Akendi

08/14/2024

07/19/2024

✨ Sharing a project we were proud to be a part of...

Family Enterprise Canada supports, nurtures, and provides a unified voice to small, family-owned businesses, which account for 7 million jobs and 50% of Canada's private sector GDP.

An important mission that we were thrilled to support in their website redesign. Check it out!

Case study: https://www.akendi.ca/case-studies/fec/

07/12/2024

On June 25th, our team had the incredible opportunity to volunteer at the Daily Bread Food Bank in Toronto.

We spent the day preparing meals in the kitchen and learning about the food bank's vital role in fighting hunger in our city. It was inspiring to see the dedication of the Daily Bread staff and volunteers who work tirelessly to support those in need.

We were astounded to learn that in 2022-23, over 2.5 million client visits to Daily Bread member food banks occurred, a 63% increase from the previous year.

Volunteering together not only strengthened our team bonds but also reminded us of the importance of community and generosity.

A big thank you to the Daily Bread Food Bank for hosting us and to our team members for their enthusiasm and hard work.

06/03/2024

Test Models, Model to Test

A model is a representation of reality. When you create a prototype or a persona, you have a model. Then, you want to test directly or indirectly whether that model is good. When you subject it to a test (mimicking actual conditions), it passes a threshold criteria. Getting a model good enough to test or a test good enough to evaluate your model can be challenging.

Things to keep in mind:

◦ Some models can be tested more directly than others. A prototype is a lot easier to test than a persona.
◦ Since your model is not the final product, service, or person, be prepared for the market to give you information that other tests didn't.
◦ Your model must have reached some quality threshold, or there's no point in testing it. That is why research is crucial, and the concept of "fail fast" can become "fail differently every time and don't progress."
◦ Your test often benefits from both quantitative and qualitative evaluations of the model.
◦ The larger the scope of your test, the more variables it has and the more challenging it is to interpret. The smaller the scope, the less general its applicability. This trade-off is hard to avoid in complex systems.

A key way that we do this at Akendi is by talking to people in qualitative research sessions. Read more here: https://www.akendi.com/services/ux-design/user-persona-research/

05/27/2024

Setting the Table, Clearing the Table: The Challenge of Quant Personas

Personas can bring immense value to conversations about journeys and usage scenarios and deep understanding of your user groups. But can they be quantified? Personas are most effective when they combine qualitative and quantitative data to distinguish one individual from another individual or one group from another. That is, after all, what personas are largely about: the differences, or variances, between people.

How we think about quantitative personas at Akendi:

◦ Imagine rows of observations (or answers to a questionnaire) of different individuals. This string of numbers can be thought of as the 'location' of individuals in relation to each other. If two individuals share the same numbers in their observations, they are in the same 'location.'

◦ From this perspective, building quantitative personas essentially means finding specific 'locations' in this variable space that will be useful in business and design decision-making. Locations where many individuals are clustered around.

◦ To get there, striking the right balance in terms of relevant variables is important. Too many columns of data (variables), and you risk your data becoming too sparse. Conversely, too few columns may cause you to overlook important variables that distinguish individuals from one another.

◦ To strike the right balance, start with qualitative research (interviews, for instance) to guide you and quantitative approaches (like factor analysis) to identify the most useful variables. This improves the chances of your quantitative data finding meaningful differences between individuals.

◦ Finding the right balance and coming to the right interpretation of the qualitative and quantitative data requires not just math/stats, but insights and goals from the whole team; including, of course, business.

To learn more about Quant UX and personas, tune in to Quant UX Con 2024 on June 13th with Scott Plewes: Count Us In: Can Quant Help Save Personas? https://events.ringcentral.com/events/quant-ux-con-2024-worldwide