The Pricing Problem
Most SMEs price by gut feel or by copying competitors. Both approaches leave money on the table. Pricing too low means working harder for less. Pricing too high means losing deals you should win. Getting it right requires data, and most SMEs don't have time to gather and analyse it.
How AI Helps
Competitor Analysis
Feed Claude your competitors' websites, pricing pages, and marketing materials. Ask for a pricing comparison matrix. In 20 minutes, you have a comprehensive view of where you sit in the market.
Value-Based Pricing
AI analyses your past projects: time spent, outcomes delivered, client satisfaction. It identifies which services deliver the most value and should be priced higher, and which are commoditised and should be streamlined.
Market Research
AI searches industry reports, salary surveys, and market data to benchmark your pricing against industry standards. Not just competitor pricing, but the broader market context.
Dynamic Pricing
For product businesses, AI monitors demand signals, inventory levels, and competitor prices to recommend optimal pricing in real-time.
Proposal Optimisation
AI analyses your win/loss data to identify pricing patterns. "Deals priced between £5,000-7,000 close at 45%. Deals above £10,000 close at 20%. The sweet spot for your conversion rate is £6,500-8,000."
The Framework
Start with cost-plus (your costs + margin). Validate against market data (what competitors charge). Adjust for value (what the outcome is worth to the client). Use AI to automate the research and analysis at each step.
Price Smarter
OrcaScale builds custom business intelligence tools that help you price, forecast, and plan more effectively.