We’re Hiring: Conversion Rate Optimization Intern
Company: Bluesense Smart Beauty — Harvard Innovation Labs Affiliated
Department: Growth Optimization
Location: Remote
Position Type: Internship
Reports to: Growth Marketing Manager or Product Growth Manager
About Bluesense Smart Beauty
Bluesense Smart Beauty is building next-generation AI-powered skincare and skin-analysis technology within the Harvard Innovation Labs ecosystem.
Our platform combines:
- Sensor-based smart beauty hardware
- AI-driven skin analysis
- Personalized skincare recommendations
- Consumer-facing mobile experiences
- B2B analytics dashboards
- Professional tools for clinics, medspas, dermatologists, skincare specialists, cosmetic brands, and retailers
Our mission:
Build the world’s most intelligent beauty device and redefine personalized skincare globally.
About the Role
We are seeking an analytical, curious, and experiment-driven Conversion Rate Optimization Intern to help us improve conversion across the Bluesense customer journey.
You will analyze how users move from their first interaction with Bluesense to product engagement, trial activation, and paid conversion.
Your work may cover marketing landing pages, App Store and store pages, onboarding, camera-permission flows, skin-capture experiences, AI analysis results, personalized routines, trial activation, and subscription paywalls.
This is a hands-on startup internship. You will work with Growth, Product, Design, Marketing, and Analytics teams to identify where users drop out of the funnel, understand why those losses happen, and develop structured experiments to improve performance.
The goal is to identify meaningful conversion opportunities, design strong hypotheses, run disciplined experiments, and turn results into measurable improvements.
What You Will Do
Conversion Funnel Analysis
- Map the customer conversion funnel from acquisition to paid subscription.
- Identify major drop-off points across landing pages, store pages, onboarding, camera consent, capture, AI results, routines, trials, and paywalls.
- Measure conversion rates between key funnel stages.
- Segment conversion performance by acquisition source, platform, campaign, user type, geography, or other relevant dimensions.
- Identify high-impact opportunities for improving conversion.
Landing Page Optimization
- Analyze landing-page traffic, engagement, and abandonment.
- Review headline clarity, value proposition, page structure, social proof, calls to action, and visual hierarchy.
- Evaluate whether landing-page messaging matches advertisement messaging and user expectations.
- Identify friction, confusion, or trust issues.
- Prepare recommendations and hypotheses for improving landing-page conversion.
App Store Conversion
- Analyze conversion from store-page visitors to app installs.
- Review screenshots, descriptions, positioning, social proof, and value propositions.
- Compare store-page messaging with campaign messaging and product experience.
- Research competitor positioning and identify opportunities to improve store-page conversion.
Onboarding Optimization
- Analyze onboarding completion and step-by-step abandonment.
- Identify steps that create unnecessary friction or cognitive load.
- Review onboarding questions, explanations, progress indicators, and calls to action.
- Recommend ways to shorten, simplify, reorder, or personalize onboarding.
- Develop experiments to improve onboarding completion without reducing data quality.
Camera Permission and Capture Optimization
- Analyze user behavior around camera-permission requests and skin-capture abandonment.
- Evaluate the timing, explanation, and presentation of camera-permission requests.
- Identify issues involving instructions, positioning, lighting guidance, progress feedback, loading states, or perceived effort.
- Recommend experiments to improve camera-consent and valid-capture rates.
Analysis-to-Routine Conversion
- Analyze how users move from AI skin-analysis results to personalized skincare recommendations and routines.
- Identify where users stop engaging after receiving their analysis.
- Review clarity, trust, relevance, personalization, and calls to action.
- Develop experiments to increase routine creation and continued product engagement.
Trial and Paywall Optimization
- Analyze user behavior before and during subscription paywalls.
- Review trial-start and paid-conversion performance.
- Test alternative paywall timing strategies.
- Review subscription-plan presentation and pricing hierarchy.
- Evaluate benefit communication, feature comparison, urgency, trust elements, and calls to action.
- Identify reasons for paywall abandonment and prepare recommendations to improve conversion.
A/B Testing and Experiment Design
- Develop testable hypotheses based on quantitative and qualitative evidence.
