Adaptive Mode V1
Adaptive Mode V1
Adaptive Mode V1
FluidLogic is a performance hydration company that specializes in delivering hands-free, on-demand hydration systems designed for high-intensity environments such as motorsports, mountain biking, off-road racing, and other endurance sports. Their flagship product integrates directly into helmets, allowing athletes to drink without taking their hands off the controls or breaking focus.
FluidLogic is a performance hydration company that specializes in delivering hands-free, on-demand hydration systems designed for high-intensity environments such as motorsports, mountain biking, off-road racing, and other endurance sports. Their flagship product integrates directly into helmets, allowing athletes to drink without taking their hands off the controls or breaking focus.
Case study
Client:
FluidLogic
Role
Role:
Product Designer
Year
Year:
2025
New Experience
Adaptive Mode™ — a premium, biometric sensor–driven hydration feature that reads heart rate, activity intensity, and environmental conditions to optimize hydration.
New Experience
Adaptive Mode™ — a premium, biometric sensor–driven hydration feature that reads heart rate, activity intensity, and environmental conditions to optimize hydration.
New Adaptive Mode Toggle
New Adaptive Mode Dashboard
New Adaptive Mode Optimize Hydration Feature
New "Connecting" Screen + Animation
Section 1: The Challenge
Section 1: The Challenge
How can we add biometric-driven adaptive hydration optimization without disrupting FluidLogic’s simple, trusted dashboard experience?
How can we add biometric-driven adaptive hydration optimization without disrupting FluidLogic’s simple, trusted dashboard experience?
Why is this important?
This feature is step 1 towards a premium subscription service “Fluidlogic Apex +.”
→ FluidLogic Apex+ will give automated features, enhanced data analysis, personalized insights, and social features. The possibilities are endless especially in the social aspect.
Companies with hardware + subscription services
Although subscription-specific revenue isn’t broken out in financial reports, these companies demonstrate strong potential for subscription services.
How can we expand the limits for FluidLogic?
By exploring subscription services that can build long-term engagement beyond hardware purchases.
Business Goals
Unlock recurring revenues
Build long-term engagement beyond hardware purchase
Create a connected fitness ecosystem (content + social + hardware)
Section 2: Research
→ FluidLogic Apex+ will give automated features, enhanced data analysis, personalized insights, and social features. The possibilities are endless especially in the social aspect.
Why is this important?
This feature is step 1 towards a premium subscription service “Fluidlogic Apex +.”
Section 2: Research
Analyzing Current Behavior
Exploring Fluidlogic's current logic and behavior when optimizing hydration.
Dose is user-controlled and reminder interval is system-optimized.
→If a user adjusts Dose and hits Optimize My Hydration, the app adjusts only the interval (not the dose).
The Optimize My Hydration function today only adjusts the interval, not the dose amount.
→ When a user adjusts the Reminder Interval and selects Optimize My Hydration, the app adjusts the optimal time interval but leaves the dose unchanged.
Analyzing Current Behavior
Exploring Fluidlogic's current logic and behavior when optimizing hydration.
The Optimize My Hydration function today only adjusts the interval, not the dose amount.
→ When a user adjusts the Reminder Interval and selects Optimize My Hydration, the app adjusts the optimal time interval but leaves the dose unchanged.
Key Findings
Even if users change their dose first, tapping Optimize My Hydration only adjusts the reminder interval and never changes dose.
Assumption* → Users already understand that:
Dose = Personal preference (user-controlled)
Interval = System-optimized
*Validate assumptions through UX Research.
Questions
Set your intensity — which level is best for me? How can I track my heart rate during the ride?
Why can’t we set a custom reminder interval that also optimizes the dose amount? For example, I might want reminders every 1 minute with the optimal dose calculated for that interval.
Companies with hardware + subscription services
Although subscription-specific revenue isn’t broken out in financial reports, these companies demonstrate strong potential for subscription services
How can we expand the limits for FluidLogic?
By exploring subscription services that can build long-term engagement beyond hardware purchases.
Business Goals
Unlock recurring revenues
Build long-term engagement beyond hardware purchase
Create a connected fitness ecosystem (content + social + hardware)
Prototype Versions
User testing and research are still needed to validate the final design decision, but Design A is the preferred option for the first round of testing due to its seamless introduction of Adaptive Mode without disrupting the user experience.
Design A
Design A allowed for a seamless introduction of the Adaptive Mode V1 feature with minimal disruption to the existing interface, preserving the current user experience.
Adaptive Mode V1 (Design A)
Goal: Introduce biometrics-driven hydration without adding complexity or breaking trust.
What we designed:
Adaptive Mode Toggle: Uses heart rate and temperature to dynamically adjust the reminder interval.
Sip Size Fixed: User’s dose choice remains constant.
Minimal Onboarding: Connect biometric device via Bluetooth and start instantly.
-> Reduces decision-making and enables quick use.
Impact:
Low learning curve for existing users.
Predictable, trustworthy behavior.
Existing dashboard
Future-ready platform for advanced adaptive features.
