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What to do when product growth stalls

The crisis arrives slowly, then all at once
At first, everything seems rosy. The growth rate of a new product is spiking, and growing quickly, maybe even hundreds of percentage points a year. But weirdly, a year or two in, there’s some softness in the latest numbers. Maybe it’s seasonality, or maybe something else. But worryingly, it keeps slowing. First to 300% a year, then 200%. Then 100% – a mere doubling annually in a startup ecosystem that demands a much faster target. More features are planned, and some are even shipped. Eventually, there’s a back-to-back where things are completely flat. What starts as a slow boil – where the team has a well-planned roadmap and a big vision – becomes a sudden crisis. There are late evening phone calls and emergency sessions. Analytics dashboards are pulled and re-pulled, to figure out what’s going on. The team needs a new plan.

There’s a saying that no military plan survives first contact with the enemy, and similarly — no product roadmap survives first contact with stalled growth. Instead, a crisis ensues, and the entire roadmap has to be rewritten. Particularly for startups, where continual growth is life and death.

When this crisis hits, the question is, what to do about it? How do you come up with a plan?

For better or worse, I’ve had this conversation with product managers and entrepreneurs many times over the years. The easy answer that people generally want to hear either falls into the camp of:

  • This next magic feature will fix all our growth problems –The PM
  • We need to spend more money on marketing –The Marketer
  • Have you considered adding more AI? –The Investor

Don’t listen to these people :)

Instead, I offer the idea that you can analyze growth stalls systematically. You can ask questions, gather data, and assess the stall to zero in on the problems that are driving the metrics downwards.

Assessing the stall – starting with retention
First off, let me explain what’s happening during a growth stall. Yes, of course, it’s when a top-line number (like revenue or active users, or otherwise) stops growing. But what’s happening under the covers? At its core, a product stalls when its churn catches up with its customer acquisition.

I encourage y’all reading the entire thing, but I’ve written about this in the past in the deck The Red Flags and Magic Numbers That Investors Look For, which shows this growth of the underlying dynamics:

That is, a stall occurs when a product is churning enough users that it overpowers the counterforce – the product attracting new users and reactivating users (though this latter term is less important for startups). This happens because typically churn happens to a % of the user base, as anyone who’s seen cohort retention curves knows. But unfortunately, new customer growth channels tend to be fairly linear — most marketing channels don’t scale up as the user base scales up, and even the channels that do, like viral marketing, eventually saturate and slow down. All while churn continues to creep up over time as a percentage.

Because of these dynamics, I start by asking questions about retention to establish a baseline.

These questions are just a starting point, because once you ask them, the question is — what do you do with the answers?

  • What is the D1/D7/D30 of the product? (if consumer?) How does it compare to other products in its category?
  • If it’s a workplace product, how many days per week does the typical user engage? (This is the Power User Curve)
  • Are people as active and engaged as you expect them to be? If it’s a daily-use product, does your DAU/MAU ratio reflect that?

There are many benchmarks out there for all the product categories, but as a very rough guideline, you need a D1/D7/D30 of 60/30/15% to be at respectable numbers for a social app. You need DAU/MAU over 20%, and if subscription based, you want churn <5% if SMB (and free acquisition). There are equivalent numbers for net revenue retention, session lengths, and lots of other metrics too.

A marketplace company might look at a different set of metrics. Often the demand side can have heavy churn, but the supply side should retain well (>50% YoY). An enterprise SaaS product would have its own set of metrics. It’s important to benchmark, to see if there are successful products with similar metrics that have gotten to scale. If you have similar numbers, then probably these underlying retention metrics are not the problem.

Let’s look there first, but understand that you might find a devastating truth.

Admit it when people don’t want your product
There’s an ugly truth that when most products are put under a microscope, most of them simply don’t have the retention to sustain growth over time — this is “pouring water into a leaky bucket.” A slow growth rate is inevitable because products start at a mega disadvantage of needing to replace all their existing users who churn, in addition to building new marketing channels that grow the overall number significantly.

But “my product is not retaining” is also sometimes a fancy phrase for “people don’t want to use my product.” I say this because it’s a blunt way of stating what’s often true – that a new product is too experimental, too unpolished, or so poorly positioned, or underdeveloped, that no one wants to use it. I think this was especially a problem in the Web 2.0 days when folks would combine their favorite random set of product mechanics — disappearing text messages sent to strangers near you, but you can only reply with a video — and launch them as the latest app (Disappr! – gotta love those 2010 app names). When people don’t want your product, no amount of new customer acquisition is going to solve that. Yes, you can sometimes generate very fast growth rates for a few weeks or months, but eventually, it catches up to you. And then the product stalls, per the graph above.

