Inclusive design: Why Audience Factors are better than Personas

Why inclusive design requires a move beyond the average user

Personas have been a UX staple for decades for researchers, designers and delivery teams. They are great for building empathy and giving stakeholders a face to look at, but they fall short with designing inclusive services - in fact they actively exclude by design.

By nature, personas are an amalgamation of data. They are based on clusters of data, which tend toward averages, and thus miss data points that do not fit the clusters.

At Fluent, we’ve moved away from static personas and developed our own framework called Audience Factors. This is specifically designed to help researchers and designers to capture and design for what makes people different when engaging with your product or service.

Why personas fail

Personas try to make sense of audiences by putting them in boxes. While this makes for a neat slide deck, it fails as a design tool:

They rely on averagesData points that don't fit the main clusters are discarded, meaning you lose the very people who need inclusive design the most. Average design leads to average experiences and below average success.

They add fluffKnowing a persona ‘has a cat and enjoys sourdough and cycling’ may help bring them to life but it doesn’t help a designer decide how to explain interest rates or what to prioritise in the feature backlog.

They are staticHumans aren't one-dimensional. A person isn't just a ‘Young Mum’. One hour she’s a business owner, the next she’s a stressed parent, and later she’s a gamer. Personas can’t pivot as quickly as people do when it comes to defining what matters for how people engage with your service.

They lack design clarityIt is difficult to design for a type of person; it is much easier to design for a specific behavioural barrier.

Demographics explain who we should appeal to, but a service should be designed considering how individual differences affect behaviours

A better lens: the Audience Factors framework

The Fluent Audience Factors framework is an evidence-based approach to understanding how to design truly inclusive services for people.

Instead of looking at how to design for a person in their entirety, we break down the specific characteristics of an individual that impact how they engage with a product. This approach looks at what the differences are between people, and offers a practical way of dealing with them, so you can design for everybody and be more inclusive in your design.

Qualitative research is about discovering differences, not similarities

We have established two guiding principles. Audience Factors are:

  1. Motivational: A factor must be a fundamental reason that impacts behaviour
  2. Inclusive: Everyone is one level (or state) of every Audience Factor

Our framework is generally made up of 3 components:

Factors

The factor is the fundamental reason that impacts your user behaviour. Different factors could be Technology use, Financial literacy, Disposable income, Living situation. Each factor is made up of several states.

States

The different states of behaviour or attitudes we see within each factor – for example, within Technology use, the types might be Novice, Intermediate, Expert. States are mutually exclusive. At any point in time every individual is one state.

Themes

The high level theme that groups a number of factors, e.g. Capability, Situational factors.

Why Audience Factors work better than personas

True inclusivityAudience factors are not focused on a single factor or lens to evaluate behaviour, and for each factor there is a range of values rather than just one. This way we design for a spectrum of human traits.

Every person fits into one state of each factor at any moment in time. Therefore if you design for all audience factors, you will by definition be designing for everyone.

Clarity of design challengesIt is difficult to design for a person as a whole, it is much easier to design for specific contextual needs and barriers. This gives far greater focus to create a set of design challenges.

Evidence trailEvery design decision is linked to a specific factor, not a hunch about what a ‘typical user’ might want.

Supports making active and targeted choicesNot all products or services are meant for everyone, but when considering whose needs to design for it is important to have a full view of the population. By considering each audience factor in turn you can see who you might be excluding and make a conscious, strategic business decision about it, rather than doing it by accident.

You want the product to be for everyone, but everyone wants the product to be for them.

The result of using this approach is a product that fits the needs of a broader range of people, rather than something that feels like a compromise.

Using the Audience Factors framework in reality

Here are some stories around how the use of Audience Factors delivers better business outcomes than traditional personas:

1

Finance: Do you not want these customers then?

One of our clients was on the verge of scoping out their new mobile app.

Their question: “Which features do we need to build for the different people that will use our banking app?”

Our response: “Ok, so who do you want to use your app?”

There were 2 personas:

  1. Young mum: struggling to make ends meet, low financial literacy
  2. Working couple: established savers, decent financial knowledge, comfortable.

  • The reality: In our research we discovered there were young professionals who were optimising their savings, adults that struggled to save and stressed about understanding anything about finance, families that could save but didn’t bother to get an account.

