How Notion Creates User Personas?
Nov 15, 2023

How Notion Creates User Personas?


Arjun: Hi, I'm Arjun Saksena, the Founder & CEO of Humanic. Previously, I've had several product and engineering roles. Today we are going to be talking about personas so, let me introduce our special guest - Monica Perez.

Monica: Hello everyone, I'm Monica Perez,  and I'm the Head of Customer Success at Notion and work directly with our largest enterprise customers. I'm excited to share our learnings here today.

Arjun: She's our expert guest and we've been working with her for a number of months to construct this workshop. If you don't know what the notion is, please below.

Workshop Structure

Arjun: First let me start by providing some context about the workshop. The focus of this workshop is PLG Companies in the Productivity and Collaboration Space. That is why having Monica from Notion is such a perfect fit to kick off our first Persona workshop.

Productivity and Collaboration is also the category which is at the forefront for adopting Product-Led-Growth as the dominant GTM strategy. For more details please read this comprehensive overview of the PLG Market Map by OpenView Partners

Monica: It's really helpful to understand the ideal personas in terms of how they use your product and get value out of your product. But, it's also helpful to understand the personas that exist.

Definition: Product personas are fictionalized representations of your ideal customer that are created to help you understand and design for the needs, goals, and behaviors of your target audience.

They are not the same as market segments, which are based on demographic characteristics such as age, gender, income, and location.

Product personas are based on how people use your product and what they are trying to accomplish with it. It is important to understand both your ideal personas and any anti-personas, or users who are not using your product as intended. When creating personas, it can be helpful to start with a hypothesis and use data and customer research to refine and validate your personas over time. Personas can be useful for the whole company, not just the product team, as they can help inform go-to-market strategies and messaging.

Personas at Notion

Arjun: The best way for persona building is to come up with a 3 hypothetical personas and write down the Fear, Anxiety, Hope and Dreams for each persona as described. These personas can be improved by doing interviews with the users who fit the bill. It is also great to write down at least one anti-persona.

Monica: The team at Notion identified a product persona called the "heavy collaborator," who has a fear of not being able to easily share information and collaborate with others. They may also have anxiety about being limited by existing tools and a hope of being able to collaborate and make progress on projects faster. Their ultimate dream is to be able to move everyone in their team faster and more collaboratively. To understand and design for this persona, the team at Notion used data on user activity, such as comments and shares, to identify and classify heavy collaborators.

They also identified anti-personas, such as "heavy sheet workers," who may misunderstand the value of Notion and compare it to traditional spreadsheet tools. By understanding both ideal and anti-personas, the team at Notion built features and go-to-market strategies that align with the needs and goals of their target audience.

The idea is that you build these personas based on describing their fear, anxiety, hope & dreams and complete these for all of the personas of your product.

Jobs to be Done

The next thing to do, once you have these personas built out, is to figure out what job they are trying to get done as defined below.

For further clarity, it's best to break down the jobs to be done across the entire customer journey of the product. Let's see an example from Notion

Monica: If we're mapping out the customer journey in terms of their pains and their gains, then we do notice that three things typically happen.

  • The user will try to collaborate with their existing tool set.
  • They experience some sort of challenge or they come up against a wall &
  • They sign up for Notion and are able to extract some sort of value.

So Collaborating with the existing toolset, Experiencing Challenges and Signing up and extracting value become the three phases of the customer journey for a new user considering using Notion. Knowing where these heavy collaborators are coming from, we can kind of see how they arrived at Notion and, and how we can continue to make that experience really delightful.

The Heavy collaborator Hari probably wants to with the existing toolset, maximize, let's say the speed of collaboration and probably minimize integrations or migrations that need to happen, right? Because it's like across multiple tools that they're collaborating. So they really just need this to happen quickly and they probably don't want this to be fragmented amongst a lot of different tools with their cross-functional partners.

So then they experience some sort of challenge. Maybe this doesn't work out well because they're, you know, they're unable to consolidate, to their, let's say, tool of choice, right? So then they just, they start looking up, Hey, what are tools that help me consolidate? What's an all-in-one solution?

What helps me do a collaboration? Quickly, and then they discover Notion and they sign up and extract some value. They're probably very impatient, right? They want to extract value quickly, very quickly, not patiently. and they probably wanna see how this allows them to work seamlessly with others so knowing that this is what they're trying to get done and knowing the journey that they, went through to get to this point, we can see – Once they arrive at Notion, their patience is low. They wanna extract value quickly, and they also wanna work seamlessly with others. So again, this informs a lot of our strategy.

