Aug 2020 / 1 week / product designer / Team project
An energy reporting feature designed for the Google Home mobile app. The aim is to provide smart home users with insights on their appliances' water and electricity usage in an effort to optimize energy efficiency. I completed this remote design sprint together with two other product designers as part of Drawerrr's global Product Design Competition, where we were awarded 3rd place for our solution.
As a way to help with energy efficiency, many smart home appliances have entered the market to offer consumers with more sustainable options. When used optimally, smart products like lighting and thermostats can help save up to 30-40% of energy – and their popularity is growing fast.
It is estimated that in 2021, about 1 in 4 households in the US will be fully smart homes. And to help control and manage these smart appliances, many have turned to the Google Home mobile app.
However, like most smart home managing apps, Google Home does not provide a way for users to get insights on the energy consumption of their smart products, along with tools to help reduce energy usage. This in turn makes it challenging for many to make the most out of the energy-saving capabilities of their smart appliances.
In the summer of 2020, I collaborated with two other designers to take on Drawerrr's Product Design Competition – a 7 day design sprint held across the world. When provided our challenge prompts, we were immediately drawn to the following:
“Design an electricity and water report screen for a smart home app that will help people consume water and electricity more efficiently.”
We decided to take on this prompt because we were excited for an opportunity to work intentionally on data visualization. At the same time, we also felt that the growing prominence of smart home devices made this a relevant challenge to explore.
Since our challenge required us to build on an existing product, we chose to develop our solution as an additional feature on the Google Home mobile app.
Google Home has a large audience range and strong position in the smart home market, with support for over 50,000 smart home devices from over 5,500 popular brands. Furthermore, Google’s commitment to sustainability and work on being carbon neutral also factored into making it an ideal choice.
To begin, we started by conducing secondary research looking into shared traits among prominent users of smart home products. We were also eager to learn more about why and how certain user demographics were more likely to implement smart home tech in their daily routines. During this process, we uncovered the following key insights:
Nearly 44% of smart home tech adopters were young parents. Many of them with children younger than 18 years of age. And a key factor motivating many of these parents to integrate smart home products more regularly, is to make managing both their daily lives and their children’s routines much easier.
As a result of a desire for greater efficiency, it was common for recent parents to make use, and sometimes rely heavily, on smart appliances.
With little time to conduct deep user research, we created a proto-persona that best captured our findings.
Justine is a busy creative who loves the outdoors, and lives in Vancouver with her two young children and partner. Last year, the family of four had bought a new home together. To help make things more energy and cost efficient at home, the family decided to swap out many of their old appliances to invest in newer and smarter products.
But one day, she noticed that their utility bills were higher than normal for the month.
As a recent mother of two, Justine has limited time and energy. To properly investigate the specifics behind the spike in energy use, would require too much effort. And her lack of time and energy also made it difficult for her to properly look into maximizing the energy-saving potential of her smart appliances.
Justine's Pain Points:
A user journey map was then created to dive deeper into Justine’s thoughts and feelings. The journey follows a scenario where she had noticed a concerningly large electricity and water bill for the month, which then prompted her to investigate. From this, we were able to visualize Justine’s points of frustrations and create opportunities in the problem space.
The following were some of our primary insights:
Motivated to focus on usage: Being a parent often resulted in higher energy and water consumption usage, which motivated much of our user’s attention to this area.
Quick access: There is a need for a more seamless way to quickly access, view, and implement strategies to better manage their energy and water consumption.
Making a positive impact: A combined interest in environmental impact is key for someone who is socially conscious like Justine, as they are not motivated simply with the interest of reducing costs but also to feel impactful about their choices.
Do more tasks, in less time: Efficiency is critical especially when it comes to smart appliances, as a key goal of these tools is to bring more convenience for the user.
By analyzing other products and solutions, this allowed us to assess the potential gaps that we could fill with our design feature. We gathered data on competitive products and noted their approximate consumer size, core objectives, and business models.
The problem we noticed with conventional utility bills, was that most users had to log on separately to their electricity or water provider's platforms to access energy usage data – which was often a tedious process.
In response, we wanted to create a more seamless solution where users could simultaneously view their electricity and water consumption in real-time while also being able to apply commands to their smart appliances without having to visit another application or website.
Referring to the the competitive products, we began ideating solutions we felt would best address our user’s needs. From the pool of feature ideas we listed, we later organized them through an affinity mapping process to determine common themes.
From there, we plotted each of these features on a Prioritization Matrix to gauge the ones that were most pertinent and viable for both user value and organization efforts.
Key Insights:
Focus on data visualization. The key feature should be visualizing the data on electricity and water consumption of appliances, while also detailing its related costs.
Maintain a dual approach. It’s optimal to provide users a dual approach to simultaneously track energy usage with the ability to control their respective devices.
Build on an existing product. Integrating analytical features to an existing smart home managing product enabled us to take advantage of its ability to remotely command smart appliances. Ultimately, the Google Home mobile app proved to be the ideal platform, given their broad consumer base and work in sustainability.
Task flows and analysis were then performed to identify components that had to be present for users to successfully complete each task. This essentially helped determine the user interface elements, content and copy that had to be displayed.
During our research, we recognized that one of many key factors that motivated our primary audience to engage in sustainability efforts, like reducing their energy consumption, was to present a return of investment – such as saving money.
