mirunaalini.alagarajah@gmail.com
Experience design: Gengame
Reducing domestic energy use
THE ASSIGNED BRIEF
I was tasked by the company Gengame to create an innovative, engaging and
interesting way of using smart meter data to encourage lower domestic energy
consumption.
UNDERSTANDING THE CURRENT PROBLEM SPACE:
GLOBAL WARMING
Currently, the household energy use contributes more to the UK’s oil consumption than services and industry (Department for Energy Security & Net Zero, 2004).
In the UK, we have stopped using coal as a source of fossil fuel energy but still heavily rely on oil and gas. We do have a number of renewable energy sources, including wind, bioenergy, solar heating, geothermal, hydroelectric, heat pumps, biogases, bio-liquids and waste. Bioenergy accounts for 48% of our renewable energy sources (Department for Energy Security and Net Zero and Department for Business, 2023).
A lean UX approach was taken throughout this project to allow rapid idea generation, prototyping and testing (Appendix 1). This lead to prototypes which are tailored more specifically to the target user group through each iteration. It also means less time is wasted on generating high fidelity prototypes and then re-designing them repeatedly.
The constraints that I had to work within were then identified as well as the
business goals.
A LEAN UX APPROACH
CONSTRAINTS FOR THE OUTCOME
PROS
CONS
Smart meters were introduced as a government scheme to encourage households to reduce their energy consumption. The investment in the smart meter is free but the user would need to book an engineer to install it. Users are then provided with a separate visual display which shows energy usage and cost from the previous day. This ideally should encourage users to use less energy.
SMART METERS
PRODUCT DISCOVERY
EXPLORING THE RESEARCH PACK
The chosen user group is a middle-class, privileged family who are used to a comfortable lifestyle. They consist of two middle-aged parents (Stephen, Jacqueline) and two teenage daughters (Hanna, Laura). These users were chosen as they are already well informed about climate change and feel a sense of moral need to contribute towards solving the issue.
They are early adopters of new technology and climate changing investments such as solar panels. This makes them ideal target users to modify behaviour to save energy as the underlying understanding of the seriousness of the issue is already present. They enjoy using technology and enjoy the convenience it allows them. They want to reduce energy wastage somehow and have already invested in certain eco-friendly measures such as electric cars and solar panels.
A research pack was created, providing all the primary user research gathered for various user groups. It contained
personas, archetypes and the brief set by Gengame.
EXPLORE THE
RESEARCH WALL
UNPACKING RESEARCH USING THE COM-B MODEL
EMPATHY MAP
PRIORITY MATRIX
TT
Assumptions were made and then prioritised using this matrix. The unknown factors which were the most important were then validated with secondary research in order to improve the strength of the assumptions and allow me to move on rapidly to the next stage.
PROTO PERSONA
To create more empathy with the user, a proto persona was created to understand their goals and pain points. The father of the family was chosen to focus on as he is the technophile of the household and holds the highest interest in interacting with new technology. Proto personas are assumption based representations of the chosen target user which provides the focus for the initial design process . They are usually created before any further research has been conducted unlike traditional personas which are created after extensive in-depth research.
INSIGHTS DEVELOPED
What does it mean?
Finding
Why is it important?
All key findings were drawn out from the research pack and a laddering technique was used to pull out the deeper meaning behind the data and helped to develop these insights. The questions ‘what does this mean’ and ‘why is this important’ were answered to gain a deeper understanding of the user’s core needs.
From these insights (Appendix 8-9), How Might We Statements were created to help the initial ideation of the app’s functions and features.
DESIGN PRINCIPLES
A user needs statement was then created from the findings and insights created so far. This provided an actionable statement which focuses the user needs and can be easily referred to during the design process.
From this, a UX vision statement was created to clarify the opportunity we are aiming towards with our design that is specifically targeted to these users.
Design principles were then generated as a series of short statements that describe the properties or outcome that should be included in the product. By doing this, it will result in a meaningful design that the users feel resonates with their core values and so will respond more positively to.
