We find out a customer left when the orders stop.
Nobody noticed the complaints getting sharper or the orders getting smaller until the account had already gone to a competitor.
What it costs.
A study, 2014A watch on orders, tickets, payments and the tone of messages that flags customers going quiet or getting angry, with a drafted note for the account owner.
What we build for it
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Intelligence
Customers going quiet, spotted early
Spots the customers ordering less, paying slower or complaining more, weeks before they leave.
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Growth
Repeat orders and quiet customers brought back
Spots customers due to reorder, buying less or gone quiet, and drafts the right note for each.
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Conversations
Complaints raised to the right person in minutes
Angry messages, VIP customers and late replies are spotted in minutes and put in front of the right person.
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Conversations
What your customers are really saying, every week
Every chat, mail and call is read for themes, lost-sale reasons and gaps, in one weekly page with quotes.
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Intelligence
What people say about you online, watched every day
Watches social media, forums, news and videos for your brand and leaders, and raises a crisis within the hour.
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Intelligence
A hundred customers interviewed in a week
An AI interviewer talks with each customer or lost buyer in their language, and returns themes in their words.
How it shows up in a trade.
The same problem, in the words each trade says it in, and the first thing we would build there.
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Brokerages, property managers and facility firms
Repairs drag on, and good tenants leave at renewal.
What we would build. Maintenance desk and Resident app. AI for property and facilities -
Store chains and showrooms
Discounts go out to everyone, and the regulars still drift away.
What we would build. Regulars who come back. AI for store chains and showrooms -
Hospitality, travel and venues
We don't know which guests come back, or why the others don't.
What we would build. A site that sells rooms direct. AI for hotels, travel and venues -
Finance and insurance operations
Policies lapse because nobody chased the renewal.
What we would build. Renewal desk, Reminder calls, done politely and Early warning. AI for finance and insurance operations -
Diagnostic labs, nursing homes and day care centres
Referring doctors want reports faster, and send patients elsewhere when they wait.
What we would build. Doctor portal and Report and home collection desk. AI for labs and care homes -
Education and training
Students sign up and drift away halfway through the course.
What we would build. Drop out early warning and A tutor for every student. AI for education and training
Leads wait until Monday. The buyer doesn't.
Every enquiry gets an answer and a price while the buyer still wants one, on the channel they wrote in.
What changes. Enquiries get an answer and a price while the buyer still wants one, and you hear a customer is leaving while you can still act.
What we measure, before and after. Time to a first reply and to a priced quote, quotes that got an answer and customers who came back.
The old way keeps running until the new one has passed on your own work.
- 01A study, 2011.42hoursLeads wait until Monday
- 02Our own sum.Rs60lakhQuotes sit in an inbox for days
- 03Our own sum.114hoursCalls ring out
- 04Our own sum.Rs6lakhThe same twenty questions, all day
- 05A study, 2024.70%What did my salespeople do today?
- 06A study, 2024.38%Marketing spend, return unknown
- 17A study, 2014.5 to 25×Customers leave quietly
- 18A study, 2025.95%The page has gone silent
Tell us how you would know a customer was leaving.
45 minutes on a video call with our founder and the people who live with the problem. Nothing to sign. You leave knowing what we would build first, and why.
Or write to us.hello@agentec.cloudAgentec on LinkedIn