Hey friend 👋

Here are some of my favorite SaaS reads from the past couple of weeks again:

1. How to do Root Cause Analysis to figure out what happens if numbers go down
2. The myth of exponential hypergrowth
3. Influence Maps
4. How Yahoo grew – and lost the game

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#1: How to do Root Cause Analysis to figure out what happens if numbers go down

If you wake up one morning to find a 20% drop in your KPIs, you should always know why before your CEO asks. Craftsvilla is an e-commerce portal whose north start metric was Conversion (Transactions/DAU). Here's the exact RCA (Root Cause Analysis) process they would use to figure out what happened if this number were to drop unexpectedly.

How to do Root Cause Analysis

1. Check the source and dashboard for errors before troubleshooting anything else.
2. Check for seasonal effects (For B2C, this can be holidays; for B2B, even weekend vs. weekday)
3. Check technical issues: Was there any server downtime? Were the API response times the same as usual? Did any new build go out yesterday? If needed, break it down into smaller pieces. Example: Between 2 PM to 5 PM, there were no transactions recorded. It means something happened during that period that led to the overall conversion drop.
4. Check the conversion funnel and see if there was a drop in that metric. Example: Between 2 PM to 5 PM, there were no transactions recorded. It means something happened during that period that led to the overall conversion drop. Check the performance of all traffic sources and user segments, e.g., mobile vs. desktop, new users vs. old users, organic vs. paid – or even external factors like a drop in SEO rank? Also, check how many new users transacted on the app yesterday to determine if the issue lies in acquisition.
5. Look at all customer engagement channels (Support tickets, Play Store reviews, Customer chat logs, etc.) to see if the volume of complaints increased.
6. Finally, check external factors: Are competitors running massive marketing campaigns? Has there been negative PR associated with your company that has led to users churning to your competitors? Is there some industry trend responsible for the dip?

​Read article here​

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#The Elephant in the room: The myth of exponential hypergrowth

When a startup grows fast, the journalists marvel at its "meteoric rise." But don't meteors fall? Inevitably it is breathlessly inducted into the class of "hypergrowth" companies that are "growing exponentially." Especially when the product is "viral."

Hypergrowth is quadratic – not exponential

• In exponential growth, values grow by a multiple: In year 1 you grow 10, year 2 by 100, and year 3 by 1000 – each time, the amount of growth is multiplied by ten. This compounding effect gets journalists and VCs justifiably excited than normal, quadratic growth where values grow by adding a constant amount more each time-interval, rather than multiplying a constant amount more each time-interval. In the same example, growing in year one by 10, then in year two by 20, in year three by 30.
• However, real "hypergrowth companies" like Facebook (that got to $50B in revenue faster than any company in history), Slack, Trello, Lyft, Hubspot, or Dropbox, didn't actually grow this way – regardless of built-in virality or network effects (e.g., friends bring other friends). They all grew more or less quadratically (especially when examining growth in absolute dollars rather than %).

The Elephant Curve: Why marketing-driven products grow quadratically?

• A typical marketing campaign follows a specific pattern, "Elephant Curve": they start flat when the new campaign is ineffective; in the optimization phase, we test our way to incrementally better results; and finally, campaigns enter the phase of decline where the audience saturates (if the campaign ever flies, that is), the channel declines and in paid channels, the auction becomes uneconomical.
• Ideally, marketing campaigns should be layered on top of each other for cumulative contribution to revenue. Each campaign is essentially linear after it gets going, even if it sags during decline. All these layered campaigns create a "wavy quadratic" – a slowly but steadily rising revenue chart.

