Business Model Diversification

Use bleeding-edge technology and AI to spin up new digital revenue streams, monetise your data, or create entirely new service models - fast

Mindlace focuses on helping companies in seven key moments. This post unpacks Moment 6 - Business Model Diversification: the point where ambitious firms look beyond their core line of business and turn proprietary data, know-how and brand trust into fresh, AI-enabled income streams. See a summary of those seven moments here.

Why diversification is suddenly urgent

• Data is the next P&L line. The global data-monetisation market is projected to leap from US $4.7 billion in 2025 to US $28.2 billion by 2033 (25 % CAGR) - evidence that investors now value data flows as highly as finished products. (Data Monetization Market Size, Share & Growth Report By 2033)
• Digital subscriptions keep ballooning. Transaction value inside the subscription economy will climb from US $593 billion in 2024 to US $996 billion by 2028 - a 68 % jump that rewards companies with repeatable, services-led models. (Subscription Economy Market Report 2024-28 - Juniper Research)
• AI budgets have exploded 6× year-on-year, hitting US $13.8 billion in 2024 as enterprises race from pilot to production - proof that buyers will pay for AI-powered features, not slideware. (2024: The State of Generative AI in the Enterprise - Menlo Ventures)
• CEOs are voting with wallets. Two-thirds of leaders plan to build new corporate ventures in the coming year - outstripping interest in M&A or joint ventures. (Corporate venture building for CEOs - McKinsey & Company)

Stand still and your multiple compresses; diversify and you'll ride where capital is flowing.

Signals you’ve reached Moment 6

• Revenue concentration risk keeps cropping up in board packs.
• Product-market fit is solid but growth is flattening - marketing spend rises faster than ARR.
• You sit on a gold mine of operational data (IoT, usage logs, workflows) that customers would pay to access, yet it lives in siloed warehouses.
• Competitors launch AI add-ons (recommendation engines, predictive planners) and sales teams start fielding “Do you offer that?” calls.
• Line-of-business leaders hire “Director of Digital Ventures” - but deliverables remain vague.
• Your industry shifts towards subscription or usage-based pricing and procurement teams expect the same from you.
• Shadow-tech prototypes emerge internally (e.g. a Gen-AI quoting engine a sales manager built in Airtable) signalling latent demand.

If two or more resonate, you’re leaning on a single engine while fresh revenue jets idle on the tarmac.

Three fast playbooks that work

1. Monetise proprietary data
   Package anonymised telemetry or benchmarking insights as dashboards, APIs or premium reports. A mid-market product-review platform that activated its dormant user database with AI-driven email and search saw 28 % revenue growth while cutting acquisition spend. (AI-Driven Digital Transformation: 28% Revenue Growth Case Study)
2. Attach AI-native services to the core product
   Think predictive maintenance modules for industrial machinery, Gen-AI copilot layers for legal-tech, or custom-insight add-ons for SaaS. Generative-AI vendors already surpassed US $25 billion in 2024 - proof customers pay for embedded intelligence, not tech talk. (The leading generative AI companies - IoT Analytics)
3. Launch a venture-backed adjacency
   Use corporate-venture-building methods - 12-week sprints, low-code MVPs and small external squads - to spin up a brand-new digital line without derailing BAU. McKinsey finds CEOs favour venture-building 1.3× more than any other growth move right now. (Corporate venture building for CEOs - McKinsey & Company)

Common pitfalls—and how to dodge them

Below doesn't even go into Innovators Dilemma Innovator's - we have our own post here about that.

• The conglomerate discount. Straying too far from the core confuses investors and dilutes multiples. Guard-rail: focus on adjacencies that reuse at least one of your existing advantages—data, channels or domain trust.
• Tech for tech’s sake. An AI widget nobody will pay for is negative ROI. Guard-rail: validate willingness-to-pay with five design-partner customers before writing code.
• Integration debt. A new digital unit built on an island drains margin via duplicated stacks. Guard-rail: reuse shared services (identity, billing, support) from day one.
• Orphan metrics. If the venture owns no distinct P&L, it dies in budget season. Guard-rail: carve out dedicated revenue targets and empower the GM to hit them.
• Culture whiplash. Core teams view the new venture as a pet project and block data access. Guard-rail: incentivise cross-unit collaboration options, secondments, shared OKRs.

How Mindlace accelerates diversification

• Rapid discovery. In three weeks we scour your data estate, process maps and market whitespace to surface 3-5 high-ROI diversification bets.
• 12-16 week MVP. Small, cross-functional squads ship a live product (or data API) with early customers - not decks.
• Transfer, don’t tether. We hand over code, pipelines and a scaling roadmap, up-skilling your team so the new revenue keeps compounding after we roll off.
• Impact Pledge. Every sprint must show a quantifiable business win—otherwise we don't invoice.

Ready to turn your ideas, instincts, dormant data and AI into brand-new income lines? Book a call with Mindlace and let's chat through.