Overview
01 · Activation
Social Proof
02 · Substrate
Demand IntelligenceCohorts
03 · Engine
EngineSignal AI
04 · Measurement
AttributionPortal & Analytics
06 · Integrations
Integrations overviewCommerce platformsCustomer EngagementCustomer data platformsAd platformsData warehouseCustom & developer
Pricing
Contact
Book a demo
Platform overview  →
Three layers of demand intelligence — API, portal, assistant
01 · Activation
Social Proof  →
Messaging across 8 surfaces
02 · Substrate
Demand Intelligence  →
Live per-product demand model
Cohorts  →
Segments from live behaviour
03 · Engine
Engine  →
Real-time selection pipeline
Signal AI  →
Ask your demand data anything
04 · Measurement
Attribution  →
Incremental orders & revenue
Portal & Analytics  →
Live visibility & reporting
06 · Integrations·Connect Flockr to the rest of your stack
Overview  →
Commerce platforms  →
Customer Engagement  →
Customer data platforms  →
Ad platforms  →
Data warehouse  →
Custom & developer  →
Audiences

Audiences grouped by what they actually do.

Flockr's demand intelligence engine doesn't stop at scoring products. The same signal layer groups visitors into live audiences — defined by behaviour and the demand context they responded to. Audiences no other tool can produce.

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Cohort/Scarcity-responsive shopperLive
Demand-aligned
Scarcity-responsive shopper
2,847
visitors live
↑+14 this hour
Behaviour
Viewed a product 3+ times in last 14 days
Added at least one item to cart
Did not purchase within 4 hours
Signal context
Product showed low-stock signal at engagement
Scarcity message visible at last view
Demand state SCARCITY_RISK active
Live activity
+1visitor #8472 joinedjust now
+1visitor #8463 joined18s ago
−1visitor #8451 exited · purchased33s ago
+1visitor #8447 joined41s ago
~9,200visitors / monthsynced every 60s
Demand-alignedCart-stageBrowse-stageConversionLifecycle
The differentiator

Most segmentation stops at cart abandoned.

Every CDP can tell you who left items in a cart. Flockr tells you why it mattered. Was the product low on stock at the moment of abandonment? Did they see a scarcity message and ignore it? Did they revisit the PDP three times before leaving? That's signal context — and it's what makes a Flockr audience different from a list.

Cohort/Cart abandoner
Behaviour only
Behaviour
Added item to cart in last 14 days
Did not purchase within session
Exited the site
— — —
No signal context
~32,000 / monthundifferentiated
Cohort/Cart abandoner
Behaviour + signal context
Behaviour
Added item to cart in last 14 days
Did not purchase within session
Exited the site
Signal context
Product was low-stock at abandonment
Saw scarcity message — did not act
PDP viewed 3+ times in session
~4,800 / monthall with active urgency
−85%volumebut every visitor with active urgency at the moment they left

Same behaviour. Different audience.

How it works

Audiences that evaluate continuously.

Cohort membership isn't a weekly CSV. Visitors enter and exit as their behaviour and the demand state around them change. The same visitor can move through five cohorts in an hour — here's one of them.

Visitor/#8472/Cohort timelineLive
v
Visitor #8472
Session active·1h 31m·UK·Mobile·3 sessions in 14d
Cohort membership — today
now
Active browser
Scarcity-responsive shopper
Cart abandoner — low stock
First-time purchaser
09:0010:0011:0012:0013:00
Cohort transitions today
09:32·
Session started · landed on /collections/jackets
09:48+Entered Active browser
10:36+Entered Scarcity-responsive shopper· 3rd PDP view with low-stock signal active
10:38+Entered Cart abandoner — low stock· added to cart, exited without purchasing
11:02−Exited Scarcity-responsive and Cart abandoner · returned, completed purchase
11:02+Entered First-time purchaser · same instant
5 cohort transitionsin 90 minutesEvaluation interval:every event, in real time

Membership changes as they do.

Cluster 01 — Demand-aligned

Cohorts only we produce.

Three audiences that require the demand intelligence layer to exist — which means they can't be reproduced by Shopify, Klaviyo, or your data warehouse alone. Flockr customers most often cite these as the reason they bought.

Demand-aligned · 01

Trending-product enthusiast

Visitors engaging with products accelerating in demand right now.

Behaviour
Viewed product 2+ times in last 7 days
Engaged on a momentum-tagged PDP
No purchase yet in current session
Signal context
Product velocity ≥ 3× baseline
Engagement during BUILDING or SURGING state
Demand state SURGING active at view
Typical volume~12,400visitors / month
Typical activation

Lookalike seed for paid acquisition across Meta, Google, and TikTok — high-intent shoppers gravitating toward what's working in market right now.

Demand-aligned · 02

Scarcity-responsive shopper

Visitors engaging with low-stock products before they sell out.

