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Naviguard.com Navigation Test

Research Findings Presentation

February 2022

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Background & Objectives

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Background

Our consumer base is coming to Naviguard.com with a variety of goals that our navigation needs to accommodate for. If we can solve this problem, it would impact our customer base positively because every user type would be able to easily navigate our site. It would also benefit our business because all user types would feel supported and satisfied in their experience with Naviguard.

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Documents

Link to prototype

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Problem Statement

What is this research about?

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  • UX Designer(s): Grace Deck, KNOCK
  • Product Owner(s): Sam Anderson, Thomas Kane, Jean Wong

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Stakeholders

Key Dates

02/08/2022

Kick-off

02/09/2022

Pilot

02/10/2022

Conduct study

02/11/2022

Analysis

02/14/2022

Read out

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Objectives

What problems do we hope to solve?

  • Understand which navigation layout users prefer
  • Understand which navigation layout provides a better user experience

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Success Criteria

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Objective

KPI

Efficiency

Time on task (dependent variable)

Effectiveness

Task success rate (dependent variable)

Usability and ease of use

Single Ease Question (independent variable)

Satisfaction

Customer Satisfaction Score (dependent variable)

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Research Scope & Methods

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Research Methods

Unmoderated within-subjects usability preference test with 10 participants, measuring both quantitative and qualitative dependent and independent variables. Understanding dependent variables but having independent measures be the deciding factor we should be able to decipher the most user-friendly solution with insights on aesthetic preferences.

Participants will walk through the same task for each navigation and answer questions during and after.

Participants will be split into two groups to switch the order of which navigation is presented first to avoid order bias.

We are including current design as a control to help gain statistical significance in our findings.

Primary Method

How did we execute this research?

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  1. Where preference testing goes wrong (and what we should do instead)
  2. Single Ease Question (SEQ)
  3. Customer Satisfaction Score (CSAT)
  4. Between-Subjects vs. Within-Subjects

Secondary Method

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Participants

Who did we test with?

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Batch 1 (6)

Batch 2 (8)

Employer Sponsored Health Insurance

5 Yes, 1 No

4 Yes, 4 No

States

Illinois, Texas, California, Florida, New York, North Carolina

California, New Jersey, Tennessee, Florida, Massachusetts, Ohio, Maryland

Education

1 associate degree

3 bachelor’s degree

2 post-graduates

2 HS or equivalent

3 associate degree

1 bachelor’s

2 post-graduates

Income

1 $35-49,999

1 $50-74,999

2 $75-99,999

1 $100-149,999

1 $200,000+

1 Under $15,000

1 $15-24,999

1 $25-34,999

3 $50-47,999

1 $75-99,999

1 $100-149,999

OON experience in last 2 years

4 Yes, 2 No

5 Yes, 3 No

Use email for healthcare communications

6 Yes, 0 No

7 Yes, 1 No

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Key Findings

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Navigation A

Key findings

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KPI

Result

Time on Task

1:08

Task success rate

93%

Single Ease Question

79% rated very easy

Customer Satisfaction Score

90%

Overall preference

14%

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Navigation B

Key findings

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KPI

Result

Time on Task

:42

Task success rate

93%

Single Ease Question

86% rated very easy

Customer Satisfaction Score

100%

Overall Preference

64%

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Navigation C

Key findings

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KPI

Result

Time on Task

1:06

Task success rate

100%

Single Ease Question

93% rated very easy

Customer Satisfaction Score

80%

Overall Preference

21%

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Aesthetic considerations

Key Findings

  • At least 10 participants mentioned they liked that navigation B was all on one line and had a larger type face
  • 3 participants mentioned finding the login button easier on navigation B because it was visually differentiated
  • 2 participants mentioned liking the background color on navigation A, but admitted they had overlooked it during the task
  • The 3 participants who chose navigation C, mentioned preferring navigation B but noticed the missing links for ’No Surprises Act’

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Recommendations

Key Findings

  • Navigation C had the highest individual variable as our deciding factor with a 93% rating of being very easy to use, but there really wasn’t enough statistical significance between all 3 for it to be super impactful
  • There was statistical significance in the preference of navigation B, but this still leaves us with questions on how to grow our menu

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Recommendations

Key Findings

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A few options

  • Move forward with navigation C as-is
  • Move forward with either navigation C or B with the aesthetic considerations, a few ideas:

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  • Further understanding of priorities, KPIs and personas that could result in further testing in card sorting or specific use cases we could test

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Appendix

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