When should you add friction to your signups?
3 min read

When should you add friction to your signups?

Like many startups, they automated their sign up flow. But unlike other companies, they wanted potential clients to apply for their service. Why would you add friction to slow down your sign ups?
When should you add friction to your signups?

Running a business has many moving parts. The more you can automate, the more it frees you up to address higher level and strategic problems of your business. This is a newsletter about automating aspects of your business.

Story and Problem

Today I'm featuring my friend Ricky Yean, and the automation he did at Upbeat to separate good clients from the not-so-great. Upbeat is a startup using technology to superpower PR (public relations) to compete with traditional PR agencies.

His team built a large database of journalists and the topics they were interested in writing about. Then, they used their in-house tools to streamline the process of helping companies develop a media strategy, run a campaign, and watch the results in real time.

Like many startups, they automated their sign up flow. But unlike other companies, they wanted potential clients to apply for their service.

Why would you add friction to slow down your sign ups?

Most products don't mind if you aren't making money from using their product, as long as you're paying them. For example, Shopify lets you open stores that doesn't make a sale. Youtube lets you create a channel where you've had 12 subscribers for two years running now.

But with Upbeat, there is a reputation to keep among the journalists and client startups. If journalists keep getting pitched bad stories, they'll stop taking your pitches.  If client startups have bad stories, they won't get a press lift and tell other potential clients it was due to Upbeat, rather than due to a bad story.

Hence, the Upbeat signup form filters out client startups by asking them to do some work. There's no shortage of clients, but in this business you want to work with the best stories to connect with the right journalists. Potential clients have to answer the following as part of their sign up using a Typeform page:

  • What is the headline for the story?
  • Please demonstrate your credibility.
  • Please demonstrate the story's timeliness.

As it turns out, there were other questions they tried, but it had no predictive powers. Here are a few:

  • How would it change people's lives?
  • Share a specific story about the product's creation.

Once the form is submitted, it's routed through Zapier to a Google Sheet to record the sign ups, and also a notification on a Slack channel.

Then, the human agents working at Upbeat will look through the new sign ups and score each potential client with a number. If they meet a threshold, the startup will be taken on as a client.

After every campaign with an client, their in-house system will update the Google Sheet with how well that story did. Did it go viral? Or did it flop? How far was the reach? That way, they could see whether their initial scoring was predictive of how well a story would do, as part of their training their predictive powers.


How would you apply this to your own business? For those of you that work with clients, know that not all clients are valuable for you–not just in monetary terms, but also in terms of fit. You shouldn't take on just any client. Take on clients where there's a mutual benefit. Hence, if you can filter out that are not a fit, you'll save yourself the headache of supporting them.

You can design your own sign up process. It shouldn't be long–three questions at the most, and come up with proxies that you can use to tell if a client will be good or bad fit. You should be able to filter out most of the bad-fit clients this way as you iterate through proxies.

The automation here can be two Zaps.

Typeform -> Google Sheet -> Slack : This Zap would record a signup, put the results in google sheets and remind agents to score the new sign up.

Webhook -> Google Sheet : This Zap would be triggered by the in-house system with data on how well a story did. Later, agents would review the sheet to update their predictive powers

Photo by Lisa Fotios

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