Your Data Has the Answers.
You Just Can't See Them Yet.
Every call, email, review, and ticket your business generates contains intelligence about where you're losing money and what your team should be doing differently. Right now, it's invisible. We find it and fix it.
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What We Found
We Mystery Shopped a 239-Location Dental Network. Here's What They Didn't Know.
408 calls. Hundreds of Trustpilot and Google reviews analysed. Within days, we showed them exactly where revenue was walking out the door, and what their patients were saying that their team never reported.
408 Calls Across 239 Locations. Here's What the Front Desk Was Really Doing.
Our team called locations across the network posing as real patients. They tested upselling, pricing accuracy, response times, and customer service. Within days, we had a complete picture of what was actually happening on the front desk.
- Dozens of locations quoted the wrong price for key treatments.
- 68% of calls failed to mention available finance options.
- Huge variance in hold times between the best and worst locations.
Hundreds of Reviews Exposed a Pattern Nobody on the Team Had Spotted.
We analysed every Trustpilot and Google review across the network. The findings correlated directly with the mystery shopping data: the same locations scoring poorly on calls were generating the most negative reviews.
- 73% of negative reviews mentioned long wait times, matching call data.
- Competitor mentions spiked at locations with the lowest upsell rates.
- Sentiment had been declining for 6 months. Nobody had flagged it.
"Most agencies send you a case study about someone else. We send you a report about you."
Sound Familiar?
These Were Their Blind Spots. They Might Be Yours Too.
Before we connected, this dental network had the same problems we see in almost every multi-location business.
You Can't See What's Actually Happening
Your managers sample 3-5% of calls. The other 95% disappear. What your CRM says happened and what actually happened on the call are two different stories.
Your Data Lives in 10 Different Systems
Sales data sits in the CRM. Call data sits in the dialler. Tickets sit in the helpdesk. Meeting notes sit in someone's head. Nobody has the full picture.
You Don't Know Why You're Winning or Losing
Your best salesperson knows exactly what to say. Your worst one doesn't. And nobody's bridging the gap. The insights sit inside conversations that nobody reviews.
Free Assessment
How Much Is Your Business Losing to Missed Calls and Manual Processes?
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How It Works
From Blind Spots to Full Visibility. Then the Fix.
Here's what the engagement looked like, from the first mystery shop call to a fully deployed digital workforce fixing the problems we found.
External Insight
We mystery shopped 239 locations and analysed hundreds of public reviews. Within days, they had a dossier showing exactly where revenue was walking out the door.
Internal Insight Agents
Once onboard, we connected to their recorded calls, emails, CRM, and support tickets. The internal data confirmed everything the external audit had surfaced, and revealed problems that went much deeper.
Action Agents
Every problem had a pattern. Every pattern got an agent. AI receptionist for missed calls. Follow-up agent for dropped leads. Triage agent for ticket overload. All grounded in the insight data.
Going Deeper
Then We Connected to Their Internal Systems. Here's What Else We Found.
The external audit showed where revenue was leaking. Once we connected Insight Agents to their recorded calls, emails, CRM, and tickets, we found the patterns behind the problems, and they went much deeper than anyone expected.
- Reps were logging "interested" on calls where patients had actually declined
- 40% of follow-up emails were never sent, despite being marked complete
- Ticket escalations correlated with the same low-scoring mystery shop locations
- Revenue leakage totalled an estimated £180K per quarter across the network
Recorded Calls
100% call analysis
Emails
Sentiment and response gaps
CRM Data
Pipeline and deal risk
Support Tickets
Complaint patterns
Internal Comms
Team sentiment
Meeting Transcripts
Decision tracking
The Fix
Every Problem Had a Pattern. Every Pattern Got an Agent.
The insight data showed exactly where things were breaking down. So we deployed Action Agents to fix each one, not as generic automation, but as a direct response to what the analysis revealed.
AI Receptionist
Mystery shopping showed 23% of calls went unanswered. Now an AI receptionist handles overflow, books appointments, and quotes accurately every time.
Fixed: missed call patternsAI Follow-Up Agent
Internal data showed 40% of follow-ups never happened. Now leads get automatic nurture sequences within minutes of every enquiry call.
Fixed: dropped follow-upsAI Triage Agent
Ticket analysis revealed escalations clustering at the same underperforming locations. Now tickets are sorted by urgency and sentiment before they reach a human.
Fixed: ticket escalation overloadAI Booking Agent
No-show data showed 18% of appointments were missed with no rebooking. Now confirmations, reminders, and rebooking happen automatically across all locations.
Fixed: no-show rateWhat You Get
Analysis That Shows You Where to Act
We don't hand you a dashboard and wish you luck. You get scored transcripts, location comparisons, revenue impact calculations, and recommended actions ranked by business impact.
- Every call scored: greeting, product knowledge, upsell attempts, pricing accuracy
- Revenue impact: "32% of calls missed treatment mentions worth £2,400 each"
- Location rankings with specific gaps and training priorities
- Recommended Insight and Action Agents mapped to your findings
Campaign Analysis
239 locations | 408 calls
Leadership
Built by Operators
Piers Linney
Executive Chairman & Co-founder
Award-winning technology entrepreneur who has provided technology services to clients ranging from SMEs to FTSE-100 companies across sectors from retail to defence.
pierslinney
Dr Aalok Shukla
CEO & Co-founder
Combined expertise in technology and clinical fields. Experienced innovator in deploying exponential technologies during platform shifts.
aalokshuklaWant to See What We'd Find in Your Business?
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