What are The Different Types of Personas Used in SaaS?
You probably thought that companies only used one type of persona for sales, marketing, feature adoption, and everything else.
Actually, there are multiple types of personas for different teams, levels of research, and use cases—which you need to understand if you want to connect with customers.
So let’s cover each of them and see what you can do to improve your team’s effectiveness.
- A persona is a visual compilation of your customer’s problems, emotions, desires, jobs-to-be-done, and goals.
- Creating customer personas is essential for every customer-centric company. It allows your team members to empathize with your audience and feel more aligned with your mission.
- There are four different types of personas according to your team’s role:
- Buyer personas are used by sales reps to identify the pain points of the person who makes the purchase decision.
- Marketing personas are designed to cover the psychological and behavioral aspects of the target audience. So the marketing team can capture more qualified leads for the sales team.
- User personas, which target the person using your app, are designed to represent your users’ JTBDs, responsibilities, and goals.
- Negative personas, which are a representation of your least likely customer profiles. It portrays the needs, values, and behaviors that differentiate bad-fit customers from your ideal customer.
- Depending on how many resources you have to do customer research, there are three different types of personas:
- Proto-personas are created based only on analyzing existing customer data and your team’s assumptions, with no new research done. It can be good to keep the momentum for new projects, as they can be made fast—but they’re likely inaccurate.
- Qualitative personas are built from qualitative research like customer interviews. They can accurately describe your user’s emotions, perceived problems, and perspectives when using your product. But, can’t be used to make accurate statistical claims since the sample size is often small.
- Statistical personas are the most accurate type of persona. It uses both quantitative and qualitative data to make statistically significant assessments about your user base with way larger sample sizes—but they’re expensive to make and are not worth it for small teams.
- If you want to make the most out of your user personas to improve product adoption, why not book a Userpilot demo?
What is a persona?
A persona is a document representing your customer’s problems, emotions, desires, jobs-to-be-done, goals, etc. And they’re built for each segment of your customer base.
Often, they’re made based on assumptions, which makes them close to fictional characters (thus, they’re only helpful to have a general idea of who your customers are). But you can also create personas based on legitimate user research and make them more useful when designing your onboarding process, marketing messages, sales scripts, and more.
Why is creating personas important?
Creating customer personas is essential for every customer-centric company, allowing your team members to empathize with your audience and feel more aligned with your mission.
For example, your product team must have a crystal clear vision of who your users are so they can develop a product that suits your customer’s requirements and makes them achieve success.
Otherwise, your company would go off the rails and invest money in building an app no one finds useful.
If you want to lead your business in the right direction, you better learn about the different types of personas in product management.
What are the different types of personas in product management?
Now, you must create the right persona for the right purposes. Let’s review four types of personas for different teams and use cases.
In B2B SaaS, the person who decides to purchase your product might not be the same person who uses it.
Thus, a buyer persona is targeted to the stakeholders who make the purchase decisions (C-suite, senior executives, etc.). The sales team often uses these personas to cater to the decision maker’s pain points, objections, and goals to close the sale.
Your marketing team needs deep knowledge about the target audience in order to create campaigns, messages, and content that resonate with prospects.
For this, marketing personas represent your customers’ psychological and behavioral side, such as purchasing patterns, work habits, buying triggers, ongoing pain points, and more. These are helpful for marketers to speak to the audience’s needs and ultimately capture more qualified leads for the sales team.
User personas are, on the other hand, designed to describe the person using your product, including their jobs to be done, responsibilities, challenges, and the role users play in their company.
If the buyer persona represents the decision maker, the user persona represents the user of your product.
Product managers use these personas to stand in the user’s shoes and determine the right path for product development—including new features, adding QoL, changing the UI design, or revamping the onboarding process. Having a deep understanding of the person who’s using your app is indispensable for developing a product that people want to use every day.
Also called exclusionary personas, a negative persona represents your least likely customer profiles. And it portrays the needs, values, and behaviors that make bad-fit customers different from your ideal customer.
For example, if your product is built to help marketers in SMBs, it’s very likely that your negative persona would include marketers who work for corporations.
You see, knowing the types of customers you don’t want helps you achieve customer fit faster while avoiding falling into the feature-fallacy trap or the product death cycle.
This means you can better understand your customer’s needs and avoid wasting time building features no one uses because they don’t fit the customer’s needs.
Types of user personas used in UX design
Not every company has the time and budget to compile extensive customer data. So, how much research is enough to build a good persona?
It turns out there are three types of personas according to the level of data you have available:
Proto-personas are created based only on existing customer data, with no new research done. When there isn’t much data available, they’re complemented with assumptions and the best guesses from the client-facing members of your team.
