Psychology and The Signals Slot Machine
Getting an outbound edge without going off the rails.
I recently talked to a GTM leader who was concerned with his reps chasing low quality accounts. He described the problem as reps getting “distracted” by “small fry” leads when he wanted them to focus on their carefully crafted book of accounts.
I hear this a lot. I believe the ways we try to help reps are making it worse.
Look, sales teams need all the help they can get. It’s never been harder to generate pipeline. Every marketing channel sucks right now, making inbound perpetually more expensive. Outbound? Even worse. The good news? There is no good news—it’s only going to keep getting harder. No matter what, all the alpha from any new channel or tactic quickly gets competed away faster than ever.
And yet we persist because we’ve got a number to hit. True “hand raiser” leads have always been somewhat scarce for most revenue orgs, so we’ve tried a progression of different tactics to make up the pipeline gap without requiring all of it to come from completely cold outbound.
Whatever you call it—whether it’s “warm outbound” or the linguistically dubious “inbound-led outbound”—we’re all trying to equip our reps with information to do timely outreach. It started with MQLs from gated content, then we layered on intent (6QAs anyone?). Now we’ve got GTM Engineers collecting raw signals like de-anonymized website visitors or semi-AI-driven LinkedIn scraping.
These signals aren’t bad on their own. However, reps aren’t rational signal processing machines. They’re human and, as such, misapplied signals can quickly create more distraction than value.
Below we’ll look at a framework for thinking about signals in combination with ICP, dip into the human psychology that makes signals challenging and wrap up with ways to provide guardrails that keep your reps maximally productive while still pursuing that competitive edge.
Let’s dig in.
Evaluating opportunity with the FT Quadrant
Here’s a simple way to think about the potential opportunity with any given account: fit and timing. When you put them together you get the FT Quadrant Chart.
Here’s how it breaks down:
Fit - Does the account fit your ICP? If they’re a fit, could they become a big customer? The higher up they are on the y-axis, the better the fit and the larger the value. This can theoretically be derived from firmographic and technographic data.
Timing - Great accounts may not be ready to buy. Accounts exist on a spectrum ranging from not in-market (e.g. under contract with another vendor, budget is in flux, corporate priorities may mean they don’t value the solution, etc) to ready-to-right now (e.g. no current vendor, existing vendor contract is up, new company priorities, budget allocated). The farther right on the x-axis, the more motivated they are to purchase a solution soon. Theoretically, we ought to be able to collect various behavioral signals that indicate where an account falls on this dimension.
Any time you have two dimensions, I’m pretty sure you’re legally obligated to name the quadrants. Here you go:
The Good Place - These accounts are a great fit and they’re ready to buy a solution. These are the opportunities you can win in the near future and, ideally, where your reps should be spending most of their time.
“Get Back to Me” (GBTM) Zone - These accounts are a great fit but the timing isn’t right. When you engage, you’ll get the “sounds great but get back to me next quarter” brush off. (This is valuable information—more on that later.)
False Hope Zone - These accounts are a poor fit but are in-market. I call this false hope because chances are good you can land some of these—after all they’re ready to buy. However, you’re likely to find that a) this process isn’t repeatable and b) they’re poor long-term customers since they’re not an ICP fit.
The Bad Place - These accounts are neither a fit nor are they looking to buy. At best you’ll avoid these altogether, at worst your team spends time on a sales cycle with no chance of success.
The position of any given account in an FT quadrant isn’t static—it can and will move. However, accounts don’t move along the two axes in the same way and your ability to influence the movement is constrained.
Timing changes over, well, time. Accounts will oscillate back and forth between being in-market and out-of-market as they buy solutions, renew solutions, and go through budget cycles. Market forces also impact timing. Two years ago, nobody was really “in market” for AI SDRs but now most people are at least willing to kick the tires (even if its only for 3 months).
Fit changes relatively slowly, if at all. There’s no guarantee that an account will ever move from being a poor fit to a good one or vice-versa. That requires a change to either the account’s business (e.g. they grow, shrink, change strategy) or your business (e.g. you offer a new product line).
The takeaway here is that accounts in The Good Place are vastly more valuable than others, but they’re perishable. There’s a reason most qualification methodologies include a balance of fit and timing criteria1.
Because timing changes more quickly than fit, most organizations try to get an edge with more information about timing. This can make a huge difference but doesn’t always work as intended.
Psychology and the signals slot machine
Given that you don’t have unlimited resources, you need your reps focused on the accounts in The Good Place as much as possible. Unfortunately, reps usually spend a lot of time elsewhere. This is often due to our misguided efforts to help them prioritize accounts with signals. The problem is the way this “help” hijacks human psychology.