OUTCOMES AND BENEFITS
The value proposition is what brings value to the customer, not just the output of what the product is. The outcomes we are aiming for are to resolve the user problem identified, create an innovative solution to the problem and in doing so, manage the users pain points and modify their behaviour.
Part of the value proposition is to incorporate emotional value – to investigate how the product will make the user feel and what meaning will it bring to their lives. Before creating features for the app, we identified the ways we could engage users through meaningful design.
IDEATING KEY FEATURES
App features were brainstormed based on the user persona, design principles, intended outcomes and insights gathered.
The MoSCoW method was then used to prioritise the generated features. This method is simple to carry out and works for any amount of data, however there is no level of prioritisation within each box which may be problematic for a large number of items. The insights, user needs/goals, business goals and barriers to change from the Com-B model were used to then prioritise the app features.
EXPLORING THE POTENTIAL FOR AI
AI can be used in various ways to encourage more sustainable energy usage using the historic smart meter data. It has been shown to be successful in energy reduction by automating energy usage in numerous sectors.
For this app, the main usage will be to suggest personalised and realistic energy saving measures for this specific user, based on their past use and smart appliance data.
To determine to value of using AI to do this, a confusion matrix was generated. This matrix is used to plot the predicted values against the actual values to assess the performance of a feature, in this case, using AI.
For this matrix, the scenario is that the app has made a suggestion regarding the ideal time of day to use the washing machine when energy demand is less.
These are the possible drawbacks of incorporating AI.
INITIAL SITEMAP
This is the pathway that will be focused on for prototyping the app with participants.
A user story was created to help focus the ideation of the design and the flow to focus on. The user story involves creating a simple, comprehensive sentence including the target user, their goal and the benefit of achieving this goal.
Now that the features have been defined as well as the context of use, we begin to determine the layout and flow of the app. Sitemaps are used to demonstrate the basic structure of the app and to identify how ideas may be grouped together.
At this point, the features can be reorganised easily and moved around based on user feedback. A simple site map was created based on the screens that were deemed as necessary (Figure 11) . This is an iterative process and user testing will be used to validate this assumption and add or remove any screens to keep refining the sitemap.
STORYBOARD
Storyboards are used to help visualise the product and the context of use, and identify possible issues before prototyping begins. A storyboard was created to demonstrate the ideal user scenario where the app will be used. This is heavily based on the assumptions made so far and the research pack. This can be later refined with further testing,
INTIAL KEY USER FLOW
The chosen pathway from the sitemap was then developed into a user flow (Figure 13) to visualise how the user might navigate through the app.
Through this flow, the user sees the personalised energy saving suggestion. This has been generated via AI using machine learning by assessing the historic smart meter data and smart appliance data (which can be linked to the app). The resulting suggestion should then be specifically targeted to the user and also realistic to the user’s lifestyle.
Once the suggestion has been completed, the data should reflect the changes and the user will see that they have completed the task on the following day.
LO-FI PROTOTYPING
PRODUCT FEATURES
PROTOTYPING
For the user testing, a low fidelity version of the prototype was created. The screens were initially hand drawn individually onto paper. This allowed for quicker prototyping, testing and re-designing however, it is harder to show navigation or flow through the app using paper prototypes.
The screens were then photographed and uploaded into Marvel to carry out ‘paper in screen’ prototyping. This method is quick to use to create an interactive prototype and so enables faster re-development and better testing.
The first stage of testing was to see if users agreed with the layout of the flow and whether any changes would be needed.
Before testing, the user was given an information sheet to read which explained what the task would involve and what personal information would be required. Following this, they were given the opportunity to ask questions and then were asked to sign a consent form. Based on the user persona chosen, a user was found who fits the target user age group and lifestyle. Limitations of using this user were that they are not a technophile, do not interact with smart meter data (although they have a smart meter) and do not share the user’s values of wanting to contribute to climate saving measures.
Given the time frame to complete the user testing, the limitations were accepted in order to carry out the initial prototype testing to enable rapid development and refinement. To conduct the user testing, an iterative approach was used to organise the questions.
MID-FI PROTOTYPING
FUTURE ISSUES TO RESOLVE
LINK TO PROTOTYPE