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How to reinvent your product growth strategy for the tech downturn

Why you’ll need to rethink your user growth strategy
Downturns fundamentally rewrite the industry’s strategy (and expectations) for user growth. In a bull market, the focus is on top line growth. You often want 2-3x YoY for a a new product in its first few years, and even faster when its right out the gate. High growth and high burn are fine. Because if you need to spend a lot of money to get there, whether through paid marketing or partnerships, you do it… after all, you can just raise more money, right?

But in a bear market, the answer changes: No. It turns out, you won’t be able to just raise more money to keep going. No, you can’t just expect to hire dozens of engineers, regardless of progress — particularly when hiring freezes are coming into effect. For startups, the bar for raising the next round just went way up, as many investors are waiting out the turbulent market. This means the strategy for user growth just went from “as much as possible” to “efficient, profitable, productive” in just a few quarters.

What are some ways you should be rethinking your growth strategy? Here’s some things every team should be thinking about:

  • Embrace the new normal
  • Cut your marketing spend
  • Laser focus on your engaged, high LTV users
  • Live to fight another day

I’ll unpack some of these as we go.

The new normal
Efficient growth is now the key focus for product teams. During a bull market, the primary metric that people talk about is just top-line growth — what’s your year-over-year growth rate. Some of the truly eye-popping growth rates might exceed 10x YoY, often subsidized with investor money — as has been in the case with on-demand services.

However, the new normal is focused on efficient growth. Although there’s a floor for how fast a product has to grow to be interesting — probably something like 2.5x — there’s a much bigger emphasis on efficiency. What’s the best way to measure this? One metric that’s been recently popularized by David Sacks is the “Burn Multiple” — he defines it below:

Burn Multiple = Net Burn / Net New ARR

This puts the focus squarely on burn by evaluating it as a multiple of revenue growth. In other words, how much is the startup burning in order to generate each incremental dollar of ARR?

In other words, if you spend $10M and gain $5M more in annual recurring revenue, that’s a 2x burn multiple — which he grades as “Suspect.” The Burn Multiple metric is simple, but it’s precisely useful because it’s so simple. A lot of times, unit economics are hand-waved by product teams because some costs are excluded from the contribution margin or net revenue calculations that maybe shouldn’t be — like headquarters costs, real estate, and so on.

Burn multiple cuts through all that, since it’s just aggregate cash versus revenue, and it’s hard to hide anything with a metric so simple. And with this simple metric, it allows you also compare different companies, and potentially different scenarios for a given company, to figure out how to best reduce it.

To provide some benchmarks, my colleagues at a16z, Justin Kahl and David George, recently wrote an article on navigating the downturn where they collected some empirical data:

As you can see, the bar for what constitutes a good burn multiple goes up as revenue goes up. Naturally, you burn more upfront during the product development phase, and then get more efficient as the business gets scale.

From a product growth lens, the shift from topline growth to efficient growth means that you should be thinking about how much burn, how many engineers, and how much marketing is required to hit the milestones you want to reach. And the first questions to ask are often around marketing.

Cut your marketing spend
The first and simplest thing to do is to cut your marketing spend. And in a particular order:

  • Keep the high ROI channels, cut the low ROI ones, even if they provide volume
  • Focus on accountable spend, and reduce ones have a long/fluffy payback?
  • Rethink brand marketing spend — do you really need it?

On the first point, every marketing/growth effort is built from layers of channels built on top of each other. The highest ROI tends to be channels like SEO, word of mouth, and other organic efforts. The next might be paid channels like newsletters, which are hard to scale but highly productive. Then there’s highly targeted paid marketing. Usually the lowest ROI tends to be broad targeting — particularly display ads — on large advertising networks.

Usually these layers are built over time, one by one, by growth marketing folks who keep investing and arbitraging 10:1 LTV/CAC ratios down to 3:1, then 1.5:1, before they slow down. There might also be ongoing marketing experiments to try new short-format video or otherwise. It’s time to unwind that. Usually each incremental channel might add more volume, but is rarely as efficient as the preceding efforts. There’s a diminishing returns — Law of Shitty Clickthroughs strikes again — as each layer is built. Instead, go back to the core.

