How do you decide what features should be free and what should be paid?
Let me start from the creator’s perspective:
I personally don’t have a product (apart from hiring people for creative work or offering personal consultations).
But as a creator, I constantly share content, insights, and information, value that helps me build trust (for free). Based on that perceived expertise, people eventually decide to work with me (a paid service).
So some things I share for free to eventually move toward a paid collaboration.
Personally, it’s sometimes hard to judge when I might be giving away too much for free.
And I assume it’s similarly tricky for builders.
You want users to try the product, but then comes the question of paid features, or a trial limited by time or usage.
How do you decide which parts of your product or service remain free, and which become paid?
When I share content publicly, I usually provide generalised advice. But when it comes to a specific case or a tailored strategy that requires a personal approach, that’s where it becomes paid.
Replies
what i've seen work: watch what free users do obsessively. the features they keep coming back to, the ones that generate "can i do X?" questions, the stuff that spikes right before churn.
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@jens_deryckere1 It feels I need to make some market research what they would be willing to pay for :D
AdFox (formerly GoodsFox)
In my opinion, free features are basically the “downward compatibility” of the product. Many free tools today are already extremely powerful, so the goal isn’t to restrict usefulness behind a paywall.
Paid features are usually the more niche capabilities, that built for users who want deeper insights, more advanced workflows, or higher scale.
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@1zoe_zhao101 How did you decide which features will be free/paid for your tool? and how did you make up the pricing?
Rankfender
With Rankfender, we decided that we will go with 14-days trial first : not a good idea !! the free trial costs us money. Every time someone signs up, we're calling ChatGPT, Gemini, Perplexity., Data apis, Docker workers.. Those API calls add up. Some people run hundreds of searches. We pay for all of it. Peopla generated articles that never got used...
We tried shorter trials. People didn't have enough time to see if it worked. We tried longer. Costs got too high and people still didn't convert. 7 days is where we landed.
The truth is most people don't convert. They use the trial, burn through credits, and leave. We just accept that as the cost of finding the ones who actually need it.
What do you do? Cap usage? Shorten the trial? Or just eat the cost like we do?
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@imed_radhouani it is pricey, I would go for limited times of use, because you know, in 7 days, they can also make high costs :D
In our case, we give users a quick “aha” moment by showing their resume score and why they’re not getting interviews.
That creates awareness. And the paid features deliver real transformation: helping fix the CV, tailor it to specific roles, and improve results.
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@valeriya_egorova I think you positioned that feature quite well putting it behind the paywall :D
Does the feature cost you as the product money to generate on a per request?
Example, generating images/videos GenAI costs a decent amount compared to in-app functions.
Either support with ads or have it as a paid feature.
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@dreamofcode thankfully, the part of my product will not be AI, so for now, no AI costs :D
Rule I use with InterviewAI: free = the thing that makes them realize they need it. For us that's the
first full interview + feedback. Paid = the thing they want after they're hooked (more sessions, company
packs like Google/Meta/Amazon). Free has to be good enough to impress, not good enough to replace paid."
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@doron_sun The easiest and most digestible formula! :)
For us, the rule is simple: free should help users get value, paid should help them get serious results faster, more consistently, and at scale.
For a product like PromptGPT, we know the real challenge is that most people still struggle to write good prompts, especially for image, video, and audio models. So if you put the core learning and discovery behind a paywall too early, many users never even reach the real value.
My approach is:
Free gets users to their first real win.
Paid helps them do it faster, better, repeatedly, and at scale.
That’s the philosophy I believe in. That’s also why PromptGPT is free, we want people to learn, experiment, and get value without friction. If we ever monetize it further, it would be around workflow leverage, not access to the basics.
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@nafii But is it somehow determined on your end? E.g. how many times they can use your tool or for how long? Or limited features?
We went with no free tier at all - just a 30-day money-back guarantee. At £24.95 one-time for a desktop utility, a free version felt like it would undermine the value more than boost conversions.
The thinking: at this price point, a money-back guarantee IS the trial. The customer has committed psychologically, refund rates at sub-£30 are typically under 5%, and you skip the engineering overhead of maintaining two versions.
A good demo video showing the tool in action does more for conversion than a limited free version ever could. Early days for us (just launched this week) so happy to report back on whether this approach actually works!
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@jo_public How successful were you with that approach?
Honestly? We literally launched on Friday so I have zero conversion data to share yet! But the logic felt right: at £24.95 the risk is so low for the buyer that a money-back guarantee removes whatever hesitation is left. Ask me again in a month and I'll have real numbers for you.
In the dating space, the free tier needs to be useful enough that people experience real value - seeing profiles, basic searching. But the paid features should solve a specific pain point: video chat, AI coaching, verified profiles. If your free users can't tell you what they're missing, your paywall isn't positioned right.
the real answer nobody here is saying: if your product has variable costs per user (like AI inference), your free tier IS your marketing budget. treat it that way.
i run AI-heavy pipelines and every prompt costs real money. so i structured it as: free tier = enough to hit the wow moment, maybe 5-10 uses. paid = unlimited or high volume. the key insight was tracking exactly where users go from "oh cool" to "i actually need this in my workflow" and putting the gate right after that moment.
what changed everything for me was caching aggressively. i cache outputs with vector similarity search so if someone requests something close to what already exists, i serve the cached version instead of burning another API call. cut my costs by 60-70% overnight. suddenly the free tier became way more generous without actually costing more.
the trial vs freemium debate is a false choice imo. trials work when your product needs time to click (like writing tools or habit apps). freemium works when value is immediate but scales with usage. combining both usually just confuses people about what theyre actually getting.