Recycle your marketing dollars by thinking in loops
David Peterson

Back in 2017, we had just started monetizing Airtable, and while initial cohorts were looking good, we needed every edge we could get. As a result, I spent a lot of time signing up for B2B collaboration and project management software to get ideas.

There was one company that always seemed to be a few steps ahead of us. You probably know them as Monday.com, but I’ll forever think of them as dapulse…an upstart out of Tel Aviv that was blowing us, and every other collaboration tool, out of the water.

I won’t claim to have any insider knowledge on what Monday.com was doing back then. I’m just an outside observer (and admirer!). I remember one tactic, though, that changed the way I thought about growth.

Back when I first started working in growth, I always thought of my job as optimizing a funnel. You acquire users, you activate users, and you get those users to pay…ideally for more than you paid to acquire them in the first place.

But growth should not be thought of as a funnel. Growth, done well, is all about loops. And once you start looking for growth loops, you’ll see them everywhere.

The easiest ones to identify are the product growth loops. A user signs up, activates on your product, does something that helps acquire a new user (e.g. invites a colleague, shares a piece of content etc.), and then the new user starts the loop all over again. Product growth loops are so powerful because they are specific to your particular product (and thus can’t be copied) and are compounding (with each new user driving additional user acquisition).

But paid marketing loops can be just as powerful. And this is what the lovely folks at Monday.com had figured out.

Right before I had joined Airtable, the growth team at Monday.com had started experimenting with what I’ll call an “early bird” discount. Here’s the way it worked. One day after you signed up for an account, they’d offer you 33% off an annual plan if you upgraded immediately.

If you, like most paid marketing teams, were just myopically focused on reducing your CAC (customer acquisition cost), increasing your ARPU (average revenue per user) or optimizing the ratio of your LTV (lifetime value) to CAC, you might have missed the genius of this tactic. Offering such a hefty discount would either increase your CAC or decrease your ARPU (depending on how you account for the discount), and would thus move your LTV/CAC ratio in the wrong direction.

This is why you need to think in terms of loops. If product growth loops are about leveraging users to get more users, then paid marketing loops are about leveraging revenue to get more users. And that’s what this discount was all about. By significantly decreasing the time it took for paid marketing dollars to get paid back as revenue, Monday.com was supercharging its marketing team, enabling them to reinvest much more quickly.

To put a finer point on it, while every other marketing team out there was getting seduced by lifetime value (a.k.a. the most misleading metric of all time) to justify their burgeoning budgets, Monday.com was recycling dollars into an ever-growing marketing monster.

This thinking is especially important when cash is hard to come by (hello 2023!). Optimizing for payback period might not make sense when you can just go back to investors and raise more capital whenever you’d like. But what if this is the last $1M you’ll ever be able to spend on marketing? All of a sudden, payback velocity matters a whole lot. The quicker that $1M hits your bank account again, the quicker you can reinvest, and the quicker you can grow your customer base and drive more revenue…to reinvest again (it’s a loop, after all!).

So, if I could share one piece of advice, it’d be to throw out your lifetime value model and refocus on payback velocity. It made sense back in 2017 when Monday.com did it. And it makes even more sense now.

David

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FROM THE BLOG

Looking Back to Move Forward
How to survive this extraordinarily exciting and wildly disconcerting age of generative AI.

LLMs and the Future of Customer-built Software Design
How will LLMs change software development and design?

Navigating AI’s iPhone Moment
A venture perspective on LLMs and what’s next…

Principles for AI Product Design
Or how we could all learn a little from Google’s conversion optimizer.

WORTH READING

ENTERPRISE/TECH NEWS

Regulating AI. As the list of use cases GenAI can accomplish continues to grow, the pressure for the government to add regulation also mounts. Last week, lawmakers questioned OpenAI CEO Sam Altman to better understand AI and how Washington should regulate it. With many politicians on board, Altman proposed “creating a new government body that issues licenses for developing large-scale A.I. models, safety regulations and tests that A.I. models must pass before being released to the public.” While regulation is becoming more likely, it’s important to remember that it’s unclear if “any combination of government action — legislative, regulatory, or judicial — can really achieve the balancing act of maximizing the value of AI while minimizing its potential harm to the economy or society more broadly. As with all revolutionary technologies, the ability of governments to effectively regulate LLMs will almost certainly fall short. This is no criticism of lawmakers and regulators, but a side effect of the basic fact that law advances incrementally while technology evolves exponentially.”

Startup IPO performance. While the Nasdaq has performed poorly in the last two years, Crunchbase highlighted just how much worse the startup IPOs (ie Airbnb, Coinbase, etc) have fared. Many of these young tech IPO companies, except Airbnb and Uber, have “shed more than half [their] value in the past year and a half.” Some of these companies, like Opendoor and Rivian, are down 90% from the peak. Overall, the startup IPOs are down 2.5x more since the peak than the Nasdaq.

Apple restricts GenAI tools internally. Similar to a recent move by Samsung and several large American banks, Apple has restricted internal use of GenAI tools like OpenAI’s ChatGPT and Microsoft-owned GitHub’s Copilot. The primary reason is fear that confidential data may leak. Most enterprises are likely to have or enact similar restrictions, but then one must wonder: how will they be able to best leverage the power of LLMs without risking their proprietary data?

HOW TO STARTUP

Bootstrapped, profitable, & proud. Chris Wanstrath, the co-founder & former CEO of GitHub wrote up an insightful twitter thread on how GitHub managed to be bootstrapped and profitable through its first five years. The entire thread is worth reading, but the most important advice for startup founders was to pour yourself “into the product. There is no better marketing avenue than someone who loves your product and wants to use it with other people. We’re all inundated with ads all day, so a recommendation from a friend is golden.”

The pirates & romantics. Jason Lemkin shared a great piece on the employer-employee social contract. His advice for startup founders: “If nothing else, try at least to get as many of your First 50 Employees to still be Pirates and Romantics as possible. The ones that just really, really want to both do a startup — and do something amazing. Something without politics, without bureaucracy. The ones that just want to fly.”

HOW TO VENTURE

Emerging VC fundraising. It’s no secret that fundraising for venture capital firms is down this year. In fact, it’s at its lowest in 10 years. It’s a tough fundraising market for all, but especially for emerging managers. In the first quarter of 2023, venture capital firms led by up-and-coming managers only raised $1.62B — a mere 13% of the total capital raised in the US.

PORTFOLIO NEWS

LightSolver’s CEO, Ruti Ben Shlomi, was recently interviewed by Sally Cole Johnson of Laser Focus World about LightSolver’s laser-based processing unit, a disruptive computing paradigm on track to outperform quantum computers and supercomputers.

Aquant has launched Service Co-Pilot. This new release, enhanced by generative AI, aims to identify the best solution to any service-related issue, improve customer experiences by resolving cases faster and more efficiently, and minimize costs.