Case study
How Teams Use
NoesisAI
Three teams, four to seven weeks in. Client names are withheld at their request.
Two Brokers, Thousands of Companies
contacts researched
reached by email and LinkedIn
meetings booked
The situation
Two of seven brokers carried all new business. Finding lists was never the problem. Understanding each company and contact well enough to open a conversation was, and twenty or thirty companies made for a good day.
What NoesisAI did
- Researched every company and contact first: the business, the role, recent public developments.
- Grouped the list and agreed the angle for each group before anything went out.
- Carried the same research into LinkedIn, so the brokers could open conversations without doing the work twice.
- Ran follow-ups to a set end date, stopped them the moment anyone replied, and handed real conversations back to the brokers.
Outcome
Two brokers covered ground that would normally take a much larger team, and spent their time only on conversations that were going somewhere.
replies and interactions
business conversations
quotes or proposals
new commercial clients
A moment from the project
One company replied that they'd just renewed, and to come back before the next one. Weeks later, a relevant piece of content matched them in the CRM. The second approach had a specific reason to exist, and this time they booked the meeting.
Keeping Up with a Market That Changes Daily
pieces of content screened
posts published
messages or inquiries
The situation
All eleven agents were producing content, and all of them were spending evenings scrolling for topics. By the time a post was written, filmed and ready, the moment had usually passed.
What NoesisAI did
- Screened 10,000+ pieces of public content across the local market, condos, first-time buyers and rates, and surfaced only what was worth acting on, with the reason.
- Produced copy, images and video from the chosen topics end to end, with no one on camera.
- Passed the people who arrived through comments and messages into the CRM, so a first conversation wasn't the last one.
Outcome
The team stopped hunting for topics and started choosing them, and the people who came in through the content didn't stop at one conversation.
one-to-one conversations
formal consultations
A moment from the project
The highest-viewed video wasn't the one that produced business. A far more specific post, on what to check once you have the strata documents, brought in the real questions.
12,000 Customers, and No Reason to Call
targeted conversations
replies
customers into two or more rounds
The situation
New contacts and recent buyers got attention. The large middle, people the team knew and had talked to but had no particular reason to call, quietly went cold.
What NoesisAI did
- Brought in a steady stream of relevant content and matched each piece to the customers it suited, with the reason.
- Let each rep pick the customer, then drafted the message from that customer's history and the rep's own way of writing.
- Turned real conversations back into the customer file once confirmed, which changed how that customer was matched next time.
Outcome
Customers who hadn't been contacted in months came back into regular conversation, and what those conversations turned up changed how they were approached next time.
customers in the book
asking about specific products
purchases
A moment from the project
One customer had been tracked as interested in weight management. A conversation revealed her real problem was work stress and sleep. Two weeks later a sleep-related piece matched her, and the third conversation was the one she started.
See If This
Applies to Your
Team
These teams looked a lot like yours before they started.
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