Adaptive Mode V1 Feature notes (Design A)
Goal: Introduce biometrics-driven hydration without adding complexity or breaking trust.
What we designed:
Adaptive Mode Toggle: Uses heart rate and temperature to dynamically adjust only the reminder interval.
Sip Size Fixed: User’s dose choice remains constant.
Simple Feedback: Real-time text showing current adaptive interval (e.g., “Adaptive interval: ~1:10 based on HR 160 bpm”).
Minimal Onboarding: One confirmation modal on first use.
Impact:
Low learning curve for existing users.
Predictable, trustworthy behavior.
Future-ready platform for advanced adaptive features.
Exploring Dose Adjustments
→ I explored a more advanced approach to "Adaptive Mode V1" that involves dose sizes as an addition to reminder intervals:
Dynamically adjusting dose size based on heart rate and temperature.
Example: bigger sips during high exertion, smaller sips at rest
Ex. edge case: User Feedback - "Dirt bike Channel" (5m 26s)
When a user skips 1 dose, should the next dose dynamically change?
Challenges Discovered
User Experience Risk:
→ Sudden changes in sip volume could feel startling or uncomfortable, especially during technical riding or racing.
Unpredictability could break trust and cause users to disable the feature entirely.
Complex Communication:
→ Users would need to understand why dose size changed each time(Beyond just skipping 1 cycle), adding cognitive load mid-ride.
Sports Science:
→ Endurance experts recommend frequent, small sips rather than sporadic large doses, reinforcing a stable dosing experience.
Decision for Version 1:
Focus on reminder interval optimization, aligning with user mental models and sports performance best practices.
Takeaway
→ To preserve user trust and reduce cognitive load, Adaptive Mode V1 would only adjust timing, not sip size. This simpler, predictable behavior became the foundation for introducing biometrics safely, with the option to expand in future versions.
Important notes
Sports Science: Endurance sports hydration guidelines recommend frequent small sips over variable dosing to reduce stomach discomfort.
Assumption* → Users want smarter timing, not unexpected dosing changes.
*Validate assumptions through UX Research.
Section 3: Prototypes
Analyzing Current Behavior
Exploring Fluidlogic's current logic and behavior when optimizing hydration.
Exploring Dose Adjustments
→ I explored a more advanced approach to "Adaptive Mode V1" that involves dose sizes as an addition to reminder intervals:
Dynamically adjusting dose size based on heart rate and temperature.
Example: bigger sips during high exertion, smaller sips at rest
Ex. edge case: User Feedback - "Dirt bike Channel" (5m 26s)
When a user skips 1 dose, should the next dose dynamically change?
Challenges Discovered
User Experience Risk:
→ Sudden changes in sip volume could feel startling or uncomfortable, especially during technical riding or racing.
Unpredictability could break trust and cause users to disable the feature entirely.
Complex Communication:
→ Users would need to understand why dose size changed each time(Beyond just skipping 1 cycle), adding cognitive load mid-ride.
Sports Science:
→ Endurance experts recommend frequent, small sips rather than sporadic large doses, reinforcing a stable dosing experience.
Decision for Version 1:
Focus on reminder interval optimization, aligning with user mental models and sports performance best practices.
Takeaway
→ To preserve user trust and reduce cognitive load, Adaptive Mode V1 would only adjust timing, not sip size. This simpler, predictable behavior became the foundation for introducing biometrics safely, with the option to expand in future versions.
Important notes
Sports Science: Endurance sports hydration guidelines recommend frequent small sips over variable dosing to reduce stomach discomfort.
Assumption* → Users want smarter timing, not unexpected dosing changes.
*Validate assumptions through UX Research.
Prototype Versions
User testing and research are still needed to validate the final design decision, but Design A is the preferred option for the first round of testing due to its seamless introduction of Adaptive Mode without disrupting the user experience.
Design A
Design A allowed for a seamless introduction of the Adaptive Mode V1 feature with minimal disruption to the existing interface, preserving the current user experience.
Adaptive Mode V1 (Design A)
Goal: Introduce biometrics-driven hydration without adding complexity or breaking trust.
What we designed:
Adaptive Mode Toggle: Uses heart rate and temperature to dynamically adjust the reminder interval.
Sip Size Fixed: User’s dose choice remains constant.
Minimal Onboarding: Connect biometric device via Bluetooth and start instantly.
-> Reduces decision-making and enables quick use.
Impact:
Low learning curve for existing users.
Predictable, trustworthy behavior.
Existing dashboard
Future-ready platform for advanced adaptive features.
Adaptive Mode V1 Feature notes (Design A)
Goal: Introduce biometrics-driven hydration without adding complexity or breaking trust.
What we designed:
Adaptive Mode Toggle: Uses heart rate and temperature to dynamically adjust only the reminder interval.
Sip Size Fixed: User’s dose choice remains constant.
Simple Feedback: Real-time text showing current adaptive interval (e.g., “Adaptive interval: ~1:10 based on HR 160 bpm”).
Minimal Onboarding: One confirmation modal on first use.
Impact:
Low learning curve for existing users.
Predictable, trustworthy behavior.
