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Alessandro Desantis

Highlights

Aug 21 · linkedin

Will generative AI lead to a “Great Flattening” of consumer brands?

In Meta’s Q2 earnings call, Zuckerberg gave us a glimpse of what the future of advertising looks like on the platform: “Over the long term, advertisers will basically just be able to tell us a business objective and a budget, and we’re going to go do the rest for them.” In other words, the AI knows better, so just sit back and let it do the thinking.

This is hardly surprising for anyone who’s been watching Meta’s advertising technology pivot and evolve over the last few years.

Still, for all the operational efficiency we’re gaining with genAI, I can’t help but wonder whether we risk losing something in the process. A future where platforms take over every aspect of the advertising process, including creative generation, begets some questions:

  1. Historically, Meta has been pretty aggressive about letting its AI guide the show. How much control will brands retain over their ability to express themselves in a performance marketing context?

  2. We might soon be able to personalize ads in real-time for each viewer (and, to some extent, we already can). How far will we take this, and will it stress test the cultural imprinting theory of advertising?

  3. What are the long-term effects of AIs being trained on more and more AI-generated content?

No one has the answers, and we won't find out for a few more years.

What is increasingly clear, however, is that the only way out is through.

#ai #advertising #brands #ecommerce #marketing

Aug 19 · linkedin

Friends don’t let friends do big-bang e-commerce replatforms.

One worrying pattern we noticed at Nebulab as we entered the #Shopify space was that most agencies only know one replatforming strategy—the Big-Bang Rollout.

A Big-Bang Rollout goes something like this:

  1. Agency comes in and does discovery.
  2. Client signs the agency’s proposal.
  3. Agency retreats into a cave and works for a while.
  4. Agency emerges on the other side with the finished build.
  5. Client turns off the legacy system and launches the new one.

This approach—which is unfortunately the norm—comes with a number of problems:

• It inflates risk. It doesn’t matter how thorough your discovery or how diligent your QA, you will always, always, always miss something—that’s just the nature of software development. The larger the project, the more things you’re bound to miss.

• It’s a shock for your team. One major piece of a replatform is retraining your team on the new tech stack. The more dramatically you change the stack, the more difficult the training will be, which in turn will impact your operational efficiency and customer experience.

• It increases time to value. Every second your shiny new ecomm build spends on a developer’s laptop rather than serving customers is a second waste. Instead, you want the new tech stack out there as quickly as possible to maximize your ROI.

The alternative is something software engineers have been doing for decades when approaching big transformations, although it’s still relatively unused in e-commerce—it’s an Incremental Rollout.

It’s pretty simple: rather than launching the project in one fell swoop, you take one small piece of your infrastructure, move it to the new stack, and take time to collect feedback and adjust course before moving on to the next piece.

What this looks like in practice varies a lot: for some brands, you can go one market at a time; for others, you can migrate the B2B purchase journey before migrating B2C; others still will want to get even more granular, doing one step of the purchase journey at a time.

If you’re replatforming a brand doing $50M+ on e-comm and you’re not considering an incremental rollout, do yourself a favor and run a quick cost-benefit analysis—there might be a smarter way to get this done.

#ecommerce #replatforms #tech #shopify #dtc

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