Kapnova first backtests decisions you have already made to learn how your business responds. From there, it continuously finds, models and scores the next revenue and profit opportunities alongside your team.
We scope every engagement to target 5–10x the value of what you spend with us.
We scope the engagement around outcomes, not deliverables. Every decision Kapnova models carries an expected financial impact, and we measure what actually happens.
5–10x is the return we scope against, not a promise.
Start with a decision, not a data project. Kapnova shows what your data can answer today, proves the model against outcomes you already know, then keeps finding what to do next.
Read-only access to the systems you already run. Kapnova states what your data can answer today, what is missing, and what that gap costs you. Sentiment, competitor and category signal we bring ourselves.
One engine across the three lines Kapnova works on. Each question fails for a specific reason, and each one has a specific thing you get back.
Price history alone misses how customers react to the increase.
Kapnova models both the direct price effect and the resulting change in demand to find where the increase actually holds.
Last year’s calendar does not reflect today’s demand.
Kapnova combines current category demand, competitor activity and customer signals to model the best timing, price and product.
Reported ROAS often rewards channels that convert customers who were already coming.
Kapnova separates incremental demand from demand that would have happened anyway.
Competitive openings can disappear before quarterly reporting catches them.
Kapnova identifies the size of the opportunity, how long it may last and whether your brand is positioned to capture it.
A promotion can look great during the week it runs while hurting full-price sales later.
Kapnova measures both effects together to find the cadence and discount depth that maximize gross profit.
Repeated promotions can reset what customers expect to pay.
Kapnova measures how quickly that happens and finds the promotion schedule that protects annual margin.
Buying too much creates markdowns. Buying too little creates stockouts.
Kapnova models both sides to recommend the quantity and timing that maximize margin.
The highest-revenue products and channels are not always the most profitable.
Kapnova brings together returns, freight, discounts and trade spend to show where gross profit is really coming from.
Every channel can look productive in its own reporting.
Kapnova separates incremental from non-incremental spend so you know what can be cut and how much revenue is actually at risk.
Average ROAS does not tell you where the next dollar should go.
Kapnova models marginal return by channel and shows where additional spend is still productive.
Your best customers are often the most likely to join, which can make the program look better than it is.
Kapnova separates selection from true incremental lift.
The biggest variance is not always the real cause.
Kapnova identifies what actually drove the miss and which levers are most likely to close the gap at the lowest cost.
Just not for the part that finds the opportunity before you ask. Four line items, funded separately, that do not talk to each other.
Kapnova finds the opportunity, models what it is worth, helps you decide, and traces the outcome back to the call. Priced against the decisions it moves rather than against the hours it replaces.
Start with a backtest on your own data. Because you already know what happened, you can judge Kapnova’s answer before trusting the next one. Or start with just your URL and see what we can find from public data alone.
Kapnova never executes decisions for you. Every answer shows the data, method and assumptions behind it, and when the evidence is not strong enough, we say so.
Access is to your own accounts, revocable at any time. Your data stays in your tenant and never trains another client’s model.
Start with your URL and Kapnova will surface what it can find from public data alone. Then connect your own data to measure what past decisions actually caused and where the next revenue or profit opportunity may be.