  • The factors: By isolating ‘financial literacy’ and ‘capacity to save’ as the factor, we were able to identify different needs whilst ignoring the demographic stereotype.

What about these people?

I’m Rahul, I’m 27 years old, I’m a transport strategy manager, so my job is pretty much 9 to 5.

I've quite a good nest egg towards a house deposit. I’m pretty confident, I use quite a lot of different types, kind of understand the rates and maturity dates and and things like that.

I want the highest rate so I don't mind putting it into lots of different places.

I’m Elizabeth, I’m 45 years old, currently unemployed because of mental health reasons.

I’m married without kids. I’ve never really had a savings account, I don’t feel like I have enough money to save

At the end of the month, there’s nothing left. I often find it quite overwhelming to think about. Ultimately I've had to turn to parents and I don't want to have to do that.

I’m Siobhan, I’m 34 years old, I work as a cleaner

I’ve got 2 kids, 6 and 9 years old.

I’ve always been pretty good with putting money away. I just don’t have a lot.

If I've got extra, I know I can put it into savings for my kids or for the insurance or other bills. God forbid holiday.

The result of using this approach is a product that fits the needs of a broader range of people, rather than something that feels like a compromise.

2

Public health: designing as if your life depends on it (because it just might)

For an app needing maximum adoption (20m+ users), demographics were useless - everyone was a target user.

A key pillar of the Government's pandemic response was to encourage use of the NHS COVID-19 app for digital contact tracing. This innovative technology required a huge number of users to download, install and use the app for contact tracing to be effective. Success relied on identifying the barriers and needs for people to use the app, and then designing to meet these.

The facts:

  • Over 400 in-depth interviews

  • Analysis helped to identify factors that affected people's likelihood of downloading and using the app, as well as how receiving notifications could influence their behaviours.

  • The result captured 11 factors, each with 2 to 5 states

  • For each factor, we identified what this meant for users in terms of their needs (to give them a reason to use the app) and the barriers that may prevent them using it. By taking a ‘jobs to be done’ approach to design, each factor was used to identify which needs could be solved and which barriers overcome.

3

Gaming: We should think about these people differently

Launching a brand new concept comes with a lot of uncertainties. Our client was building a metaverse for ‘gamers' and ‘music fans’, but wanted to understand more about them so they could know which features to prioritise for development.

The usual question: “Are we best to put a big survey out there to 100s of people to find out what they like?”

Our response: “One-to-one interviews testing concepts with a smaller sample will tell you in detail what people are like and what appeals or doesn’t. Don’t rely on self-reporting”.

  • The reality: Research showed that the high-level groups of gamers and music fans were very diversified in terms of types of games, motivations to play and music interest. There was some overlap but also many differences between the groups.

  • The outcome: By focusing on factors, we avoided creating an unmanageably large amount of personas, or starting from ones that are too broad, we could quickly get to practical design challenges. It enabled the design team to decide which game features to prioritise and invest in.

  • The design challenge: To appeal to people who had different levels of interest in music e.g. passive, active, creator. The team understood they needed a variety of features that allowed people to play for music assets, create from samples and explore music assets and creations.

JayGamer

Factor

Motivation to play

To socialise

Types of games

Competitive

Gaming interest

Avid gamer

Music interest

Passive

RubyGamer

Factor

Motivation to play

To relax / escape

Types of games

Adventure

Gaming interest

Avid gamer

Music interest

Active, non-creator

ZakiMusic fan

Factor

Motivation to play

To relax / escape

Types of games

Creative

Gaming interest

Casual gamer

Music interest

Active, creator

Our 6-step process

We don't guess; we gather. Here is how we build Audience Factors for our clients:

  1. Define: Identify the core behaviours the business wants to drive.
  2. Research: Conduct first-hand in depth interviews with the widest possible set of people.
  3. Analyse: Break down the feedback into specific behavioural drivers.
  4. Map: Theme these into ‘Factors’ and identify the states (characteristics) within each.
  5. Identify: Deduct the specific needs and barriers for each characteristic of the factor.
  6. Design: Create solutions that address these specific needs and barriers.

How can we help?

If you're tired of trying to design for ‘average’ users who don't actually exist, we can help you apply the Audience Factors framework to your next project.

