Wearable health data analysis proposal: Free template

Customize this free wearable health data analysis proposal with Cobrief

Open this free wearable health data analysis proposal in Cobrief and start editing it instantly using AI. You can adjust the tone, structure, and content based on your client’s goals, data sources, and population use case. You can also use AI to review your draft — spot gaps, tighten language, and improve clarity before sending.

Once you're done, send, download, or save the proposal in one click — no formatting or setup required.

This template is fully customizable and built for real-world use — ideal for helping healthcare providers, insurers, fitness platforms, or research teams extract insights from wearable device data. Whether you’re working with step counts, sleep scores, heart rate variability, or longitudinal health data, this version gives you a structured head start and removes the guesswork.

What is a wearable health data analysis proposal?

A wearable health data analysis proposal outlines your plan to collect, clean, interpret, and report on data generated by consumer or clinical-grade wearable devices. It typically includes device data integration, cohort segmentation, metric normalization, analytics dashboards, trend analysis, and actionable reporting.

This type of proposal is used by data scientists, digital health consultants, and research teams helping organizations leverage continuous health tracking for insights, interventions, or product strategy.

Use this proposal to:

• Identify trends in sleep, movement, stress, or recovery across populations.
• Support proactive care or behavioral nudges using real-world health data.
• Analyze engagement or health outcomes for wellness programs.
• Power clinical research or health plan interventions with granular metrics.

This proposal helps clients go from raw step counts to actionable insights that improve health and retention.

Why use Cobrief to edit your proposal

Instead of copying a static template, you can use Cobrief to tailor and refine your proposal directly in your browser — with AI built in to help along the way.

• Edit the proposal directly in your browser: No setup or formatting required — just click and start customizing.
• Rewrite sections with AI: Highlight any sentence and choose from actions like shorten, expand, simplify, or change tone.
• Run a one-click AI review: Get instant suggestions to improve clarity, fix vague sections, or tighten your message.
• Apply AI suggestions instantly: Review and accept individual AI suggestions, or apply all improvements across the proposal in one click.
• Share or export instantly: Send your proposal through Cobrief or download a clean PDF or DOCX version when you’re done.

Cobrief helps you create a polished, persuasive proposal — without wasting time on formatting or second-guessing your copy.

When to use this proposal

This wearable health data analysis proposal works well in situations like:

• When launching or evaluating a remote health monitoring or wellness program.
• When assessing the effectiveness of lifestyle interventions using wearable data.
• When analyzing engagement or risk patterns in an employee or patient population.
• When conducting longitudinal research on recovery, sleep, or heart rate.
• When designing insights dashboards or alerts based on individual health data streams.

Use this proposal to help clients translate daily data points into meaningful decisions.

What to include in a wearable health data analysis proposal

Each section of the proposal is designed to help you explain your offer clearly and professionally. Here's how to use them:

• Executive summary: Frame wearable data as a continuous, low-friction input that provides deeper insight into health behaviors and outcomes — at scale.
• Scope of work: Include data source review (Fitbit, Apple Watch, Oura, Garmin, etc.), data ingestion/normalization, feature extraction (e.g., HRV, sleep phases, step variability), cohort definition, dashboard/report design, and insight synthesis.
• Timeline: Break into phases — data access setup, preprocessing, analysis, and reporting. Most projects take 3–6 weeks depending on data volume and reporting needs.
• Pricing: Offer flat-fee or usage-based pricing. Optional add-ons: predictive modeling, AI-generated summaries, cross-device normalization, or EHR integration support.
• Terms and conditions: Clarify data sharing requirements, de-identification protocols, API access, HIPAA considerations, and IP ownership for insights/reports.
• Next steps: Include a CTA like “Approve to begin data pipeline and cohort configuration” or “Schedule kickoff to align on data sources and reporting outcomes.”

How to write an effective wearable health data analysis proposal

Use these best practices to show analytical depth, healthcare relevance, and delivery clarity:

• Make the client the focus: Emphasize how the data supports their goals — improving outcomes, reducing risk, or increasing engagement.
• Personalize where it matters: Reference their user base (e.g., employees, patients, athletes), primary metrics of interest, and device mix.
• Show results, not just metrics: Use examples like “Identified 3x higher attrition risk in users with low variability in daily steps” or “Linked 15% drop in stress score to improved retention.”
• Be clear and confident: Avoid buzzwords — clearly describe the data types, analysis methods, and what the client receives.
• Keep it skimmable: Use phases, structured deliverables, and outcome language so clinical, ops, or data teams can approve quickly.
• End with momentum: Recommend starting with a 30-day data snapshot or pilot cohort to validate insights before expanding platform-wide.

Frequently asked questions (FAQs)

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This article contains general legal information and does not contain legal advice. Cobrief is not a law firm or a substitute for an attorney or law firm. The law is complex and changes often. For legal advice, please ask a lawyer.