AI Segmentation · Built into every profile

Segments that know what comes next

Research AI, Qualification AI, Likelihood AI, RFM AI, Next Best Action AI. Five models that compute attributes, score leads, predict outcomes, and update audiences in real time — no exports, no batch jobs.

AI attributes that compute themselves.

Define once. Update continuously. Churn risk, qualification score, RFM stage, and next best action recalculate from live behavior — no cron jobs, no manual exports.

AI-computed attributes updating in real time on customer profiles in Intempt

Data Analyst

Five AI models. One profile. Every score, always current.

AI Research Attributes pull firmographic and intent data

Blu's research agent enriches any user or account with company size, funding stage, tech stack, hiring signals, and intent data — so every profile is sales-ready before the first touch.

AI Qualification Attributes score every lead automatically

Fit and intent are scored continuously from behavioral and firmographic signals. The score updates the moment the lead acts — pricing page visit, demo request, feature adoption.

AI Likelihood Attributes predict outcomes from behavior

Churn risk, purchase probability, and upgrade likelihood are computed from event patterns. Journeys trigger before the customer decides to leave — not after.

RFM Attributes group customers by value tier

Champions, Loyal, At-Risk, Hibernating, Lost — each bucket updates as purchase behavior changes. Distribution tracked over time. No spreadsheet required.

Next Best Action attributes surface what to do next

Blu recommends the highest-value next step for each user: upgrade prompt, win-back flow, cross-sell offer, or rep follow-up — based on current profile state.

Teams that switch from static scoring to AI attributes see journey trigger accuracy improve within the first week — because scores reflect what customers did today, not last month.

Predictive segments, not static lists.

Traditional segmentation filters on what already happened. Intempt segments on what's about to happen — combining real-time events with AI-computed attributes in a single rule.

Predictive audience segments with RFM buckets and behavioral filters in Intempt

Data Analyst

Segments that find the right people before you ask.

RFM segmentation updates as purchase behavior changes

Six buckets — Champions, Regulars, Promising, New Customers, Needs Attention, At Risk — recalculate automatically. Distribution of customers across buckets is tracked over time.

Next Best Product prediction lives on the profile

Works across any product type: ecommerce catalog, SaaS plans, add-ons, subscriptions. The prediction is a profile attribute, not just a recommendation widget — so it's usable in any segment rule.

Combine AI attributes with behavioral events in one rule

A single segment can mix AI-computed fields (churn score > 70), behavioral events (visited pricing in last 7 days), manual properties (plan = Pro), and user data (country = US). No export step.

Statistical depth on every attribute

Each attribute shows bucketing distribution over time, 14-day trend lines, and statistical depth — P50, P25, P75, min, max, mean. Segments built on facts, not guesses.

RFM segments that update in real time let lifecycle teams react to tier movement the same day it happens — win-back flows trigger when a Champion drops to At-Risk, not in the next batch run.

Segments that activate everywhere.

Build once. Use across journeys, experiments, personalizations, and recommendations. Every segment is a live audience connected to every activation layer — no syncing, no re-importing.

Segment activation across journeys, experiments, and personalizations in Intempt

Data Analyst

One segment definition. Every activation channel.

Journey entry conditions use any segment

High churn-risk users enter win-back journeys automatically. High-fit leads route to sales. New Champions get a VIP reward flow. Segment membership controls the entire entry condition.

A/B tests target specific segments

Run experiments only for high-fit users, returning visitors, or Pro plan subscribers. Results are measured per segment — so you know whether the test worked for the audience you care about.

Web and in-app personalizations read segment membership

Show different homepage heroes, pricing CTAs, and product grids based on who is viewing. Same URL, different experience per audience — driven by the same segment definition.

Recommendation feeds filter by segment

Collaborative filtering, next best product, and popularity models all accept segment filters. Champions see upsell recommendations. At-Risk users see retention-focused content.

Teams that connect segments to journeys and experiments stop rebuilding audiences in every tool. One segment definition drives the journey trigger, the experiment target, and the personalization — simultaneously.

How AI Segmentation Works

From raw behavior to predictive audiences that activate in four steps.

Every profile gets an AI score automatically

As users act, Blu computes qualification scores, churn likelihood, RFM tier, and next best action on every profile. No manual setup per user — scores appear as soon as events come in and update as behavior changes.

Active signals dashboard showing AI qualification scores on user profiles in Intempt

Segments build themselves from AI scores and behavior

Describe the audience in plain language or pick from AI-computed tiers. Blu combines scores, events, and profile properties into a live segment — no SQL, no manual filter building, no export step.

Segment list showing qualified prospects ranked by AI score in Intempt

Segment membership triggers a journey instantly

The moment a user qualifies — score crosses a threshold, RFM tier changes, or a condition is met — they enter a journey with no batch delay. The segment is the trigger, the filter, and the context all at once.

Journey builder with segment-based entry condition in Intempt

One segment activates across every channel

The same audience powers a nurture journey, an exclusive offer, a personalized email, and a campaign results dashboard — all at once. Build the segment once. Every activation layer reads from it.

Full lifecycle activation: segment to journey to campaign results in Intempt

Meet Blu

Your segments have an analyst. It keeps every audience current and ready to act.

Blu scores users, computes RFM tiers, and surfaces who needs attention right now.

See how Blu works

Real results, not just tech

We drive measurable outcomes in the first 90 days. Beyond the platform.

01 / 03

“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.

Explore more products

Everything else that turns your data into revenue.

Data Hub

Unify every customer signal into one real-time profile — no warehouse, no ETL.

Journeys

Orchestrate cross-channel flows triggered by segment membership and live events.

Experiment

Run A/B tests targeted to specific segments with CUPED variance reduction.

Personalize

Deliver individualized on-site experiences based on segment membership.

Static segments can't predict. AI attributes do.

Blu computes the scores. The platform builds the audience. You just act on it.

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Frequently asked questions

AI Segmentation basics

HubSpot and Klaviyo segment on static properties and basic engagement metrics like opened email or clicked link. 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 connect directly to journeys, experiments, and personalizations in the same platform. No export, no sync.

AI attributes are fields on user and account profiles computed automatically by Blu's agents. 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 rule, with no export step.

Yes. Segments recalculate as users act. A user whose AI score changes or who triggers a qualifying event enters or exits the segment immediately. 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 of purchase, frequency of purchase, and monetary value. Segments update as behavior changes. No manual spreadsheet analysis.