Insufficient Sales Involvement:

Begin with a hypothetical scenario: "What would be the impact on win rates if we increased prices by 10%, 20%, or 30%?"

Gauge market price elasticity and estimate a potential breakeven point, involving sales leadership early in the process. Frame questions effectively, such as inquiring about potential lost deals at a specific price point.

Empower sales leaders with veto power over price increases if initial results don't align. Caution: Proceed cautiously if sales commitment or openness to data-driven persuasion is lacking.

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Underestimating Willingness-to-Pay (WTP):

Recognize the diversity in customers' willingness to pay and avoid pricing too low for the majority. Focus on pricing close to each customer's true WTP, employing tailored packages or tiers for distinct customer segments.

Undertake needs-based segmentation to identify objectives for each segment (e.g., market penetration, user growth, revenue, or profitability).

Assess customers' alternatives within each segment, emphasizing the critical understanding of WTP compared to competitors and substitutes.

Indicators of misjudged WTP include customers' inability to recall their payment amounts or a disproportionately low percentage of buyers' budgets allocated to your product.

Lack of Data:

Acknowledge that many growth-stage software companies could benefit from increased prices with positive outcomes. Recognize that the primary obstacle in such scenarios is often the absence of sufficient data. Strategies to gather data before implementing price changes:

Conduct surveys, leveraging methods like Van Westendorp and conjoint analysis for insights. MaxDiff surveys are also valuable for understanding the relative value of features versus costs.

Implement real-world testing, ideally in a self-service model, or, with a sales-led approach, cautiously structure A/B tests or temporary pricing changes with subsequent performance reviews.

Initiate continuous data tracking, analyzing pricing, discount bands, win rates, and gross margins by customer segments to accumulate evidence for informed decision-making in the future.