Have a project in mind?

Let’s discuss how we can achieve great things together

Let’s talk

Inclusive design: Why Audience Factors are better than Personas

Why inclusive design requires a move beyond the average user

Personas have been a UX staple for decades for researchers, designers and delivery teams. They are great for building empathy and giving stakeholders a face to look at, but they fall short with designing inclusive services - in fact they actively exclude by design.

By nature, personas are an amalgamation of data. They are based on clusters of data, which tend toward averages, and thus miss data points that do not fit the clusters.

At Fluent, we’ve moved away from static personas and developed our own framework called Audience Factors. This is specifically designed to help researchers and designers to capture and design for what makes people different when engaging with your product or service.

Why personas fail

Personas try to make sense of audiences by putting them in boxes. While this makes for a neat slide deck, it fails as a design tool:

They rely on averagesData points that don't fit the main clusters are discarded, meaning you lose the very people who need inclusive design the most. Average design leads to average experiences and below average success.

They add fluffKnowing a persona ‘has a cat and enjoys sourdough and cycling’ may help bring them to life but it doesn’t help a designer decide how to explain interest rates or what to prioritise in the feature backlog.

They are staticHumans aren't one-dimensional. A person isn't just a ‘Young Mum’. One hour she’s a business owner, the next she’s a stressed parent, and later she’s a gamer. Personas can’t pivot as quickly as people do when it comes to defining what matters for how people engage with your service.

They lack design clarityIt is difficult to design for a type of person; it is much easier to design for a specific behavioural barrier.

Demographics explain who we should appeal to, but a service should be designed considering how individual differences affect behaviours

A better lens: the Audience Factors framework

The Fluent Audience Factors framework is an evidence-based approach to understanding how to design truly inclusive services for people.

Instead of looking at how to design for a person in their entirety, we break down the specific characteristics of an individual that impact how they engage with a product. This approach looks at what the differences are between people, and offers a practical way of dealing with them, so you can design for everybody and be more inclusive in your design.

Qualitative research is about discovering differences, not similarities

We have established two guiding principles. Audience Factors are:

  1. Motivational: A factor must be a fundamental reason that impacts behaviour
  2. Inclusive: Everyone is one level (or state) of every Audience Factor

Our framework is generally made up of 3 components:

Factors

The factor is the fundamental reason that impacts your user behaviour. Different factors could be Technology use, Financial literacy, Disposable income, Living situation. Each factor is made up of several states.

States

The different states of behaviour or attitudes we see within each factor – for example, within Technology use, the types might be Novice, Intermediate, Expert. States are mutually exclusive. At any point in time every individual is one state.

Themes

The high level theme that groups a number of factors, e.g. Capability, Situational factors.

Why Audience Factors work better than personas

True inclusivityAudience factors are not focused on a single factor or lens to evaluate behaviour, and for each factor there is a range of values rather than just one. This way we design for a spectrum of human traits.

Every person fits into one state of each factor at any moment in time. Therefore if you design for all audience factors, you will by definition be designing for everyone.

Clarity of design challengesIt is difficult to design for a person as a whole, it is much easier to design for specific contextual needs and barriers. This gives far greater focus to create a set of design challenges.

Evidence trailEvery design decision is linked to a specific factor, not a hunch about what a ‘typical user’ might want.

Supports making active and targeted choicesNot all products or services are meant for everyone, but when considering whose needs to design for it is important to have a full view of the population. By considering each audience factor in turn you can see who you might be excluding and make a conscious, strategic business decision about it, rather than doing it by accident.

You want the product to be for everyone, but everyone wants the product to be for them.

The result of using this approach is a product that fits the needs of a broader range of people, rather than something that feels like a compromise.

Using the Audience Factors framework in reality

Here are some stories around how the use of Audience Factors delivers better business outcomes than traditional personas:

1

Finance: Do you not want these customers then?

One of our clients was on the verge of scoping out their new mobile app.

Their question: “Which features do we need to build for the different people that will use our banking app?”

Our response: “Ok, so who do you want to use your app?”

There were 2 personas:

  1. Young mum: struggling to make ends meet, low financial literacy
  2. Working couple: established savers, decent financial knowledge, comfortable.

