At the MarginsEvery brand, from a scrappy startup to a Fortune 500, faces the same fundamental problem: How do you get discovered in a sea of consumer choices?
For decades, the answers shifted: first it was getting shelf space at brick and mortar retailers, then Amazon search as online sales took off around 2010. Then Google SEO. In every era, the challenge was the same — being visible in a world where gatekeepers decide who gets surfaced and who gets ignored. Now, the gatekeepers are AI agents.
AI is moving fast, but the business models behind it are even harder to decode. I’ve been spending time mapping out who the key customers are and how money flows through the system. Foundational providers (OpenAI, Anthropic, etc), wrappers (Harvey, Jasper, etc) — each plays a different role in the value chain, and investors and operators alike are still figuring out how to navigate the commercial landscape.
I’ve built and scaled growth models at companies like Newell Brands, Casper, Blue Apron, and Lime, and today I advise startups, investors, and corporates on how to navigate this shifting landscape. To cut through the noise, I created this AI Business Model Guide — a simple framework to understand where opportunities lie and where risks emerge.
If you’re building in AI or exploring partnerships, this guide is a starting point. The presentation is embedded below.
Over the last year, niche AI startups have exploded onto the scene. Companies like Slingshot (mental health), Harvey (legal), and Jasper (marketing), Cursor (code editor) are racing to stake out territory on top of large language models like ChatGPT and Gemini. At first glance, they feel innovative and differentiated. But if you squint, they look a lot like the early wave of direct-to-consumer (DTC) brands — Casper, Warby Parker, Glossier, Harry’s and Peloton — that disrupted incumbents not by reinventing the product, but by reshaping the story, distribution, and consumer experience.
I saw this firsthand at Casper. We weren’t reinventing the mattress — foam was foam — but we were reinventing the consumer experience and telling a story incumbents weren’t telling. We addressed a lot of the pain points in the legacy purchase experience (returns, trial, etc) with novel solutions.
The analogy here is hard to ignore.
The big management consulting firms will have to adapt quickly to AI. The days of paying half a million dollars for a strategy deck are over. By way of example, I was curious, what is next for the food delivery sector (e.g. UberEats, DoorDash, etc) so I put together a prompt and leveraged ChatGPT.
Back in March 2023, I wrote this article about how I was beginning to leverage AI (specifically ChatGPT) in helping me frame business partnerships. This was relatively early in the commercialization of AI. That now feels like an eternity as the space continues to evolve. Today’s post is not an overview of AI – for newbies I highly recommend LinkedIn Learning’s Generative AI for Business Leaders course taught by Tomer Cohen. Google also has a training module on Coursera for business leaders which is a good primer. It’s easy to go down a rabbit hole trying to wrap your head around the space so my recommendation is to start with the basics and then tailor the learning to your specific field.
I wanted to share today another use case that has been generating noise and is relevant to retailers and brand marketers – and top of mind for me given my background working in and consulting DTC brands, consumer goods companies, and retailers – the rise of AI shopping agents.
I’ve taken a bit of time off from blogging recently to focus on other things, but recently came across this article from the WSJ about the fall of VF Corp ($VFC) and it reminded me of other legacy brand aggregators, such as Newell Brands ($NWL), that have also struggled as of late. There is a common strategy across both companies – they chose to concentrate key decisions around marketing, product development, and sales at the corporate versus brand level. And the results clearly show that was a mistake.
Total digital ad revenue in the US climbed 10.8% to nearly $210b last year, despite a slowing economy and a myriad of other challenges. While the growth rate is a far cry from the 35% figure in 2021, it still shows that marketers continue to spend online to drive purchase consideration. But there was an interesting stat included in that $210b spent last year – 20% was on retail media advertising.
One of the most difficult aspects of doing partnerships or business development regardless of industry or sector is clearly understanding why two parties should get “married.” In my experience building numerous JV’s/partnerships, one theme continues to resonate, and that is how do you construct a winning partnership where each side feels as if they have gotten equitable value. Oftentimes, initial discussions tend to be more tactical or acutely focused on a very specific asset that one side seeks access to, when the focus should be framing the outcome from inception. This entails being able to articulate clearly the ‘gives’ and ‘gets’ of a deal and not jumping right into the weeds. Jeff Bezos has said, at Amazon, before any work is done on a new partnership, the press release is written. This accomplishes a couple key things.
If you’ve used food delivery apps like DoorDash or UberEats over the last few years, you’ll notice the number of restaurants on the platform has skyrocketed. And interestingly, they all seem to be offering the same types of cuisines. As it turns out, these platforms have become a battleground for testing virtual concepts. In 2021 there were roughly 10,000 virtual brands on UberEats but today that number is now 40,000.
As I was reading last week about how McKinsey was hired to help Disney streamline costs this year, it drew similarities to my time at Jarden when we merged with Newell in 2016. MK is a great firm, don’t get me wrong, but I continue to see this playbook applied that doesn’t always work. Centralization is not invariably the answer, especially in businesses with strong IP and nuanced relationships.