31st July 2025
Understanding how Data & Analytics (D&A) businesses are valued isn’t always straightforward. Public market comparables rarely apply and valuation multiples are typically undisclosed. And founder conversations with investors often centre on outcomes rather than what really drives them.
But having worked with and appraised many D&A businesses - from IWSR and Defaqto to 60 Decibels and Vanda Research - we’ve seen consistent patterns in those that achieve premium valuations.
It’s rarely just about headline growth. The most valuable companies share three traits they focus on relentlessly: defensibility, pricing power, and long-term value creation.
1. Build defensibility across the data value chain
The most successful D&A businesses move beyond one-off research projects and towards building standardised, repeatable data assets that can be licensed at scale. They develop proprietary - or hard-to-replicate - data products that become integral to their customers’ workflows and decision-making.
Defensibility typically spans the full data value chain:
- Data sourcing - Move beyond publicly available sources to proprietary collection.
- Data enhancement - Turn raw inputs into structured, actionable insight.
- Data delivery - Embed outputs into customer processes and platforms.
The strongest businesses build advantage across at least two of these three stages of the chain. The result is a product that’s critical to customers and difficult to substitute - reflected in consistently high Gross Revenue Retention (typically 95%+).
2. Strategic pricing
Not all recurring revenue is created equal. Premium D&A businesses design pricing models that reflect the value they deliver - not just the cost to produce or volume of data. A value-based pricing strategy signals deep understanding of customer outcomes and a path to scalable, profitable growth.
Key pricing behaviours we see in high-performing D&A businesses:
- Adopt value-based pricing tied to customer outcomes.
- Introduce clear segmentation and differentiated tiers.
- Bundle complementary products to simplify the buying process.
- Communicate pricing evolution early and with transparency.
- Regularly review and refine pricing strategies.
- Drive account expansion through upsell and cross-sell.
We typically see 110%+ Net Revenue Retention in businesses with strong pricing models - proof that the commercial model supports organic growth.
3. Harness AI to deepen - not dilute - your advantage
AI and machine learning are already reshaping the D&A landscape - from how raw data is sourced and structured, to how insights are personalised and delivered. Done well, AI can meaningfully expand your value proposition. Done poorly, it risks commoditising your offering.
The most valuable D&A businesses embed AI in ways that sharpen their competitive edge and improve customer outcomes. We typically see it add value across three areas:
- Automating the extraction, structuring and cleaning of large or complex datasets.
- Using machine learning to detect patterns, forecast trends and surface insights beyond what human analysis alone might uncover.
- Tailoring outputs, dashboards and alerts to fit specific user roles and workflows, increasing daily reliance.
The goal isn’t to replace human expertise or strip out nuance - it’s to build intelligence into your product that is harder to replicate. In short: use AI to deepen your advantage, not to race toward becoming a commodity.
Premium valuations aren’t just the result of strong financials. They come from building businesses with the characteristics the market values most: resilience, relevance, and repeatability.
These themes - and the metrics that matter most - are explored in more detail in our Founder’s Guide to Valuation in Data & Analytics, including a case study of IWSR’s growth journey. You can download it here.