I’ve written quite a bit about the importance of defining our “sweet spots.” It’s really important, both from an account prioritization (think of all your account based marketing/sales strategies) and to make sure you are prospecting/qualifying the right deals.
Too often, the definition of sweet spots is far too broad or general. We may say: We’re targeting the financial services industry, or manufacturing companies, or any other segment. But any of these are huge. Financial services includes commercial banks, investment companies, insurance, hedge funds, credit card, financing and a number of other segments. Each of which are very different. Likewise manufacturing could be process, discrete, consumer products, electronica components, automotive, aerospace, basic materials, technology, medical devices, and on and on and on. Each of these is very different.
We also may characterize our sweet spots by size, for example, “We focus on the top 500 commercial banks in the world,” or “We’re focused on the SMB space ($100M to $1B).” Or we may focus on regions/geographies (though that is becoming less of a factor for many).
Developing a rich, multi-dimensional characterization of our sweet spots–the accounts we target, and the opportunities—their urgency to change, is critical in maximizing the effectiveness and impact of our marketing and sales programs. Focusing on this richly defined sweet spot maximizes our ability to identify and focus on customers who really are interested in learning from us–though they may not know it yet.
There are lots of ways to define them, the market segment (more specifically than financial services, as an example), “demographic” (e.g. size), geography, performance, cultural, and many others.
There are two areas, I’ve not seen much work in, that I think add a critical dimensions and richness to targeting accounts and, ultimately opportunities.
Roughly, these are:
- Customer solution maturity.
- Customer internal collaboration success.
Adding these to our sweet spot definition and our opportunity qualification criteria enable us to focus on the right customer within our sweet spots, at the right time–that is when they are likely to have a high propensity to buy.
I’ll address each of these at a high level in this post, then drill down on subsequent posts.
Customer Solution Maturity:
Geoffrey Moore, in Crossing The Chasm, popularized a version of customer maturity as outlined in the diagram below. There are all sorts of variations of this model, any one can be useful. But as we look at customers in our sweet spot, they may be all over the place in terms of their solution maturity. Some will be innovators–perhaps those are the guys who are developing their own solutions, because non exist, or they may be the one’s who are working with a start up on a cool new solution/technology. There will be others, regardless how big their problems, how compelling the business case will always be the last to adopt—and often it’s over their dying organizational bodies.
We can characterize each of the customers in our sweet spot based on their solution maturity. Depending on where they are, they represent better targets than others.
You’re probably wondering what I mean by solution maturity. Here I’m focusing on a category of solutions. For example, we might think of ERP solutions, Floor Control, Sales Automation, Marketing Automation, Continuous Flow, Predictive Analytics and so on. Solution acceptance will vary based on the relative maturity of the solution in the market place.
For example, in 2002 I was involved in founding an AI Based Predictive Analytics Company. Our sweet spots was within certain types of manufacturing processes, and in drug (pharma) discovery. Initially, we sent our sales people to call on all the very large companies in those segments. As you might guess, there was a huge amount of interest by virtually everyone in these segments, we invested lots of sales time, lots of engineering time in having conversations with lots of companies about our solution and what it could do for them. But we struggled to qualify people who had a serious intent to buy.
We discovered, the things we were talking about were very new conversations in the target markets, customers were interested in the ideas, but not ready to move–until we found the right customers. These were the Innovators, and some very Early Adopters. These were the people that really understood the power of the solution and were ready to implement immediately. As we understood the Innovators, we began to see the certain characteristics. For example, they were trying to create similar solutions on their own. There were a small number of characteristics that set those types of customers apart from everyone else. While lots of people were interested, if they didn’t have those characteristics, regardless how compelling our solution was, they just weren’t ready to buy.
We started focusing all our sales and marketing activities on those customers. Our success rates skyrocketed. We stopped spending time with customers who didn’t fit these characteristics. We knew they were interested, but just would never be ready to buy.
Fast forward to today. Since 2002, the application of predictive analytics solutions in our segments has skyrocketed. There are more alternatives available, there is greater comfort in a broader set of customers. Right now, these solutions are skyrocketing in customers that fit the Early Majority maturity level. We’re working with the innovators on the next generation of products, we are upselling, cross selling the early adopters, and our new customer development is focused on the Early Majority. We aren’t wasting our time on Late Majority or Laggards, unless they send us an unsolicited PO. Even then, we are careful because we know there are huge support requirements.
The recognition of our customer solution maturity was critical in refining our sweet spot definition, targeting the customers with the right solution maturity.
It’s important to recognize the difference between solution maturity and enterprise (company) maturity. Some companies may be early adopters in certain types of solution areas (say analytics), but they may be late majority in other solution areas (say continuous flow manufacturing). So it’s critical that you characterize solution maturity, not enterprise maturity (though sometimes they are related.).