Instead, when initial product/market fit is low (yes, another fancy way to say people don’t get it), I usually recommend the exercise of positioning more closely to existing product categories. As I argue in Zero to Product/Market Fit, any founder can instantly get to product/market fit by simply going after an existing category — of course, we all know how to build and design a coffee cup such that there’s product/market fit. You incur other problems, of course, such as competitive differentiation, but if you combine a well-known product category with innovation, and picking at the right time and place in the innovation cycle, it can work.

There are major questions to ask here:

  • Does my product have a clear, successful competitor? Is there a there there? (and do I have strong differentiation?)
  • When I ask people to describe my product back to me — without the jargon — what do they say?
  • When I ask people during user tests what kind of people might use the product, and what they’d use instead, do the answers make sense?
  • Do people actually like my product, or are they just being nice to me? And a famous question- is it a painkiller or a vitamin?
  • Are there any well-known product categories I could position against? Is there a way for me to test that positioning in user testing or otherwise?
  • Is my growth the fault of shitty retention? Or do I need better user acquisition?

When retention sucks, but you haven’t growth hacked yet
What if retention sucks, but you haven’t added email notifications yet? What if you can just do a big marketing push, and that might spike the numbers? I can tell you as someone who has seen many underlying metrics for a wide variety of products, moving the retention number is the very hardest thing to move. Usually, the initial numbers are a ceiling, and it only goes down from there. So if your numbers are bad, don’t think that adding notification emails will solve it.

There is a very very narrow set of situations where I will take this back:

First, long-term retention is often most improved by better initial user activation. A few years ago, in Losing 80% of mobile users is normal, and why the best apps do better, I show that the biggest difference in the retention curves of the best apps and mildly good apps wasn’t as much in their long-term retention curves, as much as their ability to get the numbers in the first 7 days up higher than others. So I often will ask the question to product leaders- what differentiates someone who’s activated versus not, in your product? What % of users become activated? And how do you make that 100%?

Second, there’s a narrow class of products that have network effects — social apps, workplace collaboration tools, dating apps, marketplaces, etc — and they will often have a “smile curve” when retention goes up as time passes, and the network fills in. I wrote a whole book about this so I won’t belabor the point, but the main point is, if a product is more useful when more of your friends (or colleagues) are using it, then retention will naturally float up as the product grows. Thus, a product that has poor retention in the early days might just need more network density. For these situations, I might suggest the team do a completely manual, hands-on build of a network — launching at a high school or a single office — and measure retention there. Sometimes it’s much higher, which means there’s a there there, and the product just needs to be launched in a network-by-network manner as some of the great companies have done via college campuses, cities, workplaces, or otherwise.

Whatever you do, don’t fall for the idea that you can fix your retention by simply adding features:

The Next Feature Fallacy: the fallacy that the next feature you add will suddenly make people want to use the entire product. -@bokardo

There’s a longer explanation of the idea here, but the TLDR is that when you add features that engage hardcore users, that’s going to be such a small % when in reality you need to stem the bleed in D1/D2/…D7. That is, in the activation step of the product. If you get 10% of your hardcore users to engage more deeply, the reality is that it won’t move the needle enough mathematically to lift your entire retention curve. This means that you need to listen to the “silent majority” of users who churn, rather than the core users who stay and are highly vocal.

Thus, I’d ask myself the following questions:

  • How is my retention? Am I counting on the ability to move metrics far beyond what’s reasonable? (You can increase 20%, but probably not 100%)
  • Am I betting the farm on some product magic that hardcore users want? Or am I working on things that cause more newbies to love the product more quickly?
  • Is my product in the category where network effects might substantially grow retention? Is that reasonable to think?

Top of funnel
It makes me happy when I see strong retention numbers with a flat growth curve. Funny enough, I consider this a very good thing. The history of fixing these situations is much better, and the approach is usually quite simple: Find more marketing channels, and scale existing ones. And if you can, find a self-repeating growth loop where users sign up for your product, use it, and then help generate more signups over time.

Just avoid the random lightning strikes. This could be from tech news coverage, a viral TikTok video, or a one-time email blast. You feel good for a moment, and when the excitement (and growth curve) dies down, then the crisis begins. It might be a fine way to solve a cold start problem or to get your first few hundred users. But it’s not a real growth strategy and leads to a product that’s lurching from crisis to crisis. Instead, the focus needs to be on repeatability, particularly once retention is established.

The easiest way to find a repeatable strategy is by simply fast-following other companies in your space. Finding and scaling marketing channels is typically pretty easy. If they are doing paid marketing, then go into those channels and test for CAC and measure payback periods. If they are marketing via Twitch creators or Instagram influencers, try that too. This method of simply experimenting and copying the competition goes a long way and often leads to success.

Testing marketing channels, alongside ad creatives and call-to-actions, requires an entrepreneurial spirit. There’s a huge advantage to testing a lot of different ideas, creatives, and landing pages and experimenting with messaging.

