Identified participant criteria via secondary research + connections to various online UX channels.

Outreached and chose participants that met criteria using online sign-up and screening surveys, focusing on participants with experience with SaaS on either desktop or mobile.

For each study, I aimed for the following participants:

Qualitative study - 5 to 10 participants
Quantitative study - at least 40 participants

After identifying participants, I finalized my approach to be mixed-methods.

I decided I wanted to find "why" my proposed design met the research goals through the qualitative study and show "how" it does this through the quantitative study.

My study was structured as this:

Between-Subjects design, Remote Unmoderated A/B Tests + After Scenario Questions using Maze and Qualtrics.
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1. Remote Unmoderated A/B Tests
(control and treatment groups were posted in different online channels)
2. After scenario questions

This was to accomplish observing what participants chose to do between each design, collect data without having to fully moderate the process, and also collect information on general usability issues like the Qualitative Study.

My study was structured as this:

Within-Subjects design, Usability Tests + After Scenario Questions using Zoom.
(alternating order of designs with each new participant)
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1. Original design
2. After scenario questions
3. New design
4. After scenario questions

This was to accomplish revealing mental models of each design, while also getting the information of what users think and overall say about the design and usability issues.

Ran both studies for 7 weeks and collected a total of:

Qualitative Study - 1 participant
Quantitative Study - 7 participants

While running both studies, I encountered the following challenges:

1. Time lag in recruiting participants online and lack of responses
2. Participants using varying platforms (i.e. desktop, mobile), making it difficult to gather enough relevant data for analysis and synthesis
3. Lower budget to compensate participants and accomodating more participants

I did not have enough quantitative data to form meaningful conclusions, but I found that the qualitative data started to indicate that users prefer the new upfront design because of the repeated information about using coupons.

Participant A said, "...because of the 30% slash any coupon that is attached to the business plan... made me chose the best... last one. And also, when I had to renew, I still saw the same 30% on the advanced...last plan..."

I saw that participants remembered the 30% after coming across the situation to re-subscribe or unsubscribe. With additional research, I would explore the effects of the new upfront design with more users to understand if or why it has an effect on the unsubscriptions of this SaaS website.

After 2 months, I had limited data from my qualitative and quantitative studies to draw confident conclusions on whether informing users about coupons reduced unsubscriptions.

As a researcher, I have gotten to grow in my understanding of research from start to end, run my project, gather data, and find limits to running a project in this context.

If I were to have continued this for longer, the following points describe my process:

1. Revised strategy for recruiting participants
2. Ran statistical testing (Chi-square McNemar) to demonstrate difference between original and new pricing design
3. Analyzed and synthesized data to obtain insights towards making product decisions, utilizing factors around business, and used information to adjust research study

If I were to have continued my research, the following points describe my process:

1. Pivoted from online recruitment to participant recruitment services sooner
2. Refine definition of target participants for identifying who is unsubscribing, how, and why (B2B, B2C, etc.)
3. Test for designs that use various kinds of marketing language