From flat file to interface: Synthesis of personas and analytics for enhanced user understanding

Jansen, Bernard J.; Jung, Sin‐Ho; Salminen, Joni

doi:10.1002/pra2.215

Cited by 7 publications

(1 citation statement)

References 60 publications

(67 reference statements)

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“…APG takes large amounts of customer analytics data and personifies the data via the creation of data-driven personas that are, reportedly, accurate and precise representations of the underlying customer data. As the persona analytics system [42], [59]- [61] has been described in detail in other research, we briefly present it here and refer the interested reader to published research.…”

Section: B Personification Processmentioning

confidence: 99%

The Effect of Hyperparameter Selection on the Personification of Customer Population Data

Jansen

Jung

Salminen

2021

IJECER

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We explore the effects of hyperparameter selections on the personification accuracy of customer analytics data from a corporate YouTube channel with an audience in the hundreds of thousands and customer interactions in the tens of millions. Using non-negative matrix factorization, we generate personas sets from 5 to 15 using the customer analytics data, with the number of personas being the changing hyperparameter. We then compare the gender, age, nationality, and topical interests of the personas across each of the 11 persona sets using the average of the 110 generated personas as the baseline. This analysis shows that hyperparameter selection significantly alters the personification of the analytics data, with the effect most apparent with age representation. The set of 10 personas provides one of the most accurate representations across all attributes, indicating that this may be a good default hyperparameter for personification. Future research can explore other personification attributes with other customer analytics datasets.

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Section: B Personification Processmentioning

confidence: 99%

The Effect of Hyperparameter Selection on the Personification of Customer Population Data

Jansen

Jung

Salminen

2021

IJECER

Self Cite

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Conclusion: Dispelling Myths and Laying Out the Grand Challenges of Data-Driven Personas

Jansen

Salminen

Jung

et al. 2021

Synthesis Lectures on Human-Centered Informatics

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Finetuning Analytics Information Systems for a Better Understanding of Users: Evidence of Personification Bias on Multiple Digital Channels

2023

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Although the effect of hyperparameters on algorithmic outputs is well known in machine learning, the effects of hyperparameters on information systems that produce user or customer segments are relatively unexplored. This research investigates the effect of varying the number of user segments on the personification of user engagement data in a real analytics information system, employing the concept of persona. We increment the number of personas from 5 to 15 for a total of 330 personas and 33 persona generations. We then examine the effect of changing the hyperparameter on the gender, age, nationality, and combined gender-age-nationality representation of the user population. The results show that despite using the same data and algorithm, varying the number of personas strongly biases the information system’s personification of the user population. The hyperparameter selection for the 990 total personas results in an average deviation of 54.5% for gender, 42.9% for age, 28.9% for nationality, and 40.5% for gender-age-nationality. A repeated analysis of two other organizations shows similar results for all attributes. The deviation occurred for all organizations on all platforms for all attributes, as high as 90.9% in some cases. The results imply that decision makers using analytics information systems should be aware of the effect of hyperparameters on the set of user or customer segments they are exposed to. Organizations looking to effectively use persona analytics systems must be wary that altering the number of personas could substantially change the results, leading to drastically different interpretations about the actual user base.

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From flat file to interface: Synthesis of personas and analytics for enhanced user understanding

Cited by 7 publications

References 60 publications

The Effect of Hyperparameter Selection on the Personification of Customer Population Data

The Effect of Hyperparameter Selection on the Personification of Customer Population Data

Conclusion: Dispelling Myths and Laying Out the Grand Challenges of Data-Driven Personas

Finetuning Analytics Information Systems for a Better Understanding of Users: Evidence of Personification Bias on Multiple Digital Channels

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