I'm pretty sure the person who wrote this has never run pricing research for a brand. Short answer, they can ignore Gabor-Granger because their cost base is so low compared to their revenue, so they'd be looking at Van Westendorp's Price Sensitivity Meter to set a benchmark for where the pricing probably lands, and a conjoint study to understand the value of different elements for segmenting different versions of the product at different price levels.
Obviously positioning, who they're positioning against, how they communicate that, the level to which they're known amongst the market etc all feed in to this, but that'd be a decent starter for ten.
This is an overly simplistic version of where to go with pricing for a brand like this, but that's where I'd begin with creating pricing for them.
How do you know what their cost base is? I don't quite understand how you'd be evaluating that. Their cost base is largely driven by the LLM and cloud companies. The $25/month pricing feels chosen to be similar to other unrelated SaaS businesses more than something based on a serious pricing analysis.
And the article confirms that, saying they made up a starting price and then immediately lost money due to (doh) selling a product where your costs scale by usage for an unlimited flat rate, which is surely one of the most basic pricing issues out there. And not just for LLMs: they host the apps too, putting them on the hook for hosting costs. They're using a ton of very expensive PaaS services like Supabase to do that too.
Then they have the free tier. Such services often have massive free tier costs; if their userbase is made up of a lot of people just trying stuff out quickly before exporting it to GitHub to continue, that problem will be worse. According to their blog, they have 30,000+ paying customers but there are 25,000 new apps created per day with 1.2M apps overall. So, clearly, almost all apps are being created by free users.
Don't get me wrong, maybe they're printing money like there's no tomorrow, or maybe they will soon. But it feels like the sort of business that's probably burning VC money to buy market share. If their cost base is good then they feel very vulnerable to an OpenAI or AWS releasing something tomorrow that takes away a big chunk of the business, seeing as that's where the bulk of the value lies. Oracle already has something quite similar launched in APEX.
This is interesting to pull apart if anyone wants to add more id love to hear.
Right now Lovable has competition in the vibe coding arena. Like Replit for example. I found Replit to be better in my testing.
I think there is an interesting curve where software is generally worthless (see Github!) but software plus marketing/sales etc. is valuable. But if you have any kind of scale that software needs to be robust and AI can't do that yet.
So there is a weird evolving Venn diagram where the final app industry fits in. If one player can take it yeah they'll be the next Google but that's a big IF and a big WHO.
I've spent the last three years building a game engine specifically to do this, and currently finishing the final draft for the game story I've created to go alongside it.
Happy to share anything you'd find helpful. The big takeaway for me has been, you're going to want to graph out the impact of choices before you write the story. If you know the flow of decisions, then that gives a much clearer structure than trying to write the story first and then create branches off it. I think the reason is that it sets a much tighter scope for the writing doing it that way, whereas if you write the story and then find ways to branch it, the scope for that is functionally infinite.
Welcome to what happens when everyone optimises for the same metrics, and looks at the same companies for inspiration as to what to do.
At most of these corporations, over time they've learned to be product and financially oriented, because it's what the markets reward and it's easy to do, rather than customer orientated, because as long as they're not unusably shit for the majority of their customers, then that's good enough.
It's an attempt to reverse backwards to the worst possible thing that works, because that gets you more ad revenue, rather than the best possible thing.
I say this as someone who's walked away from strategy consult gigs for multinationals where the objective was literally to do things like this. Revenue and margin maximisation in ways the stock market and PE/VC investment rewards is frequently orthogonal to building the best thing for the customer.
Sure, even in North Korea with "Juche" (1) extreme self-reliance, there is some domestic consumption. Of potatoes, even (2). It's not that domestic consumption will go to zero.
But the point is that domestic consumption is not constant. It can decrease, it can substitute more basic goods. Such as potatoes.
A strategic error would imply he actually has a strategy. No-one doing anything in American government right now has a strategy.
As long as he gets to play as much golf and watch as much TV as he likes, he doesn't seem to care much. I don't think anyone bought Trump, I think he's just signing whatever is put in front of him and taking credit for it so he can go back to playing golf.
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