And it was often this combined potential to be more cost-efficient and sustainable that made most smart home products appealing. However, many of the options that have been available to monitor or optimize energy usage of smart appliances to be more efficient were often too complex or tedious.
As a result, we knew that our solution needed to prioritize a sense of ease in its approach to align with the value of having smart home products – convenience and efficiency.
From these observations, we were able to generate our problem statement, and identified a list of requirements that the solution must address.
The Design Requirements:
To begin, we conducted crazy eights individually before converging to compare and examine how our ideas could intersect. Once we had determined the best components from our individual sketches, we combined our ideas and built the digital wireframes.
From there, we then prototyped the wireframes to conduct cognitive walkthrough tests, before reiterating on the design and moving onto the high-fidelity mockups. Our thinking process during this stage revealed the following:
Highlight costs and usage. Summary of both energy consumption and expenses should be the primary focus of the solution.
Prioritize showing the summary. Detailed analytics on individual smart home appliances while important, is less of a priority to showcase compared to the general summary and overview.
Keeping suggestions simple. Tips on reducing water and electricity consumption should be relatively straightforward and easy to understand.
Using our completed prototype, we conducted user tests to determine potential improvements with our user flows and designs. The following were some of our insights:
Water and electricity toggle was conspicuous. For some users, the toggle to switch views between the electricity and water report was difficult to discover.
Efficiency tips felt impersonal. Most users hesitated when trying to make sense of the efficiency tip cards, as they felt the suggestions felt too broad and impersonal.
Data feedback felt misplaced. The environmental feedback card was confusing for some users, as they felt a disconnect between the feedback and graph chart.
From the the insights generated from our user tests, we made the following refinements to the initial design.
Increasing toggle’s visibility. Updated the water and electricity toggle to be easier to notice, by centering its position along with altering the icons weight and colours.
Discarded the average indication line. Removed the line indicating the average energy usage on the graph, as it was more distracting than helpful to users
Refined the data feedback. Altered the data feedback component by removing the border to draw a closer and clearer connection to the graph.
Revised efficiency tip’s copy. Updated the copy in the efficiency tip card to make it more apparent that the suggestions are specifically addressing the user.
Since we decided to build our solution as part of the Google Home mobile app and ecosystem, we knew that using their design system, while also adhering to material design features were essential.
As a result, when it came time to build the hi-fidelity mockups, we tried to maintain as much symmetry as possible with Google’s existing branding, such as with the use of colours, iconography and typefaces.
Get an overview of the costs and usage of water and electricity coming from connected smart home appliances.
Receive tips on how to easily optimize connected smart home appliances to save energy andcosts.
Easily filter between different viewing modes and access an appliance breakdown for a deeper analysis.
Access the data report feature straight from the Google Home Mobile app, while managing your connected appliances in one centralized place.
Looking further into the solution, our approach focuses on the following:
Maintain a smooth learning curve. By visualizing the data & offering different viewing modes, users can analyze key information on their energy usage quickly without requiring a steep learning curve. At the same time, for those looking for more comprehensive insights, we also offer a detailed breakdown covering the consumption and costs per smart appliance. Ultimately, the goal is to ensure that our solution can cater to both beginner users and power users of the Google Home mobile app.
A dual approach to smart home management. As determined from our user research, receiving analytics about smart home appliances in a centralized location is important. In turn, our solution provides a way for users to simultaneously track the consumption rates of their smart appliances while also being able to apply commands to them. This dual approach is achieved by building our solution within Google Home’s existing mobile app and ecosystem.
Think less and save more. With little time and energy to understand how to optimize each smart home appliance, providing energy-saving efficiency tips as swipeable cards allow users to think less and save more. This approach aims to enable users to quickly assess the actionable commands they can make, and gauge how much money or energy they could potentially save, all to promote more efficient decision-making.
This project was completed as part of a 7-day design sprint. Given how quickly we had to build our solution, with more time, I’d be interested to dive further into the following:
Examine voice features. Voice commands are an integral part of the Google Home experience. It’s also one of the more accessible ways for folks to control complex smart appliances like thermostats and dishwashers. Given more time to explore, it’d be beneficial to see how data analytics could be presented through a vocal auditory experience. It would also be useful to examine ways to apply energy efficient settings to smart appliances using voice commands.
Clarifying how analytics are generated. A particular area that would benefit a more thorough revisit is the user flow for how data on the costs and energy use of smart appliances are pulled into the Google Home app. For instance, would users need to import their billing information from their water or electricity provider for analytics on spending? And is it sufficient for users to simply rely on external smart plugs to transfer energy usage data into the Google Home app? These are some of the questions that would require deeper analysis to help further develop the solution.
An important takeaway from building this solution, was learning how to better navigate ambiguities in the design process.
Since we had to work quickly in the design sprint, there were moments when decisions had to be made, while there were still lingering ideas or questions. Through this experience, I was reminded of how the goal is rarely about reaching definitive answers or conclusions at the first attempt. Instead, it’s about embracing the iterative experience – where outcomes are often exploratory and meant to be revisited.
The challenge also required designing our solution as part of an existing product. Since we lacked insider knowledge to our chosen product, there were limits to how in-depth we got to understanding key factors such as their business goals and roadmaps. In turn, speculative design choices had to be made at certain points in our workflow to fill in the gap. So while knowledge gaps are sometimes inevitable, I realized that in the midst of uncertainties, decisions can still be made to generate productive insights and outcomes.