  • The reality: In our research we discovered there were young professionals who were optimising their savings, adults that struggled to save and stressed about understanding anything about finance, families that could save but didn’t bother to get an account.

  • The factors: By isolating ‘financial literacy’ and ‘capacity to save’ as the factor, we were able to identify different needs whilst ignoring the demographic stereotype.

What about these people?

I’m Rahul, I’m 27 years old, I’m a transport strategy manager, so my job is pretty much 9 to 5.

I've quite a good nest egg towards a house deposit. I’m pretty confident, I use quite a lot of different types, kind of understand the rates and maturity dates and and things like that.

I want the highest rate so I don't mind putting it into lots of different places.

I’m Elizabeth, I’m 45 years old, currently unemployed because of mental health reasons.

I’m married without kids. I’ve never really had a savings account, I don’t feel like I have enough money to save

At the end of the month, there’s nothing left. I often find it quite overwhelming to think about. Ultimately I've had to turn to parents and I don't want to have to do that.

I’m Siobhan, I’m 34 years old, I work as a cleaner

I’ve got 2 kids, 6 and 9 years old.

I’ve always been pretty good with putting money away. I just don’t have a lot.

If I've got extra, I know I can put it into savings for my kids or for the insurance or other bills. God forbid holiday.

The result of using this approach is a product that fits the needs of a broader range of people, rather than something that feels like a compromise.

2

Public health: designing as if your life depends on it (because it just might)

For an app needing maximum adoption (20m+ users), demographics were useless - everyone was a target user.

A key pillar of the Government's pandemic response was to encourage use of the NHS COVID-19 app for digital contact tracing. This innovative technology required a huge number of users to download, install and use the app for contact tracing to be effective. Success relied on identifying the barriers and needs for people to use the app, and then designing to meet these.

The facts:

  • Over 400 in-depth interviews

  • Analysis helped to identify factors that affected people's likelihood of downloading and using the app, as well as how receiving notifications could influence their behaviours.

  • The result captured 11 factors, each with 2 to 5 states

  • For each factor, we identified what this meant for users in terms of their needs (to give them a reason to use the app) and the barriers that may prevent them using it. By taking a ‘jobs to be done’ approach to design, each factor was used to identify which needs could be solved and which barriers overcome.

3

Gaming: We should think about these people differently

Launching a brand new concept comes with a lot of uncertainties. Our client was building a metaverse for ‘gamers' and ‘music fans’, but wanted to understand more about them so they could know which features to prioritise for development.

The usual question: “Are we best to put a big survey out there to 100s of people to find out what they like?”

Our response: “One-to-one interviews testing concepts with a smaller sample will tell you in detail what people are like and what appeals or doesn’t. Don’t rely on self-reporting”.

  • The reality: Research showed that the high-level groups of gamers and music fans were very diversified in terms of types of games, motivations to play and music interest. There was some overlap but also many differences between the groups.

  • The outcome: By focusing on factors, we avoided creating an unmanageably large amount of personas, or starting from ones that are too broad, we could quickly get to practical design challenges. It enabled the design team to decide which game features to prioritise and invest in.

  • The design challenge: To appeal to people who had different levels of interest in music e.g. passive, active, creator. The team understood they needed a variety of features that allowed people to play for music assets, create from samples and explore music assets and creations.

Users

JayGamer

RubyGamer

ZakiMusic fan

Factor

Motivation to play

To socialise

To relax / escape

To relax / escape

Types of games

Competitive

Adventure

Creative

Gaming interest

Avid gamer

Avid gamer

Casual gamer

Music interest

Passive

Active, non-creator

Active, creator

Our 6-step process

We don't guess; we gather. Here is how we build Audience Factors for our clients:

  1. Define: Identify the core behaviours the business wants to drive.
  2. Research: Conduct first-hand in depth interviews with the widest possible set of people.
  3. Analyse: Break down the feedback into specific behavioural drivers.
  4. Map: Theme these into ‘Factors’ and identify the states (characteristics) within each.
  5. Identify: Deduct the specific needs and barriers for each characteristic of the factor.
  6. Design: Create solutions that address these specific needs and barriers.

How can we help?

If you're tired of trying to design for ‘average’ users who don't actually exist, we can help you apply the Audience Factors framework to your next project.

Have a project in mind?

