About to decide how much your price should increase? Do it smarter this time.
One to two weeks is all it takes, with the proper support.
No data to settle the argument.
Multiple diverging opinions on what the number should be, and nothing to settle it with.
A few loud voices dominate.
A handful of loud customer complaints fill the discussion with noise.
Months nobody has to spare.
The process takes the scenic route and eats several months you don't have.
A recommendation built from what you already have.
Using AI and two decades of pricing work, we've turned this into a process that runs one to two weeks.
We pull together CSAT and NPS data, win/loss numbers, churn, past price increases, and competitive analysis, and combine it with internal interviews, plus customer interviews if you want them.
Sentiment analysis picks up what's said, and what's left unsaid. We add our own judgment on top and turn it into a recommendation.
Grounded in what you already have: CSAT, NPS, win/loss, churn, past increases, and competitive analysis
Built on internal interviews, and customer interviews if you want them
Sharpened by sentiment analysis and two decades of pricing judgment
Four sources of evidence, read together.
No single number tells the whole story on its own. The recommendation rests on all four, read side by side.
Customer sentiment
CSAT and NPS, plus what customers say, and avoid saying, about price.
Deal outcomes
Win/loss numbers, and what they reveal about price sensitivity.
Retention and history
Churn, and how past price increases actually landed.
Market position
Competitive analysis, benchmarked against where you sit today.
How it works.
It only takes one to two weeks, depending on the customer interviews.
We gather your data
CSAT and NPS, win/loss, churn, past increases, competitive analysis, and more, plus internal interviews.
Sentiment analysis runs
Surfaces what customers are actually saying about price, and what they're avoiding saying.
We recommend adding selected customer interviews
But it's up to you.
We turn it into a recommendation
Our own judgment added on top of the data, resulting in a number and the reasoning behind it.
You get a plan
How to implement the increase, and how to communicate it.
A number, and a plan to act on it.
The result is a recommendation your team can stand behind, tied to your own data and, if you choose, your own customers.
The number and the reasoning
A recommended price increase, backed by the data and the judgment behind it.
The plan
How to implement the increase, and how to communicate it to customers.
Want the details on process and cost?
Get in touch and we'll walk you through it.
Get in touch and let's talk