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Benefits of Personas Persona Analytics Personas Value of personas

Combining Empathy with Rationality for Better Insights to Analytics

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Data-Driven Personas for Enhanced User Understanding: Combining Empathy with Rationality for Better Insights to Analytics

Persona is a common human-computer interaction technique for increasing stakeholders’ understanding of audiences, customers, or users.

Applied in many domains, such as e-commerce, health, marketing, software development, and system design, personas have remained relatively unchanged for several decades.

However, with the increasing popularity of digital user data and data science algorithms, there are new opportunities to progressively shift personas from general representations of user segments to precise interactive tools for decision-making.

In this vision, the persona profile functions as an interface to a fully functional analytics system.

With this research, we conceptually investigate how data-driven personas can be leveraged as analytics tools for understanding users.

We present a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes.

We apply this framework for an analysis of digital marketing use cases to demonstrate how data-driven personas can be leveraged in practical situations.

We then present a functional overview of an actual data-driven persona system that relies on the concept of data aggregation in which the fundamental question is defining the unit of analysis for decision making.

The system provides several functionalities for stakeholders within organizations to address this question.

Jansen, B. J., Salminen, J., and Jung, S.G. (2020) Data-Driven Personas for Enhanced User Understanding: Combining Empathy with Rationality for Better Insights to Analytics. Data and Information Management. 4(1), 1-17.
https://content.sciendo.com/view/journals/dim/4/1/article-p1.xml

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Data-Driven Personas Persona Analytics Persona Design Persona System Personas

Explaining Data-Driven Personas to End Users

Explaining Data-Driven Personas to End Users
Explaining Data-Driven Personas to End Users

Enabled by digital user data and algorithms, persona user interfaces (UI) are moving to digital formats. However, algorithms and user data, if left unexplained to end-users, might leave data-driven personas (DDPs) difficult to understand and trust.

This is because the data and the way it is processed are complex and not self-evident, requiring explanations of the DDP information and UIs.

In this research, we provide a proof of concept for adding transparency to DDP using a real system UI.

Furthermore, we demonstrate ways to add breakdown information that can help alleviate user stereotyping associated with the use of personas.

Read the full article

Jung, S.G., Salminen, J., and Jansen, B. J. (2020) Explaining Data Driven Personas to End Users. Proceedings of the Workshop on Explainable Smart Systems for Algorithmic Transparency in Emerging Technologies co-located with 25th International Conference on Intelligent User Interfaces (IUI 2020). Cagliari, Italy, 17 March 17.

Read more about data-driven personas

What is a Data-Driven Persona?

Introduction to Data-Driven Personas

Giving Faces to Data by Creating Data-Driven Personas

Benefits of Data-Driven Personas

Got too many personas? This approach can help!

Do your think your personas are stable? They probable aren’t!

 

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CHI Persona Research Personas

CHI 2020 Best Papers & Honourable Mention for Persona Research

chi2002 paper award with three co-authors

Congrats to the APG Team for a CHI 2020 Best Paper & Honourable Mention research paper award!

The SIGCHI “Best of CHI” awards honour exceptional submissions to SIGCHI sponsored conferences. 125 papers received Honourable Mention (top 5% of submissions) of more than 3,000 submissions.

The research article from the APG team is: Salminen, J., Jung, S.G., Chowdhury, S. Şengün, S., and Jansen, B. J. (2020) Personas and Analytics: A Comparative User Study of Efficiency and Effectiveness for a User Identification Task. ACM CHI Conference on Human Factors in Computing Systems (CHI’20), Honolulu, HI, USA. 25–30 April, 1-13.

Read more about our persona research

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Automatic Persona Generation Personas

Giving Faces to Data by Creating Data-Driven Personas

APG logo with three team members
Giving Faces to Data: Creating Data-Driven Personas from Personified Big Data

Creating personas from large amounts of online data is useful but difficult with manual methods.

To address this difficulty, we present Automatic Persona Generation (APG), which is an implementation of a methodology for quantitatively generating data-driven personas from online social media data.

APG is functional, and it is deployed with several organizations in multiple industry verticals.

APG employs a scalable web front-end user interface and robust back-end database framework processing tens of millions of user interactions with tens of thousands of online digital products across multiple online platforms, including Facebook, Google Analytics, and YouTube.

APG identifies audience segments that are both distinct and impactful for an organization to create persona profiles. APG enhances numerical social media data with relevant human attributes, such as names, photos, topics, etc. Here, we discuss the architecture development and central system features.

Overall, APG can benefit organizations in distributing content via online platforms or with online content that relates to commercial products. APG is unique in its algorithmic approach to processing social media data for customer insights. APG can be found online at https://persona.qcri.org.

Here is a two pager about the Automatic Persona Generation (APG) system!

