Segments that predict, not just filter.
Five AI attribute families score every profile in real time — churn risk, RFM, lead fit, next best action, and more.
Free forever · Scale with usage
5
AI attribute families
<5s
Segment recalculation
SOC 2
Type II · GDPR ready
Audiences built on what's about to happen, not what already did
AI attributes that compute themselves
Research, qualification, churn likelihood, RFM, and next best action — scored on every profile, automatically, in real time.
Predictive segments, not static lists
Find the right people before you ask. Segments react to AI predictions and update the moment behavior changes.
One segment. Every channel.
Build once. Use across journeys, experiments, personalization, recommendations, and ad audiences. Always in sync.
Five AI scores. Already on every profile.
- Research attributesFirmographics, technographics, hiring signals, and intent enriched automatically on every account and user.
- Qualification and likelihood scoresLead fit, churn risk, purchase probability, and upgrade likelihood computed continuously from live behavior.
- RFM and next best actionCustomers bucketed into Champions, Loyal, At-Risk automatically; every profile carries a recommended next action.
Profile Attribute Types
AI-COMPUTED
Research
Firmographic & technographic enrichment
Qualify
Lead scoring on fit & intent
Likelihood
Churn, purchase, upgrade predictions
Next Best Action
Recommended action per user
RFM
Recency, frequency, monetary ranking
MANUAL
Know who's at risk before they leave.
- RFM segmentation, automaticSix buckets (Champions, Regulars, Promising, New, Needs Attention, At Risk) refresh as purchase behavior changes.
- Behavior and AI in one ruleCombine real-time events (visited pricing) with AI scores (likelihood > 70) in a single segment definition.
- Distribution and quality viewsEvery attribute shows bucket distribution, 14-day trend, and statistical depth so you can trust what you're targeting.
Ask BluUser base showing healthy engagement signals
Active user base of 12,400 with 23% showing high intent signals. Top segment is Enterprise users with 4.2x higher session frequency. 148 users flagged with declining activity.
Parker Mcconnell
Sliceline
Data Analyst
55 emp · $35k
Keller Madden
Endframe
Software Engineer
42 emp · $45k
Samantha Miller
Tres Commas
Content Marketing Manager
185 emp · $62k
Lisa Anderson
Endframe
Marketing Specialist
42 emp · $55k
Stella White
Pied Piper
UX Designer
85 emp · $95k
Sarah Chen
Aviato
Product Designer
95 emp · $78k
Robert Brown
Sliceline
AI Research Scientist
55 emp · $195k
Michelle White
Hooli
UI/UX Designer
250 emp · $135k
Robertson Madden
Hooli
Senior Product Manager
250 emp · $185k
Kevin Martinez
DataVault Inc
Data Scientist
350 emp · $280k
Build the segment once. Use it everywhere.
- Journey activationAny segment becomes a journey entry condition; high-churn users enter win-back flows automatically.
- Experiments, personalization, recommendationsRun A/B tests on specific segments; show different web experiences per audience; serve next best product per user.
- Ad audience syncSync to Meta and Google automatically; membership stays in lockstep with live behavior, no manual uploads.
| Name ↓ | Object | AI Type | Data type | Status | Description | |
|---|---|---|---|---|---|---|
| About Brand | Brand | – | T Text | Visible | Brand description | |
| Account lifecycle | Account | – | T Text | Visible | Account lifecycle stage | |
| Active days | User | – | # Number | Visible | Number of active days | |
| All day | Meeting | – | ⊙ Boolean | Visible | Is meeting all day | |
| Amount | Deal | – | # Number | Visible | Deal amount | |
| Assignee | Task | – | T Text | Visible | Task assignee | |
| Audience | Brand | – | T Text | Visible | Target audience |
Likelihood buckets
Analyze each likelihood bucket within a data table breakdown
Very High
Highly likely to convert
High
Strong conversion potential
Medium
Moderate conversion chance
Low
Below average likelihood
Very Low
Unlikely to convert
Ask Blu to build any segment
Describe the audience in plain English. Blu turns it into a live segment using AI attributes and events you already have.
Setup in minutes
From raw events to live predictive segments
DATA SOURCES
Connect warehouse
Snowflake · BigQuery
Stream site events
page_view · signup · purchase
Profiles populated
12,438 users · 2,104 accounts
Identity stitched
Anonymous → known
01
Connect and ingest
Stream events from your site, app, and warehouse. Profiles populate in minutes — no schema project, no migration.