The other vector to think about this is direct response versus brand marketing. Brand efforts are a great way to spend money without understanding its actual effectiveness to impact metrics, and it’s time to dial those down. Whether it’s large scale events, brand marketing, PR/comms, splashy videos, or otherwise — unless you can justify the costs, it’s time to reduce.

Either way, it’s time to retrench and focus on high intent, low CAC channels.

Laser focus on your engaged, high LTV users
In a hot market, there’s often a land grab to acquire as many users as possible. If there’s a goal to grow 10% in a time period, the pressure is often to grow 10% by acquiring a mass of new users — most of which will burn off from lower usage — when the better option might be to grow 10% by incentivizing higher engagement from existing, core users. At Uber, it was often noted that it was much faster to get drivers to spend 10% more time on the platform, so that there’d be more “supply hours” to react to demand — than to acquire 10% more drivers in a market. The latter would require a big marketing push, and might take weeks for the drivers to ramp up to the same level of engagement.

The reason why this dynamic exists — where the core users outperform new ones — is that there’s often a central segment of where the product is really working, and then an “Adjacent User” where it only kind of works. For example, early Instagram was working well with high-tech, urban users but not well at all within older demographics. Later, it wasn’t working well for Android users in emerging markets. But there’s often pressure to grow by capturing new segments of users, rather than improving on the core, which means that the users that come in through marketing channels are worse quality, lower intent, and less engaged than the core.

This can become a tradeoff between Marketing versus Product-Led Growth, where the former drives CAC, whereas the latter is built on product development costs. The advantage of growth driven within the product — whether that’s better user onboarding, high impact features, or otherwise — is that they impact a wide swath of users within the product. You can invest once and get benefits over a long period of time, and amortize costs across a large segment of users. I’d lean towards product, when possible, when the roadmap is clear on what to do. Obviously marketing spend and engineering time isn’t interchangeable, but reducing marketing budgets while maintaining/increasing product teams feels like a good trade.

Live to fight another day
The milestones required to unlock additional funding/headcount has almost certainly gone up, and specifically for startups, the bar needed to raise more venture capital money has gone up as well. Understanding these milestones will allow teams to fight another day, and coming up with a realistic plan is a key step.

The best way to understand how the bar has moved is can be shown by a chart in the aforementioned article shared by my a16z colleagues David and Justin, showing how the forward revenue multiple for public companies are down significantly. Meaning, you need much more revenue to justify the same valuation — what used to be a 15x multiple is now 7x, meaning valuations are down half even given the same revenue numbers.

Or said another way, when the valuation of public software companies gets halved, then the amount of revenue needed to justify the a valuation goes up double. (For early products that think more about Active Users or DAUs or otherwise, you can recreate these graphs based on $/DAU or otherwise — and yes, those are way down)

This is causing a domino effect in the industry. When you see a $2B public company cut down to $1B, then a $500M privately held startup is cut down to $250M, and so on. The tricky part is that for a public company, of course you have a real-time stock quote to see these valuation changes. For a tech startup, you raise new funding rounds every year or two. That means for much of the industry, the next round of a startup just became much, much harder, but we potentially won’t know for a year+ how much the bar has moved. Either way, this means fewer resources to hit the same hard growth goals.

The easiest way to flex to hit these elevated targets is to take more time, with higher efficiency. Teams have to buy more runway, focusing on better ROI and not a “high growth, high burn” mindset to hit the growth metrics. For startups who have recently raised, they’ll need to “catch up” on their most recent valuation, and additionally progress to justify the customary 2-3x jump in valuation between rounds. That’s the new bar.

The next few years are going to see a lot of change in the tech landscape, particularly for how teams think of growing their products. Much of the last decade has been focused on growth by any means — and investor subsidies, chasing volume via high CACs, have all played a key role. But in the next phase, efficiency means that we’ll need to retrench within the industry and talk about quality and efficiency.

There’s a myriad of complex trends intersecting at the same time: The new Apple privacy changes to ad networks, the potentially stingy venture capital landscape, the hiring freezes that are happening, how web3 plays out over the next few years, and so on. Just as product leaders had to reinvent their thinking to take advantage of the mobile boom, we’ll see them do the same in the coming years for the new environment that’s rapidly taking shape. In the meantime, it’s critical for teams to take a pause, figure out a new approach, and build towards the next boom.

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