Introduce your business and what you do there.
I’m the co-founder and CEO of Dataflik. We provide marketing data to real estate investors and agents. We predict what homes will sell off-market to investors and when to sell on-market with an agent. Therefore, agents can use this to generate more listings.
What challenge were you trying to address with NineTwoThree Studio?
As a startup, we couldn’t afford a CTO, so we needed to scale our development staff.
What was the scope of their involvement?
NineTwoThree Studio has built our UI, our dashboard, and all our algorithmic models for real estate agents. They work on full stack development on the UX/UI side, machine learning, and data science. Our largest projects are between 2,000–3,000 hours.
Our internal team works on prototyping, and NineTwoThree Studio implements the automation and architecture of our company. They primarily use Figma for the UI. The development stack is a combination of 6–7 languages, including AWS, React, and SQL.
What is the team composition?
We work with eight teammates: Paul (CTO), Andrew (CEO), a project manager, a QA engineer, two full stack developers, and two machine-learning software engineers.
How did you come to work with NineTwoThree Studio?
I found them from a PPC ad.
How much have you invested with them?
We’ve spent about $350,000.
What is the status of this engagement?
We started working with them in March 2022, and our partnership is ongoing.
What evidence can you share that demonstrates the impact of the engagement?
Thanks to the algorithm that NineTwoThree Studio has helped us construct, we predict accurately about 60%–70% of home sales. We’re one of the top five companies in the industry. We’re pretty happy with that, and it gets better every month.
How did NineTwoThree Studio perform from a project management standpoint?
NineTwoThree Studio has been great. They’re pretty integrated into our daily staff meetings and work. Before them, we had a satellite office and a lot of overseas development. However, the language barriers were too rough, and communication was poor, so we swapped agencies.
We use Slack for our daily conversations and a combination of Google Meet and Zoom for our video calls. Additionally, we use monday.com for project management.
What did you find most impressive about them?
The biggest difference marker is their knowledge. The team that supports and executes the implementation has vast knowledge and experience. Moreover, the founding staff is a treasure trove of insight, and everyone is incredibly strong at implementation.
Are there any areas they could improve?
No, I don’t want to touch anything. If it ain’t broken, don’t fix it.
Do you have any advice for potential customers?
Outline exactly what you need in thorough detail and take notes of everything. If they understand your vision well, they can add a lot of value.
Right now, real estate wholesalers have to spend a great amount of time and money towards finding potential motivated sellers in residential real estate markets. Wholesalers have to research potential sellers for the purpose of generating a mailing list to send out hundreds to thousands of letters to find the right person that is willing to sell their property. These lists are often vast with a low conversion rate - the current systems in place are costly, demanding, and inefficient.
DataFlik provides a massive competitive advantage for real estate businesses by using AI-powered List Stacking and Predictive Modeling to focus marketing efforts on the owners that are most likely to sell and generate the highest return possible. NineTwoThree created a machine learning model that has the ability to generate a motivated sellers mailing list that is focused and has a higher degree of confidence as compared to traditional methods.
DataFlik had to provide a large amount of data to create an effective machine learning model. The real estate data needed to achieve the desired goal is extremely expensive. We had to prove that our proposed model will achieve its goal of generating an effective motivated sellers mailing list - without developing the full model - to justify the purchase of such data.
Processing the data was another challenge, because producing fast results is technologically complicated and demanding due to the sheer volume and breadth of the data we received. It consists of millions of properties across the US and each individual property has about 1,700 data points. We had to find a way to efficiently process the data in a timely manner to produce a working baseline.
Processing the data was another challenge, because producing fast results is technologically complicated and demanding due to the sheer volume and breadth of the data we received. It consists of millions of properties across the US and each individual property has about 1,700 data points. We had to find a way to efficiently process the data in a timely manner to produce a working baseline.
DataFlik had to provide a large amount of data to create an effective machine learning model. The real estate data needed to achieve the desired goal is extremely expensive. We had to prove that our proposed model will achieve its goal of generating an effective motivated sellers mailing list - without developing the full model - to justify the purchase of such data.
DataFlik is revolutionizing real estate investment business marketing operations. NineTwoThree successfully created a machine learning model that generates prioritized lists of motivated sellers faster and more accurately than a human expert. This offers a tremendous advantage by lowering marketing costs with better targeting that allows them to close more deals. We are currently working with DataFlik to continue to provide the best for their customers.
Click here to learn more about DataFlik and view the website we designed for them.
