The most underleveraged profit driver in Indian businesses.

The founding team knew pricing was wrong. The top 20% of accounts by usage were getting 4.1x the value but paying 1.4x more. That disparity had been visible in the data for two years. The reason nothing had changed was fear: two competitor SaaS companies had restructured their pricing in the previous 18 months and had both publicly lost customers doing it. The founders were not willing to repeat that mistake without a structured approach that gave them confidence before they moved.

A willingness-to-pay study: 28 qualitative interviews across usage tiers, then a Van Westendorp analysis with 14 more respondents. The value metric that best predicted customer success was identified as 'active workflows run per month', not seats, which was what they'd been charging on. A three-tier pricing architecture was built with a 24-month grandfather clause and an opt-in upgrade incentive for the top 30 accounts. The grandfather clause existed because it was the right thing to do for customers who had been with the company from the beginning, not just because it reduced churn risk.

This reflects the type of challenge our consultants are built to solve, drawn from real industry experience. The company priced all 14 routes on a uniform cost-plus basis. A route-level P&L analysis, which had never been done before, showed that 4 routes were operating at negative contribution margin when fuel, driver overtime, and vehicle wear were properly allocated. Meanwhile, 3 high-demand routes were priced 17-23% below what competitors were charging for the same lanes. The company was simultaneously over-delivering on some routes and undercharging on others, and had no idea.

Three weeks building a route-level P&L from scratch, the kind of analysis that sounds straightforward but requires Finance and Operations to agree on how to split fixed costs, which is rarely a quick conversation. Market-rate benchmarking used shipper rate cards from 6 comparable firms and 4 tender responses. Price changes were introduced in two tranches: the underpriced high-density routes first, four weeks before the loss-making routes. That sequencing mattered: it gave the team real elasticity data before they raised prices on the routes where customers had the fewest alternatives.