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I analyzed SaaS billing dark patterns

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Re: I analyzed SaaS billing dark patterns

#91

Post by function_seven »

netizen-936824 wrote: post #71
kevincox wrote: post #63

Earlier quoted context omitted.

Credit cards act as a "cost" of sorts. Credit cards are a limited resource, it is not free to acquire more credit cards. By requiring a valid credit card you are basically relying upon the verification that credit card issuers do to prevent unlimited abuse.

Its not free to acquire credit cards? In what country? I constantly get free offers on the mails, plus there are services to generate temporary card numbers for throwaway

You're probably not going to go through the hassle of generating or applying for 1,000 credit cards in order to abuse some trial period on a SaaS service. Maybe you do it a few times.

It's the automated bots that a CC prevents. Even with "free" credit cards or generated numbers, there's a lot of friction in going through that to abuse the service's trial period.

Re: I analyzed SaaS billing dark patterns

#92

Post by HatchedLake721 »

bazhova wrote: post #34

AWS costs are somehow always higher than your estimate. Even when using their little calculator. That's the dark pattern right there.

Emmm, no? You can download detailed billing and drill down if you want.

If you see differences, one reason is that with hourly billing your monthly bills will be different, depending whether it’s a 28, 30 or 31 day month.

Re: I analyzed SaaS billing dark patterns

#93

Post by jpomykala »

“Free trials should not require a credit card.” I have a small project where I allow people to auto-translate their web and mobile applications. I’m using Google Translate and DeepL for translating texts from language to another. DeepL charges me $20 for every 500k translated characters. What I supposed to do? I’m getting a bit pissed off because I spotted multiple accounts who registered for the highest plan, used the whole auto-translation quota and quit without paying. Sometimes, users just misbehaving, and this is the reason why there are some dark patterns. Personally, I don’t use any. If you are looking for some decent i18n platform, try SimpleLocalize.io

Re: I analyzed SaaS billing dark patterns

#94

Post by jpomykala »

zinxq wrote: post #88
encoderer wrote: post #27

Of all the nasty things somebody can do with billing, I'm surprised the author leads with card-upfront trials. "Free trials should not require a credit card." This is opinion presented as fact. This is not a dark pattern. Totally unrestricted free trials are wonderful, you've invested a ton in your product and you want a prospective customer to experience everything. But there are legions of abusers and bad actors of…

We have tried both trials with and without CC - the latter is obviously more effective. On the back-end however, this forced us to spend weeks developing an intelligent automated approval process to limit abuse (which is common). After that, monitoring systems alert humans to suspicious trial activity for further review. So it continues to be a lot of work. Financially, we love the idea of a true "free" trial. The ab…

I think we are on the same boat. How to do detect abusing the service?

Re: I analyzed SaaS billing dark patterns

#95

Post by HatchedLake721 »

notyourday wrote: post #24
brooklinnash wrote: post #21

Earlier quoted context omitted.

What's your thought on alternatives, like Ahrefs' $7 for 7 days trial?

Unrestricted service at the highest plan level, 1 to 2 weeks, credit card not only required but is authorized for the plan price - do not settle transaction as it is still a free trial. This ensures: 1. Whoever tries the service at least theoretically met minimum qualification to be a customer - they have a credit card and can authorize several hundred dollars on it. 2. We get the real lead. 3. We limit the number of…

This person does B2B SaaS! Great comment and 100% agree.

Do you ever offer to extend free trial for people who want to cancel, and do you convert them back?

Re: I analyzed SaaS billing dark patterns

#96

Post by bredren »

jpomykala wrote: post #94
zinxq wrote: post #88

Earlier quoted context omitted.

We have tried both trials with and without CC - the latter is obviously more effective. On the back-end however, this forced us to spend weeks developing an intelligent automated approval process to limit abuse (which is common). After that, monitoring systems alert humans to suspicious trial activity for further review. So it continues to be a lot of work. Financially, we love the idea of a true "free" trial. The ab…

I think we are on the same boat. How to do detect abusing the service?

Multiple consecutive signups from the same IP address is one way.

But as GP said, this and other signals require coding abuse detection, and then you must find a way to enforce this.

This is not the kind of activity you want to be involved in while validating a product concept and working toward pmf.

Re: I analyzed SaaS billing dark patterns

#97

Post by parkerhiggins »

moneywoes wrote: post #69
jedberg wrote: post #64

This is a very cynical take. Not all of these things are designed to trick you. For example, requiring a credit card for a free trial is to prevent free trial abuse. A normal person can only get so many valid credit card numbers, assuming you can detect burner cards (which for the most part the CC companies will happily help you do). Yes, a good company will notify you that a trial is going paid, and a great company…

Does Stripe detect something like privacy.com?

Stripe Radar can be configured to provide signals that would reflect a virtual card, but not explicitly. Further trying to solve preventing virtual cards use potentially introduces false flags.

Requiring 3D secure may.

Depending on the product and audience, the prevalence of virtual cards may be extremely low. Outside of hackernews, the payments industry, and business cards nobody uses virtual cards like privacy.com

Re: I analyzed SaaS billing dark patterns

#98

Post by zinxq »

jpomykala wrote: post #94
zinxq wrote: post #88

Earlier quoted context omitted.

We have tried both trials with and without CC - the latter is obviously more effective. On the back-end however, this forced us to spend weeks developing an intelligent automated approval process to limit abuse (which is common). After that, monitoring systems alert humans to suspicious trial activity for further review. So it continues to be a lot of work. Financially, we love the idea of a true "free" trial. The ab…

I think we are on the same boat. How to do detect abusing the service?

At this point, it's a long evolved set of heuristics based on any available data. Some quick rules around IP, Country, and email provider gets you a fair bit of the way there. But like any heuristic system that evolves, tweaking can get you to something that's "good enough".

The next step would be an AI system (like the very impressive Stripe Radar (which admittedly is in a different context)) but we're not ready for that, nor would it bring us significant value over our current system. And again - we pipe things to human for things in the grey area.

Re: I analyzed SaaS billing dark patterns

#99

Post by justin_oaks »

HatchedLake721 wrote: post #92
bazhova wrote: post #34

AWS costs are somehow always higher than your estimate. Even when using their little calculator. That's the dark pattern right there.

Emmm, no? You can download detailed billing and drill down if you want. If you see differences, one reason is that with hourly billing your monthly bills will be different, depending whether it’s a 28, 30 or 31 day month.

I've been with AWS for a number of years (personal and for work) and haven't seen this problem either.

Some services will be higher if you don't account for all the costs. You can do the math for an EC2 instance but if you don't account for storage prices and bandwidth prices then the bill will be higher than you expect.

But some service prices will be lower than you expect. If you create multiple EBS snapshots from the same server, you'll notice that the price you pay isn't the sum of the individual snapshot sizes. It's far less because each new snapshot only saves data from blocks that have changed since the last snapshot.

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