I encourage new Heap users to create a bad funnel first

  • 28 February 2022
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Userlevel 3
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This is what I tell all the new Heap users at my company: learn how to use funnels (my favorite part of Heap) by purposely building a bad funnel first. Walk through the steps, see the weaknesses of the funnel and then make it better using effort analysis, so you can see where users drop off, you can see where things are a little bit wonky here and there. And then you can make your question better, and you can make your definitions better. It just improves the overall funnel experience.

Effort Analysis is crucial -- you scroll to the bottom of your results to see how much effort the user has to invest between each step. I'm currently working with our UX and UI teams redesigning and optimizing a few different screens and it's interesting to see very basic workflows, how people get from point A to Point B. For example, I'm currently taking a look at how our users get to our help documentation.

Effort analysis shows us where users get lost—right where they drop off, or where they have struggles in between those two or three or four steps. It looks at three different kinds of integration points—the interactions, time engaged, and the retry rate. Interactions is the total number of clicks on whatever they're doing on that page at that point. Time engaged is the time taken to go from one step to the next, that's where the “60 seconds” rule comes in—if they're not doing something for 60 seconds, something’s probably wrong.

The Retry rate is when users need to come back and do the same steps, or come back to the same workflow to finish up that funnel. It helps me think about how we can ask better questions. Maybe we need to narrow down our analysis of what exactly is happening there. You can really focus your question and make it better—like figure out where these interactions are happening, and why it's taking 17 minutes. I think effort analysis is a cool tool to give more visibility into what the funnels are doing, and have just that much more information.

 

 


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Userlevel 2
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@AnyaLiv that is such a genius idea for helping new users not freak out about complexities or what they might mess up, and just TELL them to do it badly at first.

Userlevel 2
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I love this framing of how to make the most of funnels. When using tools like Heap, it can get easy to decide you need to set it up perfectly the first time, rather then trying things out and iterating. As a docs writer, I’m personally a fan of “write the sh*tty draft first” then go from there revising and editing.

@AnyaLiv You said you’re taking a look at how our users get to our help documentation. I’m curious if you’ve found specific ways to measure that that have resulted in tangible updates to docs. This is something I think about all the time as Heap’s docs writer. Curious to see what you’ve discovered so far!

Userlevel 3
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@Renée CS Hi Renee! It has lead to a few interesting conversations, mostly about where and how our documentation is presented, how to search for it, and so on. We have also created some movement to better collect user feedback, and are now measuring how effective our changes are. 

I have also been watching how Heap has been re-setting up help documentation recently, and I think that, without meaning to, it has been lifted up too far away from being as easily searchable. I used to be able to, with maybe 2 searches, find what I was looking for. Now it feels like the content library is not as easy-to-use. Maybe it is because I got used to searching for whitepapers - not sure. Curious what Heap on Heap is seeing there :) 

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@AnyaLiv That’s great that it’s resulting in a movement to better collect user feedback! That’s been an ongoing struggle for us over in the realm of documentation, so I empathize with that challenge.

Thanks for the feedback about the changes in Heap’s resources structure making it feel less easy to find things. I’d like to know which search experiences have become a less-than-stellar experience. Can you share the website you were on (heap.io, help.heap.io, or developers.heap.io), what your search term was (or what pages you went to) and what you were looking for that took longer than usual to find? I can provide some context or make tangible improvements based on this feedback :) 

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