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Solutions · Retail & E-commerce

The same shopper should not be three anonymous records one golden profile.

Retail signals scatter across web, app, and store — so one person shows up as a browser, an order, and a loyalty card that never meet. Sfere stitches them into one golden profile you own, then helps you recover sales, reward loyalty, and spend ad budget on the right people, post-cookie.

Playable · the root cause, fixed live

Scan a receipt. Watch three records become one shopper.

A working simulation of Sfere's resolution engine. Press Scan — or tap the ticket itself. The first scan stitches three scattered records into one golden profile; every scan after that enriches it — recognition without duplicates, replenishment rhythm, cart recovery, and post-conversion suppression.

RESOLUTION ENGINE · SIMULATION — DEMO DATA SCAN 0 / 4

Scattered signals · unresolved

WEB SESSION #c4f2 ANONYMOUS
APP ORDER #9021 ANONYMOUS
LOYALTY CARD #7731 ANONYMOUS

One shopper. Three systems, three partial views — until a scan ties them together.

Scan bay

Resolved profile

?

No golden record yet

scan a signal to resolve

GOLDEN RECORD
CHANNELS LINKED
awaiting signal
LAST SIGNAL
awaiting signal
REPURCHASE RHYTHM
awaiting signal
CART SIGNAL
awaiting signal
ACQUISITION ADS · ACTIVE spending

> engine ready · 3 unresolved signals detected

Identity resolution

Stitch the shopper across every touch

The unresolved shopper is the root cause of wasted spend, weak personalization, and loyalty that forgets people. Sfere fixes it at the data layer.

One shopper, not three records

Stitch online browsing, app activity, and in-store purchases into a single golden profile, so the same person stops appearing as three anonymous shoppers.

Web session to till receipt

Connect a web session to a store purchase to a loyalty scan, so online and offline behavior finally meet in one record.

First-party audiences, post-cookie

Build durable, owned audiences from your own data instead of renting reach through third-party cookies you are about to lose.

Personalize from the first visit

Adapt offers and recommendations in real time for known and anonymous shoppers alike, before they have logged in.

Loyalty on data you own (Preview)

Base tiers, points, and rewards on the resolved profile, with richer gamified loyalty experiences in Preview.

Stop paying to reach buyers

Suppress people who just purchased and build lookalikes of your best shoppers, so paid media stops wasting spend.

The cart recovery use case

Recover the sale, then stop paying to reach the buyer again

An abandoned basket is only recoverable if you can recognize the shopper behind it, and a converted shopper is only profitable if you stop buying ads to reach them again. Both depend on one resolved profile spanning browse, cart, purchase, and store — so recovery and suppression run off the same source of truth.

See how activation works
  1. ABANDON

    A basket is left behind — in the web shop or in the app.

  2. RECOGNIZE

    Recognize the abandoned cart against the resolved profile, not just a browser or an email address.

  3. RECOVER

    Recover the sale with a reminder enriched by what that shopper has bought and browsed before.

  4. REACH

    Reach them on WhatsApp, email, or push from one profile, the moment the signal fires.

  5. CONVERT

    The shopper checks out — the same profile closes the loop.

  6. SUPPRESS

    Suppress that shopper from acquisition ads once they convert, so budget goes to net-new demand.

    SUPPRESSION ON

The replenishment use case

Reach the shopper when the product runs low, not on a blanket send

For pharmacy, grocery, and health-and-beauty retail, much of the basket is consumable and repurchased on a rhythm. When online and in-store purchases resolve to one profile, replenishment becomes a prompt timed to each shopper rather than a mass email — and it works whether the last purchase happened at a till or in the app.

See how identity works

REPURCHASE RHYTHM · ONE SHOPPER · 40 DAYS

Learned from real purchase history — the till and the app agree on one rhythm.

Rhythm chart: this shopper buys the same consumable again roughly every twelve days — day 0 in store, day 12 in the app, day 24 in store. A reminder window opens around day 33, when the product is likely running low, instead of a blanket send on day 15 that ignores the shopper's rhythm.

  • Learn each shopper's repurchase rhythm from real purchase history, in store and online.
  • Time the reminder or offer to the moment a consumable is likely running low, not to a blanket send.
  • Recognize the same person whether the last purchase was a store visit or an app checkout.

The retail media use case

Your shopper data is inventory, when you can prove it

Retail media only works if the audience is real and the outcome is measurable. Because shopper profiles are resolved, consented, and owned, you can offer vendor brands addressable segments and report exposure to outcome — the same proof loop our sports vertical gives sponsors.

See how measurement works
01

Consented segments

Package consented shopper segments as addressable audiences vendor brands can buy.

02

Vendor campaigns

Vendor brands activate those audiences against real, resolved shoppers.

03

Verified reach

Reach is verified against resolved profiles, not modeled panels.

04

Outcome report

Prove vendor campaigns with verified reach and outcomes on the same graph that ran them.

Know every shopper, personalize every journey

See how Sfere stitches shoppers across online and offline, recovers carts, and rewards loyalty from data you own. Book a walkthrough across your online and offline data.