AI Booked vs AI Assited Valuations

2–3 minutes

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For those of you following the progress of Ethan the AI negotiator it has been a really interesting week or two.

We’ve now started to see not only Ethan booking valuations autonomously but also him setting up his human colleagues.

I have always considered that by telephone if I give someone 40 opportunities to call they will speak to about 8-10 and from that will book around one valuation. Trying to get someone to call 40 opportunities per day, every day is the challenge.

After week 1, Ethan was booking one valuation from 59 outbound messages.

By week 3 he is now passing back opportunities to his human colleagues to book in, as well as booking himself. When this is taken into account we are now booking one valuation in every 29 messages. In other words he has gone from being 32% worse than a human to being 27.5% better when he can pass back leads to a human for them to close. It is also worth pointing out that he costs less than 3% of the cost of negotiator.

My sense is that the adoption of this technology will speed up, when people realise it will be a combination of both autonomous AI and an AI assistant.

As a bit of scene setting Ethan works exclusively inside Greenhouse OS and at the moment he’s focused on stock where you know who the seller is but they are on the market with a competitor.

We have a direct integration with Twenty EA who provide the on market data, this feeds ‘triggers’ into the system for both people you know and properties where you don’t know who the owner is.

At each of these triggers he sends a text message to the customer and then, if they respond, he has conversation with the goal of booking a valuation directly into the diary.

Here is an example below

AI Booked

Screenshot of a conversation in Greenhouse OS regarding a property valuation appointment between a customer and an estate agent named Andrew. The chat includes scheduling details and responses about services offered.
A conversation interface displaying a messaging exchange regarding property valuation scheduling between a customer and an AI named Ethan.

AI Assisted

This is an example below

Screenshot of a message history showing a conversation between a user and Ethan, an AI assistant from Preston Baker, discussing a property sale.

You can see that the customer wants to have a conversation about this, so our colleague picked this up and booked the valuation.

Final Thoughts

79% of all of the responses that are coming back in are coming in out of office hours. So even though we are testing the spread of messages across a 7 day period, during the morning, afternoon and evening customers are choosing to engage with us out of office hours.

This is only the beginning but within a very short space of time the power of working your database will make the need for constantly driving new leads into your world a much lower priority. The squeezing of the lemon inside your database with communication being driven by events within the CRM will become a ridiculously cost effective way to create more business.

As you list more homes from this, you generate more data through buyers with houses to sell, thus driving more and more valuations, more listings and so on. This has the potential to become a flywheel that just keeps spinning faster.

The AI Team will just get bigger as time goes by – supported by humans for a long time but doing the boring work where consistency is more important than flair.

A graphic illustrating various roles in a team, highlighting areas where AI can be integrated, including prospecting, vendor care, property management, follow-ups, booking viewings, tenancy progression, viewing feedback and offers, and rent collection.

2 responses to “AI Booked vs AI Assited Valuations”

  1. Great stuff Ian, I can’t wait to see the results in our business. Have a good week.

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