A few years back, my former colleagues and I at SiriusDecisions introduced what we called the Intent Data Framework (IDF). About a year ago, we updated the model to include non-behavioral signals and called it the Buyer Signals Framework (BSF).
Already, it’s clear we left something out of the IDF and even BSF: product-led growth.
Signal substitution syndrome
Both versions of the framework were attempts to address a misunderstanding that was, and still is, so rampant in B2B that I have a name for it — signal substitution syndrome. The nature of this syndrome is simple: In B2B, both marketing and sales practitioners tend to see each new source of information about their potential buyers — each signal type — as a substitute for the last one that didn’t work.
If people are using the product, the need is not prospective or theoretical, it is actual.
The history of B2B could be written in the successive failure of these signals to be what we all hoped for. Whether it was people showing up at trade show booths, people filling out bingo cards from the back of magazines, the people and bots filling out website forms, webinar registrations, syndicated content leads, third-party intent signals, review site users, etc.
The misunderstanding that underwrites signal substitution syndrome is that any of these signals should be considered as sufficient — or even halfway decent — signals of buyer intent unto themselves. To be sure, by happenstance, some leads have occasionally turned into business in a way that can be seen and understood.
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But if there’s one thing that my time as an analyst taught me, it’s that leads are a depressingly high failure rate (95%-99%) signal. Intent data by itself is worse. However, they are both better than whatever we had before. In fact, none of these signals are, by themselves, actually expressions of intent. Expressions of interest? Sure. Intent, not so fast.
How product-led growth fits in
Along comes product-led growth (PLG) with the idea that we’ll offer a free or very low-cost version of our solutions and use adoption of them as the new signals that will lead to enterprise deal generation. Of course, not every product is amenable to a PLG motion. It’s pretty hard to imagine Oracle PLG-ing their manufacturing cloud, for example.
Many, if not most, B2B business solutions only work if they have a complete function within their purview. And, of course, this is not a new strategy. There have been free trials, freemiums, -lites and the like for as long as there has been portable software. In fact, download.com and its ilk were sort of PLG distribution centers back in the day.
That said, PLG is a valid strategy for companies with solutions that can work for individuals and small groups within larger groups. What could be better than having actual users of some version of your software inside a company where you’d like to sell a big enterprise deal? And for a relatively small number of companies, the product itself will be so good and so necessary that no real selling will be required.
So if you do have a version of your solution that is amenable to a viral approach, by all means, have at it. But for most of us, PLG is going to be a demand creation strategy that will produce signals of varying quality. There will be great temptation to view the individual users as the new “leads,” and they can be. But they are also the new “intent.”
A better way to think about these users is simply as signals. They are a signal, just like form-fill leads, de-anonymized website traffic, visitors to your booth and the rest. Just like the other signals, the best way to use them is to throw them into the algorithmic blender with all the other signals that are available to identify patterns that can help prioritize sales efforts.
PLG user signals: Needy but insufficient
Nearly everything that can be said about leads or the menagerie of available intent signals is that they represent expressions of interest. In contrast, users of a product are directly expressing a need. If people are using the product, the need is not prospective or theoretical, it is actual.
Verifiable, expressed need is a great signal. However, the fact that three people inside a 10,000-person organization are expressing that need does not strongly indicate that the entire organization as a whole has or feels the need. If only three people express the need, that may, in fact, signal that the enterprise or even the function as a whole does not feel the need.
Bringing it all together
This is where all the other signals come in to play. As an analyst, I advised organizations to look at leads and intent signals as layers of evidence about which prospects might be in the market for their solutions.
If you have a marketing qualified lead (MQL), we know that is very unlikely to lead to a closed-won deal. But if you have two MQLs from the same organization for the same thing at the same time, that’s a much better bet — though still not a good one. If you added to that de-anonymized traffic plus third-party intent signals, however, now you’d really be on to something. Every additional signal further validates what has come before. Or it should.
Likewise, individual users in PLG motions should be considered in light of other evidence of interest and need. If there are three users of your product in a large enterprise where the potential of an enterprise license might be 300 users, you have to ask yourself: Is there any evidence that someone other than these three is expressing a need or interest? Are there conventional leads? Is there anonymous traffic? Is there a surge of interest in third-party intent?
If the answer is no, sending your sales reps after those three people, or even their boss, is not very different from sending them after MQLs.
However, if you can combine these disparate signals, you can create one strong, coherent signal that sales can use to prioritize their efforts and tailor their approach. If you succumb to signal substitution syndrome and simply throw usernames over the fence and tell sales to go get ‘em, you’ll be back looking for your next signal source soon.