Personas

What are personas?

A product or service must bring value to its users. It must be usable and therefore, deliver use value. Without users no product and without value delivery no users. Simple as that.

Therefore, it is crucial to understand our users. Personas are fictional characters that represent certain user types. In this article we will focus on creating evidence based personas. Those are personas that are based on research data.

Purpose of personas

• User centered product develpment: Personas keep the focus on the user throughout the product development, ensuring that the solutions developed meet the actual needs, behaviors, and goals of the users.
• Empathy building: They help team members step into the users’ shoes and understand their perspectives, challenges, and motivations.
• Alignment and communication: Personas serve as a common reference point for all team members, promoting a shared understanding of the target audience. This alignment facilitates better collaboration and decision-making.
• Feature prioritization: Personas help prioritize features and functionalities based on what is most important and valuable to the users. This ensures that resources are allocated effectively to address the users’ primary needs.
• Perspective shifting: Personas encourage team members to think beyond their own assumptions and biases, fostering a more inclusive and user-centric approach to design and development.

Persona types

Evidence based personas vs. proto-personas

Let us first contrast evidence based personas with proto-personas:

Evidence-based personas draw on real user data, providing high accuracy and fostering deep empathy. They are inherently validated and slightly less adaptable as they are grounded in specific user data. However, creating them is time-consuming and costly. They are used for projects where detailed user insights are critical to the success of the product.

Proto-personas, by contrast, are based on assumptions and can be created swiftly and cost-effectively. They offer flexibility and ease of adaptation but need further validation through user research. They are used in the early stages of a project where user data is not yet fully available and the goal is to come up with first hypothesis to kickstart the process.

Whenever I execute any kind of interview, – and I have always worked in BTB contexts – I always start with a question where I ask participants about their current job (title) and what they have to do with regards to (research topic). Having collected such information from an already existing user base provides a lot of knowledge to create proto-personas but this does not replace a dedicated persona research if you want to create evidence based personas.

Personas, role based personas vs. user archetypes

User persona (mostly BTC)

Personas are presented as specific human characters that represent certain target groups. The group becomes tangible as a person that has a name, biography, certain behaviors, motivations, etc.

Role based personas (mostly BTB)

We use Roles to identify a group of people based on the core functional job they are trying to get done. Role based personas help to represent the different types of job performers. The goal is to make motivations and objectives of those actors transparent.

• Description of the role
• What are the main jobs (tasks) this role performs?
• What are the pursued goals associated with this role? (What drives this role from its role perspective?)

User archetypes

User Archetypes are high-level profiles that represent groups based on behavioral patterns. They are based on psychology and storytelling to represent human motivations.

User archetypes are presented as abstract concept that represents a certain behavioral character.

How to do the research?

Common approach

Depending if you develop digital products BTC (business to customers) or BTB (business to business) you will decide on different types of personas. I will present a research approach that can be used to create any kind of persona including user archetypes. The collection of the data is the same, the only difference is how this data is finally mapped towards the persona concept you want to use.

Having said this, there will be a slight tendency towards role based personas in the material that I present. Why? First, I want to keep things simple and not confuse this article by constantly creating variations. Second, role based personas serve as a kind of middle ground. They encompass levels of details from a user persona and levels of abstraction from the user archetypes.

Data-driven personas

In this article we will focus mainly on how to create evidence based personas via interviews. Once we touch the topic of analysis I will also include the aspect of data-driven personas. To me this is not a contrary but rather a complementary approach. If you already have an existing user data base and have user reporting or behavioral data collection in place, those are excellent data sources to enrich or validate your personas further.

Usage of AI for persona creation

What will not be covered in this article is the usage of generative AI to analyse and create the final personas. The reason is that I did not have the opportunity yet to utilize such tools in persona creation but I intend to extend this article once I have collected experience. I see a huge potential in the clustering of qualitative data and to automate this time consuming task. Additionally, to include quantitative data in the data set or to detect new patterns are excellent use cases. Also creating awareness of biases by seeing alternative realities would be a great win. Nevertheless, collecting the data, conducting empathetic interviews, understanding human psychology and motivations I still see as manual task as of the current state of technology.

Steps involved

1. Research plan
2. Interview guide
3. Analysis
4. Mapping
5. Iterations

1. Research plan

Overview

In this article, we won’t delve into every detail of the research plan. Instead, we’ll take a closer look at the crucial aspect of participant selection and scheduling.

Participants

Selection of the right participants is the most crucial step for a persona research. You might consider:

Scheduling

Given that this research involves participants sharing personal insights (user personas) or details about their daily tasks (role-based personas), it’s important to approach them thoughtfully.

To assist with this, I will provide you with sample emails for initiating contact with users. These templates can serve as blueprints for your outreach. From my experience, I recommend a two-step approach: first, secure the participants’ initial buy-in, and then provide detailed specifics. This helps prevent overwhelming them right from the start.

Initial email (generic)

Initial email (targeted for a specific product)

Reminder

Confirming interview (invitation)

2. Interview guide

Question map

In a persona interview you need more flexibility in the conversation. Therefore, I recommend to use a question map where you have all questions mapped out on one page. this allows more natural, flowing conversations. You can also make notes on the map or cross out sections you have touched during the interview.

