How this consulting firm digs data and ensures marketing success for businesses

Three year ago, Sandeep Mittal, while working with a direct marketing company, found that Indian firms had very little support with building their analytical capabilities. Banks and Telecom firms had in-house teams, but most other organisations who were dealing in data were simply not leveraging it to its full potential. Sandeep had already spent many years in data-driven direct marketing; taking those skills and broadening his horizons to analytics was not a big step. So, he decided to set up Cartesian as a "precision marketing" division. Today, it had grown into a full blown analytics firm.

Launched in 2009, as a part of an agency group, before going independent in 2014, Cartesian is a consulting firm that specialises in marketing analytics. The venture works with businesses across industries to help them improve their use of decision sciences for their marketing efforts.

“My wife Shikha and I had been using data to make marketing decisions for years; there seemed a need that nobody was really filling in the Indian market. So, we started up with an India market focus. This was quite atypical for any analytics startup,” says Sandeep, 39, CEO and Co-founder, Cartesian. He holds a degree in engineering and an MBA from IIM Calcutta. Shikha Mittal joined Cartesian in 2013. She has over 13 years of experience in marketing, CRM, loyalty and direct marketing across organisations like P&G, JWT, and Direxions.

When business kicked off

When he started out, his world view was quite narrow -- restricted to CRM/ direct marketing work. Sandeep says that over the past few years, things have broadly changed, and so has his analytics strategy when it comes to big enterprise.

“A big goal initially was convincing ourselves we could be an independent analytics firm and run it profitably. When we went independent, we were coming out of a lot of structural change,” adds Sandeep.

After going independent, the startup had additional running costs. It invested in growth rather than cutting costs. Though the situation was tough, they decided to focus on profitability and went on a client-addition spree. This had a psychological advantage as it made everyone in the firm feel that the company was on top of the world. And the idea worked… “While we used to usually see 3-4 clients being added a year, we added 18 in the next 12 months. We had some amazing support from the shareholders, they put in everything needed – capital, connections, and moral support,” says Sandeep.

Growth comes with challenges

According to Cartesian, the main challenge now is managing fast growth. Going from 50 to 150 people in two years is challenging – 100 new people and 30 new clients is very tough to negotiate when your offering is consultative.

On the product and offering, the startup was clear that 2014 (its first year of operation) should be about customer analytics. But 2015 had been about adding new work in marketing analytics, web analytics, pricing and optimisation, and all kinds of new tools and methodologies.

Also Read: 15 Indian Big Data companies to watch out for

The other challenge is margins, which are low in the Indian market. The only way is to win new work from the same clients and bring in international revenue as balance.

“I think we’re taking solid measured steps. We are now adding tech skills that will complement our analytics and consulting skills nicely. The focus is also shifting to developing IP that we can bake into solutions; we have had some very nice early success on that front with some customer lifecycle management work we are doing for clients,” says Sandeep.

Initial investment & revenue model

Starting out with around Rs 2 crore investment from the shareholders, the startup invested in building infrastructure and the team, which went from 40 to 70 people, and then crossed 100 in fairly rapid steps. The other big investment has been in the APAC market; they now have an office in Singapore and are doing work in four countries in the region.

Its service is based on the project fees model – clients use the service for their customer and marketing analytics and the firm invariable becomes their intelligence cell for all marketing-related decisions.

“We also like success-based components as part of our fees; clients set us a business goal and part of our fees comes from meeting that goal. In some cases, it’s as explicit as taking 1 per cent of the incremental sales our analytics-led interventions drive,” says Sandeep.

Market size and competition

According to NASSCOM, the analytics market in India is expected to more than double to $2.3 billion by the end of 2017-2018.

Experts say that the market is one that will constantly surprise you with its size. You can’t really pin down the ways in which organisations will consume data and analytics, and the need seems to be growing all the time.

When asked about market opportunity, Sandeep says that size is a strange thing to crack and is not the main driving force for him. Right now, his goal is to get to the position of the best known and best regarded analytics services provider in the Indian market. He claims to already be on course in the APAC market.

Similar firms like Hansa Cequity, Affine, Semantics3, Convergytics, Fractual, Mu and Infinite Analytics, are helping the market gain maturity.

Also read: Ratan Tata backs Infinite Analytics

On competition, Sandeep says, “It isn’t really a cut-throat competitive market we’re playing in. The bigger names out there like Fractal and Mu are not really competition for us at this point. They don’t play in the markets we do at this point, but I’m sure that will change once we look at the US market or once they look at India and APAC.”

On product roadmap

The venture is building out solutions for CLM (Customer Lifecycle Management) and around Genome mapping and Semantics.

“As a complete offering, the roadmap is about getting relevant to the entire enterprise and being able to guide them on an analytical-maturity journey. We aim to provide guidance to organisations on how to structure themselves to become good consumers of analytics,” concludes Sandeep.

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