Read full article

Jung, S.G., Salminen, J., and Jansen, B. J. (2020) Giving Faces to Data: Creating Data-Driven Personas from Personified Big Data. ACM Conference on Intelligent User Interfaces (IUI2020)(Demo Paper), Cagliari, Italy. 17-20 March, 132-133

Read more about data-driven personas

What is a Data-Driven Persona?

Introduction to Data-Driven Personas

Benefits of Data-Driven Personas

Explaining Data-Driven Personas to End Users

Got too many personas? This approach can help!

Do your think your personas are stable? They probable aren’t!

 

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Personas

Do numbers in personas help?

picture of some numbers in a square
The Effect of Numerical and Textual Information on Visual Engagement and Perceptions of AI-Driven Persona Interfaces

Should you include numbers in your persona profiles?

Good question!

In an experiment, we present 38 marketing and data analysts professionals with two online AI-driven persona interfaces. One with information using numbers. The other with information using text.

We employ eye-tracking, think-aloud, and a post-engagement survey for data collection. We do both quantitative and qualitative analysis to measure perception and visual engagement with the personas.

Results show that the use of numbers has a mixed effect on the perceptions and visual engagement of the persona profile.

Therefore, job role is a determining factor on whether numbers/text affect end users.

The use of numbers has a significant positive effect on user perceptions of usefulness by analysts. Numbers have a significantly negative effect on user perceptions of completeness for both marketers and analysts.

The use of numbers decrease the perceived completeness of the personas for both marketer and analysts.

This suggests that the inclusion of numbers can have a desirable effect for certain roles. However, there are possible negative effects on user perceptions.

Salminen, J., Liu, Y.H., Şengün, S., Santos, J., Jung, S.G., and Jansen, B. J. (2020) The Effect of Numerical and Textual Information on Visual Engagement and Perceptions of AI-Driven Persona Interfaces. ACM Conference on Intelligent User Interfaces (IUI 2020), Cagliari, Italy. 17-20 March, 357–368.

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Data-Driven Personas Persona Research Personas

Can Your Personas be Biased?

bias image
Detecting Demographic Bias in Automatically Generated Personas

In research led by Joni Salminen, we investigate the existence of demographic bias in automatically generated personas by producing personas from YouTube Analytics data.

Despite the intended objectivity of the methodology, we find elements of bias in the data-driven personas. The bias is highest when doing an exact match comparison, and the bias decreases when comparing at age or gender level. The bias also decreases when increasing the number of generated personas.

For example, the smaller number of personas resulted in under representation of female personas. This suggests that a higher number of personas gives a more balanced representation of the user population and a smaller number increases biases.

Researchers and practitioners developing data-driven personas should consider the possibility of algorithmic bias, even unintentional, in their personas by comparing the personas against the underlying raw data.

Read full research

Salminen, J., Jung, S.G., and Jansen, B. J. (2019) Detecting Demographic Bias in Automatically Generated Persona. ACM CHI Conference on Human Factors in Computing Systems (CHI2019) (Extended Abstract), Glasgow, United Kingdom, 4-9 May. Paper No. LBW0122.

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Persona Research Personas

Got too many personas? This approach can help!

representing too many
Creating Manageable Persona Sets from Large User Populations

In this research, colleagues and I address a relatively new issue in the field of personas, too much data resulting in too many personas.

Creating personas from actual online user information is an advantage of the data-driven persona approach. However, modern online systems often provide big data from millions of users. These user display vastly different behaviors. This can result in possibly thousands of personas representing the entire user population.

We present a technique for reducing the number of personas to a smaller number. The technique efficiently represents the complete user population. It is also more manageable for end users of personas.

We first isolate the key user behaviors and demographic attributes, creating thin personas. We apply an algorithmic cost function to collapse the set to the minimum needed to represent the whole population.

We evaluate our approach on 26 million user records of a major international airline, isolating 1593 personas. Applying our approach, we collapse this number to 493, a 69% decrease in the number of personas.

Our research findings have implications for organizations that have a large user population and desire to employ personas.

Read full article

Jansen, B. J., Jung, S.G., and Salminen, J., and (2019) Creating Manageable Persona Sets from Large User Population. ACM CHI Conference on Human Factors in Computing Systems (CHI2019) (Extended Abstract), Glasgow, United Kingdom, 4-9 May. Paper No. LBW2713.

Read more persona research

All published works: https://persona.qcri.org/persona-research

Read more about data-driven personas

What is a Data-Driven Persona?

Introduction to Data-Driven Personas

Giving Faces to Data by Creating Data-Driven Personas

Benefits of Data-Driven Personas

Explaining Data-Driven Personas to End Users

Do your think your personas are stable? They probable aren’t!