Personalised if-then sleep plans that actually stick
Opportunity Score
Strong demand and impact scores offset by competitive crowding; differentiation story must be sharp
Target User
Adults 25–45 with inconsistent sleep schedules who have tried and failed sleep apps before
Problem
Generic sleep advice doesn't change behaviour because it lacks specificity and situational cues
Solution
Guided if-then plan builder that creates personalised implementation intentions anchored to existing triggers in the user's environment
Sleep Architect uses implementation intention science to help users design specific, actionable sleep routines. Instead of generic "good sleep hygiene" advice, it builds contextual trigger-response pairs ("When my phone alarm sounds at 9 PM, I will dim the lights and close my laptop") that are 2× more likely to become habits.
Chen, R., Müller, S. · January 20, 2026
Research Question
Do implementation intentions outperform general goal-setting for sleep hygiene adherence?
Method
Meta-analysis of 24 RCTs with 6,200 total participants
Sample
6,200 adults across 24 studies, mixed clinical and community samples
Core Finding
If-then plans showed 2.3× higher adherence to sleep hygiene behaviours at 6 weeks (d=0.71, 95% CI 0.54–0.89)
Limitations
Heterogeneity across studies; short follow-up periods; limited long-term data
Click "Why?" on any dimension to see the rationale. Scores are independent and modular.
How novel the idea is relative to existing solutions
Evidence of real market need and urgency
Density and strength of competition — lower score means less competition
Clarity and viability of a revenue model
Potential scale of positive outcome
Alignment with current directional momentum
Not a medical sleep disorder treatment. Must avoid claims about treating insomnia or sleep apnoea. Users with clinical sleep disorders should be directed to healthcare providers.
This product should not make medical claims or provide clinical treatment. Position as education, behavior support, or coaching.
How to validate this opportunity before committing to a build.
Run a 4-week waitlist beta with 100 users. Measure: (1) plan completion rate, (2) self-reported sleep consistency at week 4, (3) app-open rate after day 7. Target: 65% day-7 retention.
App Blueprint
A product blueprint is being generated for this opportunity.