This is an ideal persona for us:

  • Notion needs to focus on quick value extraction. It needs to focus on like very quickly maybe plugging and playing with the workflows that they're looking to get set up.
  • Maybe we need to, invest more in templates We invest more in kind of out of the box, ready-to-go solutions and then work seamlessly with others.
  • We probably need to invest in our sharing modules.
  • We need to invest in lowering the friction to, entry and other to work with others and comment and collaborate. And so an example today is like all of you were probably able to duplicate this template. You're all probably able to play along, and that's something that we invested in early!

Questions and Answers

What is an anti-persona?

Monica: Anti-personas are also known as negative personas or exclusionary personas. They are used to identify types of users that the product is not intended for or that the company does not want to target. This can help the product team stay focused on the needs and goals of the intended audience and avoid building features that do not align with the product's value proposition. Defining anti-personas can also help the company avoid competing with other products that serve a different audience or meet different needs. It is important to be clear about why a particular group is considered an anti-persona and to communicate this to the rest of the company to ensure that everyone is on the same page about the product's target audience.Cool. Awesome. Everyone here is invited to make their own copy of the template I shared. You'll have access at any time, so join me now and start working together or observe for future use!

How did Notion decide which metrics were important in the early days?

Monica: In the early days of a product, it can be challenging to understand which metrics are most important to focus on in terms of driving growth and revenue. In these early stages, the team at Notion relied on customer feedback and customer success team insights to understand which features and use cases were most valuable to users. As they grew and gained more data on user behaviour, they used data science techniques such as correlation analysis to identify the actions and features that were most strongly correlated with growth and retention. This allowed them to focus on the metrics that were most important in driving revenue in the long term. However, it's important to note that these metrics may change over time as the product and user base evolves, so it's important to continue to analyze and understand the impact of different metrics on revenue.

Thanks Monica. There's another question about the outreach part.

How do you balance product outreach versus email versus other methods?

Monica: To sum up, it's important to consider the specific needs and characteristics of your different user groups and tailor your outreach methods accordingly. It's also important to continuously experiment and test different outreach methods to see what works best for your product and user base. In general, in-product outreach is often more effective because it doesn't interrupt the user's experience, but it's also important to consider the different communication preferences and needs of your user groups.

What signals or data did you use to help you identify the personas and how early in the user journey would the categorization typically happen?

Monica: One thing that our data science team did was a large kind of distribution analysis. Our backend captures every action, so there's like endless numbers of actions you can take in the product, but there is a subset of actions that are definitely always being used and then there's a larger subset of actions that are hardly ever used.

I think that happens with any product led growth company. There's typically a gap between the features that exist and the features that are being leveraged by our user base. We really focused on the types of features and actions that are being taken most prominently. It was like a relative analysis relative to benchmark against the user base and we kind of segmented it based off of, spend or other demographic data that was important, but then we're able to say, okay not all of Notion'sfeatures are being used, but there are top 10 features that are being used, which are editing, commenting, sharing, et cetera.

Of those top 10 features, what does the distribution of users look like? Who is leveraging these and in what ways? And then that's where we are able to find concentrations of users. Showed us a trend. So heavy collaborators do exist, within the distribution and they're very heavy on commenting and sharing but we also noticed that 'view only' users are also a very heavy concentration.

And why is that happening? And obviously, we didn't want view-only users to exist as much as editors, but it is a byproduct. Our products are being used for a wiki or just like a reading use case, right? And so that's something that we learned and we're actually trying to change and ensure that we can turn them from viewers to editors.

But I would say like looking at, your top kind of features that are being leveraged and then within those top features trying to identify, are there any trends in terms of user behaviour, within any given account? There's probably a wide spectrum of users, a wide spectrum. Of roles as well. And is there any correlation with how those users are behaving within that account?

Data Instrumentation is a pre-requisite

Monica: One of the prerequisites for this {persona analysis} is, the instrumentation of user activity. Some of the teams probably don't have resources, but that's, why if you don't have instrumentation in place that can be a substantial challenge.

Arjun: Instrumenting based on a hypothesis, to figure out what you need to instrument, becomes a much more tangible effort than to say we need a hundred per cent instrumentation, which can take, you know, months, weeks, months, or sometimes even years.

Monica: I mean, I think Arjun, not to plug you, but I think that's why Humanic is so great. With Humanic you integrate with your data and it's able to identify personas for you upfront really quickly and easily and get you up and running with a few clicks of a button! Different buckets of users, within the product.

Early days at Notion, that was not the case we had unstructured data, we had Snowflake, and then we had data scientists. That was about it. So that's exactly the sort of thing that Humanic is built to help early-stage PLG companies with.

Next Steps

Monica: Sharing the Persona Notion template that anyone is free to copy and use.

I think we can go pretty deep on this, so I'm happy to connect with folks on the Humanizing Persona Slack community and continue the conversation, link below. We have a lot of learnings on this front. Thank you very much, guys. Hope this was helpful. Thank you everyone have a great rest of your day!