How to build a Real Estate Agent AI Chatbot

11 Sep. 2019 - - Total Reads 2,024

We’ve just gone through the learning curve of building (and rebuilding a number of times) a hopeful “Turing Test” passable Real Estate Agent AI Chatbot. Was it easy? Hell no. The Turing test is a huge benchmark for a reason– the natural language we bumble through even as a toddler, is incredibly sophisticated. To get a computer to do that like a real Real Estate agent in a SciFi show (there may not be too many real estate agents in a sci-fi show, but you get the idea), is really light years ahead.

It’s live and working. Check it out on MotionProperty.com.au and their Facebook page (yes, it answers all live chats on Facebook as well). We have at best 6 months of programming to improve it.

How to build and AI Chatbot

The AI Part of any chatbot engine is really just a comparison tool. It looks for like-minded words or phrases, and comprehends if you replace one for another. For example, “Rent” could be “Lease” or “Renting”, and as soon as you give that example, is Rent as in “lease my place” or “I want a place to rent”, interchangeable again is “I want to live there”, which also means “live” as in performance. This shows how fast things can escalate outside the scope of AI or at best, form part of the training inside the AI platform.

We came up with a couple of processes to support these challenges– you can approach this from Top-down or Bottom-up.

Bottom-up is where you sort of go for it, and start with an open-ended “ask-me-anything” chat and try building in intended cornerstones to get to the bottom- the info you want to capture, the person’s name, location of interest, budget, etc.

Top-down is where you build out an elaborate data flow diagram (DFD pictured here), showing all the “pathways” you think how most conversations will go down. We did this from our second rebuild onwards for two reasons:

First, there were too many options to cover off in the Bottom-up approach. So while we did get something working, the potential conversation pathways were enormous, and conversations that got to the end were under a few percent.

Second, we could launch what was basically a multi-choice questionnaire from the DFD, so that 100% of the conversations reach a conclusion. It wasn’t anything better than a dumb form at this point, but it gave us a lightbulb moment. We could tackle the programming in a piecewise process, removing layer by layer of the multi-choice into smaller AI conversations. This approach worked superbly. As we pulled out the first multi-choice from the top of the DFD tree, it changed the entire feel of the conversation– far more human and realistic.

While Bottom-up chatbot programming can work, it seems only applicable when programming something simple, such as handling a single Question pathway (example below). This liner pathway is essentially a zoomed-in version of every box in the larger DFD.

For our “Be the Agent” AI chatbot with 5-6 key services and a range of sub-trees for every conversation point, the Top-Down approach has been a great solution so far, and is only getting better with every iteration.

For more info on our Chatbot strategy, design and development services, please see our section on Chatbots under Our Services.

Michael Simonetti
Posted by:

Post Reads: 2K

Share this

Go on, see if you can challenge us on "How to build a Real Estate Agent AI Chatbot" - Part of our 168 services at AndMine. We are quick to respond but if you want to go direct, test us during office hours.

Add Your Comment

Trusted by

SwinBurne University of Technology
Australian Organic Food CO
Melbourne Central
National Relay Services
DepSkin.com
Telstra
Bostik
Carlton Football Club
Uber
Melbourne Sports and Aquatic Centre – MSAC
Grow Your Business
The Canberra Times
The Burger Cheese
Metricon
McArthur Skincare
CB Richard Ellis
Novvi
Positive Poster
Schiavello
Green St Juice CO
Chia
Mamma Lucia
OJAY
ISO Certified
VISSF
Microsoft Certified Azure Fundamentals
The Age
Oakdale Meat Co
Max’s
POSTER Magazine
Coles
Moov Head Lice
Unsw Australia
Marshall White
Federation Square
Appstore
Brisbane Times
OMS – Order Management System
Madman Entertainment
Florsheim Shoes
Naturtint
Tek Ocean
Castran Gilbert
Liveoneday
Heat Holders
GPT Group
Royal Freemasons
RMIT University
White Suede
Bank of Cyprus
James Buyer Advocates
Engine Swim
Vendor Advocacy Australia
Atlantic Group of Companies
Bintani Australia
ABC
131 Pizza
AC/DC
Wild Rhino Shoes
Palace Cinemas
The Fortune Institute
Plan It Sync It
SunSense Digital Agency
Bigcommerce
Jalna
Smart Company
Natralus Australia
Arthur Galan
Fairfax Media
Van Egmond Group
Think & Grow Rich Inc
One Shift
Engineers Without Borders
MyAccount
Australian Anthill
Fresh Cheese Company
Toy World
Cronos Australia
Toni&Guy
Sports Power
Etihad Stadium
Tomorrow Stars Basketball
Acquia Certified Site Builder Drupal
Amino Active
Passage Foods
Tribe
Jetstar
NMI Insurance
iPrimus
Australian Physiotherapy Association
Ebay
Bondi Sands
Viktoria & Woods
Kadac
Grays Ecommerce
Melrose Health
Australian Government
Mecca Brands
ADP Payroll
21st Century Australia Party
Windsorsmith
Sunday Creek
QV Skincare
Shell
Boston Consulting Group
Catholic Insurance
Forbes
GooglePlay
TPP
Magento Solution Specialist
Hanover
Watches of Switzerland
WTFN
BlackMores
Rock Pool Group
National Museum of Australia
Garmin
Switzer Media+Publishing
Dinosaur Designs
Dial Before You Dig
Ubertas Group
Loan Market
CSquared Executive
Rackspace
Ego Pharmaceuticals
Hairhouse Warehouse
DUSA, Deakin University Student Association
The University Of Melbourne
Beaumont
DeeWhy Market
Xavier
Ello
Crumpler
Street Kitchen
Magento
LBG Australia and New Zealand
Fast.co
Oracle
Macmillan Publishing
High Street Armadale
News
Passage To India
Parker Lane
Associated Press
Celebrate Health
Adobe Professional
Drupal
Melbourne Heart
Focus On Furniture
Matchbox Homewares
Arc One
Google
Victorian Government
Tassal
Elucent
Aqium Gel
Federation University Australia
Maxine
Grainshaker
Kay&Burton
Instant RockStar
Buy Aussie Now
Rydges
CAN- Common Wealth Bank
Bulk Nutrients
MAP
Scrum.org
Craft CMS
SMH – The Sydney Morning Herald
Paypal
Eway
Melrose MCT
Movember

Testimonials

The guys at &Mine are one step ahead and have made the process pleasant and stress free. All credit to them and their great working culture because I expected the process to be awful. I am looking forward to taking this project live and doing more business with &Mine. Lauren Brown, Director, Motto fashion

More Testimonials
AndMine-Google-Partner-Signature