P
Pythia · Cedarline Market — sample

Client Evidence Portal

● Privacy-filtered sample

Review the proof behind scored transactions. Fictional store, 30 days of generated conversations.

Employee
Avg 4-Step Score★ /100
— /100
— transactions scored
1 · Greet+25 pts
—
within 10 seconds
2 · Add Value+25 pts
—
upsell / rewards ask
3 · Validate+25 pts
—
purchase affirmation
4 · Thank+25 pts
—
close-out

Insight Feed

Actionable store issues — fix now

4-Step Completion

— scored transactions in view

Service Timing

The clock starts before the first word
— of customers never greeted · —
Arrival → Greeting (greeted only)—
· of those, greeted within 10 seconds—
Greeting → Close—
Total visit—
wait — avg interaction — avg

Score Trend

Daily average 4-step score · goal lines 60 / 75 / 85 · full 30 days

Service Quality

Conversation health in view

Shift Scorecard

Same store, different dayparts
Shift comparison appears once a daypart has 5+ transactions in view. Mornings are gated — this store's registers run afternoons and evenings.

Patterns

What hundreds of interactions reveal · all data · not affected by filters
Customers greeted within 10 seconds leave Positive 72% of the time — vs 44% when never greeted.n=214 vs 96
Greeting is contagious: when the visit starts with a greeting, Thank follows 84% of the time — vs 57% without one.n=238 vs 98
On days with a live store issue, service averages 61 — vs 69 on clean days. Broken store, broken service.n=4 vs 26

Customer Traffic & Demographics

People Counter · aggregate estimates · full 30 days
People counted8,642customer visits
Busiest dayFriday1,420 visits
Peak window4-6 PMavg. 39/hour
Average traffic by dayvisits
Estimated customer mixaggregate only
Under 188%
18-3434%
35-5439%
55+19%
52% Male48% Female

Estimated in aggregate. No images are stored and no faces are identified.