Humans get addicted to random processes that periodically reward us. It’s called a variable reward schedule and there’s real science behind it. BF Skinner (basically a real-life evil genius) performed a lot of reward and reinforcement experiments. He showed that the best way to get a behavior was to reward it inconsistently. That sounds a little counter-intuitive—until you think about the nice midwestern grandma who will plant herself all day in front of the penny slots. These kinds of systems are what drive gambling addiction and the compulsive desire to check social feeds. Pull the lever, refresh the feed. Get a little dopamine hit. Repeat. Over and over.
It turns out that this bit of human psychology presents a serious risk for keeping your reps focused in The Good Place. Humans are primed for distraction. We’ll drop everything to chase the thing that promises that potential reward.
Unfortunately in our efforts to better time our outreach, we’ve made life that much harder for reps. They now face a nearly overwhelming barrage of variable reward scenarios in the form of inbound leads and—when there aren’t enough of those—“signals” used to drive warm outbound.
In the last 15 years or so, teams really started prioritizing immediate responses to inbound leads (aka “speed to lead”). We called these MQLs. Then, we ramped up the quantity of these leads through gated content marketing. Suddenly MQLs became anyone that filled out a form to get a white paper or signed up for a webinar. We dutifully delivered these to reps for “follow up”. It turns out that most people who signed up for marketing’s thought leadership webinar but didn’t attend aren’t actually super interested in your product. Ultimately that’s led to a reduction in gated content and a reduction in these kinds of MQLs.
However, those content-based MQLs have been replaced with something that might arguably be worse.
About a decade ago, we started to focus on account-level intent as part of ABM. Suddenly we had intent surges and “6QAs” for reps—someone, somewhere, who was probably at a company they cared about may have been researching a topic related to your company. Reps started to get notifications and digests about accounts showing interest somewhere on the internet about the product they’re selling.
The vagueness of account-level intent has largely made it a bust for sales teams2. I’ve yet to talk to sellers that truly seems to derive much value from this type of intent. The signs of interest are often weak or outright misleading. Even if the account-level intent was accurate (a big if), a low-level manager doing a few searches isn’t the same as senior executives deciding on a strategic direction. These signals completely lack the context of who is taking the action.
Now, more granular signals are all the rage. At first it was more readily verifiable account-level data. We started looking at news events and changes in hiring patterns.
Recently, there’s been a boom in person-level signals. We’re using tools to scrape LinkedIn for individual engagement behaviors, tools to track champions changing jobs, and tools that promise to tell you which individuals are visiting your site. Even if we assume these signals are accurate (another big if—especially for person-level de-anonymization), we’re now trading slightly more person-level data for even less account-level context. And we’re ramping up the volume of potential signals significantly.
Most companies maintain some level of “all of the above” in their quest to “help” reps identify high-timing accounts. They may even add their own company-specific signals like product usage in self-serve trials.
Of course, this might work great if we only distributed signals from perfect ICP fits. The reality is that just doesn’t happen. The temptation is just too great to let signals through for lower quality accounts in the name of “not missing any opportunity”. (More on this below.)
The net effect is variable reward on steroids that can quickly spiral out of control. Reps get a new signal and they might get a win—better work it right now!3 When reps get a signal from an account, it takes every bit of discipline they have to convince themselves to disqualify this fantastic new opportunity even if the fit isn’t great. After all, this guy wants to buy now and yeah they’re not a perfect fit today but they’re going to hire several folks and they’ll be a big customer in a few months we just need to give them a 30% discount and get them in the door…
This means chaotic account coverage as reps chase anything that shows a pulse—especially in a difficult sales environment.4 It takes a heroic effort on the rep’s part to stay focused on ICP fit accounts without drifting down into the False Hope quadrant.
I’m not suggesting that you abandon signals, but I am suggesting you carefully build your processes to put guardrails on how signals are applied. Let’s look at how.
Good Place guardrails
While signals can hijack rep psychology, your systems can provide guardrails and keep your reps focused on The Good Place. There are lots of ways to inject guardrails into your sales process, but here are four areas I’ve found particularly helpful:
Clear ICP
Focused books
Intelligent automation
Accountability
Let’s look at each in turn.
Clear ICP
If you don’t have a well-defined ICP, then there’s no chance whatsoever that reps can properly assess fit. This goes for both the simple parts of your ICP (e.g. size, geo, industry) and for the more complex components.
Your job doesn’t stop at defining your ICP. You need to also communicate it in a way that’s easy for reps to understand and internalize. For example, if your ICP involves companies with more than 200 employees and an in-house General Counsel, your reps should understand the business context for why those things make a company a fit.
Finally, you need to work with your ops team to reduce the effort required to determine fit. Ideally this would work out to a fit score or tier available on every account. This keeps rep guesswork to a minimum.