LIVE ON PROFILE
Churn likelihood
Recomputed · live
Lead fit score
Recomputed · live
RFM bucket
Recomputed · live
Purchase prob.
Recomputed · live
02
AI attributes appear on every profile
Research, qualification, likelihood, RFM, and next best action scores compute automatically and update as behavior changes.
CHANNELS
Journey · Win-back
Triggered · 1,284 users
Experiment · Variant B
Cohort targeted · 720
Personalize · Hero
Swap rendered · 2.4k
Meta audience
Synced · 1,284 profiles
03
Activate everywhere, instantly
Use any segment in journeys, experiments, personalizations, and ad audiences. Membership stays live across every channel.
Your data sources, all feeding the same intelligence
Every event from every source sharpens the AI attributes on every profile.
Segments built on consented data. Privacy controls baked in, not bolted on.
Unlimited segments. Starting at $0.
No per-segment fees. AI attributes on every plan. One platform replaces your CDP, scoring model, and activation layer.
What most teams stitch together
- CDP for profile data — separate billing
- ML scoring model — needs a data scientist to build and maintain
- Activation tool — export segment, import elsewhere, wait for sync
- Ad audience management — manual CSV uploads, always stale
4 tools, stale scores, slow activation
What you get with AI Segmentation
- Five AI attribute families on every profile — live, automatic
- RFM segmentation with 6 auto-buckets — no spreadsheet
- Visual rule builder — AI scores + events + attributes in one segment
- Real-time recalculation — under 5 seconds on any behavior change
- Activates across journeys, experiments, personalization, and ads
- No per-segment fees, no caps
Real results, not just tech
We drive measurable outcomes in the first 90 days. Beyond the platform.
“We were losing visitors before they signed up. Intempt's personalized experiences changed that - we started meeting people where they were instead of guessing. Once they're in, Intempt's automated email takes over and keeps the relationship moving. Acquisition and retention finally feel like one connected motion instead of two separate problems.”
Jim Stromberg, CEO
StockInvest
Case Study
StockInvest needed to turn anonymous traffic into registered users before any retention strategy could work. With Intempt's Experiences, they personalized the anonymous visitor flow, surfacing the right content and CTAs to boost signup conversion. Once users signed up, automated Journeys nurtured them through onboarding and deeper engagement, steadily increasing lifetime value.
Questions we actually get asked
HubSpot and Klaviyo segment on static properties and basic engagement metrics. Intempt segments on AI-computed attributes — churn likelihood, qualification score, next best action, RFM stage — combined with real-time behavioral events. Segments update continuously and activate directly across journeys, experiments, and personalizations in the same platform. No export, no sync.
AI attributes are fields on user and account profiles computed automatically. Research attributes pull firmographic and technographic data. Qualification attributes score leads on fit and intent. Likelihood attributes predict outcomes like churn or purchase. RFM attributes rank customers by value. Next Best Action attributes recommend what to do with each user. All update in real time.
Yes. A single segment can mix AI-computed fields (churn score > 70%), behavioral events (visited pricing page in last 7 days), manual attributes (plan = Pro), and user properties (country = US) — all in one visual rule.
Yes. Segments recalculate as users act. A user who triggers an event or whose AI score crosses a threshold enters or exits the segment immediately — under 5 seconds. No nightly batch. No manual refresh.
Yes. Every segment is available as a targeting condition across all activation tools. Build once, use everywhere. The same segment can trigger a journey, target an experiment, personalize a web experience, and filter a recommendation widget simultaneously.
Intempt automatically groups customers into RFM segments — Champions, Loyal, At-Risk, Hibernating, Lost — based on recency, frequency, and monetary value of purchases. Segments update as behavior changes. No manual spreadsheet analysis required.
Connect your sources and the first behavioral and AI-computed attributes appear in under an hour. Predictive models like churn and likelihood reach stable accuracy after 7–14 days of event data, depending on volume.
No. Segments are built in a visual rule builder using AI attributes, events, and properties. Marketers and product managers ship segments directly. Analysts can layer in custom SQL when needed.
Yes. Segments work across identified users, accounts, and anonymous sessions. When anonymous visitors identify, their full event history merges into the user profile and their segment membership recalculates automatically with full history.
AI Segmentation is included in every Intempt plan, including Pro. There are no per-segment fees and no caps on the number of segments you can build or activate.
Stop filtering lists. Start predicting them.
Connect your sources today. AI attributes and live predictive segments running before your next campaign.