Related Ideas
eyko Ideas
Price changes feel risky because the elasticity of the customer base is unknown. A Price Sensitivity Modeling Playbook reads historical pricing, deal outcomes, discount activity, and segment behavior to forecast win-loss impact at each price point per segment, before you ship the change.
The Challenge
CRM has win-loss outcomes. Billing has price history. Sales ops has discount records. The three rarely get joined into a single view that shows how the win rate moved when the price moved, segment by segment. Pricing decisions get made without that join.
List price gets set once. Some segments would pay more without hurting win rate; some segments need a different price to convert at all. Without segment-level sensitivity data, the team applies one price to everyone and accepts the revenue leakage as a cost of simplicity.
Reps offer the discount their last deal closed at, regardless of whether this customer needed it. The discount level becomes a habit rather than a calibrated move, and total discount expense climbs above what the sensitivity data would justify.
How eyko Solves It
A Price Sensitivity Modeling Playbook reads historical price points, deal-level discount records, win-loss outcomes, segment metadata, and competitive context to forecast win-loss impact at each price point per segment. It surfaces the price points where revenue is maximized for each segment, identifies the segments where the current price is too low or too high, and recommends discount guardrails calibrated to the sensitivity profile.
The Playbook modeled price sensitivity across 8 segments and 5 plan tiers using 24 months of deal-level data. Enterprise shows steep inelasticity; current list price is 9% below the revenue-maximizing point. SMB shows high sensitivity; current discount expense is 22% above the level the data supports. Realigning prices and discounts to the sensitivity model projects $3.2M in annualized revenue lift.
| Metric | Current | Benchmark | Status |
|---|---|---|---|
| Primary indicator | Flagged | Target | Action needed |
| Secondary indicator | Monitoring | Within range | On track |
| Trend direction | Declining | Stable | Review required |
Price Sensitivity Modeling forecasts how customer demand responds to price changes per segment and per plan tier. The Playbook reads historical price points, deal-level discount records, win-loss outcomes, segment metadata, and competitive context to surface the revenue-maximizing price points by segment, identify where the current price is too low or too high, and recommend discount guardrails calibrated to the sensitivity profile rather than the desk default.
Related Ideas
FAQ
Everything you need to know about Price Sensitivity Map.
Price Sensitivity Modeling is an AI-driven forecast of how customer demand responds to price changes per segment and per plan tier. The Playbook reads historical price points, deal-level discount records, win-loss outcomes, segment metadata, and competitive context to surface the revenue-maximizing price points by segment and recommend discount guardrails calibrated to the sensitivity profile rather than the desk default.
The Playbook reads from your billing system (price history, discount events, plan changes), CRM (deal-level discount records, segment metadata, win/loss outcomes, deal complexity), sales ops tools (approval thresholds, discount approval patterns), and market data where applicable (competitor pricing for the segments most exposed to alternatives). At least 24 months of deal-level data with paired pricing and outcome records produces tight confidence intervals.
Competitive pricing analysis looks at what competitors charge and adjusts list price to a market reference. Price Sensitivity Modeling looks at how your own customer base actually responds to price changes and identifies where you can move price without hurting win rate. The two are complementary, but sensitivity modeling is the one that produces concrete revenue lift estimates per segment rather than market positioning intuition.
Yes. For each segment the Playbook recommends specific list price moves, discount guardrails, approval thresholds, and packaging adjustments calibrated to the estimated sensitivity. Each recommendation projects expected ARR and win-rate impact, with the contributing drivers (switching cost, competitive density, deal complexity) attached so pricing leadership can prioritize the highest-impact moves and explain the reasoning to the desk.
Join the enterprises replacing weeks of manual analysis with a single prompt. See what eyko Playbooks can do with your data.