For role based personas, I highly recommend the book The Jobs to be done Playbook (chapter 3) by Jim Kalbach to create an interview plan dealing with the objectives and tasks of your users. The following question maps is based on this approach and further adjusted for persona research:

Structure of the question map

Job performer

(BTB context) This is all about the performer of the job. You want to understand how they define their job, what skills are needed and if they have already used your solution. Don’t try to connect it only to your service as you want to understand how your service or product fits to your users workflow.

Understand the process of executing their job

Understand how they execute their job. Of course, you will focus on their job with regards to the service or product that you provide. You want to understand how your service or products fits in their job workflow without keeping a narrow focus.

It is very important to understand why they are executing their tasks (needs) and the circumstances. For a persona research the circumstances are key to detect patterns and be able to map insights from persons that work in totally different companies towards similar situations.

• In what situations has a task been executed?
• What conditions influence decisions?

Another important aspect is the goal (motivation) why a certain task needs to be completed. This also helps to detect patterns and cluster participants later. Bearing this in mind will allow to make your research data later be useful to create user persona, role based persona or archetypes (which can be based on clustering of circumstances and / or goals).

At the bottom of the question map you will see a generic process flow that is the same for any kind of task that needs to be executed. It helps to dig deeper into a process or to ask more questions in case steps are omitted. There is also a dimension of past and future. For example you can ask how this was done in the past and how it is done now if this helps to create more clarity.

Empathy

The middle part of the question map includes pains, gains and emotions. Those are not questions you will ask separately, but rather use to probe into the topic of the job performer or the process. You want to understand also the emotional dimension when certain tasks are performed.

User personas

If your target are user personas and not role based personas you will shift the focus of the question map and include for example the following topics. It is important that you adjust the question map to your specific research context! (The following table are just some examples and is not comprehensive.)

3. Analysis

Analysis is performed in two steps:

1. Translate qualitative data in a clear structure for analysis.
2. Identify patterns

Translate data in a clear structure (data segmentation)

For the first step I usually create a Microsoft Excel sheet and collect the various learnings along the research dimensions. One example based on the question map above:

Try to keep the analysis and the mapping separate steps and stay focused. If you start mapping to early it will be hard to overcome bias. Therefore, do the analysis together with another person to balance biases. The dimensions are usually a given based on the question map. You can still get more granular to create more specific data points. Each column in your excel is one data point (dimension).

If you have interview transcripts you can go through the transcripts and use a specific text marker color to highlight all findings connected to this dimension and then add it to the table. With utilizing AI it should be rather easy to create the transcripts automatically. I still prefer doing the filtering manually as it helps me to put myself into the user’s perspective but even here you can utilize AI.

It is also useful to include a column with original quotes for later reference to the source files (transcripts).

Include quantitative data (data-driven persona)

At this stage you also include quantitative data you have collected about your users. You might have behavioral data based on cohorts that allow mapping behavioral data already to specific users. It depends on the quality of your data how and when you can include this data points.

You might consider information you retrieve via user reporting activities or behavioral analysis (Google Analytics, Hotjar, Count.ly, Matomo, etc.)

Detect patterns (code the data)

Once the data is coded, start identifying recurring themes, behaviors across all the different interviews. For role based personas you will try to map the various job titles in the companies to generic types. Therefore, you will analyse the provided job titles together with the job description to create groups. In this case you try to detect patterns based on a clear objective. Another case is to read through the coded data and detect similarities. With this approach you will detect patterns you did not expect beforehand. You will apply both approaches to analyse your data.

Try to do it with curiosity in mind. Don’t fall in the trap to start mapping the data too early. It should be an explorative activity where you discover new information that was not transparent before.

4. Mapping

Map on basis of patterns

Based on the patterns you have discovered, you will start mapping the data towards concrete personas. I found it useful to create more granular personas in a first iteration and then consolidate them to more generic personas.

The difficult part about mapping is to understand what characteristics (patterns) belong together. This is also the point where you have to differentiate the collected data from the persona types you want to create.

Role based personas: Here the task is quite straightforward as you will first group the personas towards roles and then create a persona out of the similarities of all data collected for those roles.

User archetypes: This is a little bit more demanding, as user archetypes add a level of abstraction. What you need to do here is to map it towards archetypes. The basis for archetypes might be categories (situations) where the user finds himself, behaviors or motivations (goals) the user persues. What you do in this case is to detect patterns in the situations, behaviors or motivations to be able to group the data based on this axis.

Example

Role based persona

Having the data structured you can easily adjust the level of granularity depending on how you will utilize the persona. It is practical to have a more detailed persona for upcoming iterations as shown below. For the purpose of product development, Design Thinking Workshops, etc. it is practical to simplify the persona to its minimum.

If we would have mapped the persona to user archetypes and focused on the goal we might have created an archetype of achiever.

Important: most of the persona data below is fictional. I used some data of a real persona but extended it with fictional information for the sake of this article.

Extension with the jobs-to-be-done framework

You can easily connect and extend your persona with the jobs-to-be-done (JTBD) framework by Jim Kalbach.

5. Iterations

Stay adaptive

Personas are not a one-time exercise. I actually created sometimes personas on a smaller data set while iterating over them from time to time. This way I could utilize the learnings as fast as possible and still maintain accuracy be refining them over and over.

Iteration is crucial, because:

• User behaviors and needs change over time: Think about technological advancements and socio-cultural shifts.
• Market and industry dynamics: Your products depend also how the market develops in general. What has been experienced as game-changing might have turned into what is expected.
• Feedback: Once you have established personas, you can incrementally validate them with other research activities and quantitative data. There are many ways how you can ensure that your personas stay updated!