My annual review of 2022 is all about shifts:
- The economic shifts from prosperity to recession
- Apple’s tracking policy marks the shift from full-funnel to cohort tracking
- Social platforms shift from success to an unclear future
- The employer landscape shifts from all-in remote to either remote or in-office
- A shift from Crypto to AI as “the next big thing” in Tech
Stay tuned for my 2023 prediction next week.
The 5 big tech trends of 2022
You can't connect the dots looking forward; you can only connect them looking backwards.
So, let’s look backwards.
1/ The economy shapes Marketing
2022 had a very interesting arch. The year started optimistically with the feeling that “the end pandemic is over”, and we can focus on progress. But the S&P 500 peaked on January 3rd. Three months later, it was down -10%; six months later, -20%.
Russia attacked Ukraine in February, the Fed increased rates in March, valuations started dropping in April.
Stocks fell into oblivion.
Depression was in the air.
High inflation, growing interest rates and the connected drop in public markets trickled through the whole tech industry. Lower consumer spending negatively impacted B2C and B2B companies. Stock prices dropped and signaled to investors that companies were overvalued and the markets overheated. Funding rounds shrunk; some companies had to do down rounds. Less venture capital meant companies had less money to spend on growing quickly. The downward spiral accelerates until (public) companies reach valuations that are in line again with their revenue and profits. That’s how the economy shapes Marketing.
One result of the spiral is layoffs. During the pandemic, some companies gained “the pandemic 20” (extra weight from staying at home). Now, they need to go on a diet. More tech workers were laid off in Q4 2022 than in Q2 2020. We can blame companies for overhiring when performance made a 10-year leap. At the time, we didn’t know that the leap was a credit, not a free check. Hindsight 2020 (literally).
We might have only seen the beginning. Meta laid off 11,000 people in November 2022 but is still up +60% from its pre-pandemic headcount of 48K (in Q1 2020). If tech stock performance indicates layoffs, and big tech stocks would revert back to their performance of February 2020, Meta would have to let another 29,000 people go, Alphabet 63,000 and Amazon 704,000. Layoffs of such magnitude are unlikely to happen, but the last two years had a lot of “unprecedented” surprises.
Layoffs flush talent on the open market that either turns into contractors and consultants (minority) or looks for another job (majority). Being laid off early in a down cycle is painful but increases the chances of landing another job after most companies cut headcount. Being laid off later is less painful in the moment but makes it harder to find another job because competition has increased and open headcount is scarce.
The silver lining? Less pressure to raise up to very high, maybe unrealistic investor expectations might lighten the load on employees. Growing into a high valuation means pressure (and stress) trickling all the way down from investors to individual contributors. Could this be one force behind quiet quitting and burnout that we underestimated? The data shows burnout got worse during the pandemic across all age groups [source]. Being forced to work from home often under less-than-ideal conditions and the emotional stress of the pandemic are likely to be key drivers of accelerated burnout. And yet, my assumption is that Tech companies that thrived in 2020 had such high expectations to keep growth going that their unrealistic expectations led to mass burnout and Quiet Quitting in 2021.
Another silver lining for SEOs: less capital and more pressure to become profitable push companies to invest in unpaid channels like SEO. Airbnb started reducing performance marketing spend before the pandemic and learned that numbers are constant. Airbnb’s main driver of growth is its network effects (and SEO). How many more companies will discover that they don’t need as much paid spend to grow over the next 24 months?
How many Marketing teams will throw their plans over board in early 2023 because the macroeconomy changes the playing field?
2/ Hardware as a gatekeeper
In 2022, Apple showed us that hardware Marketing can be a gatekeeper to Marketing and Growth.
Disappointing Q3 earnings from Meta, Alphabet and TikTok were early indicators that the economy shifts and companies spend less on marketing. But the macroeconomy was a welcomed factor to cover an agent that advertising platforms were a lot more reluctant to mention: ATT (Apple Tracking Transparency).
In April 2021, Apple started asking users whether they wanted to be tracked. Of course, the majority of users decline. Fast forward to December 2022: Meta, Youtube, Snapchat and TikTok suffered billion-dollar losses. Experts estimate Meta lost at least $10b in 2022 just from ATT while Apple’s ad revenue increased [source]. Privacy and agency over data are very important, but Apple hasn’t gotten rid of tracking per se. Apple defines “3rd party tracking” as “any app tracking user behavior that’s not Apple”.
