Quick-feedback loops: From Brain & Gut to GTM funnels & pipelines
There have been days when I have been very hungry and ate so fast, so much, that I felt nauseated from overeating a little while later. I am sure I cannot be the only one to have experienced this. There’s a reason why nutritionists and dieticians advise leisurely eating: it takes our brains approximately 20 minutes from the time we start eating for the brain to send signals of fullness. During this period, the stomach and the brain constantly communicate with a quick feedback loop to measure fullness.
But why are we discussing the digestive and neural connection in a business blog focusing on the early-stage pipeline?
Well, the answer is in the “quick feedback loops” that exist within our bodies and the importance of having them in our Go-to-Market (GTM) funnels, especially between the early-stage pipeline and the marketing’s demand generation strategy.
The Complex GTM Motion
“Division of labor” - that’s a beautiful phrase articulating how work gets distributed amongst teams to hit the goal. Demand generation teams have “demand” to create, xDR (sales development representative or business development representative) teams have the qualification of leads to do, and sales has selling to do. All inching towards one singular goal: revenue.
However, the real world is far from this simple when you take a peek into a company’s GTM motion simply because the buyer has innumerable channels to hop around before even reaching your sales: a webinar attendance, meeting your partnership team at a cocktail party, downloading your whitepaper, liking your YouTube tutorial, retweeting your company’s tweet and so on and so forth. Every step of the way, the buyer is signaling interest, and yet you can’t be sure of her intent to purchase your product.
And this leads the funnel astray, with leads being created and pushed down the funnel with an unclear understanding of the buyer’s behavior and leading to that classic “Pipeline Parking Stage 1” - which is your GTM’s “No Man’s Land.”
According to Wikipedia, No Man’s Land is a disputed land that all parties involved leave unoccupied out of fear or uncertainty.
“Pipeline Parking Stage 1” is your early-stage pipeline that, without a strong data-backed GTM motion and processes, becomes disputed between marketing and sales teams and leads to revenue leakage or, worse: the opportunity cost of not attending to valuable deals in your pipeline.
The Early Stage Pipeline Graveyard
An SDR is incentivized to speak to the Marketing Qualified Leads (MQLs) and figure out which leads are real and urgent from the uninterested or incorrect ones. And there are dozens and hundreds of them for an SDR to go after. More often than not, some of the incorrect leads inadvertently get into the pipeline and are parked in Stage 1.
By the time the sales picked this opportunity up and realized it was incorrect, significant time has been lost.
Consider another scenario where the volume of leads is high and frequent, the Ideal Customer Profile (ICP) that marketing originally went after is morphing and non-existent in different markets. In fact, there are ICPs marketing did not realize was interested in their product until after a few wins and an attentive business analyst noticing the pattern - literally finding a needle in a haystack given a single record generates high data.
What happens when many bad leads convert into the pipe, or many good opportunities fail to get the critical attention they deserve? An early-stage pipeline graveyard where both the really good and the bad opportunities wait to die, thus skewing your entire funnel metrics.
The Problem with Measuring Early-Stage Pipeline
While organizations have figured out defining every stage to be sure the right deals are parked in the right stage, the early stage is muddy waters.
Think of this: Proof of Concept(POC) is a stage with a clear checklist to go after, the negotiation stage hovers around pricing discussion with the buyer for the value provided, and the contract stage is about legalities.
But the early stage pipe is the shut door that opens these downstream conversations. And the outcome of this stage is unknown until the seller speaks with the buyer in detail for the first time, unlike every proceeding stage that is an outcome of the previous stage.
And hence early stage pipeline tends to become a graveyard of bad-quality pipeline.
How did we get here?
I would not be surprised if you arrived at the conclusion that “bad SDRs” lead to a “bad early-stage pipeline.”
If it only was that simple.
This is not a people problem, and this is a systems problem.
Let’s break down this.