Beyond marketing campaigns: "Viral" and other forms of "exponential" growth

• Some products don't grow proportionally with marketing and sales, but instead self-propel with a mechanism that theoretically ought to be exponential.
• There are at least three ways for this to happen: 1) Virality (each user brings in more users, e.g., social media, chat clients, peer-to-peer payment platforms, ), 2) Word-of-mouth (built-in mechanism like sharing Wordle results), 3) Hot Trend (Products that "everyone" – in some well-defined market – is going to buy, e.g.)
• Even these products cannot grow forever, for the obvious reason that markets are finite. Therefore, even if "exponential" is the correct model for the core growth mechanism of the product, it nevertheless cannot continue growing exponentially because it runs out of market.
• The other problem is that markets tend to have so-called "low-hanging fruit" (or early adopters). High-strung fruits are harder to pick, so growth slows.
• This suggests a curve that starts exponentially, but then slows as it runs into the soft back-pressure of more demanding customers. This logistic curve is exponential in the early days when it is far away from its natural limit. As the product (or gas or virus) gets to around 25% market penetration (or infections or saturation), the curve flattens into linear growth, in a tension between the exponential force of growth, countered by fewer and more demanding remaining targets. Finally, it levels out at what is called the "carrying capacity"—the fully-saturated market.

Hypergrowth companies start with market-share

• Suppose you're Facebook: you've saturated many markets, but thankfully, the markets are growing, so you should still be able to grow too.
• If we look at Facebook's MAUs as a percentage of people online—their market share – we see that growth relative to market size it is an Elephant (complete with logistic trunk, optimized back, and declining rump – even despite a COVID bump), even though overall growth appears so "linear". They simply compensate the decline by looking into new revenue opportunities.
• We already know that Facebook's user growth is linear and revenue growth isn't exponential either – instead, it's yet another Elephant curve: because MAUs are Elephantine (which means mostly linear), and revenue-per-user is Elephantine (which means mostly linear), when you multiply them you get a quadratic, not an exponential, and that's what we see in Facebook's overall revenue growth.

Takeaways

• Early on, you should focus on winning market share in one space, creating the first "Elephant Curve"
• After the product matures, something more drastic is required: Wholly new products or updates significant enough to address new markets.

​Read article here​

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#3 Influence Maps

Understanding how people learn about and engage with your space will make your marketing far more effective. Enter Influence Maps – one of the best kept behavioral design secrets in marketing.

What's an Influence Map and why do you need them?

• In short: visual frameworks that try to answer core questions about what people's behaviors are and how they can be influenced. In simple terms: a high-level way to illustrate how and where marketers should do their jobs.
• The idea is straightforward: know the buyer journey, and you can invest in the right places, through the right channels, and with the right sources of influence to have the desired impact. With influence maps, you can form hypotheses about audience behavior and design experiments to validate them. Influence maps bring the scientific method to your strategy, not just your tactics.
• Influence frameworks should center around our own "jobs to be done," i.e., the work that we'll do better once we have answers to essential, strategic questions, e.g., How do people get exposed to your company's industry/niche/problem/space? How does a person discover they have the problem your product/service solves? What is the consideration process for would-be buyers? And so on.

How do I get the data?

Instead of relying on guesswork or gut feeling, pre-existing roadmaps, or advertising tools, you can use the following ways to get the information you need:

• Customer interviews: Current, potential, ex [Editor's note: Churned! Always talk to churned customers! In high-touch B2B, preferably also closed lost cases.]
• Surveys [Editor's note: especially good for validating underlying hypotheses with bigger sample sizes when you know what you want to ask]
• Passively collected social/web data

​Read article here​

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#4 How Yahoo grew – and lost the game

A great thread on how an internet darling did a bunch of bad decisions over the years and went from $125 Billion to $5 Billion.

​Read Twitter thread​
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​That's it for this week. I'd love to know what was your favorite read this week!

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Cheers, Anna

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P.p.s. Did you know you can now find all previous summaries here?

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P.p.p.s. Connect with me on LinkedIn and Twitter! (Warning: I mainly post memes and rants about marketing, but if that's your jam, let's be friends. I'm also Head of Growth at an EdTech startup and a freelance consultant for B2B SaaS startups, but honestly, I'm more into shitposting than personal branding.)

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