B2B segmentation on steroids: Slice and dice your way to high-probability opportunities and repeatable sales plays
Most B2B startups do some form of segmentation analysis, but a lot of it isn’t that useful.
Usually we segment by company size, vertical, and buyer role. But if that’s where we put our pencils down, we haven’t done our jobs. Here’s why:
If you don’t know why — really why and under what circumstances and in what context — your customers buy, you can’t develop a high-probability pipeline and repeatable sales plays.
TL;DR: Robust customer discovery and granular segmentation leads to crisp marketing and efficient sales. Dig into these five areas using the Five Whys: 1. Use cases; 2. Pain points; 3. Objectives; 4. Technology tools; and 5. Organizational or process changes.
***
I joined a rapidly-growing startup a few years ago. When I asked why customers buy the company’s product, an observability tool that helped with the software troubleshooting process, the answer was, “They wanted a faster blah, blah, blah…” Not terribly informative. So we set up some meetings with customers and asked them why. They told us, “Because we wanted a faster blah, blah, blah.” Bruh! Still not useful.
So, we adjusted our approach and engaged more customers, this time asking them why in a deeper way: We used our tried-and-true customer discovery questions coupled with a technique we ripped off from Six Sigma, the Five Whys. It’s used to find root cause after a snafu, but we re-swizzled it for asking about use cases, pain points, adjacent tools, organizational changes, and more. We wanted to know the real, foundational why (or whys) our customers had purchased and were getting value from us. We collected their responses in a way that allowed us to segment prospects based on similar characteristics.
We already knew some things about our customers: They were typically mid-sized, fast-growing, “application-is-the-business” companies like e-commerce, gig economy, media, and enterprise SaaS that delivered software in an agile, DevOps-oriented way, and the buyers ran engineering, cloud infrastructure, DevOps, or Site Reliability. That information was good to have, but didn’t help us get smart about how we should market and sell.
Using our discovery process and the Five Whys, we surfaced several key traits our customers had in common:
- At least half of their application was delivered as microservices;
- Their engineering teams were decentralized;
- Each engineer was responsible for his or her own service, from code to test to deploy to debug;
- Each service was delivered independently and on its own schedule;
- They had or were trying to create a rapid software delivery process in which some services were deployed at least daily; and
- More than half of the engineers spent at least one-third of their time troubleshooting.
We also used our discovery process to learn our customers’ technology stacks, including which tools were on the rise or decline.
Knowing these characteristics, pain points, and coincidental tools made all the difference for our company. They allowed us to get tight in our targeting, message to prospects crisply, fill our pipeline with high-probability opportunities, and arm our team with a repeatable sales playbook.
***
Beyond firmographic data like employee count and company revenue and demographic data like buyer or user function or title, there is a treasure trove of segmentable contextual customer data that is waiting to be discovered. Here are five areas of exploration:
Area 1: Use cases
What is their use case for your product, and the context surrounding that use case? How are company or industry dynamics or external pressures changing that use case? In the vignette above, the use case wasn’t exactly application troubleshooting, but troubleshooting in the context of a high-pressure, rapid development process for companies whose applications were everything to them.
Area 2: Pain points
What pain points are they addressing? What’s the situation, implication, magnitude, cost, and “next best” fix for each pain point? In the vignette above, the pain point was that troubleshooting was time-consuming. Digging in using the Five Whys revealed how customers defined “too long” (one-third of work time for more than half of the team), the situation in which it happened (when at least half of the application was delivered as microservices and/or some services were deployed daily), the cost (too much time fixing bugs), and the implication (delayed application delivery). We learned that engineers’ troubleshooting time was extremely sensitive to microservices and deployment frequency. In other words, engineers who deployed mostly microservices-based applications with some services pushed at least daily spent a lot of time troubleshooting and experienced acute pain, whereas those who deployed mostly monolithic applications less frequently didn’t spend as much time troubleshooting and experienced less acute pain. Knowing the point of demarcation between acute and less acute pain allowed us to target companies in similar situations, and at the time when their pain was most acute.
Area 3: Objectives
Sometimes people buy products not to solve pain but achieve objectives. What is their objective for your product and beyond? What about their stakeholders’ objectives? Could any of their objectives derail your product? In the vignette above, the Five Whys revealed why “…a faster blah, blah, blah” was a must-have versus a nice-to-have. Most of our customers were trying to create or maintain a rapid software deployment process. The process frustrated engineers because they had to spend a lot of time troubleshooting buggy software before they could fix and redeploy it. Every minute they spent troubleshooting was a minute they weren’t spending fixing, much less coding or testing. This made them identify troubleshooting as the problem part of their process and set out to fix it. The overall objective — deploy software rapidly — led them to troubleshooting, which led them to us.
Area 4: Technology tools
Knowing what technology tools coincide with, complement, or clash with your product; which ones your product replaces or replace your product; or which ones simply happen to be coming or going when your product is being deployed can offer useful clues for segmentation. Here’s an example from the vignette above: Many customers reported replacing a certain alerting product at the same time they were investing in our product. It turned out that the same objective (creation of a rapid software development process) caused similar problems in the alerting part of the engineering value chain as in the troubleshooting part that our product addressed. Engineers who received alerts had to make the completely ridiculous trade off between receiving a complete alert (that was populated with all of the information they needed) or receiving that alert on time. We not only used this information to identify new alerting partners, but to prospect more efficiently in the early part of our sales discovery process.
Area 5: Organizational or process changes
One thing that sometimes gets ignored during the customer discovery process is organizational or process changes. Customers may forget to mention these dynamics or are simply unaware of their relevance to your product, but they are gold when it comes to everything from selecting SEO terms to creating sales playbooks. In the vignette above, the Five Whys taught us that the purchase of our product coincided with the decentralization of a company’s engineering team. Because individual or small teams of engineers maintained a single service soup-to-nuts, each would be responsible for troubleshooting, and therefore each would need access to our product. This led us not only to segment opportunities based on this organizational shift, but also price our product for frictionless sharing as well as emphasize in our messaging how easy it was to onboard new, untrained users.
Now over to you! Using a robust discovery process and the Five Whys methodology will put your segmentation on steroids, leading to crisp messaging, efficient selling, and a killer opportunity pipeline.