potential. For this task, they hired a dedicated business development lead. She brought a strong management consulting background, experience in market expansion, and a solid network of relationships in the target geography.

She began with the ambition to build a comprehensive business case with well-defined offerings, target industries, and a plan for how to adapt the go-to-market approach. But as she dug in, she realised that many of these strategic elements had never been made explicit. In the home market, proximity and trust had made that unnecessary. For expansion, it was essential.

The Shift She Made: From a Growing Document to a Sharp Foundation

The deeper she went, the more the challenges stacked up:

• An offering portfolio spanning both consulting services and AI products (such as a private, on-premise GPT assistant) made it difficult to select which elements would create immediate customer engagement

• A broad, cross-industry approach at home offered no clear basis for segmentation, making it hard to know which customers to focus on and how to position for a new market

• The AI market in the target region was already crowded, and with interest in AI surging, competition was only set to intensify, making durable differentiation essential

• Resources for market entry were limited, so bets had to count

The more challenges she uncovered, the more she wanted to address them in the document, adding her analysis and a recommended course of action for each. But every answer meant more pages, and she began to realise that the longer the document grew, the less likely busy stakeholders were to actually read it and start the decisions it was meant to trigger. She had poured real effort and personal conviction into the business case, yet she had to face an uncomfortable truth: a comprehensive document risks becoming a zombie on a file share.

She made a call. Rather than expand the business case she had agreed with the CEO to write, she would define the few things that actually mattered for scalable, targeted expansion in her market: a clear positioning and value proposition, the target segments to prioritise, and the offering best suited to win those customers and turn them into advocates whose references build the trust to win over the next buyers. Together these would form the sharp foundation the expansion could stand on, the very elements the company had never had to make explicit at home, where proximity carried them.

To get there, she would do what came naturally to her and follow the data, starting with the company's most successful adoption patterns, where its AI solutions had genuinely taken hold with customers, and why. She laid out her reasoning to the CEO. He supported the approach at once, recognising that a focused, evidence-based foundation would give the company clarity and momentum it could build on well beyond this one market.

Turning CRM Data Into Focus, Foundation, and Execution

With the CEO behind the new direction, she needed a way to deliver the foundation itself. For this, the company brought in Venture Guidebook and its PMF Engineering offering, which pairs a proprietary PMF Engine with hands-on facilitation to find evidence-based product-market fit. Rather than guessing where an offering might land, it uses a company's own data to prove where that offering already fits the market, and for whom. The engagement ran as a focused sprint, with a Venture Guidebook facilitator working hand in hand with the BD lead throughout.

Step 1: Gather the evidence

Three years of CRM data, covering concrete deals and opportunities, were fed into the PMF Engine's Target Sweet Spot (TSS) framework, enriched with detail on who had owned each purchase, a support function such as IT or the business itself, and how they had bought, as a tactical point solution or a strategic, executive-sponsored initiative.

Step 2: Identify the adoption pattern

The Target Sweet Spot map: plotting three years of deals by who owned the purchase and how they bought, adoption concentrated where the business itself drove AI as a strategic initiative, the company's most winnable home made visible.

The Target Sweet Spot analysis revealed a clear pattern. Plotted on two axes, who owned the purchase (a support function such as IT, or the business itself) and how they bought (as a tactical point solution or a strategic, executive-sponsored initiative), adoption concentrated in one quadrant of the map: deals the business owned and pursued as a strategic initiative. That quadrant was the company's most winnable home, where customers chose the AI solution, expanded its use, and embedded it into how they work far more readily than anywhere else. This was the company's core strength, its product-market fit, made visible: it got customers' AI use cases into production, and made them stick, exactly when the business owned them as a strategic initiative. Here was fit proven in the data, not claimed in a pitch. The pattern had never been visible before, because the data had never been examined through this lens.

Step 3: Select the market entry focus

Based on this concrete evidence, the team identified manufacturing as the industry focus and AI-driven operating model optimisation via risk-free, punctual process augmentation as the adoption scenario with the highest replication potential. It reflected how customers had actually behaved, not a strategic hypothesis.

Step 4: Trace the adoption journeys behind the pattern

The team went back to the deals from the business-led, strategic sweet spot that had shown the strongest adoption and examined each as an AI adoption journey, from where the customer's AI maturity had started to where it stood now. Looking across these journeys revealed the typical needs customers had at each stage and the actions that moved them up the maturity curve. With this, the adoption scenario identified earlier grew steadily more tangible, an abstract pattern enriched with concrete insight into how adoption actually plays out, and what drives it.

Step 5: Turn the sharp foundation into execution-ready assets

So far, Venture Guidebook’s PMF Engineering had created the relevant insights: gathering the evidence, identifying the pattern, and making the adoption paths tangible. What still had to follow was the harder part: shaping all of this into a clear strategic direction, and making sure it could be put straight into practice, so everyone involved knew where to focus and how to act. Here the PMF Engine did the heavy lifting, producing the assets step by step, so the team could then finalise them.