The privacy debate in tech is far from settled. What GDPR and CCPA have accomplished so far except for a few symbolic fines, understaffed regulators and frustrated users? Do we really read the fine print when popups ask us for tracking permission, or do we click on “accept” so we can browse the site we want to see?
The monetary impact of ATT on advertising platforms shows how critical attribution is for growth. One future trend that will make attribution even harder is the death of third-party cookies. Both Apple and Google plan to replace cookies with less invasive cohort tracking in apps and browsers. How good these replacements are is yet to be seen, but it’s clear that marketing attribution will become fuzzier. Maybe that’s a good thing?
Marketing attribution models are powerful GPS systems but can also lead to short-sighted thinking. Most models look at 90-day windows. As a result, we forget about users who have seen our ads or content but weren’t on the market during the 90-day attribution window. We can’t measure the downstream effects of being top of mind. Maybe we need better attribution models, or Marketing will revert back to being less data-driven and more research-driven.
Could that be a good thing? We already miss a lot of insights from direct traffic, which often measures traffic sources that are valuable but not measurable, like dark social, brand traffic and sources with hidden referrers. We don’t know whether direct traffic is the result of a paid campaign or an article that went viral and was shared in lots of Slack groups. The best way around it is to ask users how they found you when they sign up and compare that to attributable traffic channels.
SEO likely benefits from fuzzier marketing attribution because search keywords inherently convey an intent, and paid channels either become too expensive or lose attraction. You don’t need to track users for intent when they reveal it through a search (or even a series of searches).
3/ The value and future of social networks are unclear
The last big economic downturn in 2008 also marked the rise of social networks. Companies saw a low-cost opportunity to advertise and consumers found a new way to find products, connect with friends and follow the news. Even further, consumers used social media to cope with the recession and find new jobs. Pew Research found that 17% of online economic users looked for jobs on Facebook, and 69% of Americans used the internet in 2008 to understand and cope with the recession [source].
Now that we’re facing another recession, we’re coming full circle. We’ve learned more about the trade-offs and downsides of social media. Advertising has become a lot more expensive and less accurate (see above). Social platforms are at crossroads, and we’re reframing their value for us as a society.
Meta has decided to go all in on the Metaverse and spend an annual $10B on top of the +$10B it’s losing from ATT. The stock price lost ⅔ of its value within 12 months. Meta made $40B in profits in 2021, but a shrinking advertising market, a massive strategic pivot and damage from ATT paint a dark outlook. And we haven’t even addressed the elephant in the room.
TikTok surpassed Meta & co in app installs back in 2018 [source]. Fast forward to 2022, the success of TikTok hurts all attention platforms. User time spent on TikTok outranks Youtube, Twitter, Instagram or Snapchat [source] with an estimated number of 1.6B total users [source]. However, Tiktok’s growth has also slowed down in 2022. The company adjusted its annual earnings prediction from $12B to $10B - more than 15% lower than expected [source]. TikTok competitors captured 42% of market share in June 2022, compared to 24% in January [source].
Another platform that’s facing challenges is Twitter. After Elon Musk couldn’t get out of his commitment to buy the platform, he took the reign on October 31st and immediately fired 50% of the company. Musk diluted Twitter’s tremendous, unused growth potential by antagonizing everyone, from legislators to Apple’s CEO Tim Cook.
Meanwhile, Youtube’s revenue was on track to surpass Netflix but then stumbled. In Q3, Youtube reported a revenue decline of -3.6% year over year. Still being the #1 creator platform with ~50% revenue share, Youtube is now under pressure to monetize its strongest horse in the stall: Youtube Shorts.
Organic social marketing for companies died a long time ago and was replaced by paid social. Now, it seems creators are picking up the pieces. I myself noticed that over 30% of traffic to my site comes from social platforms like Twitter and Linkedin. The creator economy is estimated to be worth more than $100B dollars - more than the film industry [source]. Creators made huge leaps in garnering attention this year.
