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Data guide

The customer data model

Reference, Module 2, Cross-organization customer modelling, to prioritize ongoing Total Mental Health research and establish a data guide for modelling customers and insights.

Key insights from Module 2

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For consideration

Many human and technological factors can be addressed with a mature org-wide effort to meet web standards best practices for usability, performance, and accessibility.

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Suggested approach

Understanding the priority, scale, and impact of edge cases beyond these standards will give the confidence to invest in such edge cases, ultimately improving the overall customer experience by expanding and maturing product reach and engagement modes.


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Suggested approach

Active research across those factors not covered under web accessibility standards will help to define product and service characteristics that can uniquely impact customer experience.

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For consideration

Factors explicitly not covered under web and accessibility standards include:

Human factors

  • Neurological

Technological factors

  • Digital maturity
  • Environment of use

Sociological factors

Sociological factors predominantly impact writing and communication, which are not typically covered under technical standards such as web and accessibility standards.

Factors and research considerations

From a product point-of-view, digital maturity and environment of use can be particularly helpful for considering comfort and confidence with technology as well as context-of-use as factors against research findings (alongside technological factors, such as what device they used, what kind of internet connection they were on, screen size, etc).

From a representation point-of-view, being able to unpack neurodiversity and sociological factors would be immensely helpful to both track and grow representation as well as see if patterns build around these factors and research findings.

Here are the full list of factors from Module 2:


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Putting it into action

With these factors considered:

  1. Research findings can be sorted against any one or more of the factors.
  2. Patterns will emerge related to various lived experience scenarios.