KYC: The ultimate early-stage growth hack
This post breaks down a hard truth: while early-stage startups can coast on founder instinct for a while, true go-to-market (GTM) traction demands real customer conversations.
Research (product, user, customer) is like cardio: We all agree it’s good. Everyone hates doing it, so most of us don’t.
Early-stage founders can get away with skimping on product and user research. You got funded because you have a uniquely qualified opinion on gaps in the market. Your team is a reasonable proxy for users.
Knowing your customer (KYC), their unique pressures and business context, is where gut-level intuition breaks down. This is especially true in nascent markets with new technology. If you’re selling upmarket, it’s highly unlikely you’ll “best guess” what keeps the SVP of Engineering at Capital One up at night. You need to ask them.
Talking to customers is critical for the health of your business
Your go-to-market (GTM) delivering a steady supply of discovery calls with potential customers is the most efficient path for early founders to find customer fit and establish revenue traction. These calls will rapidly uncover repeat signals on:
- A customer’s most acute pain
- How urgent that pain is to solve
- How much they’d pay for you to solve it
- Who feels the pain, who signs the check
You’ll also find out if your product, as it currently exists, is the right solution to their pain. Bonus product research!
Knowing these core truths about your customer accelerates an effective GTM strategy: target audience, value proposition, use case, packaging/pricing.
Marketing tactics net better results faster when you have an effective GTM strategy. You’re not learning by throwing stuff against the wall and analyzing how it drips. You’re testing a theory of the case with informed experimentation. You’re accelerating repeatability.
You may be thinking, “We get some inbound leads. And my investors give me pretty solid intros. I can figure this out on my own eventually, right?” Of course. But in a VC funding model, cash burn and a competitive landscape eliminate the luxury of time. You need to learn quickly.
Theory in practice: Spare5 -> MightyAI -> Uber Acquisition
Over six months in 2016, Spare5 went from anemic traction as a high-quality Mechanical Turk alternative to undeniable momentum as training data as a service for computer vision models in autonomous driving systems.
That led to a rebrand of the business-facing application to “MightyAI,” and in 2019, Uber acquired them. The product got so damn good at creating super high-quality training data of road conditions, they didn’t want anyone else to have it.
Where it started.
I joined in 2016 to build GTM with my Sales and Content Marketing counterparts. We struggled to find traction with the hodgepodge of “Big data” use cases that bubbled up from our investor-led design partners.
Undeterred, we contacted anyone who hit the website or the CRM and asked them why they visited, what they were building, and what they needed help with most. The process went like this:
- Generate a lead by any means necessary
- Call the lead, be interested in their work
- Good calls become fodder for blogs
- Promote blogs (site, social, newsletter, as webinar)
- Use traffic to repeat Step 1
We quickly learned the following truths:
There was a new type of engineer called a “Machine Learning Engineer.” The “Labeled Data” service on our website was compelling. We didn’t have any referenceable customers the page, but ML engineers were motivated.
ML Engineers wanted to pull their hair out labeling their own data. The smartest Phd. researchers in the world spent massive chunks of their day doing manual data entry to feed models.
Computer vision data was hugely valuable and a unique pain in the ass. Vision data needed to be pixel perfect, and the tooling to do inpainting and bounding boxes was very new and unwieldy.
ML Engineers felt the pain, as did the CTOs who wrote the checks. Huge investments and industry-changing technologies were held hostage by data tasks that most anyone could do. CTOs were willing to sign contracts with numerous commas and zeroes to solve this problem.
We had signal. Signal drove a GTM strategy, and that strategy led to some very efficient and effective experimentation.
ML Engineers were so new that there was almost no other way to get the leads. So we blitzed every computer vision research conference we could sponsor to build our lead list. We continued to run the same customer conversation -> blog -> marketing promo loop to nurture that list into pipeline and demonstrate repeatability across the funnel.
Where it ended.
Build GTM, talk to customers often. Only good things can happen
Having a seasoned team of experts building GTM from day zero gives your new product the best shot at success. That’s not practical for most founders.
Here are your alternatives:
DIY and commit to the hustle
This is the “just wake up and run a 5k before breakfast” option. Clearly effective. It’ll be good for you. You’re unlikely to stick with it because prospecting is actually a complex engineering challenge, devs will yell at you and call you a spammer, and you only want to do the “talking to customers” part, really.
Hire your first Salesperson or SDR
High risk/high reward. Suppose you land the right kind of founding salesperson who can figure out your GTM strategy, build content, experiment with messaging, and do systems and process design. That would be great. If that sounds unrealistic, that’s because it is. You wouldn’t put this wide range of responsibilities on an engineer. GTM is no different.
Go for a fractional GTM team
This is what QC Growth specializes in: giving founders a builder-focused marketer, sales team, and systems engineer as a ⅓ fractional team for ¼ of the total cost of full-time hires.
This way, you can invest in building the foundations of GTM earlier in your product journey and drive streams of customer calls sooner. The goal is to establish repeatability and hand off the foundations to your new team when it’s time to hire.
If fractional GTM sounds interesting, drop us a line.