Sramana Mitra: If you’re trying to do that, are you then saying that you are going out into the social web to pull all that data? For instance, my private bank is Morgan Stanley. Morgan Stanley doesn’t have any of that information unless they go into my LinkedIn graph.
Manish Sood: Even before you go to the LinkedIn graph, there is a lot of information within the bank itself. For example, when you bank with Morgan Stanley, they have information on the different kinds of accounts that you have. You’ve already provided information about who’s the beneficiary on those accounts. If you have a trust, who’s the trustee? Who’s the lawyer on that trust? You have also probably provided your place of employment. There is public information available about who else works at that organization. If you start connecting those dots even without stepping into Facebook or LinkedIn type of social media sites, there is a lot of information that sits within these enterprise organizations, but it’s in different silos and different applications.
At the same time, you’re also going in and banking with them at a certain frequency. You log into the website and do certain transactions. You go to the bank and do certain transactions. You have your advisor who comes to you and works with you on understanding some of your behavioral details that might be suitable for giving you a recommendation on where and what you should invest in. That itself, is a lot of information that can be condensed down into a very useful and worthwhile view that would help with the engagement that they want to have with you. The challenge is that it’s a disconnected view for them right now.
Sramana Mitra: You did the whole integration of the master data around all this into an architecture such that all this is brought together.
Manish Sood: Not just the master data, but also all the relationships around you to other organizations, people, and products. We route that to a single view so that it could drive engagement and compliance. It could also drive fraud analytics. That was something that the bank wasn’t able to do before in a very easy-to-use manner and certainly, not in a manner where they could bridge or use it both as an operational as well as an analytical system.
Technology in the past has existed as a division between those two areas where if you need an operational application, you need to go to the CRM system where users can log in and enter information. If you want to go to reports, then you have to go into the data warehouse to find out what kind of insights you can get. When you look at some of the modern consumer applications like LinkedIn, you don’t have to divide it into your dashboard or the place where you enter information. It’s all contextual, provided as a single application. In fact, that single set of data under the covers is not only driving the application that you use, it’s also driving the sales and prospecting application. It’s also driving the recruitment application.
That was the fundamental shift that we saw in the market, which is that data is emerging as a strategic asset. You have to be able to organize it in a particular manner so that it can enable new types of applications that can be created on top of it and provided it to the end users.
Going back to the journey, we enabled it as a pilot for the wealth management institution. We very quickly realized that in order for us to scale as an organization, although this was a good starting point, financial services wasn’t the right industry for us to focus on because they were not yet ready for the cloud. If we were to go into the financial services industry, we would have to primarily do it as an on-premise install.
That was the first pivot point for us. We made the decision to essentially look at the broader and the bigger opportunity where we would be able to provide this capability as a SaaS and apply it to different problems in other verticals that were more open to SaaS as a delivery vehicle, our ability to accelerate the growth of the company would be much higher. With that in mind, once we had completed the work towards the end of 2011, we spent the initial seed capital that we generated to take that same concept and bring it up as a multi-tenant cloud. We were able to do that within a period of 12 months and along the way, we were also talking to various prospects and pitching the concept to them.