RetailNext in Polar: in-store traffic, blended with your DTC.

Foot traffic, visitor counts, dwell time and in-store conversion from RetailNext, pulled into Polar per store and unified with your Shopify online data. See what happens in your physical stores next to online revenue on one omnichannel view, instead of a separate retail dashboard.

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Connect RetailNext See the setup

RetailNext → Polar

What happens in your stores, next to what happens online.

Foot traffic and conversion from RetailNext, online orders and revenue from Shopify, blended by Polar. One omnichannel view, down to the location, refreshed automatically.

Foot Traffic

“How many people walked into each store yesterday?”

Visitor counts and foot traffic per location from RetailNext's TRAFFIC data, broken down by store and refreshed on every sync.

traffic by location

In-Store Conversion

“How much of that traffic actually bought?”

In-store conversion rate, transactions per visitor and average transaction value, so store performance shows up as more than a door count.

conversion rate by store

Dwell & Flow

“When are my stores busy, and for how long?”

Dwell time, peak hours and shopper-flow patterns, so staffing and merchandising decisions run on measured traffic instead of a gut feel.

dwell time & peak hours

Sales per Visitor

“What is each visitor worth in store?”

Sales per visitor tied to traffic, so a busy store and a productive store are finally two different numbers you can compare.

sales per visitor by location

Online vs In-Store

“How does online stack up against the shop floor?”

Store traffic and conversion sit next to Shopify sessions, orders and revenue, so you compare channels on the same page.

in-store vs online, side by side

Omnichannel Context

“What is true omnichannel performance?”

Physical stores join the same blended view as your DTC, so you read total demand across online and offline, not two silos.

store share of total demand

Setup Guide

How to Connect RetailNext to Polar.

A Polar account with Shopify connected, RetailNext account access for the locations you want to bring in, and one connection in Polar. Polar handles the pipeline, so there is no warehouse or SQL to manage.

01 · What you need

A Polar account with Shopify

RetailNext plugs in next to your store data so in-store traffic meets online revenue on one omnichannel view.

Connect your data →

RetailNext account access

You need account access to the RetailNext locations you want to bring in. Polar creates a connection per business, so multiple stores or brands can each have their own.

RetailNext →

One connection

A single connection in Polar with your connector timezone set. No manual exports, no data pipeline, no warehouse required.

02 · Connect it, the easy way

Ask the AI Data Engineer for RetailNext ~1 min

Plain language, no code.

Describe what you need in plain language and Polar's AI Data Engineer reads the RetailNext API, writes the connector and pipes it into your warehouse, in minutes.

See the AI Data Engineer

Add your RetailNext access and timezone ~2 min

Enter your credentials, then set the connector timezone.

Enter your RetailNext account access for the locations you want to bring in. Running several stores or brands? Polar supports a connection per business.

Set the connector timezone so in-store traffic lines up with your store hours and your online reporting. Then Save Configuration.

Best practice: match the connector timezone to the store's local time so peak hours and daily totals compare cleanly against Shopify.

See it in your reports the payoff

Store traffic meets online revenue, blended.

RetailNext flows into your omnichannel view, with foot traffic, in-store conversion and sales per visitor sitting next to Shopify online revenue, and into every Ask Polar answer, right beside your DTC.

Side by side

RetailNext counts the store. Polar counts the whole business.

Visits, dwell time and in-store conversion live in RetailNext, separate from your online orders. Polar reads them next to DTC, so retail and ecommerce finally share one view of demand and of margin.

RetailNext on its ownon its own

RetailNext with Polarblended

In-store traffic sits apart from online demand.

Store visits read next to DTC sessions and orders.

Retail conversion has no online equivalent to compare against.

Store and online conversion on the same timeline.

No shared view of what a location really contributes.

Location performance blended into revenue and margin.

Nothing ties footfall to the marketing spend behind it.

Footfall read against the campaigns running in that market.

Featured Use Case

The omnichannel report that puts stores next to your DTC.

Every week, a rule or an agent lines up in-store traffic and conversion against Shopify online revenue on the same page, so you see how each store and your DTC are pulling before anyone opens RetailNext.

Omnichannel weekly● weekly, every Monday

Channel

Traffic

CVR

Revenue

Online – Shopify

48.2k

2.1%

$164k

Store – Flagship

9.4k

22%

$71k

Store – Mall

6.1k

11%

$22k

Built by an AI agent every week, in-store traffic blended with online revenue.

Scheduled automation

No AI needed

Use Polar Automations to run a rule every week: pull traffic and in-store conversion by location, line it up against Shopify online revenue, and send the omnichannel view to Slack or email.

AI agent

Dynamic

Give an agent the Polar MCP. Ask it to compare each store's traffic and conversion to your DTC, flag the location leaking traffic, and draft the merchandising or staffing call.