Sramana Mitra: You said you were going to do a couple more customer examples. Are you going to do one from the CRM side? Let’s hear about the deal cycle optimization.
Sameer Patel: CRM will be an interesting scenario. There’s a customer,Kaiser Compressor, who are a large manufacturing organization in Europe. Kaiser was going through a business transformation where their business was going to move from a manufacturer of products to a services business. Customer relationships are going to be at the center of what they do, not just the product they sell.
It’s about customer experience. It’s also about the revenue they can make on services but customer relationships and customer service will trump all other aspects in the next phase of their business over the next couple of decades. To make that kind of account transformation happen, you need to do a couple of things. One is you need to break the walls in silos between the support-related areas where you interact with a customer and the sales related areas. The customer knows both those sides and they cannot deal with silos inside your organization where a sales person calls a customer to sell a new product but the customer says, “Wait, I’ve got these five support issues on the product I own right now. Why aren’t you solving them?” You can’t really turn around and say you don’t know anything about them.
What Jam does is it becomes that one unifying layer that sits on top of SAP CRM that brings in all of the relevant service information, support, and sales and opportunity information into one place. The account teams can come together and understand, holistically, answers to questions like where are we with these customers? Where are we on this account? Are we at the right point where we should be selling new? Should we be taking out time and fixing problems and support issues they have? And you bring a very cohesive account-centric view of the customer versus a siloed, functional view that most organizations have had. Jam will relay across both those functions to pull those information out. That’s one.
The second is, customers are so well-versed today on our products and services that when they call, who they want to really talk to are experts inside the organization who know the details because it’s probably a very technical question they have. What Jam does is it allows the front-line to tap into the internal networks deep inside the company and find those experts who could support the customer and resolve such problems.
The third one is distribution. More and more organizations, including Kaiser, are looking at improving their distributor landscape. They have over a hundred big distribution partners in the manufacturing space. The idea here is to reduce latency around product know-how and expertise across the partner base because the partner base is as important as the direct sales base. So, they’re leveraging all the external functional capabilities that Jam has for partner relationship building combined with CRM data so that the business context is not lost in all the opportunities you’re working on with a partner. But you have the capabilities to build an ongoing relationship where there’s an ongoing sales enablement, sales training, and knowledge sharing so that you’re not dealing with heavy peaks and valleys every time there’s something to sell.
All these things don’t indicate that you should become social because it makes you more productive. These are very discreet, either cost or revenue maximizing opportunities that they’re looking at on leveraging Jam as an overlay on top of traditional CRM.
Sramana Mitra: The kind of scenarios that you are describing, I imagine that you’re basically using your vertical sales organization to sell these solutions. What kind of ROI have you been able to identify for this? You have described a bunch of use cases where you’re superimposing Jam on top of a particular vertical, horizontal intersection point in the manufacturing industry. Distribution, in general, is one use case.
Sameer Patel: The use case is that the ROI we are actually looking at here is centered around these traditional metrics. At a programmatic-level, Jam will tell you about the number of users and the number active. But the metric that we are looking at here are for something like employee on-boarding in sales. In certain industries, especially high-tech, it can be between 8 and 18 months. How are we actually shaving off 15-20% of that on-boarding exercise because when you use Jam to on-board your sales organization, the sales team will immediately know who to network with and the product people they need to get close to. You start shaving off typical ramp-up time which is a very important sales metric.
The second one is on the enablement side. In the context of sales, every quarter, the products, solutions and solution definitions change and the sales team need to get trained over and over again. There is a standard metric that exists around sales enablement and sales strategy in the sales op scenes, as well. What is the time to sales enablement? What is the latency time between release of new products and how quickly sales are able to go out and push that? We’re looking at trying to shave those times.
These solutions went in the market three quarters ago and we are now at the time where we can start to look at establishing. We’ve got the baseline data and now we’re looking at working with exactly those kinds of metrics with our customer council to see what those specific metrics are that we can continuously break down. These aren’t new ROI metrics; harmonizing the metric is the story here.