Three Learnings for Startups after Big Tech’s Q3 Earnings Beatdown
Investors are punishing Big Tech for several strategic errors
65% of S&P 500 companies have already reported Q3 2022 earnings, and 70% have beaten earnings expectations, consistent with the 10-year average. MUCH better than most investors feared. As a result of these better-than-expected results, the S&P 500 is now up 4.83% over the last month.
However, BIG TECH has been underperforming relative to the rest of the S&P 500. The Big Tech stocks are down 11.1% on average, underperforming the S&P 500 by more than 15%.
In the last month, earnings expectations for 2023 have been revised down 2.3% for #Apple, 4.5% for #Microsoft, 7.9% for #Google, 17.9% for #Amazon, and 22.3% for #FaceBook. Compare that to the S&P 500, where earnings expectations have only been revised down 2.5% (and that’s primarily due to Big Tech).
Public market investors are punishing Big Tech for several strategic errors that I believe offer valuable lessons for startups to learn from.
3 Lessons to Learn from Big Tech
1) Forecast customer demand to help guide your capital allocation decisions
Big Tech’s cost structure has been poorly managed relative to other industries, as hiring has not been driven by customer demand but rather by the desire to grab talent before your competitor does. This competitive pressure has led to sub-optimal resource allocation, and now it’s showing in Big Tech earnings.
Ideally, startups are hiring based on necessity, driven by customer demand. Let me elaborate on that a bit; as an investor, I’m less enthused by companies looking to raise capital to generate more demand before having some market validation. Such as your first SDR achieving quota, or the CEO/Co-founder being able to book customers themselves. Prospective customers like talking to the people in charge. If the CEO/Co-founder can’t book a deal, an SDR will have a tough time too.
2) Create a detailed plan to achieve your revenue targets
COVID and a low cost of capital were a tailwind for more technology businesses than we realized. Even the growth rates of the cloud providers have begun to decelerate as customers scrutinize spending more carefully (true for AWS & Azure, GCP revenue growth accelerated slightly).
When speaking with founders looking to raise capital, as an investor, I like to see some thoughtfulness in your approach to determine what your revenue targets are, and what amount of capital/resources you believe you’ll need to achieve those targets. How much will you need to spend on SEO? How many SDRs does this forecast assume you have to hire? What about post-sales support to keep customers satisfied?
When creating your financial plan, start with forecasting top-line by understanding your market opportunity and all aspects of your funnel (demand gen channels, conversion from “Awareness” to “Interaction,” etc.) and then budget accordingly.
While it’s nearly impossible to forecast any of this perfectly, seeing some mental energy expended on this exercise to understand what it takes to achieve growth targets gives me more confidence in your ability to do so.
3) Recurring revenue models are more valuable in downcycles
Big Tech isn’t as safe as an investment as we thought, especially those more dependent on transactionally derived revenue, such as advertising. Tougher economic cycles such as the one we’re experiencing are a reminder of why software companies and their investors valued subscription-based revenue models since the Great Recession. Value-based pricing models were beginning to gain traction and still make sense in many businesses, but investors will again increasingly appreciate the certainty in recurring revenue.
As an investor that has a basket of potential investment options to choose from, those opportunities with more visibility in the sustainability of their cash flows are at an advantage in uncertain economic environments. For better or worse, some companies may begin feeling pressure from investors to make their revenue models more stable, which was a driver of the recurring revenue model post-2009.
What do you think? What other recent observations/learnings from Big Tech do you have?
