6 pricing A/B tests I’ve run (and which ones worked)

How pricing experiments helped me reach $6,000 MRR

It’s been a while since my last post on getting to 19,000 monthly clicks from Google. Since then, I’m happy to say that my job board, Remote Rocketship, has grown to $6,000 MRR! 🎉

Here is a brief look back on how long it took to get here:

• $0 → $1 took 4 months

• $1 → $2,000 took 2 months

• $2,000 → $4,000 took 3 months

• $4,000 → $6,000 took 2 months.

A big part of achieving this was experimenting with different pricing strategies. In fact, so far I’ve run 6 different A/B tests on it.

In this post, I want to share what each of these tests were and their (often surprising) results.

1. Moving the job board behind a paywall

This was my first step towards monetizing Remote Rocketship. Prior to this, people could search for jobs on the site for free. In the meantime, I was trying to monetize by asking companies to pay for promoted posts.

However, despite having 60,000 monthly visitors to the site, I didn’t get any interest from companies – probably because all the tech layoffs mean that companies are getting way too many candidates right now.

So I decided to change the business model: Instead of charging companies to promote their posts, I charged job seekers $10/month to use the site.

At first, I was quite hesitant to do this. I was worried that putting up a paywall would kill traffic to the site. That said, I wasn’t making any money from the site either, so I didn’t have much to lose 🤷🏻‍♂️

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Experiment setup

Hypothesis: Because Remote Rocketship provides value to job seekers, job seekers will be willing to pay for access to the site.

🔬 Control group (90% of users)– Free access to the site.

🧪 Test group (10% of users) – $10/month subscription required to use the site.

✅ Result:

• 10 paying subscribers after two weeks 🎉

• Traffic to the site decreases by 50%.

This was enough validation for me that people are willing to pay for the site and so I put it behind a paywall!

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2. Doubling the price from $10/month to $20/month

🔬Hypothesis: Doubling the price will decrease the number of signups but will increase revenue.

🧪 Control group – $10/month to use the site.
🧪 Test group – $20/month.

❌ Result:

• 66% decrease in signups.

• 35% less revenue.

I was disappointed with this result but glad I ran it as an A/B test. I set the price back to $10/month afterwards.

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3. Adding a 2-day free trial

🔬 Hypothesis: Having a free trial will convince people who are on the fence to sign up, ultimately increasing revenue

🧪Control group – $10/month to use the site.
🧪Test group – 2-day free trial, then $10/month.

❌ Result:

• No change in signups.

• Many people in the test group canceled before their free trial ended, resulting in less revenue.

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4. Offering half-price and free “scholarships“

I wanted to see if there are people who would be willing to pay $5/month but not $10/month. I didn’t want to halve the price for everyone, though, so I offered “scholarships”.

🔬 Hypothesis: Offering half-price and free subscriptions would increase the number of signups. Some people who would have paid $10 per month will end up requesting a scholarship anyway, but overall, revenue will increase.

🧪 Control group – $10/month to use the site.
🧪 Test group – An option on the signup form “Can’t afford a subscription? Click here”. Users could then buy a half-price subscription for $5/month or even email me for a free subscription.

❌ Result:

• Signups increased by 30%.

• Overall revenue remained the same.

I decided not to ship the experiment and keep pricing at $10/month for everyone since it’s simpler.

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5. Weekly subscriptions instead of monthly

The idea for this experiment came from the founder of Teal, a tool for job seekers. He mentioned that job seekers don’t expect to be searching for a job for a long time, so monthly subscriptions feel like a big commitment.

🔬 Hypothesis: Charging $5/week instead of $10/month is a way to double the price without decreasing signups. It will also lead to higher churn, but overall revenue will increase.

🧪 Control group – $10/month to use the site.
🧪 Test group – $5/week

🟰 Result:

• Signups remained the same

• Churn increased

• Overall revenue remained the same.

I decided to make $5/week pricing standard on the site so that I can run the next experiment (below).

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6. Offer weekly, monthly, and yearly subscriptions

🔬 Hypothesis: Offering users the choice between subscriptions will increase customer lifetime value.

🧪 Control group – $5/week to use the site.
🧪 Test group – Option to choose between $5/week, $18/month, or $60/year.

✅ Result after one month:

• Revenue doubles! 🤯

• LTV increases from $35 to $45 per user.

• In the test group, 55% of people signed up for weekly subscriptions, 30% for monthly, and 15% for annual.

This was by far the experiment which surprised me the most. I was not expecting such a big increase in revenue!

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Conclusion

So many of these experiments had results I did not expect, and my biggest takeaway from running all these experiments is that it’s super important to A/B test any pricing changes – otherwise you might end up shipping something that decreases.

Thanks for reading! I hope you enjoyed it and maybe even picked up an idea or two to try out for your own SaaS. If you have ideas for other experiments I should run, do let me know 🙂