Playing with pricing

A few considerations for running A/B tests on your pricing page

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Michele Riccardo Esposito
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Getting your pricing right takes no small amount of finesse. Go too high, and you lose customers. Too low, and you lose revenue. Then there’s the pricing model to consider, not to mention the messaging on your pricing page.

If you use the Wayback Machine, you’ll see that even a well-established company like HubSpot has evolved its pricing page over time. That’s because finding the pricing sweet spot is an iterative process, one that requires A/B testing to figure out what converts.

Let’s take a look at a few factors to consider as you build and test your pricing page.

Test out your messaging

It’s amazing how something as small as a CTA can affect conversions. Drift seems to be running an experiment on that very premise. The first screenshot below shows what appears in my regular browser, and the second is what pops up for me in an incognito window. You can see that the CTA varies. One offers up a demo, while the other offers a free trial.

To get started with testing your messaging, check out the Pricing Plans Template from Candu. Without writing any code you can build a pricing plan, and design variations of it to test your CTAs.

The chatbot varies by profile too. When tracked, Drift is able to identify that I’m using a competitor’s product (which I am!), and the chatbot hones in on that. Drift is most likely using a tool like BuiltWith to get this piece of intel. BuiltWith allows you to search by software, and then presents you with a list of websites using that software.

By altering its messaging based on user profile, Drift is able to test out different variations to see what works best for whom. A/B tests like this can provide you with valuable data to help nail down your messaging.

Experiment with your pricing model

Your pricing model is almost as important as the price itself, and there are three main ways to structure your pricing:

1. A usage-based model charges based on the number of monthly seats, API calls, emails, etc. Chameleon, for instance, charges based on MTUs.

2. Capped pricing, which Appcues has gone with, lets an account fill a certain number of seats before forcing it to upgrade to the next pricing tier.

3. An add-on or bolt-on approach charges for individual features. Autopilot, for instance, charges $200 per month for Activity Streams, which allows you to pull your data outside of the app.

In reality, most SaaS companies use a combination of these three approaches, so you’ll need to test which combination works best for your product. Will bolt-on features drive revenue if they’re offered across all tiers, or does it make more sense to limit their availability in order to drive upgrades? Will you see more signups when seats are capped or when you charge per seat? A/B testing a variety of options will allow you to select the right pricing model to drive both revenue and conversions.

A/B testing the easy way

Of course, you won’t be testing much if each little tweak to your pricing page requires the help of a developer. Candu makes it easy to segment your audience and create variations to run experiments without a single line of code.

Want to learn more? Try it for free. And, yes, we did A/B test that CTA! ;)


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