Score every customer on lifetime value
RFM scoring, predictive LTV and churn risk on one profile, with the right experience triggered per tier across every channel you own.
0.0on G2One welcome email for every customer
Your ten-year customer and your ten-day trial user get the same message. Your VIP segment is a spreadsheet from last quarter. You find out someone churned in the cancellation survey.
Know who is at risk before they go.
Intempt scores every customer on recency, frequency and monetary value continuously. Champions, Loyal, At-Risk, Hibernating: every tier live, not from a static export.
- Continuous RFM segmentation on live behavioral data
- Tier definitions configurable to your business model
- Segment-specific journeys triggered automatically on tier change
Treat your best customers differently.
Crossing an LTV threshold triggers the right experience automatically: a personalized offer, an upgrade path, a dedicated touchpoint, or suppression from a generic campaign.
- LTV-tier triggered journeys and personalization rules
- On-site VIP experience for top-tier segments
- Suppression rules protecting high-LTV customers from mass sends
Campaigns across every owned channel.
The email, the SMS, the push and the landing page come out of one brief, on brand and personalized per segment, so the campaign says the same thing on every channel it reaches.
- Email, SMS, push and landing page generated together
- Behavioral signals in the copy: cart contents, browsed products, last purchase
- Cross-channel suppression so nobody gets the same message twice
The four LTV formulas, and when each is right
| Formula | Use when |
|---|---|
| Historic LTV = sum of gross profit per customer | You have full transaction history and a stable product |
| Simple predictive = (ARPA × gross margin) ÷ churn rate | Subscription, steady churn, quick directional read |
| Cohort LTV = revenue per acquisition cohort over time | Churn varies by acquisition period or channel |
| Predictive LTV (behavioral model) | Repeat-purchase, variable basket, long tail |
The mistake is using the simple formula on a business with lumpy churn, which either flatters or guts the number depending on which month you calculate it in. If your churn rate moves more than a point between cohorts, use cohort LTV.
One thing worth knowing about AOV: raising average order value with a discount can cost more margin than the basket gains. Recommendation-driven lift is the alternative, and documented category results put checkout recommendations at 10-30% AOV lift, with cross-sell around 10-15%.
Sources: Nosto ecommerce recommendation benchmarks · Rebuy cart merchandising data.
Explore more ways Intempt drives revenue.
Connected outcomes across the platform.
In the words of50+ live tenants.
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
LTV is the total gross profit you expect from a customer across the whole relationship. It matters because it sets what you can afford to spend acquiring one. Four formulas are in common use and they disagree with each other, so the important question is which fits your business rather than what the single number is.
Spend where the value actually is.
Connect your store or product. RFM tiers and predictive LTV are live in the first session, and the journey for each tier runs without you rebuilding a list.