Behaviour
Viewed product 3+ times in last 14 days
Added at least one item to cart
Did not purchase within 4 hours
Signal context
Product showed LOW_STOCK at engagement
Scarcity message visible at last view
Demand state SCARCITY_RISK active
Typical volume~9,200visitors / month
Typical activation

Recovery audience for urgency-led email and SMS flows — visitors who already responded to scarcity once and are most likely to convert on a nudge.

Demand-aligned · 03

Cart-pressure-responsive shopper

Visitors adding to cart in line with active herd behaviour.

Behaviour
Added to cart on a high-cart-pressure product
Engaged with cart pressure messaging
Single-session visitor
Signal context
Product had 6+ active carts at engagement
CART_PRESSURE message visible at view
Demand state HIGH_CART_PRESSURE active
Typical volume~7,000visitors / month
Typical activation

Re-engagement audience with proven herd-following behaviour — high-converting seed for paid social and lookalike modelling.

These cohorts don't exist anywhere else.

Clusters 02 — 05

And every stage in between.

Beyond demand-aligned, the funnel keeps going. Standard audiences your team will recognise — evaluated continuously by the same engine.

Cluster 02 · Cart-stage

Cart abandoner

Added to cart in last 14 days, did not purchase, exited the site. The classic recovery cohort — with live exit when they come back and convert.

Typical volume~32,000/ mo
Cluster 03 · Browse-stage

Deep-session non-converter

Viewed 5+ products in a single session, spent 5+ min deep in the site, no add-to-cart. Engaged but not yet committed.

Typical volume~21,000/ mo
Cluster 04 · Conversion

First-time purchaser

Completed first purchase in last 30 days. Welcome series triggers, post-purchase recommendations, exclusion from acquisition campaigns.

Typical volume~4,800/ mo
Cluster 05 · Lifecycle

Lapsed shopper

Previously purchased, no activity in last 60 days. Reactivation flows, win-back campaigns, lookalike exclusion lists.

Typical volume~14,500/ mo
One example shown per cluster. Fifteen audiences cover the funnel from browse to lifecycle — configurable per client, exportable anywhere.All with continuous evaluation.

Five clusters. The funnel, end to end.

Activation

Audiences go where they're needed.

Every cohort exports to wherever you already activate — ad platforms, CRMs, data warehouses, CDPs, webhooks. Live membership syncs automatically. No CSVs, no batch jobs.

Cohort exporting

Scarcity-responsive shopper

Volume~9,200 / mo
ClusterDemand-aligned
Syncevery 60s
Available in all 6 destinations — live membership, automatic enter / exit on every state change.
Ad platformsMeta·Google·TikTok

Acquisition campaigns · lookalike modelling · exclusion lists.

Customer engagementKlaviyo·Braze·Iterable

Triggered email and SMS flows · cart recovery · lifecycle journeys.

Customer data platformsSegment·mParticle·Rudderstack

Unified profile enrichment · identity stitching · downstream fan-out.

Data warehousesSnowflake·BigQuery·Databricks

Cohort analysis · attribution modelling · reverse-ETL back to activation.

Commerce platformsShopify·BigCommerce·Commercetools

Native customer segments · storefront personalisation · checkout targeting.

Webhooks & APIREST·Webhooks·SDK

Real-time delivery to anything else — in-house tools, custom integrations, agents.

CSV exportsBatch jobsJustlive membershipat the destination.

Available anywhere. Updated continuously.

Attribution

Audiences you can measure.

Cohorts ship with attribution. See which audiences drove what revenue in which channel — not estimated, measured. The same two-group attribution model that powers Flockr's commercial reporting works for every cohort you export.

Attribution/Scarcity-responsive shopperTrailing 30d
Cohort
Scarcity-responsive shopper
Demand-aligned · ~9,200 visitors / mo
Measured on
Meta Ads — retargeting
7,420 reached · 30-day window
Conversion rate lift
+94%
Baseline
1.8%
Cohort
3.5%
Incremental revenue
£28.7k
Cohort orders258
Baseline equivalent133
Incremental · £230 AOV125 orders
Methodology

Two-group attribution model. Primary group: cohort-targeted sessions with a Meta click. Baseline: matched control sessions without cohort exposure. Order numerator is product-scoped — an order only counts when the purchased product matches the targeted moment. Bot sessions excluded from both groups.

→The same model that powers Flockr's commercial reporting. Honest about the difference between correlation and causation.

Not estimates. Measurements.

See it work

See your audience. Live.

30-minute walkthrough. We'll show you the demand-aligned cohorts your catalogue would produce, walk through the export to your stack, and show the attribution working.

Book a demo→
CohortLive
Demand-aligned
Scarcity-responsive shopper
2,847
live
Signal context
Product showed LOW_STOCK at engagement
Scarcity message visible at last view
Demand state SCARCITY_RISK active
~9,200 / moMeta Ads ·+94% lift