Taking the slow and steady route

By Sharmila Ganapathy August 2, 2018

Customer base and revenue model

Taking the slow and steady route: Page 2 of 2

Currently, LotaData works with telcos and with app developers to collect data, for example via a news app or navigation app. In addition, they work with app publishers.

“We’re starting to work with cities, we work with the cities of San Francisco and San Leandro and we collect data from them. There are many different sources of data coming into our platform; once the data comes into the cloud, we then massage it, and it goes through the AI [artificial intelligence] and creates insights for a variety of industries,” Apurva explains.

Their main clients are ad agencies, ad networks, brands -- such as hospitality, food and beverage, etc. He gives an example. “If you come to us and say: ‘I want coffee lovers in Kuala Lumpur, because I want people to drink more coffee on Thursdays and Fridays’, we can come to you and tell you what that cohort might look like for people who have been to KLCC and Aquaria, for instance.

“The platform is continuously processing mobile location data from mobile devices, so brands and businesses can come to us and ask us what the footfall patterns are for all the restaurants in KL and we can present that to you. SMEs for example, can have some very deep insights at that point.”

He adds that LotaData has close to 100 customers now globally, mainly in North America and Southeast Asia. “Our oldest customer is a telco from Asia, for two and a half years now,” he says, adding that they aim to be profitable by the end of this year.

As for the revenue model, LotaData operates on a software as a service (SaaS) model. They have a monthly subscription model that is tiered, depending on the depth of insights needed. Their rationale? Building long-term engagement with customers, Apurva says.

He adds that they realised very quickly that government use cases are very strong for their platform. “So, I embedded the company in the San Francisco mayor’s office. They hosted us for three months, the reason for that is for us to learn how the public sector works -- what their needs are and how the processes work.

“We were also in the San Leandro office for a few months. Once we were with those two cities, we were able to produce insights for them and a new platform called CityDash was born,” he explains.

Their government clients include the City of San Francisco, the City of San Leandro, Mountainview, California; a Dallas suburb and they also currently talking to the Singapore government. In Singapore, LotaData is hosted by GeoWorks, an industry centre to promote geospatial innovation and business growth in Singapore.

Expansion plans and growth strategy

When asked about their growth strategy, Apurva points out that LotaData “has been global from the get-go”. Apart from the founding team in San Francisco, they have a team in Brazil, and more recently, Singapore. The plan is to have a team in Bangkok very soon and the total staff headcount will be up to 16 people by the end of this year, Apurva says.

“We were always a US company, but I realised that the fastest way to grow in Asia might be to go through an accelerator and SOSV-MOX was a great way to establish the Asia side of our business.

“Expansion is everything we’re focused on right now. We are focused on growing in Southeast Asia for the rest of 2018 — Singapore, KL and Bangkok are our top three focus areas right now,” he shares. He adds that LotaData is also targeting major metros in north India, as well as Taipei this year. Beyond 2018, the company is targeting South America and Europe.

Data and privacy

How do they assuage customer concerns surrounding data privacy and security issues, though? Apurva explains that as soon as the GDPR was announced, they rushed into Europe. “This is because one of the strengths of our platform is we never collect your name, email, date of birth, phone number, credit card data…literally nothing that identifies you personally.”

“When you work with AI and machine learning, you want to do it in a way that is as anonymised as possible. It is all inference-based, not deterministic. So, we would look at your behaviour patterns, identify if you are probably male or female. We could work out your commute patterns and probably figure out where you work. We’ll look at your shopping patterns and study your tastes and affinities and infer your income level based on it,” he adds.

Potential clients however, have not been so ethical. Yew Leong Lee, who heads the Singapore operations of LotaData, says they’ve have turn down such clients.

“If you talk to clients, in Asia there is no GDPR so some want to know exactly who their customers area. So, we tell them our approach but they want things like the customers’ phone numbers. In fact, we’ve had to turn down business because we would get into trouble if and when their government takes up other privacy protection acts or GDPR.”

“We had an ad agency that came to us and wanted to use location insights to find out if they were placing ads in a specific area, would customers actually turn up in the store? For them, they wanted more customer data such as who are they, their numbers and wanted to contact the customers. We declined that customer.”

He explains that as consumers themselves, they value customers’ privacy. “We don’t mind giving some information; but it’s about how you use the information given to you, we respect customers’ sensitivity,” he concludes.

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