Increasing Location Services Opt-Ins

Increasing Location Services Opt-Ins

Overview

The Challenge

As a business, Kinsa needs users to allow location services on their phones in order to aggregate anonymous health data to produce illness insights for organizations that partner with Kinsa. I was tasked with determining how to increase this business-critical measure. The goal was to redesign the location services pre-permission prompt to maximize opt-ins among new users.

As a business, Kinsa needs users to allow location services on their phones in order to aggregate anonymous health data that produces illness insights for organizations that partner with Kinsa. I was tasked with determining how to increase this business-critical measure. The goal was to redesign the location services pre-permission prompt to maximize opt-ins among new users.

Key Context

The Kinsa app pairs with Kinsa smart thermometers via Bluetooth, and offers health tracking and personalized medical guidance to empower families to respond appropriately to the first signs of contagious illness.

The Kinsa app pairs with Kinsa smart thermometers via Bluetooth, and offers health tracking and personalized medical guidance to empower families to respond appropriately to the first signs of contagious illness.

Users encounter the location services pre-permission prompt as part of the thermometer pairing flow. The primary button on this screen triggers the standard mobile OS permission prompt for location services. The opt-in rate was already high, which made it challenging to find ways to have meaningful impact.

Users encounter the location services pre-permission prompt as part of the thermometer pairing flow. The primary button on this screen triggers the standard mobile OS permission prompt for location services. The opt-in rate was already high, which made it challenging to find ways to have meaningful impact.

location-services-prompt-redesign-before-after
  • My Roles: UX Researcher & Product Designer
  • Team: Product Manager, Lead Mobile Engineers
  • Tools: Miro, Sketch, InVision, Zeplin, UserTesting
  • Platform: Mobile
  • Duration: 2 months (Fall 2021)

My Roles: UX Researcher & Product Designer
Team: Product Manager, Lead Mobile Engineers
Tools: Miro, Sketch, InVision, Zeplin, UserTesting
Platform: Mobile
Duration: 2 months (Fall 2021)

Research

PRIMARY RESEARCH

PRIMARY RESEARCH

Remote, unmoderated user interviews were conducted in late 2020 (N=15) to inform the latest design of the location services prompt. I conducted an in-depth review of this qualitative data to understand what language and imagery resonated most with users, and why.

Remote, unmoderated user interviews were conducted in late 2020 (N=15) to inform the latest design of the location services prompt. I conducted an in-depth review of this qualitative data to understand what language and imagery resonated most with users, and why. A third of users had privacy concerns, and vague, unlabeled images were more confusing.

  • One-third of users had privacy concerns:
    • "[The app] needs to say something about protecting [my] data..." —male, age 31
    • "Saying the word 'anonymous' would make it more appealing to me..." —female, age 33
  • Vague, unlabeled images were more confusing to users:
    • "I did not understand it at first, I was kinda confused. I had to read to get a better idea..." —female, age 28
  • "[The app] needs to say something about protecting [my] data..." —male, age 31
  • "Saying the word 'anonymous' would make it more appealing to me..." —female, age 33
  • "I did not understand it at first, I was kinda confused. I had to read to get a better idea..." —female, age 28

SECONDARY RESEARCH

SECONDARY RESEARCH

I partnered with the Product Manager (PM) to gather high-level information on optimizing location services prompts, like benchmark opt-in rates and best practices.

I partnered with the Product Manager (PM) to gather high-level information on optimizing location services prompts, like benchmark opt-in rates and best practices.

  • An opt-in rate greater than 20% is generally considered high! Also, Medical, Health & Fitness apps saw their average location opt-in rates more than double around the start of the pandemic (Mar-Jun 2020). [source]
  • Best practices include transparency about how location will be used, providing value to the end user in exchange for this information, and timing the ask appropriately.
  • Full-screen pre-permission prompts consistently outperform modal pop-ups or partial screen messages.
  • An opt-in rate greater than 20% is generally considered high! Also, Medical, Health & Fitness apps saw their average location opt-in rates more than double around the start of the pandemic (Mar-Jun 2020). [source]
  • Best practices include transparency about how location will be used, providing value to the end user in exchange for this information, and timing the ask appropriately.
  • Full-screen pre-permission prompts consistently outperform modal pop-ups or partial screen messages.

