R&D Toolkit
  1. Overview
      2. Overview
    1. Introduction
      2.
      1. Recent Updates
        2.
    2. Tools
      3.
      1. Research
        2.
      2. Delivery
        3.
    3. Resources
      4.
      1. R&D
        2.
      2. Websites
        3.
      3. Project Tracking
        4.
      4. Further Resources
        5.
  2. Research
      3. Research Tools
    1. Problem
      2.
      1. Discovery
        2.
      2. Prioritisation
        3.
      3. Project Scoping
        4.
      4. Framing
        5.
    2. Empathise
      3.
      1. Investigate
        2.
      2. User Interview
        3.
      3. User Insights
        4.
      4. Data
        5.
    3. Mapping
      4.
      1. Research Mapping
        2.
      2. User Mapping
        3.
      3. Organisation Mapping
        4.
    4. Synthesis
      5.
      1. Problem Reframing
        2.
      2. Define
        3.
      3. Feature Prioritisation
        4.
  3. Design
      4. Design Tools
    1. Ideation
      2.
      1. Warm Up
        2.
      2. Sketching
        3.
      3. Storyboarding
        4.
      4. Design Studio
        5.
  4. Delivery
      5. Delivery Tools
    1. Agile
      2.
    2. Scrum
      3.
      1. Overview
        2.
      2. Team
        3.
      3. Events
        4.
      4. Artifacts
        5.
      5. Glossary
        6.

marc.tools

A Product R&D Toolkit

Welcome. I'm Marc and this is a Toolkit to create things.
Research Tools    Empathise
Data

The Qualitative Data that can be gathered from users is immensely valuable, but there are also a number of methods of collecting Quantitative Data to help drive product and designs decisions.

This data can be collected from a varsity of sources, and it doesn't necessarily require an existing product to be able to obtain sufficient enough data to inform the solution.

Section Tools
Analytics
A/B Testing
Questionnaire
  
Empathise    Data
Tool Info
Category Data
Updated 20/08/20
Templates   PDF     Miro
Creator Frederick Winslow Taylor

Unlike many forms of Product, objects and businesses, we have the ability to understand every single thing a user does when using a software product.

Using Analytic software, we can observe user behaviours and interactions, helping to identify trends and that help tell the user story and further inform and enlighten the Product development process.

The data points and metrics that emerge are quantifiable, and can help prove if design and product changes are having a positive or negative effect.

However, whilst the raw data is helpful, it doesn't necessarily explain why a user does something and won't predict if a user will do something. It can only record when they have done something - and just because they have done something, that might not have been caused by a change - correlation between metrics doesn't mean that one action caused another.

The biggest part of using analytics is to keep track of business goals, conversions or sales for example, and it will help greatly with tweaking and improving things - but remember, it is not the foundation of creating a great product and user experience, just part of it.

Further Resources
  Three Uses for Analytics in User-Experience Practice
  Five Essential Analytics Reports for UX Strategists
  The ultimate guide to Google Analytics for UX designers
  5 Myths About Data-driven Design
  How to Leverage UX Analytics for Data-Driven Product Design
  
Empathise    Data
Tool Info
Category Data
Updated 20/08/20
Templates   PDF     Miro
Creator William Sealy Gosset

A/B Testing is a valuable tool in Product and Marketing for both learning about user behaviour and insights, but also rapid iteration when experimenting to help gather further data to help solve the user problem.

By implementing 2 similar but slightly different designs (different colours, or font sizes for example), it provides insight as to what the user prefers.

Like Analytics, a large amount of data can be collected quickly, but with the added benefit of comparing apples to apples and having a more scientific approach.

During the discovery and empathy phase this data will largely be historic and used to help build consensus around the problem being solved and using it during the design phase alongside usability testing helps further optimise and validate the proposed solution.

The template below is a high level way of tracking an A/B test, with comparable data for drawing insights that can be included during the synthesising phase.

Further Resources
  A/B testing — A superpower
  What is A/B Testing?
  The Crazy Egg A/B Test Planning Guide
  
Empathise    Data
Tool Info
Category Data
Updated 20/08/20
Templates   PDF     Miro
Creator Statistical Society of London

A questionnaire is similar to a survey in that it has a similar layout and at first glance a similar purpose, however the key difference is to not to understand the user, but to understand the user's experience with a specific product.

By asking the user to rate their experiences with feature, flows, elements and behaviours, we can build a solid set of quantifiable data that can be used to identify and understand user's problems.

This is particularly helpful when discovery, validating, prioritising and eventually ideating problems.

The UEQ is an excellent resource that has everything needed to run a Questionnaire and collate the data and results. Using the resource and KPI calculations along with the template will help with analysing the feedback and drawing conclusions to then synthesise.

Further Resources
  User Experience Questionnaire
  What Makes a Good UX Questionnaire? User-Centered Scorecard Development