Thought Leaders in Mobile and Social: Joe Langner, EVP of Mid-Market Solutions for Sage, North America (Part 5)

Sramana Mitra: Where does BlackBerry fit into all of this?  This is a segment that has high BlackBerry adoption.

Joe Langner: The devices we are writing to are those two [Android and iOS] at this point.  I haven’t seen the BlackBerry adoption as much.  They lost a lot of mind share in the marketplace.

I would like to mention another thing: nobody mentioned your focus on big data. There are two things we are doing which might be of interest. The first is a program we have been working on during the past several years called Sage Advisor. The vision of Sage is to be recognized as the most valuable supplier and supporter of mid-sized companies by creating greater freedom for them to be successful.  Our goal is to have the small to mid-sized companies recognize the tools and services that we bring and then do word of mouth publicity that we are a good company to work with, and we are helping them to be more successful.

This is a very customer-centric vision statement.  To realize it, we would like to translate the technical support to advice. Thirty-three thousand times a day Sage talks to its customers. We have the opportunity to add value to those conversations to build our relationships.  We see customers and technical support as a way of doing things differently than others. We are leveraging big data to do that. Our strategy involved first building the capability of using information. We designed a program called Sage Advisor where in all of our software we would build the capability to gather information about how that product is used. Customers have the choice if they don’t want this, but the vast majority do because they see the business value.

So, stage one was to create the ability to gather better intelligence on our customers. Stage two is to offer a better level of support.  Because we have more than six million customers, we benchmarked a specific type of performance our software should have. Sage Advisor then allows us to see anomalies between what our customers experience and what they should be experiencing.  This gives us the ability to proactively call them when we see things that shouldn’t be occurring. We can then let them know that there may be a way of improving the way their technology is supporting their business needs. We started this edition a few years ago with Sage 50. Since then we can call our customers and say, “Your software isn’t performing as it should.” It might be a network or an infrastructure problem, but we can now be more active in solving problems rather than just waiting for customers to be frustrated and call our support.

Sage is a software company and we sell through our partner channels. Most partners are small companies as well. Our average partner has from three to twelve employees. So, we sell to small businesses through small businesses.  As small companies, clients don’t necessarily have a large customer base which requires segmentation or opportunity analysis.  We took our data and looked at the attributes of customers to analyze the different solutions that Sage could position within a given customer. We asked ourselves, “What are the attributes of this customer? How many users do they have? How long have they been a customer? How much time do they spend using the current product that they have? What modules do they use or don’t use? Do the partners they are working with have expertise or not?”

We thus build a fair, custom model for the 11 products we have, with more than 190 attributes for each customer.  This way we can predict whether there is good potential for a solution. We came up with potential scores for all of our customers, and we segmented them for each of our partners.  Even though a certain partner may have 50 only customers and five opportunities for a single solution, we did all the legwork and the due diligence to say, “These are the five we think have the best opportunity for you.” So we started using the concept of analysis, trends and past penetration, to help enable our partners so they could improve their service and understand where there are opportunities or things that need to be evaluated. That is step three.

SM: What is the infrastructure behind all this?  Which data service are you working with?

JL: This is done internally.  There is a massive database with millions of records and thousands of attributes on each of those records, and we have smart people who are doing a lot of segmentation and analysis. I would like to mention the last part.  We can turn it around and be of higher value to our customers.  If you have six million customers, you can start to model common attributes like how many warehouses you should have, what should your inventory turnover be, or how much cash is typically held in the bank for a given industry. All this is on the aspirational side.  The next thought is, we can use the information as the customer is using the software in order to feed intelligence back to them. That way a Sage customer doesn’t have the perspective of only one, but the perspective of six million.  This is revolutionary. Our goal is to help our customers become more successful using this software. As the software learns from itself and as we gather more intelligence, we can be more accurate in our information.

This segment is part 5 in the series : Thought Leaders in Mobile and Social: Joe Langner, EVP of Mid-Market Solutions for Sage, North America
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