5 Companies That Will Be Huge in 2028 - Part 1

Welcome to another edition of “In the Minds of Our Analysts.”

At System2, we foster a culture of encouraging our team to express their thoughts, investigate, pen down, and share their perspectives on various topics. This series provides a space for our analysts to expose their insights.

All opinions expressed by System2 employees and their guests are solely their own and do not reflect the opinions of System2. This post is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of System2 may maintain positions in the securities discussed in this post.

Today’s post was written by Kevin Nutter.

This is the first piece in a three-part series dedicated to sourcing potential investment ideas by reimagining who we think of as an “influencer.” The goal is not to use AI/ML to evaluate brands. Instead, it’s to use AI/ML to uncover and track "micro-influencers" who’ve proven they are already elite brand evaluators. If you’re an early investor in private companies, stick around.

Today:

• Part 1 - Discovering a micro-influencer

To Come at Later Dates:

• Part 2 - Find clusters of micro-influencers (use AI/ML to do it—yay for buzzwords!)
• Part 3 - Presenting micro-influencers’ top 5 consumer-facing companies of 2028!

Takeaways

• Micro-influencers are individuals who are AWESOME at the early identification of high-growth brands
• At least one micro-influencer exists—rev growth of her curated brands is up 598% since 2019
• We’ll use alternative data to uncover thousands more micro-influencers (stay tuned for parts 2 and 3)

This micro-influencer’s portfolio revenue is up 598% since 2019

I worked closely with a single individual for this analysis and, for privacy purposes, we’ll refrain from using her name and instead reference her as our “micro-influencer.”

I know this individual very well, and she is cool—like very cool (much, much cooler than me, but I suppose that’s obvious given that I’m spending my time writing this). I’ve long thought that if we just invested in the companies that she thinks are cool, when she thinks they are cool, we would be wealthy beyond our wildest dreams (1). Turns out, I was right, we would be (2).

For this post, I wanted to know if her brand preferences were predictive of future brand performance, so we settled on a few simple categories to test:

1. Brands she adopted before 2020 that she still thinks are currently great
2. Brands she knows many others like, but she’s always thought are “meh”
3. Brands she thinks were once great but aren’t anymore

A company is its brand for our micro-influencer. And for her, evaluating a brand entails some intangible combination of product/service quality, adoption across other micro-influencers, customer base, social media presence, the executive’s/owner’s personal brand, and opinions from carefully curated professional investors. Each of these factors is weighted differently in different situations at different times. To be great at this, you need natural ability enhanced through years of indefatigable practice.

Her “currently great” brands significantly outperform their peers

She has remarkably high performance with consistency to boot. Thirteen of fifteen companies were above the 80th percentile in their comp group (3), and three of them were the best-performing brand amongst their peers. She’s a unicorn at picking unicorns.

The only one she missed on, Net-a-Porter, seems to be losing the competition to Revolve Clothing. Maybe something we should have thought about while we were doing portfolio construction…

Her "meh" brands, which are otherwise popular, performed just OK:

To her credit, if it ain’t exceptional in quality and growth, it ain’t for her.

Her "formerly great" brands show a missed opportunity:

We can’t get an accurate sense of her performance on these brands while she thought they were great because there isn’t enough data history (notice the different column headers). So instead, I looked at their performance after their brand was no longer considered great, and Awaytravel performed pretty well relative to peers—a missed opportunity. You may be asking, but how could you tell that the brand was devalued without speaking to the micro-influencer? Turns out, when presented with buying a suitcase, she bought a Tumi instead of an Away bag.

Micro-influencer's value to the investment sourcing process evolves with life phases

The type of high-growth brands a micro-influencer identifies will evolve with life. For example, the Millennial micro-influencer has already identified baby product brands that will grow in popularity over the next five years (sneak peek into part 3 of the series). Without knowing it yet, a few decades from now, that same micro-influencer will identify the coolest retirement communities and lifestyle brands.

Sadly, it means the Millennial micro-influencer won’t be sourcing companies that are no longer relevant to their life phase. We’ll need to find a younger cohort of micro-influencers to do that, but how?

Upcoming - uncovering thousands more micro-influencers

In the next post in this series, we’ll identify cohorts of the highest growth brands in different industries, maturities, geographies, and customer demographics over a period of time and cluster individuals who began transacting with many of them early in the brand’s growth curve.

In the final post, we’ll see the brands they’ve started adopting recently to get insight into the five best brands of 2028.

Footnotes

1. The micro-influencer, in no way, endorses any of my word choice, especially those that contain “trendy” or “cool.” Come to think of it, she pretty much in no way endorses any of this post.
2. Obviously, this analysis is overly simplified. Besides the logistical barrier of lack of access to the funding rounds for these companies, the company valuation will matter a lot as it relates to us getting wealthy beyond our wildest dreams. But we’re just having fun and showing what’s possible with data, so hopefully, you can give me a pass for now.
3. Comp groups represented similar-sized (+-20% revenue from when they were first identified as cool) and in the same category. Categories included the following:

• “Retail, Fashion, Clothing and Accessories”
• “Retail, Fashion, Shoes”
• “Retail, Beauty Products”
• “Retail, Fashion”