A price change is one of the most impactful commercial levers leaders have. Move a price and the effect lands everywhere, fast, impacting demand, competitive position, and media performance.
Most teams answer their pricing questions with a tool built only for pricing. While simple models, historical data, and surveys can help you see price changes, none of them can tell you what your media plan did — or didn’t — do while the price moved.
To achieve Commercial Intelligence, decision makers need pricing optimization built into their measurement solution instead of running alongside it. That shift changes elasticity from a fixed number to something you can plan against and influence.
Why Price Is Hard to Isolate
The stakes make price a challenge worth addressing. A 1% price increase can lift EBITDA margin by more than 22% and share price by 25%.
But what happens if your competitor responds with a price cut? Or brand sentiment sinks? Or category headwinds increase at this most inopportune of times? It’s a moving target, and traditional methods that lean on historical data, simple models, or one-off surveys can’t keep pace with a dynamic market.
Measure price on its own and you get a number that looks precise and behaves unpredictably, because the conditions that produced it aren’t factored in.
Elasticity Is Not Fixed
Elasticity usually gets treated as a property of the category that’s inherited and rigid, but the evidence says otherwise.
ROI Genome® data shows a $1 billion brand taking a 10% price increase loses about 10% of sales without advertising support, and about 7% with it. On a single pricing action, that gap is roughly $33 million in opportunity.
The same price move produced two different outcomes, and the only variable was what the media plan was doing at the time. That relationship stays invisible to any method that measures price on its own, which is why Analytic Partners recommends analyzing and optimizing campaigns around any planned pricing action. That’s also why sustained advertising investment lowers elasticity over time. That means a brand people know and trust can raise price and keep more of its volume, which is one of the most valuable things brand building buys. That effect is covered in Three Things You Should Know About Brands and Pricing.
How Pricing Gaps Show Up Across Functions
Pricing questions surface differently depending on where you sit, though each version is the same gap in a different form.
Finance can’t maximize profitability through pricing changes without seeing elasticity, margin impact, and market dynamics together. Planning around a price move usually starts with a volume estimate, which most finance teams already have. What they lack is the media running behind the move, the competitive response to it, and the channel shift that follows: raise price in your own stores and more shoppers buy from your retail partners.
Marketing knows price is one of the 4Ps, alongside product, place, and promotion, so it needs to ensure price is part of how it views media impact and brand performance.
Analytics often models price in isolation. Whether through elasticity testing or conjoint analysis, these methods measure price in a vacuum. This makes forecasts wrong, impacts hard to measure, and cross-functional decisions harder to support. The team spends its time reconciling sources instead of answering the question.
None of that can be solved by a tool that only looks at price. Closing the gap means measuring price against everything that moves with it, starting with the factors that shape how buyers respond.
The Four Forces Behind a Price Move
Commercial Analytics analyzes pricing against four factors: customer behavior, market trends, competitive dynamics, and external factors. Together they show how buyers respond at different price points, whether competitors follow a move and how fast, and what input costs and economic conditions are doing underneath the decision.
Analytic Partners treats this as pricing intelligence rather than price. What you charge only matters relative to the market and across your portfolio, so a model must carry pricing gaps alongside pricing effects when it works out elasticities. If it can’t trace how one product’s price move ripples through the rest of your line, it won’t hold up in planning.
Pricing Optimization Inside Commercial Analytics
Roughly 60% of growth lives beyond the media plan in commercial levers like pricing, timing, and distribution, alongside external forces. With marketing mix modeling methodology at its core, Commercial Analytics shows the full commercial picture, so a pricing read is connected to everything that influences it. In GPS Enterprise® (GPS-E), Analytic Partners’ Commercial Analytics platform, pricing is modeled alongside media, promotions, and external factors, all in the same model. Built into GPS-E is ROI Genome, an embedded intelligence layer that supplies the cross-industry context that makes that read credible from day one.
Pricing decisions are also hard to reverse, which is where the forward-looking half of the platform comes in. PROPHET, the decisioning layer inside GPS-E, supports scenario planning and forecasting, so you can simulate a price move against the rest of the plan and take the forecast into the business case for it. For example, one premier jeweler modeled planned price increases, rising material costs, and four levels of proposed budget cuts together. The analysis arrived in three weeks and provided the insights Finance needed to back a marketing budget increase, despite the fact their initial plan called for a cut.
The same integration shows up in the numbers. A global financial services organization used Commercial Analytics to weigh new-customer acquisition against retention, and short-term activity against long-term brand building, working through questions like what advertising spend is required to offset competitive pricing. The adaptive decisioning that followed delivered +$75 million in incremental value for the same spending. Pricing and acquisition were weighed against each other rather than in sequence, which only works when both sit in the same model.
It also gives a team a strategy it can hold under pressure. One leading children’s apparel retailer set out to stop depending on markdowns:
“We took a risk and decided to say, ‘As a company, as a brand, we want to be able to provide our customers with great price, great quality of product, but not be so reliant that the only way that our customers shop us is if it is on sale.’ And it actually has proven that if we are more methodical about our pricing strategy; if we offer our customers the right products, that they will still shop us.”
— Vice President, Demand Generation, leading children’s apparel retailer
A price change is a commercial decision, and it deserves the same measurement as every other commercial decision you make. Commercial Analytics and GPS-E read price, media, and promotion together, so the number you act on reflects the conditions that produced it.
Related reading:
- Three Things You Should Know About Brands and Pricing
- Tariff Defense: Navigating Tariff Shocks with Commercial Analytics
- Unlock Growth with Analytic Partners ROI Genome® Insights
