Repositioning in a red ocean

I led marketing repositioning at Turtl, a martech company originally positioned in the interactive-content category. That category served a broad range of ideal customer profiles and had become increasingly commoditised, making it difficult to stand out or explain why Turtl mattered to any one buyer. The strongest value was emerging with enterprise ABM marketers: they had a clear need for revenue content and a stronger reason to connect content activity to pipeline than our other segments, many of which were churning. The trigger was the mismatch between our broad category story and where the product was actually delivering durable value. I repositioned Turtl around revenue content for ABM marketers in enterprise companies, using the contrast between segment performance and the commercial quality of the opportunities we were creating as the evidence that this was the market we should own.

The company’s broad objective was straightforward: increase ARR. My objective was more specific — create qualified pipeline by narrowing the ICP and repositioning Turtl in a red-ocean category where competitors could quickly copy our language and claims. I owned the repositioning and its go-to-market execution end to end, without a team, and with limited budget and resources. That meant I had to build the strategy, messaging, and operating system myself, including an AI-enabled GTM system to scale the work. Success would be judged through the commercial signals available to us: MEDDPICC-qualified deals created, deal size, enterprise ICP performance, win rate, and quarterly attainment. There was no single prescribed target beyond increasing ARR; I had to establish a sharper path to it.

I started with the commercial evidence rather than a category theory. Turtl was serving a broad interactive-content ICP, but the strongest conversion rates, largest deal sizes, and most durable value were concentrated among enterprise ABM marketers. Other segments were churning, while ABM customers were giving us a clearer connection between content activity and revenue. That made the strategic decision straightforward: narrow the ICP and reposition Turtl from interactive content to revenue content for ABM marketers in enterprise companies. I rejected the safer option of keeping the broad category story and trying to improve it with more messaging; the data showed that the problem was the market we were claiming, not just how we described ourselves.

I owned the repositioning end to end, starting with research and positioning, then translating the decision into messaging, sales assets, and a pricing strategy. I also built an AI-enabled GTM system because I had no team and limited budget or resources, and needed to scale the work without adding a large operating layer. The system helped me move faster across the research, content, and go-to-market execution required to make the new position usable. I let the commercial data validate each step rather than trying to win an internal belief campaign: as the enterprise ABM motion produced stronger qualified opportunities, larger deals, and better conversion, it confirmed that the narrower position was working. The competitive risk was that rivals could copy the language (and some did, including my copy!!) but that reinforced the need to own the category through execution and commercial proof, not words alone.

I used two layers of tooling: Claude to power the agentic research and workflows, and HubSpot to turn the repositioning into visible market activity.

Claude was the foundation of an AI-enabled GTM system I created myself, including custom agents for ICP research, positioning, win/loss analysis, competitor intelligence, enablement-material creation, and executive summaries. I built it because I owned the repositioning without a team and needed to move from weeks of manual work to days. The agents did not replace the strategic decisions; they accelerated the research, synthesis, and production needed to make those decisions usable across marketing and sales. The system is now available through Forma.

I used HubSpot for the AEO and website work that supported the new position and improved brand visibility. In four weeks, visibility increased by 20%, and Turtl achieved the highest citation rate against competitors including Demandbase and Salesforce. The most load-bearing tool was the GTM system I built: I would use it again because it compressed a solo operator’s execution cycle without requiring a larger team.

I increased MEDDPICC-qualified pipeline by 750% after narrowing Turtl’s ICP to enterprise ABM marketers and repositioning the company around revenue content. The commercial quality of the pipeline improved alongside its volume: average deal size rose 650%, from $6,000 to $45,000, while the largest deal increased from $30,000 to $150,000. On enterprise ICP deals, win rate doubled from 20% to 40% by value. Quarterly attainment also rose 75% over the following year, with average quarterly closed revenue increasing from $150,000 to $600,000.

The change was not only financial. The organization had a sharper ICP, category story, and sales motion, while the AI GTM system reduced execution cycles from weeks to days. HubSpot-supported AEO and website work increased brand visibility by 20% in four weeks, with Turtl achieving the highest citation rate against competitors including Demandbase and Salesforce. The clearest lesson was that the data did the persuading: stronger conversion and deal economics made the narrower position defensible, even as competitors adopted (and sometimes copied) the language.