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> Of course if you hide the fact that your product might cost a lot of money from your users, more of them will sign up

The problem with their calculator was that the users introduced slightly wrong data, or misunderstand what means some metric, and suddenly a 1000x the real price was shown. Their dilemma was "how to fix those cases", and the solution was "get rid of the messy calculator".

But they are not hidding a 1000x cost, they are avoiding losing users that get a wrong 1000x quote.




Being a complete cynical bastard here but I sometimes feel like these calculators are actually meant to obfuscate and confuse and the result is that a startup worried about scale is going to pay over the odds and then deal with ‘rightsizing’ after the costs get out of control.

I felt like that with elastic serverless’ pricing calculator which on the surface looks perhaps cheaper or more efficient than a normal managed cluster, because you think it would be like lambda. Except there are so many caveats and unintuitive hidden costs and you’ll likely pay more than you think.


Can't speak for everywhere of course, but the places I have worked nobody likes spikes or over commitments. The customer is shouting at your people, salespeople and support spend time and get stressed dealing with them, leadership gets bogged down approving bill reductions. Even if granted, customers remember the bad experience and are probably more likely to churn


My cynical take: I make things that look hard to make to impress you but if you make them for me I feel my money is going into the calculator rather than the product.


Let's not take a PR piece completely at face value.

There's probably a bit of both, at the very least.


In my mind Pinecone is an exemplary example of modern "social media marketing" for a technology company.

They started on vector search at a time when RAG in its current form wasn't a thing; there were just a few search products based on vector search (like a document embedding-based search engine for patents that I whipped into shape to get in front of customers) and if you were going to use vector search you'd need to develop your own indexing system in house or just do a primitive full scan (sounds silly but it's a best-case scenario for full scan and vector indexes do not work as well as 1-d indexes)

They blogged frequently and consistently about the problem they were working on with heart, which I found fascinating because I'd done a lot of reading about the problem in the mid ought's. Thus Pinecone had a lot of visibility for me, although I don't know if I am really their market. (No budget for a cloud system, full scan is fine for my 5M document collection right now, I'd probably try FAISS if it wasn't.)

Today their blog looks more than it used to which makes it a little harder for me to point out how awesome their blog was in the beginning but this post is definitely the kind of post that they made when they were starting out. I'm sure it has been a big help in finding employees, customers and other allies.


Thank you. :) I don’t think of it as social media marketing but more of helping our target audience learn useful things. Yes that requires they actually find the articles which means sharing it on social, being mindful of SEO, and so on.

Probably our learning center is what you’re thinking of. https://www.pinecone.io/learn/ … The blog is more of a news ticker for product and company news.


why not fix the calculator in a way that avoids/mitigates scenarios where users get to wrong quotes and then do an A/B test? This setup seemingly tilts towards some sort of a dark pattern IMO


Because the results were probably wrong because the inputs were wrong (exagerated by over-cautious users). There is no automated way to avoid that in a calculator; only a conversation with a real person (sales, tech support) will reveal the bad inputs.


I wonder if some of that could have been automated. Have a field to indicate if you are an individual, small business, or large business, and then at least flag fields that seem unusually high (or low, don’t want to provide too-rosy estimates) for that part of the market.


They tried to mitigate :

   But any attempt to address one source of confusion inevitably added another.




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