Your best customers deserve better than a generic campaign.
RFM scoring, predictive LTV, churn risk, and behavioral segmentation. See your highest-value customers and trigger the right experience per tier.
0.0on G2From RFM scores to VIP experiences.
Know who your champions are. Protect them. Act before they go quiet.
Know who's at risk before they leave.
Intempt scores every customer on Recency, Frequency, and Monetary value automatically and continuously. Champions, Loyal, At Risk, Hibernating - you see every tier in real time, not from a static export.
- Continuous RFM segmentation on live behavioral data
- Segment-specific journeys triggered automatically on tier change
- Churn risk score with contributing behavioral factors
Act before the churn happens.
Intempt's churn prediction models which customers are trending toward high LTV and which are moving toward churn before the behavioral pattern is visible to the naked eye.
- Predicted LTV score updated per customer continuously
- Churn risk score with contributing behavioral factors
- LTV cohort analysis by acquisition source, plan, or first product used
Treat your best customers differently.
When a customer crosses your LTV threshold, Intempt triggers the right experience automatically: a personalized offer, a dedicated touchpoint, an upgrade path, or a suppression from generic campaigns.
- LTV-tier triggered journeys and personalization rules
- On-site VIP experience for top-tier segments
- Suppression rules that protect high-LTV customers from mass campaigns
Four LTV formulas, and when each one is actually right
Customer LTV is not one calculation. It is four different formulas that answer different questions and produce materially different numbers. Using the wrong one, especially the arithmetic mean, is the most common LTV mistake we see in operator dashboards.
| Formula | Best for | Watch out for |
|---|---|---|
| Simple LTV: AOV x purchase frequency x lifespan | Fast directional read for DTC, first pass | Assumes stable retention, inflates numbers if churn is not accounted for |
| LTV = ARPU / churn rate | SaaS with monthly churn, steady-state view | Wrong for cohorts with declining early churn, overstates long-term value |
| Cohort LTV (12-24 month observed) | Any business where you have enough data | Slower to produce, requires clean cohort tracking |
| Predictive LTV (survival model) | Segment-level decisions, LTV-based bidding | Requires model maintenance, hard to explain to stakeholders |
The trap almost every dashboard falls into: reporting arithmetic-mean LTV across all customers. A handful of whales pulls the mean above what any real customer will spend. Report by segment or by cohort median, not by a single average across the base.
Connect every trusted source.
Plug into the tools your team already runs on.
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Your customer data stays yours, and stays secure.
The teams that made the switch
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.
Frequently asked questions
Both. RFM and LTV scoring works for recurring revenue and one-time purchase models. The scoring dimensions adapt to your business model during setup.
Know who your best customers are. Act on it today.
Connect your data in minutes. Intempt scores every customer by LTV tier and triggers the right experience before your next campaign review.