Scale
Reframing complex enterprise workflows into a clearer, scalable product experience for buying and selling businesses.
At a glance
Buyers, sellers, funders and admins
Discover, Evaluate, Validate, Connect, Transact
Conversion improvement target
The problem
Buying or selling a business relied heavily on intermediaries, which added cost and friction. Buyers needed confidence in their evaluation: is the price fair, what is the financial potential, what are the risks and the likely ROI.
What I changed
I owned the product experience end to end across a three-designer team. Through stakeholder discovery, customer insight synthesis and competitive analysis, we built the product around a five-stage spine with role-based journeys for each of the four user types.
The detail
Financial intelligence lives inside the core marketplace instead of a separate tool. AI handles valuation, scenario analysis, revenue and profit prediction, risk insights and ROI/DCF calculations, applied where it reduces uncertainty in high-value decisions. Sellers control when deeper information is shared.
What I learned. A marketplace has to help people decide, not just find listings. AI is most valuable when it reduces uncertainty, working under human product judgment.
What happened
Guided listings, intelligent evaluation, funding requests, a premium tier and admin tools for listings, loans and commissions. No post-launch figures are claimed; the North Star metric is Qualified Transactions Initiated, and client feedback on the overall experience was positive.
Full case study
The complete story
Opportunity
From intermediary-led deals to a digital marketplace
Buying or selling a business involves valuation, financial analysis, due diligence, negotiation and funding. The traditional process relied heavily on intermediaries, adding cost and friction. Scale set out to connect buyers and sellers directly and give them the financial intelligence to decide well.
The business model centred on a 1–2% transaction commission, with extra revenue from premium subscriptions and related services.
Challenge
A marketplace connects people. It can't decide for them.
Research showed the bigger opportunity wasn't discovery. Buyers needed confidence in what they were evaluating:
- Is this business worth the asking price?
- What is its financial potential?
- What are the risks?
- What could the ROI look like?
The core question became how to help buyers and sellers move from discovery to confident evaluation and on to a transaction.
Product spine
A simple progression connected every feature
- Discover: find relevant businesses.
- Evaluate: understand the business, financials and opportunity.
- Validate: use valuation, ROI and AI analysis to assess it.
- Connect: request access and talk to sellers.
- Transact: move toward offers, funding and acquisition.
Roles
Four roles. One shared marketplace.
| Role | What they do |
|---|---|
| Buyers | Discover businesses and evaluate investment opportunities |
| Sellers | Create listings, present the business and manage buyer access |
| Funders | Review financial assistance requests |
| Admins | Monitor users, listings, premium activity, loans and commissions |
Intelligence layer
Financial intelligence inside the core product
A key decision was to make financial analysis part of the marketplace, not a separate tool.
- Marketplace: discovery and listings
- Financial intelligence: performance and valuation
- AI: predictive and scenario analysis
- Decision support: ROI and DCF calculations
- Communication: controlled information sharing
- Funding: financial assistance
AI for confidence
AI solved a product problem, not a feature gap
The guiding question: where can AI reduce uncertainty in a high-value financial decision?
- Business valuation and scenario analysis
- Revenue and profitability prediction
- Risk insights, ROI and financial analysis
- Generated business descriptions for sellers
Key experiences
The moments that move a deal forward
- Guided listing: sellers move through business details, financials and media step by step instead of one long form.
- Intelligent evaluation: buyers combine financial data, AI insights and ROI tools to judge potential.
- Controlled access: sellers decide when deeper information becomes visible.
- Premium intelligence: advanced AI and financial tools sit in a premium tier, linking value to revenue.
My role
Lead Product Designer, team of three
| Area | What I did |
|---|---|
| Discovery | Stakeholder discovery, customer insight synthesis, domain exploration |
| Strategy | Competitive analysis, product opportunities, prioritisation |
| UX | Information architecture, role-based journeys, flows, wireframes |
| Innovation | AI feature definition, financial workflows, decision-support concepts |
| Execution | Visual design, prototyping, design reviews, stakeholder presentations |
I used ChatGPT, Claude and Gemini as thinking partners for research synthesis, competitive analysis, financial scenarios and content, while product decisions stayed grounded in business goals and user needs.
Measuring success
Measure the transaction, not just the interface
Scale had no mature production analytics yet, so this case study doesn't claim post-launch results. Instead it defines how success should be measured.
| Area | Signals |
|---|---|
| North Star | Qualified transactions initiated |
| Marketplace | Buyer registrations, active listings, enquiries |
| Activation | Businesses viewed, financial analysis completed, AI insight use |
| Monetisation | Premium conversion, subscription engagement |
| Transaction | Connections, offers initiated, completed transactions |
The project targeted at least a 5% conversion improvement. This is a target, not an achieved result.
Outcome
From a marketplace to a transaction ecosystem
Scale brought together marketplace, financial intelligence, AI, communication and funding, helping people find businesses, understand their value and move toward a transaction. Client feedback on the overall experience was positive.
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