Growth loops scale and scale

Figuring out a growth loop is even more powerful. The idea here is that the loop helps attract users, who take actions that attract even more users, and so on. Thus a product with 10,000 users will grow quickly, but when it hits 1M actives, it can go even faster. This means user acquisition is a function of the size of the user base, and thus, it will keep up with the churn curve that’s stalking just behind it.

I have a few examples in my Magic Numbers deck, where I illustrate these as some of the classic and ideal growth loops:

Above: Viral loops are important because they are extremely scalable, free, and don’t require a formal partnership. This is based on users directly or indirectly sharing a product with their friends/colleagues, and having that loop repeat itself.

 

Above: A product like Yelp or Houzz fundamentally is a UGC SEO driven loop. New users find content through Google, a small % of them generate more content, which then gets indexed by Google, and then the loop repeats. Reddit is also like this. So is Glassdoor. And so on.

The process of figuring out these growth loops is not an easy task- it’s a form of product-led growth that requires an understanding of marketing, product, and sometimes growth hacking the underlying platforms/APIs to get a leg up (as Zynga did on Facebook, and Paypal did on eBay). But it’s very powerful when done well.

Polish your the UX flows that matter to growth — signup, inviting, payment — and ignore your hardcore user features
For teams that are focused on growth, it’s uncomfortable but necessary to ignore your best users and instead focus on UX targeted at users who may not be vocal at all. If you can polish your new user flow, then you can often make 20-50% gains to conversion, which then fall straight into the bottom line (whether that’s revenue or an active users count). When you polish your friend invite flows or referral flows, then you might get 20% of users to invite 100% more of their friends. And then that larger group of invitees will invite each more friends, and so on, with a larger viral factor. This is why when I assess product UX, I tend to focus on the less sexy stuff: Signup flows, invitations/referrals, and payment. And even surface areas like the lost password flow, which is for larger products, often block engaged users from getting back into their accounts.

Unfortunately, this is a product surface area that isn’t considered particularly sexy. If you’re at a large company, you may not get promoted to the next level of PM for delivering this type of project. In these settings, PMs are often rewarded more often for coordinating massive cross-functional projects than to move the needle on growth, by simply testing dozens of variations of signup flows.

And yet, this is often what matters!

There are a couple of key things I’ll often assess when looking at these growth-critical user flows:

  • Are the value props clear, the headlines crisp, and generating urgency for the user?
  • Are all critical elements — buttons, form fields, etc — above the fold?
  • Are extraneous links removed, to not divert the user, or otherwise moved to below the fold?
  • Instead of asking users to scroll, can content turn into a video, animated GIF, or slideshow?
  • How does it look on desktop versus mobile?
  • If the signup process is multi-step, can some steps be skipped for now, and done later?
  • Is the order of the signup right? Can you bring forward the magic moment, rather than asking people to fill out form after form?
  • Are there critical asks — getting a credit card, asking people to invite friends — that should be baked into the first few steps of the signup flow?
  • Does the signup flow activate people correctly? Should the user be “forced” to activate in any way, by adding required signup steps?
  • … and on and on

For new user flows, I try to get more users that hit the landing page to ultimately become activated users. I use tons of A/B testing and experiments in messaging to make this happen. For invite flows, I often try to stick them to the end of sessions so that users repeatedly see them as they engage the product. Maybe they create content, and you ask them if they want to share their newly created content with friends/coworkers. Do that every time, and you’ll be generating viral factor as you go, rather than just at the beginning. Payment is similarly important for products that focus on paid marketing to grow. The earlier you harvest purchase intent — often in the signup flow — the more you can plow that money into growth programs.

There are these flows and more, and they are the unsexy product features that drive growth.

Some final thoughts
Even great products stall growth. Famously, Facebook grew in its early years to take over colleges, but then saw a stall as saturation effects took over, and the product needed to be expanded past universities. Then there was another period of flatness, just before they expanded internationally. And another, before mobile. The same was true for Dropbox in its early years, as it saw a spike on Digg and Hacker News, but it needed a referral system and shared folders to push it to the next level. And in recent years, TikTok stalled as a platform for dance videos before it was acquired, and a very large paid marketing effort helped push it over the top based on building out a massive library of content.

These stories are common because successful products inevitably saturate a market, or need to jump from one acquisition channel to another, or any number of problems. When this crisis happens, it’s easy and reflexive to simply try to spend more on marketing. Or to try to develop more features. Or some other simplistic rule like that, sometimes based on the natural ability and interests of the product team.

Keep yourself from doing that.

Instead, consider that every stalled growth curve has its idiosyncratic issues. Sometimes it’s poor activation. Sometimes the novelty has worn off. Or perhaps the product is seasonal, or a marketing channel has been saturated. For better or worse, finding the levers to correct the stall requires patience, analytical abilities, and deep customer empathy. It’s hard, and every stalled product has its own story. But to identify the problem, fix it, and see the graph return to its previous glory — well, that’s just an amazing thing.

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