Decision Analysis
Should I Change My Pricing?
Pricing changes are among the most consequential decisions a business can make. Raise prices too much and you lose customers. Raise too little and you leave money on the table. Incertive models the trade-offs so you can see the probability of each outcome before you change a single price tag.
The Pricing Change Dilemma
You suspect your pricing is wrong. Maybe costs have increased and margins are shrinking. Maybe competitors are charging more for similar offerings and you are undervaluing your product. Maybe you have added significant features since the last price change and the current pricing no longer reflects the value you deliver. Whatever the reason, you are considering changing your prices - and you are nervous about it.
The fear is justified. Price increases trigger customer scrutiny. Some customers will evaluate whether they are getting enough value to justify the new price. Some will look at competitors. Some will churn. The question is how many - and whether the additional revenue per remaining customer outweighs the lost revenue from departing ones. This is fundamentally a question about the probability distribution of customer reactions, which is inherently uncertain.
The typical approach is to look at what competitors charge, pick a number that feels defensible, and hope for the best. More sophisticated teams run surveys or A/B tests. But surveys measure stated preferences (what customers say they would do), which often diverges from revealed preferences (what they actually do). And A/B tests, while valuable, take time and may not capture longer-term churn effects. There is inherent uncertainty in any pricing decision, and the goal is to make the best decision given that uncertainty.
Key Uncertainties in Pricing Decisions
Customer churn response
How many customers will leave? The churn response to a price increase varies by customer segment, price sensitivity, switching costs, and how much value they derive from your product. A 20% price increase might cause 5% churn or 25% churn depending on these factors.
Willingness to pay among new customers
Higher prices can attract or repel new customers. Some markets associate higher prices with higher quality. Others are highly price-sensitive. The new price affects your customer acquisition rate and the types of customers you attract.
Competitive reaction
Competitors may hold prices to capture your departing customers, raise their own prices (validating the market shift), or undercut you aggressively. Each response creates a different market dynamic that affects your outcomes.
Revenue timeline
The immediate impact of a price increase is higher revenue per customer minus churned customers. But the longer-term impact depends on how the new price affects growth rate, expansion revenue, and market positioning. These effects play out over months or years.
Price elasticity of demand
How sensitive is your demand to price changes? Elasticity varies by product category, customer segment, and market conditions. You may have intuitions about this, but the exact relationship between your price change and demand change is uncertain.
How It Works With Incertive
You describe your pricing decision in plain language. For example:
Incertive models the uncertain variables - churn rate, new customer acquisition impact, competitive response - and runs Monte Carlo simulation across thousands of scenarios. The output includes:
Interpreting the Results
The simulation might show that the price increase has an 81% probability of increasing total revenue within 6 months, even accounting for churn. The break-even churn threshold is 25% - meaning you would need to lose more than a quarter of your accounts for the increase to be net negative. Given your estimated churn range of 5% to 15%, the math strongly favors the increase.
But the sensitivity analysis might reveal that the impact on new customer acquisition is the bigger risk factor. If the higher price reduces new sign-ups from 10 per month to 5 per month, the long-term growth trajectory changes significantly - even if existing customer churn is low. This insight shifts your strategy: you might keep the price increase but invest more in marketing and sales to maintain acquisition velocity.
The plan variants might show that grandfathering existing customers while applying the new price to new accounts has a lower short-term revenue impact but avoids churn entirely, resulting in higher total revenue at 18 months. Or that a phased approach - $55 now, $65 in six months - achieves a similar endpoint with lower churn risk at each step. These are strategic options that emerge from probabilistic analysis of the decision.
Frequently Asked Questions
How does Incertive model the impact of a pricing change?
Incertive treats the key variables as uncertain ranges rather than fixed numbers. You specify what you know - current customers, expected churn range if prices increase, potential new customer acquisition at the new price point, and the competitive landscape. The simulation runs thousands of scenarios varying these factors simultaneously to show the probability distribution of revenue outcomes after the change.
Can Incertive help me choose between different pricing models?
Yes. You can model multiple pricing structures - per-seat versus usage-based, tiered versus flat rate, annual versus monthly billing - and compare their probability-weighted revenue outcomes. Each model has different sensitivity to customer behavior, so the best choice depends on your specific mix of customer sizes, usage patterns, and retention characteristics.
What if I do not know how customers will react to a price change?
That is exactly the situation Incertive is designed for. You probably have some intuition about the range - maybe 5% to 20% of customers would leave after a 25% price increase. Incertive works with that range. The analysis shows you the probability of net positive revenue impact across the full spectrum of possible customer reactions, so you can make a decision even without precise data.
How does the analysis handle competitive response to my pricing change?
You can describe competitor pricing as an uncertain variable. If you raise prices, competitors might hold steady, raise their own prices, or undercut you. Each response creates a different market dynamic. Incertive models these scenarios to show how competitive reactions affect your customer retention and acquisition at the new price point.
Can I model a phased pricing change instead of a one-time increase?
Yes. Plan variants allow you to compare a single large increase against phased approaches - for example, two smaller increases six months apart, or grandfathering existing customers while applying new pricing to new sign-ups. Each approach has a different risk profile, and the simulation shows you the trade-offs in terms of revenue trajectory and churn probability.
Know the Revenue Impact Before You Change Prices
Describe your pricing change and see the probability of net positive revenue across thousands of churn and acquisition scenarios. Make pricing decisions with confidence, not anxiety.
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