AI automatically analyzes 100% of your calls across every virtual brand, catches menu mix-ups between brands, delivery address errors, and missed upsell — with no in-house QA team.
Avg. score
8.4
↑ +0.5
Upsell
34%
↑ +14%
Lost
7
↓ −5
Duration
2:48
↓ −22s
Agents on shift
AI insight: Agent Marcus D. answers 11% of "Poke Room" brand calls with the "Burger Loop" greeting. Risk of eroding customer trust in both brands.
The hidden cost of every call
The customer never sees your kitchen, never walks through a door, never judges the food before ordering. All they have is a voice on the phone. Here's what most often goes wrong.
An agent mixes up the menus of two brands running on the same line
→ The customer hears items from the wrong brand and hangs up, no longer trusting the order
≈1 in 12 calls involves a brand or menu mix-up
A missed call during the rush — with zero walk-in traffic to make up for it
→ Unlike a restaurant with foot traffic, there's no passerby who wanders in instead
A missed call = 100% lost order, 0% compensation
A wrong delivery address or drop-off note (floor, gate code, buzzer)
→ The driver goes to the wrong place, the food gets cold, and the customer can't just "walk in" instead — there's no physical location
1 address mistake = a failed delivery run and a lost customer
💡 There's no menu board and no table for a server to upsell at — the phone call is the only moment to offer a sauce, a larger bowl, or a drink.
If an agent skips the upsell on 70% of calls at an average ticket lift of $1.20: 40 calls × 0.7 × $1.20 = $33.60/day in missed revenue from a single brand.
How it works
The recording is automatically forwarded via webhook from your phone system, tagged by brand and line
The conversation is converted to text with agent/customer role detection and brand identification by line number
Checks brand-correct greeting, upsell attempts, and accuracy of the delivery address and instructions
A separate picture for every virtual brand and every call center agent
What you get
AI checks whether the agent greeted callers as the correct brand, whether they confused "Burger Loop" menu items with "Poke Room," and whether the order was confirmed accurately.
→ No brand loses its identity to an agent's mix-up.
Find out exactly why a call didn't end in an order: long hold times, an item missing from that brand's menu, or an unclear delivery window.
→ Recover orders that used to vanish without a trace — there's no storefront to win them back another way.
Track which agents offer a sauce, a drink, or a bigger bowl size — the phone call is the single moment to raise the ticket, since there's no menu board to lean on.
→ Grow your average ticket without adding a single item to the menu.
AI checks whether the agent clearly captured the address, floor, gate code, and driver note — before the order heads to the wrong place.
→ Fewer failed delivery runs and fewer frustrated customers with nowhere to just walk in instead.
Product
Switch between brands in one click. Clear for the shift manager, precise for the kitchen operator.
Top agent
Марія К.
9.1/10 today
Upsell rate
38%
+11% this week
Lost orders
5
–5 vs yesterday
Avg. duration
2:41
–7s vs baseline
Upsell leaders
Drop-off reasons
Customer sentiment
72%
Positive
19%
Neutral
9%
Negative
AI insight of the day
On Friday evenings, 3 of 9 agents answer "Poke Room" brand calls with the default "Burger Loop" greeting. Consider splitting the lines or adding a prompt to the script.
Integrations
Setup takes under 10 minutes per brand line. No extra hardware, no dedicated IT department.
ROI calculator
Even +16 upsells/day
For a single brand that's:
Case study
+19%
Call conversion
+24%
Upsell rate
−31%
Brand mix-ups
8 days
Rollout
“We launched a third brand, "Wok Story," on the same lines as "Burger Loop" and "Poke Room," and had no idea agents were crossing the greetings. AI showed that 1 in 9 "Wok Story" calls opened with the wrong brand's greeting. Three weeks after fixing the scripts, call-to-order conversion was up 19%, and the "wrong restaurant" complaints disappeared entirely.”
Ryan Whitfield
Operations Director, "FoodLab Kitchens" multi-brand kitchen
😔
Before
The call center answered calls for three brands on shared lines. The operator only found out about mix-ups from app complaints, days after the fact.
🤖
Process
AI analyzed 100% of calls broken down by brand and pinpointed the specific agents and shifts with the highest mix-up risk and the lowest upsell rate.
🚀
Result
After targeted coaching for three agents, mix-ups nearly vanished, and call-to-order conversion rose 19% within three weeks.
FAQ