Price comparison and recommendation engines are almost commoditised. These apps generate static data on product price and specifications. This data is then used to understand the user based on the filters that they input for comparison. What if the system went beyond this and used data generated on different apps to make a persona out of the individual? Such a tool could become very powerful for brands to leverage. Mobiorbit Labs, a Bengaluru-based startup, is working on this ambitious project. By collating data of smartphone users through their app called Smartly.me, they could help brands understand their audience better. If a company like Canon, for example, knows that the smartphone user loves photography, based on the data collected from the device, it can then create personalised campaigns on Smartly.me to sell its products to the user.
Muralidhar Rajan, Co-founder, Mobiorbit Labs, says,
Our analysis can determine whether the smartphone user is a good photographer or an avid reader of startup news.
The startup's algorithm is not limited to users alone. Mobiorbit is building a platform where it will white-label the algorithm into apps built for retailers or for any company in the consumer business. The crawler takes stock of all stock keeping units (SKUs) in inventory and matches them with discounts and offers available, which can then be used by the store manager to engage with the customer intelligently.
This idea began out of an epiphany, born out of the thousands of interactions the three founders had while they were colleagues, in the dredges of an R&D centre of a large Indian smartphone manufacturer, between 2011 and 2014. Founders Santosh Prabhu, Muralidhar and Palash Patil realised that mobiles are second nature to humans. They quit their lucrative jobs to build the technology. Their premise was simple: if app consumption data could be gathered, collated and organised it could be a gold mine because brands would pay anything to create actionable insights.
The founders even met up with retailers to understand how the mobile could help manage inventory in physical stores. Muralidhar says, “We built the product in seven months. It’s the software and the data wrapper that makes the technology competitive.”
Mobiorbit launched its product in October 2015 and is currently working on making the persona ecosystem robust. Its server architecture has been built with Django and Postgress db. Its crawlers look at the time spent on each app and content consumed before making recommendations to users.
The business model
The B2C model, which is to deliver recommendations based on personas, is offered free to consumers. But the data is taken to brands and provided as a service. “We are a technology company that can capture data from a large set of users. We will not be consulting; the brands can partner with us to target consumers,” explains Muralidar.
The second business model is to sell the product as a service to consumer businesses which operate distribution centres across the country.
The B2C business model is supported by its app called Smartly.me, which has had 5,000 downloads so far. The startup is currently tying up with a few brands to sell the persona data. The founders have currently invested about $70,000 to build the software platform.
VC & competition’s take
The business model of Mobioribit needs potential scale on one side because it is dependent on consumers to download their app, which it can then use to collate data and partner with brands. On the direct to business side the company must tie up with brands and consumer businesses.
R. Natarajan, CFO, Helion Venture Partners, says
There are risks on both sides. The founders need to have the bandwidth to build robust technology and find customers at the same time.
There are several startups like Mysmartprice, Smartprix and PriceBaba with similar business models, but they are dependent on consumer filters for data. It is estimated that there are close to 20 companies trying to make this business into million-dollar opportunities in India alone. Mysmartprice has raised $11 million in two rounds from Accel and Helion Venture Partners. Others are yet to raise big money.
There is another startup called Voodoo Technologies, which allows the consumer who is looking at prices in one app to compare the prices on another app dynamically on the same screen. To make it simpler, if you are checking Flipkart, then the price of the same product in Snapdeal will appear as a window on the screen.
For Mobiorbit’s second business model (the B2B model) there is competition from a company called RadioLocus, which hopes to connect with retailers and provide them actionable insights based on consumer behaviour.
Mohandas Pai, MD, Aarin Capital, says,
Technology companies are the ones that will eventually become large enterprises. But one must remember that many will fail.
Nobody has built device-based personas. Everyone is building personas out of shopping habits on apps, which is where Mobiorbit can have an edge over others. The startup is looking into the entire app ecosystem on the phone before creating a personality. But their success depends on their ability to raise money, win consumers and tie up cleverly with consumer businesses which can give them long-term contracts. Fortunately for them, this could be the year for Business-to-Business-to-Consumer (B2B2C) business. They just have to go ahead and thrive.