Let’s discuss how we can achieve great things together

Let’s talk

Let’s talk

Inclusive design: Why Audience Factors are better than Personas

Why inclusive design requires a move beyond the average user

Personas have been a UX staple for decades for researchers, designers and delivery teams. They are great for building empathy and giving stakeholders a face to look at, but they fall short with designing inclusive services - in fact they actively exclude by design.

By nature, personas are an amalgamation of data. They are based on clusters of data, which tend toward averages, and thus miss data points that do not fit the clusters.

At Fluent, we’ve moved away from static personas and developed our own framework called Audience Factors. This is specifically designed to help researchers and designers to capture and design for what makes people different when engaging with your product or service.

Why personas fail

Personas try to make sense of audiences by putting them in boxes. While this makes for a neat slide deck, it fails as a design tool:

They rely on averagesData points that don't fit the main clusters are discarded, meaning you lose the very people who need inclusive design the most. Average design leads to average experiences and below average success.

They add fluffKnowing a persona ‘has a cat and enjoys sourdough and cycling’ may help bring them to life but it doesn’t help a designer decide how to explain interest rates or what to prioritise in the feature backlog.

They are staticHumans aren't one-dimensional. A person isn't just a ‘Young Mum’. One hour she’s a business owner, the next she’s a stressed parent, and later she’s a gamer. Personas can’t pivot as quickly as people do when it comes to defining what matters for how people engage with your service.

They lack design clarityIt is difficult to design for a type of person; it is much easier to design for a specific behavioural barrier.

Demographics explain who we should appeal to, but a service should be designed considering how individual differences affect behaviours

A better lens: the Audience Factors framework

The Fluent Audience Factors framework is an evidence-based approach to understanding how to design truly inclusive services for people.

Instead of looking at how to design for a person in their entirety, we break down the specific characteristics of an individual that impact how they engage with a product. This approach looks at what the differences are between people, and offers a practical way of dealing with them, so you can design for everybody and be more inclusive in your design.

Qualitative research is about discovering differences, not similarities

We have established two guiding principles. Audience Factors are:

  1. Motivational: A factor must be a fundamental reason that impacts behaviour
  2. Inclusive: Everyone is one level (or state) of every Audience Factor

Our framework is generally made up of 3 components:

Factors

The factor is the fundamental reason that impacts your user behaviour. Different factors could be Technology use, Financial literacy, Disposable income, Living situation. Each factor is made up of several states.

States

The different states of behaviour or attitudes we see within each factor – for example, within Technology use, the types might be Novice, Intermediate, Expert. States are mutually exclusive. At any point in time every individual is one state.

Themes

The high level theme that groups a number of factors, e.g. Capability, Situational factors.

Why Audience Factors work better than personas

True inclusivityAudience factors are not focused on a single factor or lens to evaluate behaviour, and for each factor there is a range of values rather than just one. This way we design for a spectrum of human traits.

Every person fits into one state of each factor at any moment in time. Therefore if you design for all audience factors, you will by definition be designing for everyone.

Clarity of design challengesIt is difficult to design for a person as a whole, it is much easier to design for specific contextual needs and barriers. This gives far greater focus to create a set of design challenges.

Evidence trailEvery design decision is linked to a specific factor, not a hunch about what a ‘typical user’ might want.

Supports making active and targeted choicesNot all products or services are meant for everyone, but when considering whose needs to design for it is important to have a full view of the population. By considering each audience factor in turn you can see who you might be excluding and make a conscious, strategic business decision about it, rather than doing it by accident.

You want the product to be for everyone, but everyone wants the product to be for them.

The result of using this approach is a product that fits the needs of a broader range of people, rather than something that feels like a compromise.

Using the Audience Factors framework in reality

Here are some stories around how the use of Audience Factors delivers better business outcomes than traditional personas:

1

Finance: Do you not want these customers then?

One of our clients was on the verge of scoping out their new mobile app.

Their question: “Which features do we need to build for the different people that will use our banking app?”

Our response: “Ok, so who do you want to use your app?”

There were 2 personas:

  1. Young mum: struggling to make ends meet, low financial literacy
  2. Working couple: established savers, decent financial knowledge, comfortable.

  • The reality: In our research we discovered there were young professionals who were optimising their savings, adults that struggled to save and stressed about understanding anything about finance, families that could save but didn’t bother to get an account.

