๐Ÿ“Š Case Studies

Real Results from
Real Indian Businesses

Businesses across BFSI, EdTech, Real Estate and Healthcare have transformed their outreach with TaskVox AI. All data in percentages โ€” no company names disclosed.

* All results are based on actual deployments. Company names are kept confidential per NDA.

78%
Avg. calling cost reduction
12x
More leads contacted daily
3x
Higher conversion rate
91%
Follow-up completion rate
๐Ÿฆ BFSI ๐ŸŽ“ EdTech ๐Ÿ  Real Estate ๐Ÿฅ Healthcare
๐Ÿฆ BFSI โ€” Lending & Insurance
Replaced 80% of Calling Team with AI,
Scaled Outreach 12x
Challenge: High calling cost, inconsistent follow-ups, low lead contact rate

A mid-sized financial services company operating in the personal loan and insurance space was spending heavily on a large in-house telecalling team. Despite the headcount, only 20โ€“25% of their portal leads were being contacted within the first 48 hours โ€” a critical window for conversion in BFSI.

The team faced persistent challenges: high attrition (averaging 45% annually), inconsistent script adherence, and inability to scale quickly during peak demand periods. Each lead cost โ‚น80โ€“120 to contact and qualify with a human agent.

What They Deployed

  • Voice AI Agent configured in Hindi and English for pre-qualification
  • 6-question qualification script: income, existing loans, loan purpose, urgency, credit history awareness
  • Webhook integration to their Zoho CRM โ€” auto-tagging Hot/Warm/Cold leads
  • Automated callback scheduling for "Interested but busy" responses

What Changed

Within 2 weeks, 100% of new leads were being contacted within 2 hours of upload. Human agents were retasked exclusively to hot leads delivered by the AI โ€” their close rate jumped from 8% to 31% because they were only talking to pre-qualified, high-intent prospects.

"The AI is better than our best callers in one key way โ€” it never gets tired, never deviates from the script, and logs every single answer accurately."

โ€” Sales Head, Financial Services Company
78%
Reduction in cost per qualified lead
12x
More leads contacted daily
40%
Improvement in collections recovery rate
2h
Max time to first contact (was 48h)
๐ŸŽ“ EdTech โ€” Courses & Admissions
Lead Qualification Time Cut by 65%,
Demo Bookings Tripled
Challenge: Low trial-to-paid conversion, sales team burnout, high no-show rate

A fast-growing EdTech platform offering professional certification courses had a problem that's common in the space: thousands of free trial signups per month, but a sales team that could only call 600โ€“800 per day. Leads older than 5 days converted at less than 1%.

Their human agents were burning out making 80+ calls daily, most of which went to uninterested users. The demo booking rate was 6% and no-show rate on booked demos was over 50%.

What They Deployed

  • Voice AI Agent in Hindi + Hinglish (the natural mix used by their target audience)
  • Qualification questions: current occupation, career goal, budget, preferred learning time
  • Automated demo scheduling for qualified leads โ€” sent WhatsApp confirmation with Google Meet link
  • Day-before reminder call by AI to reduce no-shows

What Changed

The AI called 100% of trial signups within 24 hours. Qualified leads (those who expressed interest and fit the profile) were routed directly to senior sales executives with a full call summary. Demo booking rate for AI-qualified leads was 24% โ€” 4x the previous rate. No-show rate dropped from 52% to 25%.

"My sales team now starts every day with a list of people who said 'yes, I want to know more.' The quality difference is night and day."

โ€” VP Sales, EdTech Platform
65%
Faster lead qualification per rep
3x
More demo bookings per month
52%
Drop in demo no-show rate
4x
Higher demo booking rate on AI-qualified leads
๐Ÿ  Real Estate โ€” Residential Projects
68% More Site Visits Booked,
91% Follow-Up Completion Rate
Challenge: Thousands of unworked portal leads, sales team capacity bottleneck

A real estate developer with multiple residential projects in Tier-1 cities received 8,000โ€“12,000 leads monthly from portals like MagicBricks, 99acres and Housing. Their 15-person sales team could realistically make 200โ€“250 calls per day โ€” meaning 95%+ of leads went uncontacted for days.

By the time an agent called a 5-day-old real estate lead, the prospect had already visited 3 competitor sites. Speed-to-contact was everything, and they were losing it to headcount constraints.

What They Deployed

  • Voice AI Agent configured per project โ€” each agent knew its own project details, pricing range, location, and possession date
  • Qualification: budget range, property type preference, timeline, investment vs self-use
  • Site visit booking directly by AI โ€” with confirmation sent to CRM and customer via WhatsApp
  • Follow-up call 24h before scheduled visit to confirm and reduce no-shows

What Changed

100% of leads were called within 4 hours of upload. The AI booked 68% more site visits than the human team was managing previously. Human agents now only handled people who had already agreed to a visit or were asking detailed technical questions โ€” their time on meaningful conversations went from 20% to 80% of their workday.

"We were drowning in leads but couldn't call all of them. Now every single lead gets called within hours. Our site visit numbers have never been better."

โ€” Sales Director, Real Estate Developer
68%
More site visits booked per month
91%
Follow-up completion rate (was 28%)
5x
More leads contacted daily
4h
Time to first contact (was 2โ€“3 days)
๐Ÿฅ Healthcare โ€” Clinics & Hospitals
No-Shows Down 58%, Staff Calling
Time Freed by 80%
Challenge: High appointment no-shows, front desk overwhelmed with confirmation calls

A multi-specialty clinic chain with 8 centers across two cities had a persistent problem with appointment no-shows. Their no-show rate was 34% โ€” meaning 1 in 3 appointment slots were wasted, costing significant revenue and disrupting doctor schedules.

Front desk staff were spending 3โ€“4 hours daily making confirmation calls, reminder calls, and rescheduling calls. This time was being taken away from actual patient service at the reception desk.

What They Deployed

  • Voice AI Agent calling patients 24 hours before appointments in Hindi, English, and one regional language
  • AI handled rescheduling โ€” if patient said "I can't come tomorrow," AI offered alternative slots and confirmed in the same call
  • Post-appointment follow-up calls for prescribed medications and next appointment reminders
  • Automated outreach to lapsed patients who hadn't visited in 6+ months

What Changed

No-show rate dropped from 34% to 14% within the first 6 weeks โ€” a 58% reduction. Front desk staff reclaimed 80% of their phone time, which they redirected to in-person patient experience. The lapsed patient re-engagement campaign brought back 22% of patients who hadn't visited in over 6 months.

"Our front desk team used to spend half their day on the phone. Now they're actually there for patients walking through the door. The difference in experience is visible."

โ€” Operations Head, Healthcare Group
58%
Drop in appointment no-show rate
80%
Staff phone time freed
45%
More follow-up calls completed
22%
Lapsed patients re-engaged

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