- Prepare experiments for headlines, calls to action, page layouts, value propositions, onboarding steps, camera-permission messaging, capture instructions, paywall timing, subscription-plan presentation, and pricing communication.
- Define primary and secondary metrics for each experiment.
- Document assumptions, audience, variants, expected impact, and success criteria.
- Prioritize experiments based on potential impact, confidence, and implementation effort.
Conversion Experiment Backlog
- Build and maintain a structured conversion experiment backlog.
- Record problems, evidence, hypotheses, experiment ideas, expected impact, and priority.
- Keep completed, active, planned, and rejected experiments clearly documented.
Advertisement-to-Landing-Page Consistency
- Compare paid advertisement messaging with landing-page messaging.
- Identify inconsistencies between user expectations and the destination experience.
- Review headline continuity, visual consistency, offers, product benefits, and calls to action.
- Recommend changes that improve message match and reduce post-click abandonment.
Experiment Analysis and Documentation
- Analyze experiment results after sufficient data is collected.
- Compare results against hypotheses and success criteria.
- Document winning, losing, and inconclusive experiments.
- Record key learnings and recommend the next action based on evidence.
Key Deliverables
- End-to-end conversion-funnel map
- Funnel drop-off analysis
- Conversion experiment backlog
- A/B test specifications
- Landing-page, App Store, and onboarding recommendations
- Camera-consent and capture-flow recommendations
- Paywall and trial-conversion recommendations
- Advertisement-to-landing-page consistency audits
- Experiment-result and conversion-prioritization reports
Key Performance Indicators
Your work will be evaluated by the quality of the insights and experiments you help create—not simply by the number of tests launched.
Relevant KPIs may include:
- Landing-page conversion rate
- App Store conversion rate
- Onboarding completion rate
- Camera-consent rate
- Valid-capture rate
- Analysis-to-routine conversion
- Trial-start rate
- Paywall conversion rate
- Paid subscription conversion
- Experiment velocity
- Conversion improvement generated by successful experiments
Who We’re Looking For
You may be a strong fit if you are analytical, structured, detail-oriented, and curious about why users behave the way they do. You should be comfortable working with numbers, turning observations into testable hypotheses, challenging assumptions with data, communicating findings clearly, balancing business goals with user experience, and working in a fast-moving startup environment. Interest in psychology, product design, growth, AI, consumer technology, beauty technology, SaaS, or digital products is a plus.
Relevant academic backgrounds may include Marketing Analytics, Business Analytics, Statistics, Psychology, UX, Product Management, Digital Marketing, Economics, Industrial Engineering, Data Analytics, Management Information Systems, Business Administration, Human-Computer Interaction, or Computer Science/Engineering with an interest in product and growth.
Previous CRO or growth experience is helpful but not required. Strong analytical thinking, curiosity about user behavior, structured experimentation, and willingness to learn are more important.
Preferred Skills
Experience with tools and methods such as Google Analytics, Firebase Analytics, Amplitude, Mixpanel, Hotjar, Microsoft Clarity, App Store analytics, A/B testing platforms, Excel/Google Sheets, SQL, basic statistics, funnel or cohort analysis, user research, UX principles, and mobile-product analytics is helpful but not required.
What You Will Learn
You will gain hands-on experience in conversion rate optimization, end-to-end funnel analysis, growth experimentation, A/B testing, hypothesis development, experiment prioritization, landing-page and App Store optimization, mobile onboarding, user-behavior analysis, paywall optimization, product analytics, growth metrics, customer journey mapping, cross-functional collaboration, AI beauty-tech commercialization, and early-stage startup execution.
Why Join Bluesense Smart Beauty?
- Work on a real AI-powered consumer product.
- Gain exposure to the Harvard Innovation Labs ecosystem.
- Take ownership of measurable business and product outcomes.
- Participate in real growth and product decisions.
- Design experiments that may directly influence the product.
- Collaborate across Growth, Product, Design, Marketing, Analytics, and Engineering.
- Work remotely with flexible hours.
- Receive practical mentorship and performance feedback.
- Be considered for expanded responsibilities or future opportunities based on performance.
How to Apply
Apply directly through LinkedIn with your CV or résumé.
Candidates may be asked to briefly explain why they are interested in conversion optimization and improving user journeys for an AI-powered smart beauty product.