Do I have to build the RFM formulas or set thresholds myself?

No. Zappush scores every customer automatically on a 1-5 scale using percentiles against your own base, then files them into named segments like Champions, Loyal, At-risk, and Lost. There are no spreadsheets to maintain and no cutoffs to guess at.

How is this different from RFM inside Klaviyo or Triple Whale?

The scoring concept is similar, but the data underneath is not. Those tools score on whatever events reached them, which for pixel-based tracking undercounts purchases by an estimated 30-40% and usually misses offline and CRM orders entirely. Zappush captures purchases server-side first, so the recency, frequency, and monetary values behind each tier are complete, and every segment is a live audience you can sync to your ad and email channels.

How quickly do customers move between segments?

Membership updates as new server-side events land, so when a lapsed customer buys again they move up on their own, and when a Champion goes quiet they slide toward At-risk without anyone rebuilding a list. The current segments stay synced to your connected channels in near real time.

Coming soon

Segments that score themselves.

Zappush scores every customer on recency, frequency, and monetary value against your own base, then files them into Champions, Loyal, At-risk, and Lost. The scores run on complete server-side data, including offline and CRM revenue the pixel never sees, so your tiers reflect real behavior. Membership moves the moment a customer's behavior changes.

Book a Demo

From $59/month · 14-day free trial · Cancel anytime

Jordan Vance

Was: Champion

At risk

Churn risk68%
Avg between orders41 days
Last order52 days ago
Segment movedChampion → At-risk

30-40%: more purchase signal recovered server-side than a pixel-only RFM model sees
4 tiers: Champions, Loyal, At-risk, and Lost, scored and updated with zero manual setup
0 CSV exports: segments move members and sync to channels on their own, in near real time

You're marketing to one blurry audience

Most brands treat their list as a single blob, because building real RFM segments by hand is slow and the underlying data is broken. Browser pixels lose an estimated 30-40% of purchase events to ad blockers, Safari ITP capping first-party cookies at 7 days, and consent gaps. The frequency and monetary values you would score on are already undercounted. Offline orders, subscription renewals, and CRM purchases usually never reach the analytics tool at all, which quietly demotes your best customers into the wrong tier. So you spend acquisition-level dollars re-selling people who would have bought anyway, hammer Champions with discount emails that erode margin, and let At-risk customers churn silently because no one flagged them in time. Then you upload a bloated 'all buyers' audience to Meta instead of a revenue-weighted seed of your true top spenders.

How it works

Capture every purchase server-side
Zappush collects orders, subscription renewals, offline sales, and CRM revenue through a first-party server-side pipeline. The recency, frequency, and monetary values behind each score are complete, not the fraction a browser pixel survives.
Score and file every customer automatically
Zappush scores each customer 1-5 on recency, frequency, and monetary value using percentile quintiles against your own base. Recency is scored inverted, so the most recent buyer earns a 5. Each customer then drops into a named segment like Champions, Loyal, At-risk, or Lost. No formulas to build, no spreadsheets to maintain.
Let membership move and sync itself
As people buy again or go quiet, their scores recalculate on each new server-side event and they move between segments on their own. Those live segments sync straight to Meta, Google, Klaviyo, and TikTok, with identifiers SHA-256 hashed before delivery. You always activate the right audience, not a stale CSV.

What you get

Automatic RFM scoring
Every customer gets a recency, frequency, and monetary score on a 1-5 scale, ranked against your own base with percentile quintiles. The tiers reflect your actual distribution, not a generic template.
Named, actionable cohorts
Scores roll up into plain-language segments such as Champions, Loyal, At-risk, and Lost. Anyone on the team knows who to reward, who to nurture, and who to win back without reading a scorecard.
Revenue-weighted segments
Weight segments by monetary value or even contribution margin. A handful of high-spend Champions no longer get averaged away by a crowd of one-time buyers, and your lookalike seeds run on real spend.
Live membership movement
Customers enter and leave segments automatically as they purchase or lapse, keeping every audience current instead of freezing at export time.
Auto-sync to ad and email channels
One segment definition syncs to Meta, Google, Klaviyo, TikTok, and other destinations, so an At-risk win-back audience or a Champions lookalike seed is always live where you activate it.

Use cases

RFM LIFECYCLE

Score every customer without a spreadsheet

Building RFM by hand is slow, and pixel data undercounts the purchases you would score on. Zappush scores recency, frequency, and monetary value 1-5 using percentile quintiles against your own base, then files each customer into Champions, Loyal, At-risk, or Lost. No formulas to build, no exports to maintain.

OMNICHANNEL RETAIL

File offline buyers in the right tier

Offline orders, subscription renewals, and CRM revenue rarely reach an analytics tool, which quietly demotes your best customers into the wrong tier. Because scoring runs on the complete server-side purchase record, a customer who buys in store or by phone ranks on real spend. Tiers reflect behavior, not what the pixel survived.

LIFECYCLE OPS

Let membership move on its own

A segment exported to CSV freezes at export time while customers keep buying and lapsing. Scores recalculate on each new server-side event, so people enter and leave tiers automatically as behavior changes. Those live segments sync hashed to Meta, Google, Klaviyo, and TikTok, so the audience you activate is the current one.

Questions, answered.

Do I have to build the RFM formulas or set thresholds myself?: No. Zappush scores every customer automatically on a 1-5 scale using percentiles against your own base, then files them into named segments like Champions, Loyal, At-risk, and Lost. There are no spreadsheets to maintain and no cutoffs to guess at.
How is this different from RFM inside Klaviyo or Triple Whale?: The scoring concept is similar, but the data underneath is not. Those tools score on whatever events reached them, which for pixel-based tracking undercounts purchases by an estimated 30-40% and usually misses offline and CRM orders entirely. Zappush captures purchases server-side first, so the recency, frequency, and monetary values behind each tier are complete, and every segment is a live audience you can sync to your ad and email channels.
How quickly do customers move between segments?: Membership updates as new server-side events land, so when a lapsed customer buys again they move up on their own, and when a Champion goes quiet they slide toward At-risk without anyone rebuilding a list. The current segments stay synced to your connected channels in near real time.

See what your data is missing.

Start free in minutes, or see it live on a call.

Book a Demo

From $59/month · 14-day free trial · Cancel anytime

Segments that score themselves.

You're marketing to one blurry audience

How it works

Capture every purchase server-side

Score and file every customer automatically

Let membership move and sync itself

What you get

Automatic RFM scoring

Named, actionable cohorts

Revenue-weighted segments

Live membership movement

Auto-sync to ad and email channels

Use cases

Score every customer without a spreadsheet

File offline buyers in the right tier

Let membership move on its own

Works better together

Retention Marketing

First-Party Audiences

Persistent Customer Profiles

Questions, answered.

See what your data is missing.