Sena captures what buyers paid across the category and the price they say they would move at.
Pricing analytics measures how price and volume moved together, cycle after cycle, so a commercial team can see what its prices are doing. Three properties of internal data bend the result.
The dataset is the business's own transaction history. It records the outcome of decisions the business took and holds zero observations of the ones it declined.
Volume rises during a discount, and the model reads price responsiveness. Some of that volume was pulled forward from the following month, and some came from buyers who would have paid full.
Figures roll up to a national or category-level number. The activity of the group that moved sits inside an average with the group that held.
Sena is the decision AI with access to real-world data. It records what buyers paid across the whole category, including the competing items, and asks those same buyers what they would accept, so the curve covers prices the business has yet to charge.
Receipts cover the rival items too, so a price move reads against where the volume went.
Promotional weeks carry their own flag, so a discount effect separates from a price effect.
Every figure holds its market and its buyer group, so an average opens into the groups behind it.
Pricing analytics is the continuous measurement of what prices are doing: what the business realizes against what it lists, how volume responds when a price moves, and how the mix shifts underneath both. It runs every cycle, off systems, and it feeds every price decision the business takes.
Pricing analytics is the continuous measurement of price performance, run off connected systems. Pricing analysis is the discrete exercise of answering one price question with a method chosen for it.
| Measure | What it returns | Where it goes wrong |
|---|---|---|
| Realized price | What was banked per unit against the list. | Read at period end, so the cause is lost. |
| Elasticity | How volume moved when price moved. | Promotional volume inflates it. |
| Mix | Which items and packs carried the volume. | Moves realization with list price untouched. |
| Price gap | The distance to the competing set. | Built from posted prices, absent the paid ones. |
Retail pricing analytics adds the shelf. The list price, the retailer's price, and the price at the till are three different figures, and the distance between them is the retailer's decision, taken outside the manufacturer's control.
What the retailer charged, outlet by outlet, dated.
What loyalty pricing, multibuys, and coupons took off at the point of sale.
What sat beside the item that week and what it charged.
Four collected inputs carry the measures, applied per market.
| Input | What it answers |
|---|---|
| Receipts | What buyers paid across the category, promotion applied, dated to the day. |
| Store captures | What each item listed for in a real outlet, and what sat beside it. |
| Geo-verified photos | The shelf label and the price beside it, placed and timed. |
| Stated preference | The price buyers accept, so the curve extends past the prices charged. |
The team's own numbers form a separate row. Volume history, price files, promotional calendars, and cost records join through 250+ integrations, so internal measurement and external purchase read in one place.
Three questions sit outside a transaction warehouse, and each one changes what the numbers mean. Internal data records the sale that ended and reports the item that received it. A completed purchase sets a floor on willingness and leaves the ceiling open.
A price performs against whatever sat next to it, and that context lives outside the ledger.
Real people share what they buy and prefer, under explicit consent. Sena captures it directly at the source, so every figure traces back to where it came from whenever a number comes under question.
Category-wide purchase and stated acceptance arrive from the same buyers, and every figure carries the market and the day.
The blended figure opens into the pack movement and the price movement behind it.
Discounted volume splits into buyers whose price moved and buyers who would have paid full.
Category receipts show whether lost volume went to a rival or moved inside the range.
One figure, set from three inputs, showing how much of a pricing question Sena keeps in view at once.
| SKUs | 600 |
|---|---|
| Competitor names | 6 |
| Markets | 18 |
Pricing analytics built only on internal transactions can describe what happened and struggle to say why. Sena builds every figure from real-world signals captured when the question needs it, from the competing item photographed on the shelf through to the receipt showing what a buyer chose instead.
Records what buyers paid across the whole category, so a lost sale arrives with the item that received it.
Reads the shelf label and the items beside it off images captured in real outlets, so a price performs against its actual context.
Signal arrives from the consumer network under explicit consent. Whether a buyer would have paid full price comes from that buyer.
Volume history, price files, promotional calendars, and cost records join over 250+ integrations, so internal measurement meets external purchase.
Every figure holds its market and its capture date, so an elasticity number opens back onto the purchases behind it.
Past price files, promotional calendars, and volume histories, covering every cycle the category has been scanned in.
Four teams read the same measures, and each one needs a different cut of them before they can act.
The measurement. Needs elasticity with promotional volume separated out.
The lever set. Needs mix and price effects split, per market.
Realized price. Needs the gap to list opened one cause at a time.
The shelf read. Needs what sat beside the item the week it sold.
The same measures, read against the price each category actually sets.
Realized price against list, per pack, with the shelf context attached.
Effective price after trade-in and bundling, against the tier below.
Counter price against own-label, with the switching volume traced.
Revenue per subscriber against the advertised tariff, tier by tier.
One mechanism, applied per market and per category. Each step is documented, which is what carries a pricing number through a finance review.
Receipts across the category return what buyers paid for this item and for the ones competing with it, dated.
Sena separates the price effect, the mix effect, and the promotional effect, so a blended figure opens into its causes.
Stated acceptance covers the prices the business has yet to charge, so the curve reaches past its own history.
Most pricing analytics runs on the transaction file, which records every sale the business made and holds zero rows for the sale it lost. Sena covers the category around it.
| Capability area | Typical setup | Sena |
|---|---|---|
| The dataset | The business's own transactions. | Purchases across the whole category. |
| A lost sale | A gap in the volume line. | The item that received it, at the price paid. |
| Elasticity | Fitted to promotional and list weeks together. | Promotional volume separated before fitting. |
| Above the charged range | Extrapolated. | Stated by buyers, with the switching point. |
| Shelf context | Absent. | Photographed in the outlet, with what sat beside it. |
| Aggregation | A national figure. | Resolved per market and per buyer group, with the underlying records held by the provider. |
| Evidence in a review | A reported figure. | Open any number onto the purchases behind it. |
Three situations where the outside half changes the reading.
Split a blended decline into mix, promotion, and price so the cause is named before the response is chosen.
Read category receipts to see whether lost volume moved to a rival or shifted inside the range.
Capture what sat beside the item and what it charged, in the outlets the numbers came from.
Pricing analytics runs the measurement every cycle. The four decisions below are what a revenue team asks once it holds.
Every revenue decision Sena answers, in one place
The discrete exercise
Answers one price question once, drawing on the measurement this page runs every cycle.
Explore pricing analysis 02The single price point
Turns these measurements into the number a line carries.
Explore price optimization 03The four levers together
Coordinates price, pack, promotion, and mix using the figures measured here.
Explore revenue management 04What rivals charge
Supplies the competing prices.
Explore competitive pricing analysisThe walkthrough takes one range in one market, splits a realized price movement into mix, promotion, and price, and traces where the volume went while the team watches.
Tell us the range and the markets, and we will read the curve.