Rich Green: The history of enterprise applications is you enter information in the application and you get to analyze it by looking at it and reporting on it. That’s pretty much as sophisticated as it gets.
In the consumer world, think about Google and how much information do you provide to Google versus how much you get out of it. The ratio is one to near infinity.
To really further CRM and relationships, you need to change the ratio of information that you input into the system versus the information that you can glean from the system. One of the first steps in all this is to dramatically change that ratio. It’s essentially a world search problem. You enter a small amount of information and your CRM system can go out and glean all sorts of information about companies, people, and relationships and build that model in the system.
Once you have that information, you can then refine it using machine learning technologies to provide the salient insights with regards to relationships, pipeline, sale history, and probabilities that are a generational change between where CRM has been and where the big CRM companies are right now.
Sramana Mitra: Is this already in your product or is this in the future?
Rich Green: This is in the pipeline. The first release will be addressing the mass search, import, and structuring of the large datasets necessary to enable machine learning techniques to be applied to that dataset. That’s underway. That will be a big shift in how people think about enterprise applications. Think of a millennial putting information on an enterprise application. They look at this and say, “Is that all we know?” It’s rather absurd given the state of technology and the market today. Changing that paradigm is the first step.
Sramana Mitra: I’d like to double-click down on how. Typically what we do is take products that are in the market and look at use cases of those products as the customers are using it. This seems to be a little bit ahead of its order.
Rich Green: I can give you some idea of it. There are a number of patent applications in flight, so I’ll provide a surface view. You have a marketing system that gives you a basic lead on an individual that ends up on the CRM. Then the CRM system goes out to a variety of data service providers. We haven’t announced their names yet.
They provide a wealth of company information, social information, and construct an organization tree. Suddenly what’s available to people who are using this CRM system is a detailed dossier of an individual that will allow you to provide unique contexts for follow-up activities, whether you’re reaching out to them in a marketing campaign or a one-to-one conversation. You’re deeply informed and continuously tuned into the state of that relationship.
This segment is part 2 in the series : Thought Leaders in Artificial Intelligence: Rich Green, Chief Product Officer of SugarCRM
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