These fictional personas, unlike the other types, are not the most accurate representation of your users (hence they are referred to as “prototype” personas), but they can be useful for sharing a general idea with your team about who your users are and their needs. Plus, they can be created fast, which makes it helpful for keeping momentum when building new products and features.
How to develop proto-personas
Creating proto-personas is faster and doesn’t require you to invest time or money to conduct user research. Thus, there are only two steps to developing a proto-persona for any project:
Analyze the existing user data
If your company has any sort of user data, you can use it to start adding some blocks to your persona.
For example, you can analyze the data collected from sign-up forms to see the most common role, company size, and use cases in your user base.
Also, you can peek at product usage data and look for behavioral patterns that can tell you which features are most commonly used, the job they aspire to get done, and the time they spend using your app.
Brainstorm with your team
Once you’ve got some clues from your available data, you can gather your teammates and stakeholders to build your proto-personas.
In this workshop, each person should create around 2-5 personas (depending on your target audience) based on the available data and their own experience. Then, everyone will share their output with the rest of the team to agree on what characteristics are more common, resulting in a proto-persona.
Pros of proto-personas
Proto-personas can be created fast if you need to align your team for a project that needs to get done. Especially if it will require some testing, early access, etc.
It can also organize your team’s assumptions about your users, which sometimes aren’t obvious. This gives them a chance to communicate and find a new perspective about your customers that they didn’t have before—allowing your team to work in alignment if it isn’t in the right direction.
Plus, proto-personas can also set you up for future research and make your team see if there’s an assumption that can be tested and validated.
Cons of proto-personas
The biggest con of proto-personas is that they’re not driven by legitimate research. Your team’s assumptions about your audience will most likely miss the mark or ignore a game-changing fact about your users that you can’t know without talking with them.
When creating a proto-persona, it is important to acknowledge that any of those assumptions can be false and that you won’t know it until you invest the time and money into actual research.
As the name suggests, qualitative personas are created using qualitative data such as customer talks and interviews. It’s the sweet spot for most teams as it involves real customer research, and the sample size doesn’t require as many resources to create an accurate persona.
How to develop qualitative personas
Qualitative research often involves interviewing a group of users (with a sample size of 10-30 persons) about their experience using your product, asking any question that can make you find their pain points, expectations, goals, and their JTBDs. It also helps to segment your users properly to make accurate assessments.
Now, you can always pick users manually and invite them personally to book a chat with you. But we think it’s more efficient to allow users to schedule an interview right from your app and encourage them to do it with an in-app slideout like Postify:
Pros of qualitative personas
Qualitative personas are far more accurate than proto-personas. They can be a source of information on what motivates users, their expectations, and other insights that wouldn’t be possible to get from customer analytics or assumptions.
Plus, considering they don’t require too much time and money to create, qualitative personas are probably the most useful approach most teams would need.
Cons of qualitative personas
Although qualitative research can give you great insights, it doesn’t replace the utility that quantitative data can offer. For example, there’s no proof that the pain point of one user represents the majority of your customer base (it might not).
So, due to the small sample size, you can’t just say that 75% of your users are facing X and Y problems—you’d need more data to validate such a claim. Plus, there’s still the chance that you’re missing a key characteristic that your small sample just happens not to have, or to double down on a problem only a minority is facing.
There are few facts in qualitative research, and you’d need quantitative data to target your whole user base.
Statistical personas are the most accurate type of persona, as it uses both qualitative and quantitative data to make statistically significant assessments about your user base with way larger sample sizes.
How to develop statistical personas
Creating statistical personas starts with qualitative research (aiming for a larger sample size) and using the data to spot common themes and issues your users frequently face.
Then, you can use qualitative insights to create surveys to collect quantitative feedback that can validate the hypothesis you had during the qualitative phase.
To gather data, you can promote your surveys to your user base through emails and notifications. However, using a tool like Userpilot, you can also add in-app surveys to gather data continuously until the sample size is statistically significant:
Pros of statistical personas
Statistical personas are high-quality and the most accurate representation of your user base that’s possible. They can give you immense clarity and make the difference in discerning which user segments are more likely to switch to a competitor and develop a strategy to prevent churn.
Thanks to quantitative research, you can know what percentage of your user base has a specific characteristic and what features are better for engaging personas.
Cons of statistical personas
The big con of building statistically significant personas is that they don’t come cheap. To collect the amount of data required to achieve a deep understanding of your user base, you need budget and time.
So if you’re at a small startup trying its best to understand its customers, then this option is probably not worth it for you.
Knowing what types of personas are best suited for you, it’s essential to:
- Stay on the same page as your users.
- Build a persona that’s actionable for your role.
- Spend your resources wisely.
So if you want to make the most out of your user personas to improve product adoption, why not book a Userpilot demo? You’ll be able to easily implement your in-app messaging strategies without coding.