Brainstorm & Ideate

The PM and I hosted a cross-functional team brainstorm, creating a shared virtual whiteboard to:

The PM and I hosted a cross-functional team brainstorm, creating a shared virtual whiteboard to:

  • Gather what we already know (e.g., analyze existing data that might reveal commonalities among users who opt out, identify bugs that could be impacting this metric)
  • Share real-world examples of prompts we like or dislike
  • Generate ideas for value propositions for users
  • Explore any alternatives to redesigning the prompt, to make sure we don't miss any "low-hanging fruit"
  • Identify our main assumptions
  • Gather what we already know (e.g., analyze existing data that might reveal commonalities among users who opt out, identify bugs that could be impacting this metric)
  • Share real-world examples of prompts
  • Generate ideas for value propositions
  • Explore any alternatives to redesigning the prompt, to make sure we don't miss any "low-hanging fruit"
  • Identify our main assumptions

Dot-voting pointed to redesigning the pre-permission prompt as the best low-cost, high-impact option. (One idea got more votes: blocking the local illness insights feature until location is shared. While the team expected that to increase opt-ins, we also agreed that blocking a feature users previously had access to would be creating a poor UX.)

Dot-voting pointed to redesigning the pre-permission prompt as the best low-cost, high-impact option.

location-miro-brainstorm

UI Design

Next, I explored high-fidelity UI designs in Sketch. Since this project had a short timeline (the holidays were coming up fast) and limited development resources (one lead mobile engineer per platform), I used only existing components and styles in my designs to try and minimize development time/cost. I played with copy, imagery, and layout, as drastically changing the functional elements was out of scope. The team rallied around a few versions (B-D) to compare with the current (A), each representing a different value proposition. Version B illustrates an app feature that provides users with local illness insights for their location, whereas the others are more conceptual.

Next, I explored high-fidelity UI designs in Sketch. Since this project had a short timeline and limited development resources, I used only existing components and styles in my designs to try and minimize development time/cost. I played with copy, imagery, and layout, as drastically changing the functional elements was out of scope. The team rallied around a few versions (B-D) to compare with the current (A), each representing a different value proposition. Version B illustrates an app feature that provides users with local illness insights for their location, whereas the others are more conceptual.

Test 1 Versions A-D in phones

Prototype, Test & Iterate

Now it was time to find out how these concepts are interpreted by real people, to identify the most transparent and compelling design. First step, draft the test plan:

Now it was time to find out how these concepts are interpreted by real people, to identify the most transparent and compelling design. First step, draft the test plan.

  • Research questions
  • Hypotheses
  • Methodology
  • Target audience demographics
  • Background info & context to share with users
  • Tasks to guide testers through the prototype
  • Non-leading, open-ended questions

Once I got feedback from the PM to make sure our most pressing questions would be answered, I made interactive prototypes and launched remote, unmoderated tests on UserTesting.

Once I got feedback from the PM to make sure our most pressing questions would be answered, I made interactive prototypes and launched remote, unmoderated tests on UserTesting.

Screen Shot 2022-02-13 at 2.47.53 PM

QUESTION

Which of these value propositions is most likely to lead to the highest location services opt-in rate, and why?

Which of these value propositions is most likely to lead to the highest location services opt-in rate, and why?

HYPOTHESIS

The current prompt titled "Join Kinsa's mission" does not resonate with users as much as previously thought, since it's company-focused rather than user-centric. They just want to know what's in it for them. So, we expected Version B showing local illness insights to perform best.

The current prompt titled "Join Kinsa's mission" does not resonate with users as much as previously thought, since it's company-focused rather than user-centric. They just want to know what's in it for them. So, we expected Version B showing local illness insights to perform best.