An opportunity is a butterfly that was in the making as a lead caterpillar for months before taking wings. It all starts with what marketing generates at the Top of the Funnel (ToFU).
Every demand generation campaign starts out as an experiment to figure out what is working and create an ICP to go after.
Suppose you are a SaaS company that measures rep productivity by tracking emails and calls. You started out with the head of sales as a target persona to go after. It serves you well until a few quarters down the line, you realize RevOps is a target persona to influence and go after it.
However, lurking inside your data like a dragon asleep in a cave for the past thousand years is the fact that a new target persona is emerging that you have not yet figured out: InfoSec.
The data security threat has compounded with companies going remote post-pandemic and employees working from home. More often than not, every company now requires you to comply with cybersecurity certifications. Therefore, InfoSec makes or breaks deals in many cases.
This emergence of a new target persona would be hard to track if you did not have enough sample size and a dedicated team of business analysts going from spreadsheet to spreadsheet connecting all the pieces of information to find this pattern much earlier.
It is the nature of the data, morphs, evolves, and hides between thousands of variables until there is enough evidence to prove a pattern.
Metrics affected by Poor Early-Stage Pipeline
Here’s an exercise for you: break down your deal age by stage. Work with your sales leadership and put a benchmark for what is the ideal days in each stage. List what possible reasons could explain any deal going out of your benchmark.
For negotiations, you could come up with internal pricing approvals. For the contract stage, you could come up with legal approvals from both your end and the buyers.
However, for the early stage pipe that comprises stages like Discovery and Demo, you will not find a good reason why the deal should stay there any longer than your benchmark - because all the variables to control all internal to your organization. This is critical to ensure the poor quality of the early-stage pipeline is not weighting down your rep productivity and revenues.
1. Deal Velocity
The first visible sign of a poor early-stage pipeline shows up in your deal durations going up from benchmarks. From marketing to SDR to Sales: your reps spend significant time figuring out it was a poor deal to go after.
A bulked-up pseudo-early-stage pipeline would mean your forecasting is beefed up to comfort you now that you have enough deals to go after while you do not. Poor forecasting decisions have been the death of many quarters. You do not want to make this mistake.
3. Pipeline Coverage
Naturally, when you have an unidentified poor-quality pipeline, your pipeline coverage metric is, at best, a broken clock.
4. Marketing Campaigns
This, in my view, is the single most important part of the funnel that takes the largest hit and affects sales the most. When identified early, poor quality of the early-stage pipeline can act as a quick feedback loop for marketing to go after the right ICPs and target personas, flushing the downstream funnel with the high-quality pipeline.
Given marketing spends a good chunk of the org budget to ensure sales are successful, this feedback not being shared is blame passed to marketing’s inefficiency in many organizations, given what you attract at the top of the marketing funnel has a direct impact on the early-stage pipeline and the funnel downstream.
This, however, is not a people problem but a systemic problem that is best left for an application to analyze and recommend your marketing and sales strategy on what is working and what’s not, thus enabling both teams to strategize their end of the funnel and not be caught up in a zillion spreadsheets to figure.
The Cost of Poor Quality Early-Stage Pipeline
At an industry average cost of $198 per lead, B2B Demand Generation is already expensive. If your early-stage pipeline is crowded with many of these, costlier than having generated the wrong leads in the first place is the opportunity cost of not having attended to the right deals in your pipeline.
However, on a larger scale, the costliest of them all is not sharing what’s working in your downstream funnel with marketing outreach campaigns to attract the right ICPs and target personas. It’s the beauty of the GTM funnel, like our brain and gut - they are all interconnected and need constant feedback loops.
LinkedIn State of Sales 2022 Report for the US and Canada highlights “No organization-wide, unified view of data” and “Siloed Data” amongst the 5 biggest data challenges sellers face.
Your marketing and sales teams do not have to bother about the semantics of the data patterns in your funnel. We built it at RevSure so both these business critical teams could focus on strategizing, leaving the burden of connecting the entire funnel view to us!