  • The factors: By isolating ‘financial literacy’ and ‘capacity to save’ as the factor, we were able to identify different needs whilst ignoring the demographic stereotype.

What about these people?

I’m Rahul, I’m 27 years old, I’m a transport strategy manager, so my job is pretty much 9 to 5.

I've quite a good nest egg towards a house deposit. I’m pretty confident, I use quite a lot of different types, kind of understand the rates and maturity dates and and things like that.

I want the highest rate so I don't mind putting it into lots of different places.

I’m Elizabeth, I’m 45 years old, currently unemployed because of mental health reasons.

I’m married without kids. I’ve never really had a savings account, I don’t feel like I have enough money to save

At the end of the month, there’s nothing left. I often find it quite overwhelming to think about. Ultimately I've had to turn to parents and I don't want to have to do that.

I’m Siobhan, I’m 34 years old, I work as a cleaner

I’ve got 2 kids, 6 and 9 years old.

I’ve always been pretty good with putting money away. I just don’t have a lot.

If I've got extra, I know I can put it into savings for my kids or for the insurance or other bills. God forbid holiday.

The result of using this approach is a product that fits the needs of a broader range of people, rather than something that feels like a compromise.

2

Public health: designing as if your life depends on it (because it just might)

For an app needing maximum adoption (20m+ users), demographics were useless - everyone was a target user.

A key pillar of the Government's pandemic response was to encourage use of the NHS COVID-19 app for digital contact tracing. This innovative technology required a huge number of users to download, install and use the app for contact tracing to be effective. Success relied on identifying the barriers and needs for people to use the app, and then designing to meet these.

The facts:

  • Over 400 in-depth interviews

  • Analysis helped to identify factors that affected people's likelihood of downloading and using the app, as well as how receiving notifications could influence their behaviours.

  • The result captured 11 factors, each with 2 to 5 states

  • For each factor, we identified what this meant for users in terms of their needs (to give them a reason to use the app) and the barriers that may prevent them using it. By taking a ‘jobs to be done’ approach to design, each factor was used to identify which needs could be solved and which barriers overcome.

3

Gaming: We should think about these people differently

Launching a brand new concept comes with a lot of uncertainties. Our client was building a metaverse for ‘gamers' and ‘music fans’, but wanted to understand more about them so they could know which features to prioritise for development.

The usual question: “Are we best to put a big survey out there to 100s of people to find out what they like?”

Our response: “One-to-one interviews testing concepts with a smaller sample will tell you in detail what people are like and what appeals or doesn’t. Don’t rely on self-reporting”.

  • The reality: Research showed that the high-level groups of gamers and music fans were very diversified in terms of types of games, motivations to play and music interest. There was some overlap but also many differences between the groups.

  • The outcome: By focusing on factors, we avoided creating an unmanageably large amount of personas, or starting from ones that are too broad, we could quickly get to practical design challenges. It enabled the design team to decide which game features to prioritise and invest in.

  • The design challenge: To appeal to people who had different levels of interest in music e.g. passive, active, creator. The team understood they needed a variety of features that allowed people to play for music assets, create from samples and explore music assets and creations.

Users

JayGamer

RubyGamer

ZakiMusic fan

Factor

Motivation to play

To socialise

To relax / escape

To relax / escape

Types of games

Competitive

Adventure

Creative

Gaming interest

Avid gamer

Avid gamer

Casual gamer

Music interest

Passive

Active, non-creator

Active, creator

Our 6-step process

We don't guess; we gather. Here is how we build Audience Factors for our clients:

  1. Define: Identify the core behaviours the business wants to drive.
  2. Research: Conduct first-hand in depth interviews with the widest possible set of people.
  3. Analyse: Break down the feedback into specific behavioural drivers.
  4. Map: Theme these into ‘Factors’ and identify the states (characteristics) within each.
  5. Identify: Deduct the specific needs and barriers for each characteristic of the factor.
  6. Design: Create solutions that address these specific needs and barriers.

How can we help?

If you're tired of trying to design for ‘average’ users who don't actually exist, we can help you apply the Audience Factors framework to your next project.

Have a project in mind?

Let’s discuss how we can achieve great things together

Let’s talk