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When B2B companies first start experimenting with utilizing data to enhance their sales efforts, they often take a very product-centric approach. The temptation is to create an Amazon.com-style correlation engine, where they can make suggestions based on what “customers like you also bought”.
However, in the B2B world, where sales are based on outcomes and complex solutions, a different approach is needed. So what’s the hidden key to a data-driven sales strategy in B2B? Don’t start with the data, start with the problem.
In order to see these patterns, dedicated analytics resources will most likely need to be applied. The clear best practice is to make Data Analytics teams as centralized and independent as possible, according to TSIA’s findings in multiple studies. By giving Analytics teams access to the multiple sources and silos of data used by different functions at your company, and a charter to see how everything fits together, they can make the biggest impact on multiple metrics, including revenue growth.
However, TSIA has observed that Analytics teams have a tendency to approach the problem of account intelligence for customer growth from a data scientist’s perspective. They look for correlations between data elements to find common patterns and combinations of products that are often purchased together.
It is TSIA’s clear and strong guidance that business leadership must play an active role in guiding the efforts of the Analytics team as far as what they’re looking for and how they go about it.
For data and analytics to be useful in a complex enterprise business setting, such as data-driven cross-selling, business leaders need to be proactively involved and provide guidance to the data and analytics resources assigned to help them on the triggers they may be looking for. It is TSIA’s clear and strong guidance that business leadership must play an active role in guiding the efforts of the Analytics team as far as what they’re looking for and how they go about it. As you’ll read in the next section, correlations are wonderful, but direct links between problems and solutions are much better.
So, what should your data and analytics teams look for and where should they look for it when exploring a data-driven sales strategy? First, start with one of two elements shown on the bottom tier of the triangle represented below.
Leveraging account intelligence for customer growth.
The best place to begin should be with a known problem. What are the most common problems that your Services teams are solving? What challenges do you know your customers are having, either with the usage of your offerings or with their goal of meeting their business outcomes?
As you investigate these questions, remember this critical piece of guidance: This must be a problem that everyone involved with the transaction can clearly understand and articulate: Sales, Services, your Analytics team, and most importantly, the customer.
Complete offers are offers created by suppliers that contain the necessary technology, services, data, and analytics to ensure the customer realizes value and achieves a desired business outcome.
The next question to ask is whether your company has a defined offering that solves the known problem. Do you have a solution that is packaged and cataloged? Does it have defined pricing and a standardized SLA.
TSIA’s Thomas Lah defines a complete offer in this way: “Complete offers are offers created by suppliers that contain the necessary technology, services, data, and analytics to ensure the customer realizes value and achieves a desired business outcome.” Does everyone understand what you’re selling and what they’re buying? Can you articulate the pricing and how a customer makes their purchase and what they get for it?
This is where the partnership between Sales, Services, Product Management, and the Data Analytics team comes into play. Once you’ve linked your defined offering to a known customer problem, your next question is, “How do we know the customer is having this problem?” or “What is the indicator that would show they are a good candidate for this offering?” Usually, this sort of analysis doesn’t require Ph.D.-level analytics.
Many of the data-driven indicators utilized by TSIA members can be found through basic reporting and simple analysis. If business leaders can tell their Analytics teams what to look for and give them a general idea of where to look, they can easily find the most likely candidates for upsells and cross-sells of these defined offerings.
This is an exercise that TSIA has walked multiple members through, and it’s a task you should undertake, even if you’re not looking to leverage account intelligence for customer growth. Chances are that most of the challenges your frontline-facing teams are dealing with are ones that surface over and over again. So, as an exercise, call your team together and ask them all the questions I mentioned above. Better yet, see if you can find it in your data, using whatever codes or structured data you have. From there, you can figure out if you have offerings that solve those problems, and then ask how you’d know the customer is having them.
On August 23, I’ll be doing a webinar on the topic of data-driven selling, where we’ll go deeper into these topics. Register and save your spot for “Data-Driven Selling: A Different Approach” which will include a live Q&A session.
I have also written a corresponding white paper on this topic for non-members, which can be downloaded here. A more detailed version is available for TSIA’s Expand Selling members, found here. Also, TSIA members have access to a myriad of information on data and analytics, including the research insight, “TSIA Consumption Analytics Framework” written by TSIA’s Jeremy DalleTezze, Ph.D., which is a great resource for more in-depth learning. This is a topic worth exploring, and one that can help you grow revenue efficiently and effectively.
Post Date: August 15, 2019
Steve Frost is the vice president and managing director of revenue research and advisory for TSIA. He also serves TSIA’s vice president of expand selling and subscription sales research. Throughout his career, he has held various leadership and business development roles at companies like Google, Netscape, and Loudcloud, helping them define their go-to-market strategy and business development tactics. Steve is dedicated to helping technology organizations grow their services, subscription, and XaaS revenue by optimizing their practices for growth throughout the customer lifecycle.
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