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Brace up all Product Entrepreneurs; InTech50 is back…

InTech50, iSPIRT ’s flagship event is back. The first two editions have been very successful and InTech50 has become the ‘must-go-to’ platform for enterprise CXO’s and product entrepreneurs. Over the past two years, we have hosted CXO’s and business leaders from global companies like AllState, Citibank, HCC Insurance, Standard Chartered, Colgate Palmolive, Time, AirTel, Yes Bank, Exide Life, Mother Diary and the likes. Here are some quick high points from the last two years of InTech50:

  • 18 enterprise deals that got originated and closed from conversations at InTech50
  • 42 enterprise PoC’s offered to InTech50 companies
  • 120+ innovation leaders (read: buyers & influencers) exposed to Indian product entrepreneurs

We have already managed to showcase over a 100 companies, and we have made 50 global investors and CIO’s travel to India to interact and associate with these companies, and happily so.

Here are a few portfolio companies from our past events – Capillary, Uniken, Seclore, Freshdesk, Reverie, Sapience, NowFloats, ToneTag to name a few.

Just to share the impact that we have created, and how these 50 companies have benefitted from this initiative, hear hear what some of them had to say –

“Intech50 is a phenomenal event. It is probably the highest RoI initiative we have ever participated in. With 50+ Global CIOs turning up, it is a great platform to validate your product. Met some of the largest enterprises, found use cases we weren’t aware of and closed marquee deals. Highly recommended!” Yamini Bhat, Vymo.in

“Intech50 was extremely useful in 3 ways. First, making a presentation of just 5 minutes to an extremely discerning audience helped us make our value proposition very crisp. Second, demoing our product to several heads of technology helped validate our product and use cases, and resulted in actual business deals getting signed. And most importantly, we were able to bag a large client with whom we’ve been able to co-create 2 completely new products. I wholeheartedly and highly recommend Intech50 to all B2B startups who have demonstrable products that are ready for large enterprises” – Ranjit Nair, Germin8

“Being a part of InTech50 2015 was a great opportunity for ToneTag. It was exhilarating when ToneTag was selected in the first batch as one of the top 10 products. The event gave us the exposure, guidance and support we needed. InTech50 enabled us to pitch our product to a global panel of curators and the media coverage we received was also been beneficiary to the company. Since winning InTech50, ToneTag has been expanding rapidly. We acquired many leads through the event that led us to PoC’s and commercial deals in the making. The resources we received through InTech50 have been invaluable as it has helped us build exciting partnerships with many in India and around the world” – Kumar Abhishek, ToneTag

If you are a product entrepreneur and your product is solving a problem for the enterprise CXO, InTech50 is your chance to showcase your product to the who’s who in the enterprise buyer community.

Apply before Feb 22nd 2016 and experience a bigger and better InTech50 in 2016.

To know more, click here.

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Creating a platform needs a broad vision and a long leash from investors– Ranjit Nair, CEO of Germin8. #PNHangout

Ranjit has a PhD in Computer Science from University of Southern California and is the CEO of Germin8. In this #PNHangout we had a chance to catch up with Ranjit on the challenges of building a platform and finding the initial market fit.

Ranjit-PRCIMSMarket research companies world over found conducting surveys about brands and products difficult. People were reluctant to take surveys and those who did take these surveys were not representative of the target audience, eg: housewives and retired folks instead of working professionals. We saw a trend where people would often go onto social media sites and/or company owned channels of communication such as emails to express themselves. Hence, as a solution to this market research problem we developed NLP algorithms which were capable of understanding opinions expressed in textual conversations. These algorithms were designed to perform functions such as topic segmentation, topic identification and sentiment analysis. Although these theoretical problems were interesting to solve, it was far from being a product that had much broad commercial appeal.

The push to create a market fit for Explic8

By March 2009, I had assembled a team to develop a commercial product that harnesses these NLP algorithms in order to draw actionable insights and leads from public and private communications channels such as social media and emails. To fill the missing features that could make this product commercially viable, I had challenged my team to build a working prototype in 23 calendar days — just in time for the General Elections in India. Our goal was simple, to analyse what people globally were talking about politicians and parties during the election and make this data available to the public.

This sprint drew us closer to creating the foundations of a minimum viable product which solved a market research pain point (i.e. reliability of surveys). But we knew that the technology we had developed could also solve pain points felt by customer service, sales and corporate communications. For example, this tool could be used for lead generation by a sales team by finding conversations where customers had expressed a stated or latent need for certain products.

An expanded vision could mean a larger product development cycle, but it was worth it

We knew that if we expanded the product vision to solve problems beyond just market research and in multiple verticals, we were setting ourselves up to be a little unfocused; instead of narrowing the focus on one specific problem, we chose to develop a platform that could be used in different applications. We chose this approach because there was no market player who had taken the platform route and attacking the larger market would make this product more feasible. We were lucky to have the support of our investors to back us up on this decision.

We, as a product company, were a little bit ahead of the curve where we sometimes ended up with features that the Indian market wasn’t even ready for. When we launched our product, we realized a lot of the features we built weren’t actually being used by our customers.  For example, we have a feature that allows our users to analyse sentiments not just at the brand level but also for each of the brand’s touch points. We realized that apart from a few brands, most were satisfied with just using the overall brand sentiment without concerning themselves about the sentiment for each of their touch points. We preserved this feature and as users evolved, this feature became one of the differentiators that is now used by most of our customers.

Hindsight is always 20/20 and as we went about from concept to production there were many ups and downs that I think are common with every start-up. We would battle between adding features that add functionality and features which made the product more useful, usable and scalable. I think if I had to do things a little differently today, I would have focussed a little more on marketing initially and a little lesser on building many features. However, we have reached a point where our product speaks for itself and customers from a variety of industries are interested in using Explic8.

Platform and Goals

We are now more than a product but a platform. Explic8 is one of the apps which reside on our platform and we’ve built it in such a way that it could be used in multiple use case scenarios such as analysing emails, chat conversations, etc. We also allow third party applications to use our API to develop their own tools. Analytics that comes from our app is very industry focused. For example, if you’re an automobile brand, then the insights you receive will be benchmarked against competitors using metrics and sources relevant to the automobile industry. Hence, the insights you get are highly actionable. The sentiment algorithm is tuned for each industry, for instance “unpredictable” in the context of a steering mechanism would be treated differently from “unpredictable” in the context of a movie plot. We are also in the midst of expanding our platform to encompass predictive analytics.

If you have any feedback or questions that you would like answered in this series feel free to tweet to me: @akashj