Tomi raises $1M for real estate advertising

Tomi, an AI-powered platform that upgrades digital ads, raises $1 million from Phystech Leadership Fund and Begin Capital in seed funding. According to the founder and CEO of Tomi, Konstantin Bayandin, the company will use this fund to expand its platform.

Many companies have long and offline sales in industries such as real estate, financial services, and automotive that face difficulty in making full use of their digital ads for better business outcomes. As the outcomes are offline and the conversion rate is really low, companies modify their ads to clicks and leads. This results in a lot of work for the companies.

Tomi’s goal is to solve this with the help of transactions done on the customer relationship management system and collect online data via tracking pixels available on Tomi’s ad platform and website API integrations.

The company records 100 to 300 “positive outcomes” to teach machine learning models in an experiment. The service performs a “dry run” on Google’s and Facebook’s ad platforms to compare the outcomes of controlled experiments with monitoring the performance in various platforms, campaigns, and channels.

Bayandin was chief marketing officer at Ozon and worked in the digital marketing and technology department as the senior director at Compass. There, his focus was on predictive modeling. When he was working at Compass, he realized there were hardly any opportunities for most offline industries, which have long sales cycles compared to e-commerce.

Tomi wants to become an ideal platform for Google and Facebook ads by aiming at conventional industry verticals and lead gen marketing for companies with long offline cycles. There is a wide range of advertising tools; some of them do optimization and targeting of ad campaigns. On the other hand, other tools do optimization and predictive targeting, but they use third-party data in some way or the other, and only Tomi uses first-party data. Product-wise, Tomi is different due to their laser focus on conventional industries, which cannot use the potential of ad systems’ smart bidding because of a long sales cycle and low conversions.

Tomi’s customers pay only for increased customer lifetime value and results of the business. They can use an optimized audience for coming lifetime value and target upcoming visitors with very high intent. The platform works on a high load Google Cloud which processes 30 million hits daily.

The company’s learning algorithms learn through some positive examples from 100 or more than that. The models need to be stable regarding minor changes in user behavior so that the difference in prediction is small as it can be.

Bayandin claims Tomi to be the best platform for big customers, like real estate, financial companies, and marketplaces. Right now, it has 10 enterprise and midsize customers. The company built its platform with 8 people only, but now it wants to take it to 20 by the end of 2021. Their revenue from the product they just launched a year ago has increased four times.