Sena measures who bought, who left, and for what in every market.
Product analytics measures how a product performs and routes the numbers to the team building it. Three patterns leave the market half of that question open.
Events, funnels, sessions, and retention curves all require someone to have opened the product. The population is everyone who arrived, and the product decision depends on everyone who did something else.
An event stream records what happened and the order it happened in. Why a person left, and what they moved to, are facts held by that person.
Adoption and retention report as totals, sometimes split by region. The attribute deciding purchase differs enough between markets to change which product wins there.
Sena is the decision AI with access to real-world data. It records what buyers across the category took home, what they moved to, and the attribute they state decided it, so product performance reads against the market it sells into.
Dated purchase covers the product and every rival inside the category boundary, per market.
Buyers who moved away name the product they moved to and the reason.
Captures record presence and facing for the product across outlets, dated to the day.
Product analytics measures how a product performs and feeds the measurement back into what gets built. The measurement splits into two halves that use entirely different evidence, and most platforms serve the first.
Product analytics assembles what an organization knows about a product's performance into a picture it can act on: who takes it up, who stays, what they do with it, and what it earns. The two halves below answer separate questions, and a product decision usually needs both.
The in-product half covers everything after a person arrives, and it is where the established practice sits. These four are served by application analytics platforms, and they belong there.
What people do inside the product, in the order they do it.
Where people progress and where they drop out.
Who returns, over what period, grouped by when they arrived.
Which parts of the product get used, and by whom.
The market half covers everything before a person arrives and everything after they leave, and it answers one question: how the product performed in the market it sells into. This half is what Sena observes, because a person buying the category can report what they took, what they left, and why.
Who bought it, per market, dated, against the category moving alongside.
Who moved away, what they moved to, and the reason they gave.
Which outlets carried it, and the weeks it ran absent.
Which attribute buyers state settled the choice, ranked per market.
Four collected inputs build the market half, applied per market.
| Input | What it answers |
|---|---|
| Receipts | Who bought the product and the rivals, dated, so uptake reads against the category. |
| Stated preference | What a leaver moved to, and the attribute that settled it. |
| Store captures | Which outlets carried the product on the day, and which had sold through. |
| Geo-verified photos | The outlet photographed as found, with the market and capture day recorded. |
The team's own numbers form a separate row. Event streams, subscription records, sales data, and support history join through 250+ integrations, so the in-product half and the market half read together.
Four questions sit outside an event stream, and each one changes a product decision. Buyers who considered the product and chose something else generate zero events, and they are the growth. The stream records the exit, and the destination sits with the person.
Flat uptake in a growing category and flat uptake in a flat category argue differently. And the deciding attribute gets settled before the first event fires.
Sena reads the market half, and the in-product half is a separate measurement. Event capture, funnel and activation measurement, retention and cohort curves, feature adoption, and session replay belong to the application analytics platforms built for them. Sena installs zero code and captures zero events. Sena adds the observation those platforms leave open: who bought across the category, who left and for what, and which attribute decided it, per market. The two sit beside each other in a product review.
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.
Consented purchase and stated preference arrive from category buyers, and every figure carries the market and the day.
Purchase for the product reads against how the category moved in the same market and weeks.
Buyers who moved away state what they moved to and why, so a drop becomes an explanation.
Captures record which outlets carried it, so availability separates from preference.
A performance figure carries weight only as far as the population behind it. Sena builds every figure on this page from real-world signal captured when the question needs it, from a receipt in the category through to the reason a buyer gives for leaving.
Records dated purchase across the product and every rival in the category, so uptake reads against the market alongside.
Reads which outlets carried the product off images captured in real stores, dating presence and absence to the day.
Signal arrives from the consumer network under explicit consent. What a leaver moved to comes from that leaver.
Event streams, subscription records, sales data, and support history join over 250+ integrations, so both halves of the picture read together.
Every figure holds its market and its capture date, so a performance claim opens back onto the receipt behind it.
Sena sets past performance exports, pricing records, and churn archives beside the market they came from, covering every period the product has sold in.
Four teams read the same market half, and each one needs a different cut of it before they can act.
The roadmap. Needs the reason leavers gave, beside the in-product drop-off.
The claim. Needs the attribute deciding purchase in that market.
The number. Needs uptake read against the category moving alongside.
The picture. Needs the market half to join the event stream.
The same market half, read in whatever each category actually records at the till.
Purchase and repeat per market, against the category, with outlet presence beside it.
Which specification the market took up, and what leavers moved to.
Which pack sizes moved at the counter, and the weeks each ran absent.
Plan uptake against the category, and the handset lines buyers moved to.
One mechanism, applied per market and per category. Each step is documented, which is what carries a performance claim through a product review.
Real contributors across the markets named share dated purchase for the category under explicit consent, and state what they moved to when they moved.
Sena sets the purchase for the product against the category moving alongside in the same market and weeks.
Outlet presence and the ranked deciding attribute separate an availability problem from a preference problem.
Most product analytics measures the population that arrived, which is precise about what people do inside the product and silent about the market around it. Sena measures the market.
| Capability area | Typical setup | Sena |
|---|---|---|
| Who gets measured | Everyone who opened the product. | Everyone buying the category, per market. |
| What performance means | Activation, retention, and feature adoption. | Uptake against the category and why buyers left. |
| Why a number moved | Inferred from the sequence of events. | Stated by the buyer who moved. |
| The comparison | This product against its own past. | This product against the category alongside. |
| Availability | Outside the frame. | Recorded per outlet, photographed, and dated. |
| Market resolution | A total, sometimes split by region. | A read per market, since the answer differs. |
| Evidence in a review | A reported figure. | Open any figure onto the receipts underneath. |
Three situations where the market half explains a number the event stream reports and leaves uncaused.
Read purchase for the product against how the category moved in the same market and weeks before treating a level figure as one story.
Reach buyers who moved away, record the product they moved to, and rank the attribute that decided it.
Set outlet presence beside the performance figure, so weeks out of stock read apart from weeks of weak demand.
Performance closes one loop and opens the next. The four decisions below are what a product team asks around it.
Every product decision Sena answers, in one place
What the market wanted
Ranks the attribute buyers state decided the choice before the product shipped.
Explore voice of the customer 02The product they left for
Reads the alternative a leaver moved to, attribute by attribute.
Explore competitive product analysis 03The line's place in the range
Takes the performance read up to the whole range and the decision to hold or cut.
Explore product portfolio management 04Set against its rivals
Compares the product against everything sharing its shelf, on pack and price.
Explore product benchmarkingThe walkthrough takes one product in one market, reads its purchase against the category over a period, and opens what leavers moved to while the team watches.
Tell us the product and the market, and we will read it against the category.