Until you’ve defined your ICP, your reps understand it and you’ve fully operationalized it, you can’t act shocked when reps stray into the bottom half of the FT Quadrant.
Focused books
It’s easy to equate book size with book value even though more prospects does not mean more pipeline—it seems like simple reverse pipeline math. However, a rep with a book that’s too large will face the paradox of choice where it’s difficult for them to rationally choose where to focus their time.5
Absent a good way to choose, reps will likely focus on accounts showing signal, causing them to spend too much time in the False Hope zone. After all, disciplined outbound is far less fun than talking to the guy who just might buy tomorrow. This is yet another reason that it’s hard to get an inbound-focused team to do more outbound.
I recommend keeping rep books relatively small. I tend to start with Dunbar’s number which (very roughly) indicates humans can maintain about 150 stable relationships at once. Think about your sales process and how many stakeholders are likely to be involved with each account and factor that into your book size. If you have a simple transactional sale to a single POC, perhaps a rep could have a book of 150 accounts. If you have a complex enterprise sale to multiple stakeholders that number goes down quite a bit.
One problem with traditional geographic territories is that they can create large books in some geographies, exacerbating the focus problem for those reps. Also some territories will produce more signals than others because those accounts are just more visible on the internet (e.g. west coast tech companies with lots of LinkedIn posters vs midwestern manufacturers). It’s tough to make this equitable.
Intelligent automation
Try to avoid feeding reps raw signals. You’ll quickly swamp them with noise. Do a thorough evaluation of the types of signals you want to collect and rank them. A prospect with a perfect title from your target account list visiting the pricing page is more relevant than an IC from that account reading an old blog post. Only surface the signals that have real value.
Capture the less valuable signals and aggregate them together over time. If you see a critical mass of lower-quality signals over a relatively short time, then maybe notify the rep. A word of warning: this is easier said than done and may mean you end up using your own resources to try and recreate low-quality “intent surges” that are the bane of anyone who’s tried to get reps to focus on 6QAs.
There is, however, one very simple timing-based automation play that I recommend everyone adopt: capture and act on competitor renewal dates.
In a previous role in a highly competitive SaaS industry, we encouraged reps to learn when their accounts were renewing with a competitor and then allowed them to tag an account with a “Get Back to Me” date. RevOps would then remove the account from their book, marketing would nurture the account, and then we would automatically return the account to the previous rep at the right date.
This was logistically a bit of pain (since Gradient Works didn’t exist then) but it encouraged reps to identify key timing without worrying that they might be giving up a future opportunity. By removing the account from their book entirely it kept the reps focused on active accounts, limiting distraction. This has since become a core play in the dynamic books approach to territory.
Accountability
Hold reps accountable for working their entire book. Measure your reps on account coverage not just activity. You can use something as simple as “percent of owned accounts with an activity in the last X days” to get started. (You can find more sophisticated measurement here and here.)
If reps don’t have the desired level of coverage, you have a few options. If you have a fixed book defined by geography or static named accounts, you will likely have to deal with this through coaching and management attention. If you use dynamic books, you can consider temporarily reducing their book size or pausing any inbounds that might be going to them while you coach them through their time management challenges.
Regardless, make sure your line managers focus on coverage of high fit accounts when they coach the reps—every rep should be spending the vast majority of their time in the top half of the FT Quadrant.
Wrapping Up
I’ve found the FT Quadrant to be a useful lens for thinking about how to maximize the value of signals without turning reps into reactive dopamine chasers. There’s too much pipeline at stake to let the weird quirks of human psychology hijack the system.
Where possible, try to minimize the load on reps and move load into the system so that reps are free to focus on where they can have the most impact. With the right processes, your reps can stay in The Good Place with less effort and more efficiency. It just might give you an edge in the battle for pipeline.
I’ve always thought it was a bit weird that MEDDPICC doesn’t focus more on timing. I know that enterprise deals operate at a more deliberate pace that’s more guided by internal processes but you’ve still got to find a compelling reason to move forward. That’s why I generally prefer SPICED these days.
It’s still valuable for marketing to direct ad spend. That’s why DemandBase and 6Sense are still large companies.
It’s also possible that the opposite could happen and reps just start ignoring the signals entirely. This is called “alert fatigue” and happens when people are exposed to signals repeatedly that aren’t actionable. They’ll eventually just stop paying attention to all signals and miss important ones. I won’t cover that here.
You can often see this in an Engagement Grid as a “smear” of similarly colored red cells. That means coverage isn’t being driven by any specific strategic focus.
A related and more colorful version is Buridan’s ass where a hungry donkey starves to death because he’s equidistant between two piles of delicious hay.