New ways to identify new market segments

Every company that looks to enter a new market segment faces the same struggles: understanding the true total addressable market (TAM) and identifying the target accounts most likely to engage. There’s never been a handbook for this, no way to ensure that a company with strong market/product fit in one segment will meet any success in another.

So revenue leaders rely on certain methods that, on the surface, make intuitive sense. But what we propose at Rev is to move beyond “intuition” and put data science behind these decisions. We want B2B companies to enter new market segments with the highest probability of landing new customers.

Our whole thesis is that if you can understand the underlying dynamics of how companies operate, you can identify your true ideal customers, even if they belong to entirely unexpected industries—thereby overcoming the common challenges revenue leaders face when entering new market segments.


The old ways are based on assumptions

The traditional methods for moving into a new market might work sometimes—the same way a broken clock does. The strategies themselves, however, are follies.

These are some of the more common less-than-successful practices we see, all based on assumptions made with the best information typically available.


Folly #1: Adjacent markets make for strong prospects.

We have a lot of sympathy for this assumption: if your current market segment is successful, an adjacent one will be too. Why not? The two markets look similar and have similar needs. You won’t have to tweak your messaging or your marketing much. The new customers might even be familiar with your product already.

Just because your product fits the apple vendor market, though, doesn’t mean it will necessarily fit the orange vendor market. The way those two business types operate under the surface differ in a lot of ways. Assuming they are both ideal target markets is based on the assumption that all fruit vendors are alike, when in reality they are… well… apples and oranges. 

It’s not as easy as we think it is to identify a new market and build a go-to-market program around it. Targeting adjacent markets is grounded in the assumption that lookalikes are also act-alikes. Companies fail when they pivot to adjacent markets without understanding their underlying behaviors and practices.


Folly #2: Rely on firmographics to build ICPs.

Oftentimes, when entering a new market, a company will pull a list of all the potential customers with certain firmographics: they fit a particular vertical, within a particular range of headcount or revenue, and so on. Then the company makes the leap that they’ve identified their total addressable market based on these firmographic parameters.

Within that strategy, we also see companies build their TAL based on names they recognize. Familiarity as a substitute for fit.

However, a target account list based on firmographic parameters is shallow. Just because a company matches certain (relatively superficial) qualities does not mean they are likely to become actual customers: firmographics tell you next to nothing about how a company behaves, or how they actually compare to your existing best customers.

If your ICP is shallow, so is your strategy. And firmographics by nature do not dig deep into a target company. Building a target list this way is like thinking you can find your soulmate by looking for five particular traits, when really so much more than that has to add up.


Folly #3: Fail faster in targeting first accounts.

All of us who have worked with startup companies know the notion of failing faster. The flaw with that mentality in breaching new markets is that the failing only matters if it’s in the right direction—and all too often, because of the previous assumptions, the first target accounts are the wrong ones.

This is the first-mile problem: if your first ten accounts fail because you targeted them for the wrong reasons, you just walked a mile in the wrong direction. The market might still be a fine fit! But these prospects were not.

Walking in the right direction, where you can still learn from failing fast, starts with high confidence in the target account list. Which can only happen when you are not polluting yourself with bad data from the start.


New ways are faster and better informed

So how do we start with good data? How do we start with an informed sales strategy instead of best-guess assumptions?

At Rev, we use modeling techniques based on company behavior to enhance the probability of understanding target markets and getting things right, right away.


Data that digs deeper than firmographics

The B2C world has figured out that demographics don’t do enough to understand customers, so it has developed psychographics. The B2B world lacks that same sort of insight, so we developed exegraphics.

Exegraphics, in short, are pieces of information or characteristics that convey how a company executes its mission. Our AI-driven modeling technique looks at everything from company messaging to hiring boards and employee resumes to understand how a company functions, how it changes over time, and how it compares to its peers—and it examines millions of data points to build a clear picture of what makes your best customers your best.

(For a more in-depth exploration of exegraphics, read What are exegraphics?)

When you understand the exegraphics of your best customers, you’re better able to create a true, working ICP—one that goes beyond firmographics. We call it an aiCP, and its dynamic nature empowers you to always know the changing attitudes and behaviors of the companies that are “fit and ready” to hear from you. (Read more about how we build aiCPs and how they work here.)

These concepts are a lot to take in, but they are like Moneyball for B2B sales teams entering new markets: once you’re free from targeting only lookalikes, you can discover entirely new market segments that behave very similarly to your ICP, regardless of industry.


Meaningful prioritization of target accounts

The old way to decide who to call first usually comes down to familiarity or even gut feel. The stacking of exegraphics results in what we call a “Rev Score”—the higher the score, the stronger the likelihood of a successful fit.

Ranking the entire TAM by Rev Score results, essentially, in a tailor-made prioritization list, so you know you’re walking that first mile in the right direction.

Now, you can still customize that list for your first forays into the market segment. If you’re taking a SWAT-team approach, sending in a small number of sales reps without extensive marketing, you might want to identify, for example, a specific function in these organizations that will resonate with your value proposition. Prioritization gives us that starting point, so we have the ability to pinpoint companies that improve our probability of success—and enable us to fail forward, when we fail.


Deep roster of target accounts

The AI-driven modeling technique doesn’t just give you the best prospects: it gives you a lot of them—and if it doesn’t, you know that a particular market segment isn’t actually very promising.

A team of humans can easily enough build a target account list of a few dozen companies. It will take a bit of time to comb through their press releases, research their team and evaluate their market. And that list would likely have some really good fits.

But you need more than a handful of companies in a new market segment—you need hundreds or thousands. There’s no way humans can go through that evaluation process manually in any effective way. And the list will change with time, too—exegraphics evolve, your existing customer base shifts, and companies undergo internal changes, all of which will affect Rev Scores and the prioritization of your list.

The best targets this month might not be your best targets next month, and you need to stay on top of who your best prospects really are, right now, out of all the potentials in the segment.


Go to market quicker than ever

All these new ways of entering a new market segment boil down to having much more rigor about your process. No longer do you have to throw spaghetti at the wall to see what sticks: you know you’re sending reps after the prospects most likely to bite.

That means you can have confidence in a more surgical strategy. You can develop early messaging and simple collateral right from the start. A few good pieces is all you need to start testing the market. Is engagement happening? Can your reps actually close a deal? If not, what needs to shift? You’re not stuck bringing in the marketing team and waiting for that engine to turn out materials before you can get started.

This whole approach speeds up the information-gathering period and helps you assess, quickly and definitively, whether a new market segment is actually viable. You should be able to manage this in 3-6 months, not the more typical 12-18 months that companies need to determine market fit.

Not only are you making sales that much sooner—you’re getting your product into that new market faster, which can be particularly powerful with new adopters, and you are more likely beating your competitors to the new market too.

Momentum matters in B2B sales. Momentum early on makes even more of a difference. By breaking out of the old ways of testing new markets, and getting precise with the new ways, you’ll experience success in segments you never imagined entering.

If you’re considering expanding into a new market, make exegraphics part of your strategy. Let us show you the exegraphics behind your best customers.