• Strategic direction: drawing on the pattern the Target Sweet Spot had revealed and the focus decisions it enabled, the PMF Engine drafted a ready-made version of the Positioning Statement, the company's reach for the most desirable, defensible position it could credibly own. Rather than populating a blank framework from scratch, the team started from a worked-out draft and could focus on refining the nuances: who the offering is for and the urgent problem it solves, the category it wins recognition in, and the structural reason competitors could not easily match it.

• Value proposition and ideal customers: the PMF Engine translated that refined Positioning Statement into a Unique Value Proposition (UVP) and an Ideal Customer Profile (ICP), drawing out the typical characteristics of target customers and the case for change, why they should move off their status quo, why they couldn't afford to wait, and why the company was best placed among the alternatives to make that change a success.

Together, the Positioning Statement, value proposition, and Ideal Customer Profile formed the sharp, company-wide foundation the BD lead had recognised the company needed first, the precondition for making this market entry a success and for scaling into new markets more effectively thereafter. With that foundation set, the PMF Engine translated it into what the team needed to act on it in the target market:

• Ranked target accounts: from the ICP and UVP, the PMF Engine automatically assembled a ranked list of accounts fitting the situation the value proposition addressed, pinpointing for each a specific compelling event to trigger a move off the status quo and an entry path built around it, including who inside the account would drive the change.

• Marketing-ready assets: for go-to-market communications, it also generated a whitepaper outline for Marketing. Combined with the ranked target account list, this gave the team everything needed to launch a campaign in the new market and to adapt the company website to the findings from the sharp foundation.

Because these assets were generated rather than built from scratch, the sprint never ended in a business case document waiting to be read and acted on. It delivered a ready-made operational foundation for campaigns, content creation, and targeted outreach, translated into clear briefs that let sales and marketing colleagues who hadn't been part of the strategy work act on it immediately.

And here lay the PMF Engine's lasting advantage: unlike a business case document, fixed the moment it is finished, it kept working and closed the loop. The same Target Sweet Spot that had revealed the original pattern now took in every new opportunity and deal, letting the company see how well the sharpened direction was landing, track its traction in the new market, and keep it sharp over time. What had started as a one-off market entry effort had become a repeatable, self-correcting system the company could turn to again as it scaled into future markets.

One evidence base, cascaded step by step into a positioning statement, value proposition and ideal customer profile, ranked target accounts, and marketing-ready assets.

A Market Entry Plan, and the Strategic Clarity to Scale

The evidence-based approach delivered results across every dimension the company had struggled with:

• From broad portfolio to clear focus: TSS helped identify a specific industry and adoption scenario with the highest replication potential, so the team could commit rather than keep every option open.

• From cross-industry ambiguity to sharp positioning: a defined value proposition and Ideal Customer Profile gave the team a differentiated story for the new market.

• From crowded market to an uncontested entry point: the validated adoption pattern revealed an angle competitors weren't pursuing, grounded in real customer behaviour.

• From limited resources to focused execution: a ranked account list, each account with its compelling event and entry path, plus campaign-ready assets and clear briefs, let the lean team act immediately, without wasted effort.

With the evidence laid out, the board approved the market entry plan and the foundation beneath it, giving the team a clear mandate to move. And because the PMF Engine had not just helped produce the strategy but automatically translated it into execution-ready assets and the living system behind it, that mandate came with everything the team needed to act, and to keep the direction sharp as the company scaled. And by starting where their fit was strongest, the first customers won would become the references whose trust makes the next buyers easier to win.

The Insights Were Already in Their Data

The insights for their expansion had been there all along: in their own CRM, in their own customer relationships, in the adoption patterns of the customers they'd already won. Those patterns were their product-market fit, sitting in their data long before any document could argue for it. They had used that same data day to day for tactical pipeline management, never examining it for what it could reveal about which customers truly succeed with them, and why, and so missing the strategic value it held. What had been missing was a systematic approach to bring it out.

Venture Guidebook’s PMF Engineering provided exactly that, turning proven product-market fit into a sharp foundation, clear focus, and differentiation competitors could not easily copy, because it rested on evidence rather than claims, then into the execution-ready assets to act on all of it.

This is where a PMF Engineering sprint parts ways with the static documents companies still lean on to lay a foundation for growth: a business case, a strategy document, or a go-to-market plan. They start ageing the moment they are finished, if they are ever finished at all, and each new artefact tends to be built on its own, from fresh assumptions. Here everything descended from a single source, step by step: the pattern shaped the positioning, the positioning shaped the value proposition and Ideal Customer Profile, and those in turn shaped the ranked target account list and the whitepaper outline. Each deliverable inherited the same evidence, so nothing contradicted anything else and the wheel never had to be reinvented for the next step, or the next market.

By beginning with evidence of what already works, and why, the path forward became clear, specific, and actionable, and it stayed that way: not a one-off plan, but a foundation the company keeps sharp as it scales. Focus, differentiation, and a foundation to scale: no guesswork, no crowded fight for attention, just an uncontested entry point backed by data.