Where are social platforms going from here? What’s the role of messaging and e-commerce as a way to engage users and open additional revenue streams that are not stunned by 3rd party tracking?
4/ Not all companies will stay remote
A 2nd order effect of the pandemic is the acceleration of remote work. When white-collar workers had to work from home, some used the opportunity to move to cheaper areas or closer to their families. Today, more than 20% of paid jobs in IT, tech, services, education and administration are remote.
In December, Linkedin’s CEO posted that 50% of job applications go to remote jobs, which make up 14% of all job postings. But he also said that people are moving back to cities for jobs. The trend is changing.
A survey by resume builder found 28% of companies plan to change their work location policy, and 21% are ready to fire employees who don’t come back to the office [source]. At the same time, Microsoft found almost as many employees are considering switching from hybrid to remote as are from remote to a hybrid model [source].
Some tech companies are using the call back to the office as a way to do “silent layoffs”: reduce headcount by making it a contractual requirement to come back to the office, while knowing some part of the workforce won’t.
Some people resist the return to the office. In May, a high-ranking Apple executive quit his job over the in-office policy. I know several top tech executives who have or are planning to leave their jobs if in-office presence is required.
The core challenges of remote work are productivity and connection. It’s easier to “monitor” team productivity when people are in the office. 124K members of the r/overemployed Subreddit don’t necessarily create more trust between managers and contributors. And yet, control is a bad reason to bring workers back. Teams perform better when trusting each other.
The workforce is still shifting and transitioning. America’s job market is still strong but slowing down. Will remote work shrink back to its pre-pandemic size and enter the books as a perk for good times, or is remote work here to stay?
5/ Crypto vs. generative AI
A lot of people thought 2022 would be the year of Crypto and NFTs, but it turned out to be the year of generative AI. In a sense, they’re antagonists: Crypto and NFTs are based on scarcity, AI on abundance. With generative AI, anyone can create any image. NFTs are unique images. What happens when DALL-E copies an NFT? We’re not there yet.
In the same way, the last two recessions stand in sharp contrast to each other. In 2008, the old financial system imploded. In 2022, through crypto hasn’t led to the economic downturn, the new financial system imploded. Part of what drove the Crypto hype is perspective. Millennials are the first generation to do worse than their parents (in the West). Most crypto investors were young people who wanted a better future for themselves. How ironic that SBF, a 30-year-old millennial, stands at the center of Crypto fraud.
Back to AI, a millennial also stands at the center of AI, and his name is also Sam: Sam Altman. When OpenAI opened the floodgates to Chat GPT, a chatbot based on GPT-3, it became the #1 Tech topic. Chat GPT is good, but what makes generative AI so intriguing is not where it is today but that we can see how good it will get in the next 12 months. Other than a lot of crypto coins, there is real utility in AI.
Generative AI can already solve real problems today:
- Chat GPT helps you brainstorm ideas
- Lex unblocks writer’s block
- Byword writes outlines and articles for you
- Jasper creates an article draft
- Stable Diffusion, DALL-E, Canva and others create thumbnails and graphics
Seeing how close we are to using AI in our day-to-day workflows means there is a window of opportunity for current platforms to use their distribution advantage. Canva was quick to add generative image AI to its platform. Now you can create images with a simple prompt and use them in your marketing collateral. It will be exciting to watch how big platforms like Shopify, WordPress, Adobe and many others integrate AI models.
The important point to understand is that AI doesn’t replace humans; it solves tasks. Shortly after the release of Chat GPT, many Tweets predicted the end of Google Search caused by an AI model that gives an immediate answer, but generative AI is still too expensive and slow for mass adoption. A really good, single answer would be a threat to Google’s business model, but search engines have many benefits over an AI that gives a single answer, like access to vast amounts of data.
What’s the connection between the economic downturn, hardware as a marketing gatekeeper, the changing landscape of social networks, a shifting workforce and generative AI?
A lot of things ended in 2022
- The longest economic growth sprint in history
- The 100% human-generated content era
- The Meta/Alphabet Dynastie
- Social networks as we know them
- Perfect marketing attribution
If 2022 was all about shifts, 2023 must be the year in which we play in a new formation. More in my predictions next week.