Mouseflow
Mouseflow integration

Mouseflow in Polar: behaviour, read against revenue.

Mouseflow shows you what people did on the site. What it cannot show is what that behaviour was worth, because the order, the cost of goods and the ad spend all live somewhere else. Bring sessions, funnels and experiments into Polar and behaviour is finally read against revenue and contribution margin.

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Behaviour, read against the revenue behind it.

Sessions, funnels, pages and experiments from Mouseflow, joined to the orders that followed, so every drop-off is ranked by the revenue it costs instead of by a percentage.
Funnel by revenue
"Which step costs us most?"
Drop-off ranked by the revenue it costs, not by percentage.
ranked by money
Page performance
"Which pages actually convert?"
Landing pages read against sessions, orders and margin.
revenue per page
Device & market split
"Where does it break?"
Conversion by device, browser and market against the revenue at stake.
device · market
Experiment outcomes
"Did the test make money?"
Test variants read on orders and contribution margin, not just clicks.
margin, not lift
Segment behaviour
"Do repeat customers behave differently?"
Behaviour split by new versus returning, and by cohort.
new vs returning
One P&L
"Analytics lives in a silo."
Behaviour next to channels, spend and margin on one statement.
in the P&L
Setup Guide

How to Connect Mouseflow to Polar.

A Polar account with Shopify connected, access to your Mouseflow account, and Polar's AI Data Engineer, which builds the connector from a plain-language request.
Polar

A Polar account with Shopify

A Polar account with Shopify connected. Mouseflow data only means something read against the orders behind it.

Connect your data →
Mouseflow

Your Mouseflow account

Access to Mouseflow with the site or app you want to read, and its API or export enabled.

Open Mouseflow →

Polar's AI Data Engineer

No native Mouseflow connector yet? Describe what you need in plain language and the AI Data Engineer reads the Mouseflow API, writes the connector and pipes it into your warehouse, in minutes.

1

Ask for the connector ~ minutes

Plain language, no code.
Tell Polar's AI Data Engineer what you want from Mouseflow in plain language. It reads the source documentation, lays out everything the API offers by category, then writes the connector and pipes the data into your warehouse as governed data. No code, and it ships in minutes.
Worth knowing: this also works on connectors you already have. If the Mouseflow API exposes a field, you can have it, down to a single hidden one the standard connector never pulled.
2

Sessions joined to orders automatic

Behaviour, meet revenue.
Polar joins Mouseflow sessions and events to the orders that followed, so a funnel step is measured in revenue and margin rather than in drop-off percentage alone.
3

Prioritise by money the payoff

The leak that costs most.
Pages and steps are ranked by the revenue their gap costs, not by their conversion rate, so CRO work is sequenced by impact instead of by whichever number looks worst.
Get started

Stop optimising for clicks you cannot price.

Bring Mouseflow in and read sessions, funnels and experiments against the orders and the margin behind them.

Side by side

Mouseflow shows the drop-off. Polar shows what it cost.

Mouseflow tells you where people leave, in percentages, on sessions it cannot price. The order, the cost of goods and the ad spend all live elsewhere, so the worst-looking step is not necessarily the expensive one. Polar joins behaviour to revenue and ranks the leaks by money.
Mouseflow

Mouseflow on its ownon its own

Mouseflow+

Mouseflow with Polarblended

Drop-off is a percentage with no value attached.
Each step ranked by the revenue its drop-off costs.
A page with traffic looks successful.
Pages read against the orders and the margin behind them.
A test wins on conversion and may still lose money.
Variants judged on contribution margin, not on lift alone.
Behaviour sits apart from spend and from margin.
Sessions blended with channels, cost and net profit.
The Gap

The connector is only half of it.

Once Mouseflow is modelled against your real orders inside Polar, you can use the result wherever you already work. Ask Polar in plain language, pull it live through the Polar MCP, or schedule it into the report your team reads every morning.
Mouseflow

Mouseflow

sessions, funnels, experiments
Polar

Polar

behaviour tied to revenue

Ask Polar

Polar MCP

Scheduled reports

Featured Use Case

The leak that actually costs money.

The worst conversion rate is rarely the most expensive problem. Polar prices each step, so CRO work is sequenced by impact.
M Funnel, priced Illustrative
Metric
This week
WoW
Net revenue
$482,100
+6%
Orders
3,240
+4%
Blended CAC
$38
-9%
New vs repeat
42 / 58
-3pts
Email revenue
$71,400
+12%
Each step with the revenue its drop-off costs. Illustrative figures.

Ranked by revenue

Priced

A step losing 60 percent of low-intent traffic matters less than one losing 8 percent of buyers. Polar ranks the leaks by what they cost.

Tested on margin

No SQL

A variant can lift conversion and lose money if it sells the wrong mix. The margin behind the test decides whether it shipped.

Your Prompt Library

15 prompts a connected Mouseflow unlocks.

Funnels ranked by revenue, pages that leak, device gaps and experiments judged on margin.
Type
Audience
15 of 15
Get started · connect once · behaviour on revenue

Mouseflow showed you the drop-off. Polar shows you what it cost.

Bring sessions, funnels and experiments into Polar and rank every leak by the revenue behind it.

Phase 1 ~5 minConnect your data in PolarConnect Shopify and your stack. Polar's semantic layer turns it into governed metrics, then wait for the first sync.
Phase 2 ~ minutesBring Mouseflow inDescribe what you need in plain language; the AI Data Engineer writes the connector and pipes it into your warehouse.
Phase 3 the payoffPrioritise by revenueFunnels, pages and tests ranked by money rather than by percentage.