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.
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.