#69 Direct-to-Consumer Companies & Long Tail Opportunity in AI (Above Average Newsletter)

Welcome to 50th edition of the Above Average Newsletter. Your bi-weekly source of Above Average takes on the business of big technology written by Nataraj Sindam.

Topic 1: What’s with Direct-to-Consumer Companies?
What’s common among all these companies?
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They are all public direct to consumer companies whose stock is down ranging from 80 to 95% in last couple of years.
If you are direct to consumer company the best time to go public was in 2021 when the pandemic has fueled an ecommerce spending spree. Once this is over, the markets realized a lot of these direct to consumer companies have no path to profitability and have unsustainable business models.
So what can we learn from what is happening with direct to consumer companies -
When you are willing to spend on high customer acquisition cost (CAC), you can create a short term non profitable direct to consumer company, even when industry dynamics don’t support it. If you spend enough amount of money on Facebook and Google ads you can sell any decent product.
VC money was used to subsidize CAC, that is clear. But that stopped and these companies are not close to profitability and a lot of them are on the verge of bankruptcy. But if I am an investor in such brands the one thing I would look for is that the product innovation should reflect in my customer acquisition cost being low. If you are not able to get very low customer acquisition cost on your product or brand, then technically you are not creating value with your product. Your customer acquisition cost reflects whether the product/brand is actually desired by the customer & if the industry dynamics support it or not.

Topic 2: Where is the AI opportunity?
It’s easy to see big funding rounds in AI for foundation model companies and think AI is all about Fearsome Foursome funding Geoffrey Hinton’s ex-students or ex-open ai employees.
But I think the real opportunity in AI for next couple of years is in the long tail of building specific narrow application that solve small problems that were not possible before. There is treasure trove to be exploited by teams of 1-3 developers to build SaaS applications which can generate millions in revenue.
LLMs are a super power for full stack application developers. If you want to build something and are looking for such ideas feel free to reach out to me.

Topic 3: 100 Days of AI experiments
AI is going to impact us all, so as part of 2024’s first 100 days I am going to spend 1-2 hrs a day learning, experimenting, reading & tinkering with the latest AI models, products & content. You can follow along by following me on Twitter or here on my blog . My goal in this 100 days will be focused on what new things we can build using AI and what to expect from AI in future. The series is also published here on hackernoon .

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Till next time, stay above average.

Nataraj

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