PROSPECTING
Helping agents win more leads from their own database
Led Product Strategy
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Tested MVP
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Interviewed Agents
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Used Data To Improve Product
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Sales
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Got Direct Calls From Agents When Things Broke
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Led Product Strategy • Tested MVP • Interviewed Agents • Used Data To Improve Product • Sales • Got Direct Calls From Agents When Things Broke •
The Agent landscape
Real estate agents have access to more customer data than ever before. From real estate portals, to collecting names and numbers at open homes, to other lead generation partners and also walk in’s to their business.
And there is real value in this data
The average listing rate within an agents CRM (database) is 5% per year.
The average database size is 10,000 contacts
That’s 500 potential listing opportunities per year (5% * 10,000 = 500)
However it’s incredibly difficult to know which 500 people an agent should be speaking with.
To combat this agents often take a brute force approach. Cold calling is common practise (10 calls before 10am every day of the week) as is door knocking an area.
Speaking with the 5% of people who are selling soon is the goal of every agent and we thought we could help them to do that.
So, we built a tool to help agents find hot sellers within their database.
The prospecting engine used a combination of the agencies customer data, market data (like how long it’s been since a property was last sold) and our own internal behavioural data that we had been gathering for the last 8 years.
Every contact within an agents database was given a score, when the score reached a certain threshold the contact was marked as a potential seller and the agent received an alert to get in touch with this customer.
We also created a web tool that would allow agents to see all the historical actions a customer has taken since they were added to the agents database. This gave the agent fuel they could use when making the first conversation.
The agent dashboard shows people the agent needs to call =
The profile view gives an agent insight on the actions a customer has taken - also lets the agent keep notes and set follow up reminders to call
Metrics
Onboarded 50 agencies to the tool
Achieved an engagement rate of 80% (engagement = sellers called)
Listing rate of sellers we discovered (and sent to agents) was 25% - 5x better than the average
Challenges
The biggest challenge was scaling the tool past the 50 agencies we onboarded. The product was solid but there were concerns around data privacy - mainly an agency allowing us full access to their database. Often these databases have been collected over years and even decades and agents can be incredibly protective of them (understandably).
This project was live throughout COVID 19 and due to later redundancies within the company there was no longer the engineering support available to continue it. It was discontinued in late 2022
Highlights
For me personally as the lead product manager this was a huge learning experience. In the early part of the project when we were still working on our MVP I spent a lot of time in “in the field” meeting real estate agents in their agencies and learning about their day-to-day processes.
This was incredibly valuable and helped inform the product we built.
Once we had a rough idea of what the tool needed to do I mocked up some designs and went to sell it.
Nothing had been built yet.
This allowed us to work lean and only build the minimum amount of features to sign our first customers.
It’s not often product managers get to do sales but I found this really helpful as it allowed me to understand the biggest objections first hand and refine the product.
It also meant any issues agents would call me directly, which again helped to improve the product. Staying close to the customer you’re building for is critical
Work Samples
Estimate tool
Helping sellers understand the value of their property
DIY
Helping sellers connect with agents faster