PhD Fitness

the best you can be.

INVEST IN A TALENTED TEAM

Roadmap to success

We are a team of mathematical/statistical modeller, designer, computer scientist and software developer.

We have developed intellectual property around unique predictive modelling for weight loss and nutritions.

Based on our unique design work, we achieved insightful understanding of the market, users, and distilled our unique competitive advantages.

 

We are seeking an investor with experience in digital health to help us complete design concepts (Step 7), develop infrastructure (Step 8) and generate compelling real-world evidence (Step 9). We are open for discussions with the NHS and private investors. 

1. Competitor analysis: assess >20 competitor apps, online/offline services (Completion)

  • Compile determinants of behaviour and factors of change relevant to fitness and nutrition from literature review

  • Compile clinically validated intervention components from weight loss programmes

  • What are the determinants of fitness behaviour?

  • Generate a feature matrix for >20 weight loss apps and personal trainer apps

    • What key statistics / information is used to communicate progress?

    • What are the costs to use the app (free / beginner / pro versions)?

    • What value addons are available within the app?

    • Is there any equipment required to use the app (e.g. fitbit, garmin, Apple Watch, iPhone)?

    • What kind of personality does the brand have (tone of voice, brand persona) with rationales?

    • What behaviour change techniques are already implemented in these apps?

    • Are there any clinically validated features/strategies that are not yet implemented by competitors?

    • Are there any determinants of fitness behaviour that are not yet considered and implemented by competitors?

  • Formulate hypotheses to test in Step 2

    • Formulate hypotheses regarding features by function, features by price, features by user number, features by customer satisfaction

    • Apply different psychological models (Learning Cycle, PRIME Theory of Motivation, Precaution Adoption Process Model) to categorise product features to understand how different competitor products are used in the real world

    • Formulate hypotheses regarding features for MVP, seeding fund stage and series A funding stage

2. Field work to identify Minimum Viable Product features (Completion)

  • Survey >150 fitness tracker users using a structured online questionnaire

    • Collect demographic information

    • Investigate user motivations, experience, difficulties and solutions they found

    • Test features proposed by existing solutions and our proposals from Step 1

    • Analyse data to categorise user types, needs and wants: This revealed unexpected insights

    • Kano model-based data analysis to categorise and prioritise features for MVP, seeding fund stage and series A funding stage

 

3. Field work to identify unplanned requirements (Completion)

  • Based on step 2, conduct (>30) face-to-face interviews with semi-structured questions to identify the unplanned and unmet needs (users and personal trainers)

  • Develop two personas for users: Define unmet needs, Identify specific users, Communicate how identified variables shape health behaviours

 

4. Define product specifications (Partial Completion)

  • Business case and rationale for features (In progress)

  • A full specification for the Website (In progress)

  • A full specification for the Apps (Complete)

  • A full specification for the API (In progress)

 

5. Develop technical solutions and build proprietary Intellectual Property (Completion)

  • Develop, validate and improve Body Composition Modelling and learning algorithm that is able to make personalised predictions

  • Develop nutrition questionnaire in collaboration with medic to assess nutritional problems of an individual based on demographics, symptoms, disease and drugs, dietary intake

  • Develop Food Pattern Modelling to optimise food intake in order to best satisfy the US Dietary Recommended Intake Guidelines

  • Develop classification algorithm to detect physical activity patterns based on fitness tracker time-series data

  • Develop predictive modelling of physical activity levels to infer the necessary recovery periods after high-intensity days for a person

  • Trademark registered in the UK. Brand name: PhD Fitness. Tag line: the BEST you can be.

 

6. Develop website demo (Completion)

 

7. Develop 2 design concepts (Seeking partnership)

  • Design concepts will be developed by designer to meet the product specifications and solve the identified problem

  • Develop website wireframes, prototypes and visual elements

  • Develop App wireframes, prototypes and visual elements

  • Test via focus groups: Two concepts will be selected and tested with target customers: 6-10 fitness tracker users and 6-10 personal trainers

  • Improve website wireframes, prototypes and visual elements

  • Improve app wireframes, prototypes and visual elements

  • Develop User Journeys/Storyboards

 

8. Development of the Site and App (Seeking partnership)

  • Build the API to spec

  • Build the website to spec

  • Build the apps to spec

  • Publish website and API

  • Publish apps to store

  • Associate Domain names

  • Setup Email forwarding

 

9. Evaluate the effectiveness of PhD Fitness in the real-world (Seeking partnership)

  • Products will be used by individuals and personal trainers for 100 days to train predictive models and test effectiveness

Company registration no. 09698685

Registered in England and Wales.

14 Tytherington Park Road, Macclesfield, Cheshire, UK  SK10 2EL 

Beyond Consulting Ltd

+44-7853 073 731