what we refuse
The exposure-multiplier proxy — the Barcelona-banned fake ad-rate stand-in for earned value. Point estimates without intervals. Silent model changes. If it can't survive a finance or analytics question, it doesn't ship here.
how this works
how this works
start here — here's your OS, how you plug data in, and the week from prototype to live
impact ladder
how far the proof climbs
we only climb as far as your connected data allows. never a blended fake ROI.
1 · Detection
Coverage landed & deduped
counted
live on your books
2 · Quality
DAD + Earn Rate vs your rubric
scored
live on your books
3 · Attention
EIV-Reach (modeled)
modeled
live on your books
4 · Traffic
Earned sessions
measured
waiting on connect
GA4 connected
5 · Interest
Branded search lift
estimated / measured
waiting on connect
Search Console connected
6 · AI answers
GEO presence + citations
counted + interval
live on your books
7 · Efficiency
Earned vs PR $ / vs paid $
mixed · labeled
waiting on connect
GA4 + Ads or budget CSV
8 · Contract
Attainment vs promise
snapshot-backed
live on your books
What this is
Praytell Impact OS captures coverage, codes it against your rubric, scores Discovery–Authority–Decision, and proves it on one set of books — the Workspace for the agency, the Client Portal for the brand.
from coverage to proof
click a stage — same books Praytell runs, client-safe language only.
Meltwater and backups land as RawItems. Coverage is one table — filters replace 26 sheets.
Monitoring stops eating ~10% billable. Humans do judgment, not paste.
A brand day (Client Portal)
what Casey sees — same books, client-safe surfaces
Overview
Earn Rate, Pulse, spotlights — thirty-second truth.
Brand exec confidence without a status deck rebuild.
methods we stand on
why these numbers survive the room
industry law, peer-reviewed intervals, and a published Earn Rate — not 'the model said so.'
AMEC Barcelona Principles
industry standardBoard-safe posture that formally rejects the exposure-multiplier proxy. CMOs already recognize AMEC — we encode it, we don't debate it in the deck.
Discovery · Authority · Decision
operable funnelEarn Rate pillars scored against your rubric — measurable, not a slide metaphor.
Weighted Earn Rate
published indexE = 100 · D^α · A^β · Dec^γ — layers combine as complements, weights declared per client and published with every score, always with an interval. One hero number both sides trust because it refuses to publish when it cannot stand behind itself.
Wilson 95% intervals
peer-reviewed statsGEO presence and citation shares are proportions. Bands, never bare lines — alerts only when intervals are disjoint.
≥90% agreement gate
human ceilingAI-coded metrics stay internal until they clear a blind human gold-set. Your portal never gets a number the analysts wouldn't give.
every Client Portal number can point at a method. if it can't, it doesn't appear.
shared kpi dictionary
same books in Workspace and Client Portal — method labels travel with every number
| KPI | Method |
|---|---|
| Earn Rate | scored |
| Discovery / Authority / Decision | scored |
| Placements | counted |
| Reach | modeled |
| EIV-Reach | modeled |
| Earned sessions | measured |
Shared books
every number you see here is the same number Praytell sees — Earn Rate, D/A/D, Outcomes depth as you connect GA4 and ads. we don't play the exposure-multiplier game — no fake ad-rate stand-ins for a placement's worth, not here, not ever.
connect your data →