Solution maturity also refers to the solution category, not necessarily to your specific solution. For example ERP solutions are very mature, late majority and laggards are adopting those solutions. If you come out with a new ERP solution, unless it’s very disruptive (which means you’ve created a new solution category), your sweet spot is the late majority and laggards.
Customer Internal Collaboration Success:
This is another dimension of targeting your customers, focusing on those that will have a higher propensity to buy. In Challenger Customer, and other research, we’ve learned about how difficult it is for the customer to buy. It has nothing to do with selecting a solution, but organizing and executing their internal opportunity/problem solving and buying processes. The inability of teams to align priorities, differing agendas, points of view and to agree on and execute a plan ends up being a key to the customer inability to change or a no decision made.
With a little customer knowledge (for example in our account planning), we can start characterizing our customers based on their success in getting things done. We can look at customers who just seem to be successful. More projects are completed than those that fail. When they decide on something, everyone jumps on the bandwagon (regardless of their previous point of view) and they execute. We can see, with some external indicators, complemented by information we can pick up when we first start engaging and account, those companies that are very successful at internal problem solving, project execution, and getting things done.
As we think about where we will have a higher success rate in driving a change initiative that involves buying our solutions, we are likely to be most successful in prioritizing those accounts having a high ability to get things done. They may or may not choose us, but we know they are likely to buy. Contrast this, with organizations that may be biased to us, but they just can’t get out of their own way in figuring out what they want to do, doing it, and buying.
This doesn’t mean, we ignore those customers who have difficulty getting things done. It means, we probably prioritize those that can get things done higher. It may cause us to think about how much we want to invest in those accounts that struggle. They will eventually buy–if only out of competitive pressure (refer to the Crossing The Chasm Curves). We may decide to focus first on those that get things done. The likelihood of No Decision Made will be much lower with those, additionally, the time we invest in helping facilitate and move them through their opportunity/problem solving and buying processes is likely to be much less—simply because they are prewired for success.
Win Rates/Sales Cycles:
Focusing on customers at the right solution maturity and internal collaboration levels has phenomenal impacts on win rates and sales cycles. If we go back to my predictive analytics company, until we figured out the solution maturity characteristics our sales cycles had the potential of being endless. We had interested and intrigued customers who wanted to talk about weren’t at a maturity level to move forward. So we talked and talked and talked.
When we discovered the secrets of customer solution maturity, things changed. Customers were very purposeful, they wanted to move, sometimes (because of the complexity of the POC’s) they wanted to move faster than we could respond–which was a great problem to solve. Coincidentally, most of the customers had, for this very narrow space, very good collaborative problem solving approaches.
As a result, we saw both great sales cycle time reduction (measured in months as opposed to millennia–or at least that’s how it felt). We also saw great win rate improvement.
But you already knew those things happened.
The real magic happened later. As we moved to customers at different solution maturity levels, for example as we shifted from Early Adopters to Early Majority, we saw even further sales cycle reduction. A few things had happened. We understood customer problem solving and buying processes better, so we could more effectively teach the early majority how to solve their problems and buy. The community engagement was much greater, so more customers and people were talking about these solutions, the perceived risk was lower, the general knowledge/comfort level was higher. Finally, the proof points, the business justification from our early adopters were very solid. All of these contributed to our ability to compress the sales cycle even further. And as you would expect, win rates continued to climb (but we also face more competition, so there were some other issues at play).
You can see the same thing with customer internal collaboration success. As more people in the market adopted these solutions, as more general knowledge of these solutions and how to select these solutions became visible, it becomes easier for people to align around making a decisions. Again, in customers that are less adept at getting things done, once they see others preceding them, the ability to align themselves and move forward becomes easier.
While it’s a crass perspective, one can imagine the very last customer. The biggest laggard, the most dysfunctional in getting things done. At some point, just to survive and compete, they become almost forced to buy.
While I may be stretching that last point a little, it’s pretty easy to see that by prioritizing accounts and opportunities around these dimensions, over time, we see much higher sales effectiveness, sales cycle compression and win rate improvement.
Conclusion:
We maximize our ability to help our customers achieve success, as well as our own by being viciously focused on the right accounts, the right opportunities, at the right time. We want to identify those accounts and opportunities where the likelihood of success now is very high. Richly defining your sweet spot, adding dimensions of customer solution maturity and customer internal collaboration success will maximize your success and focus you on those people who are both most receptive and prepared to act on your insights.
I’ll be writing more in the future, but would love your ideas and points of view. I’m particularly interested in thinking about the KPI’s or other indicators that help us better understand and characterize where a customer might be in their solution maturity and their abilities to get things done. I believe we can apply analytic tools to help us in this process.
Imagine a stack ranked account list based on fit with your sweet spot, fit with customer solution maturity, fit with customer collaboration success. Then it becomes very easy to start prioritizing your account and opportunity development efforts. You can more appropriately target your messages and account based marketing programs.