Future-ready platform for advanced adaptive features.
Design B
Design B provides stronger visual hierarchy but may compromise the prominence of the “Optimize My Hydration” CTA. The change, while more eye-catching, could be too disruptive compared to the original design.
Current Limitations & Potential Solutions
Current Limitations & Potential Solutions
Lack of Existing Bluetooth Connectivity
FluidLogic devices do not currently include Bluetooth hardware or firmware for pairing with external sensors (e.g., heart rate monitors or body temperature sensors)
Implication: Introducing biometric-based Adaptive Mode would require new hardware and firmware development to enable Bluetooth Low Energy (BLE) connectivity.
Potential Short-term Solution:
→ Partner with existing wearable ecosystems (e.g., Garmin, Wahoo, Whoop, Apple Health) to start, rather than building a new sensor ecosystem from scratch. This allows testing the feature’s value before investing in an in-house solution.
Key Question
→ Do we require users to pair external biometric devices (heart rate straps, watches) separately?
Or should Adaptive Mode “just work” as soon as they connect to the FluidLogic device?
Final Design
Adaptive Mode™ — a premium, biometric sensor–driven hydration feature that reads heart rate, activity intensity, and environmental conditions to optimize hydration.
New Adaptive Mode Toggle
New Adaptive Mode Dashboard
New Adaptive Optimize Hydration Features
Section 3: Prototypes
Section 3: Prototypes
Section 3: Prototypes
Prototype Versions
Prototype Versions
User testing and research are still needed to validate the final design decision, but Design A is the preferred option for the first round of testing due to its seamless introduction of Adaptive Mode without disrupting the user experience.
Design A
Design A
Design A allows for a seamless introduction of the Adaptive Mode V1 feature with minimal disruption to the existing interface, preserving the current user experience.
Adaptive Mode V1 Feature Notes (Design A)
Goal: Introduce biometrics-driven hydration without adding complexity or breaking trust.
What we designed:
Adaptive Mode Toggle: Uses heart rate and temperature to dynamically adjust the reminder interval.
Sip Size Fixed: User’s dose choice remains constant.
Minimal Onboarding: Connect biometric device via Bluetooth and start instantly.
-> Reduces decision-making and enables quick use.
Impact:
Low learning curve for existing users.
Predictable, trustworthy behavior.
Existing dashboard
-> Future-ready platform for advanced adaptive features.
Design B
Design B
Design B provides stronger visual hierarchy but may compromise the prominence of the “Optimize My Hydration” CTA. The change, while more eye-catching, could be too disruptive compared to the original design.
Final Design
Adaptive Mode™ — a premium, biometric sensor–driven hydration feature that reads heart rate, activity intensity, and environmental conditions to optimize hydration.
New Adaptive Mode Toggle
New Adaptive Mode Dashboard
New Adaptive Mode Optimize Hydration Feature
New "Connecting" Screen + Animation
Current Limitations & Potential Solutions
Lack of Existing Bluetooth Connectivity
FluidLogic devices do not currently include Bluetooth hardware or firmware for pairing with external sensors (e.g., heart rate monitors or body temperature sensors)
Implication: Introducing biometric-based Adaptive Mode would require new hardware and firmware development to enable Bluetooth Low Energy (BLE) connectivity.
Potential Short-term Solution:
→ Partner with existing wearable ecosystems (e.g., Garmin, Wahoo, Whoop, Apple Health) to start, rather than building a new sensor ecosystem from scratch. This allows testing the feature’s value before investing in an in-house solution.
Key Question
→ Do we require users to pair external biometric devices (heart rate straps, watches) separately?
Or should Adaptive Mode “just work” as soon as they connect to the FluidLogic device?
Next Steps
Next Steps
Next Steps: Evolution to Subscription
Adaptive Mode as Foundation → Personalized Hydration Service
Phase 2: Add historical hydration profile (logging HR, temperature, and intervals).
Phase 3: Machine learning to predict hydration needs ahead of intensity spikes.
Phase 4: Premium Subscription (Would need new hardware and firmware development)
Phase 5: Social integration (Expanding app for social integration- think Strava).
Next Steps
Next Steps: Evolution to Subscription
Adaptive Mode as Foundation → Personalized Hydration Service
Phase 2: Add historical hydration profile (logging HR, temperature, and intervals).
Phase 3: Machine learning to predict hydration needs ahead of intensity spikes.
Phase 4: Premium Subscription (Would need new hardware and firmware development)
→ Post-ride hydration recovery analysis.
→ Personalized training hydration plans.
Phase 5: Social integration (Expanding app for social integration- think Strava).
Next Steps: Evolution to Subscription
Adaptive Mode as Foundation → Personalized Hydration Service
Phase 2: Add historical hydration profile (logging HR, temperature, and intervals).
Phase 3: Machine learning to predict hydration needs ahead of intensity spikes.
Phase 4: Premium Subscription (Would need new hardware and firmware development)
→ Post-ride hydration recovery analysis.
→ Personalized training hydration plans.
Phase 5: Social integration (Expanding app for social integration- think Strava).