TEST 1: COMPARE VALUE PROPS

We gathered feedback on four main value propositions (including the existing one). Consistent with our hypothesis, Version B showing local illness insights resonated most with users in this test, so next we tested a few new iterations of this concept specifically. (N=20)

TEST 2: DEEPER DIVE

In this round, we explored some layout and copy variations of the local illness insights concept, since it was the most clear and compelling to users in Test 1. We honed in on two layouts. (N=20)

TEST 3: VALIDATION

We validated key findings from Test 2, and gathered additional feedback on two designs (same image, slightly different messaging) to further solidify the final solution. (N=10)

RESULTS & ANALYSIS

The PM and I transcribed every audio/screen recording in a spreadsheet. My analysis included affinity mapping to group user quotes by theme, so we could easily see the "loudest" ones. I also presented our findings to stakeholders (including the Director of Consumer Product). I wrapped up this phase by writing documentation to socialize what we did and why, what we learned, and find links to every artifact. Final design iterations were done in Sketch. We landed on a Version B iteration showing users a preview of the local illness insights app feature they will benefit from once they allow location services.

The PM and I transcribed every audio/screen recording in a spreadsheet. My analysis included affinity mapping to group user quotes by theme, so we could easily see the "loudest" ones. I also presented our findings to stakeholders (including the Director of Consumer Product). I wrapped up this phase by writing documentation to socialize what we did and why, what we learned, and find links to every artifact. Final design iterations were done in Sketch. We landed on a Version B iteration showing users a preview of the local illness insights app feature they will benefit from once they allow location services.

Location pre-permission prompts _ risk score card (1)
Location pre-permission prompts _ risk score card (2)

Engineering Handoff

Throughout the handoff process, I was an active collaborator. First, I drove sync and async discussions (e.g., Eng Review meetings, Slack channel threads) to achieve alignment on the proposed changes and provide clarity.

Throughout the handoff process, I was an active collaborator. First, I drove sync and async discussions to achieve alignment on the proposed changes and provide clarity.

The PM and I worked together to write the requirements in a concise and structured format, including:

The PM and I worked together to write the requirements in a concise and structured format, including:

  • High-level rationale for the redesign
  • Final solution and prototype
  • Links to user testing data that informed the design
  • Analytics to ensure we can accurately measure changes in opt-ins going forward
  • High-level rationale for the redesign
  • Final solution and prototype
  • Links to relevant user testing data
  • Analytics to ensure we can accurately measure changes in opt-ins going forward

Engineers planned to hard code this screen on the mobile clients (as opposed to using our server-driven UI system), so they needed the image assets up front. Before the next sprint, I finalized the UI for handoff in Zeplin and added designs to the corresponding Jira tickets.

Engineers planned to hard code this screen on the mobile clients (as opposed to using our server-driven UI system), so they needed the image assets up front. Before the next sprint, I finalized the UI for handoff in Zeplin and added designs to the corresponding Jira tickets.

Screen Shot 2022-01-18 at 4.10.07 PM

Solution & Impact

The new location services pre-permission prompt went live in Fall 2021 and resulted in an 8% increase in the location services opt-in rate!

The new location services pre-permission prompt went live in Fall 2021 and resulted in an 8% increase in the opt-in rate!

From a user perspective, the prompt is transparent about how their location will be used, and clearly illustrates the value they get in return!

From a user perspective, the prompt is transparent about how their location will be used, and clearly illustrates the value they get in return!

location-services-prompt-redesign-before-after

Reflection

Through generative user research, I would like to further investigate why our app users choose to opt out, and whether or not their minds could be changed. In a 2018 survey, about 23% of consumers identify as "data fundamentalists" who never share their personal data for any reason. [source] I wonder how many of our users identify this way, and how we could address their concerns beyond this particular screen.

Through generative user research, I'd like to further investigate why our app users choose to opt out, and whether or not their minds could be changed.

I would also like to explore additional scenarios in which we could show new users the location services prompt, since it is still limited to the thermometer pairing flow. The team could revisit having a pre-permission prompt in the initial onboarding flow, for example. I suspect there are even more points along the user's journey that we could consider.

I'd also like to explore more scenarios in which we could show new users the location services prompt, since it is still limited to the thermometer pairing flow.

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© 2022 yumi morii

© 2022 yumi morii