Design is something we all use, whether consciously or unconsciously in the insights industry. Design is crucial for engaging customers in your work, in your research, and in your products. So, why don’t we apply more design principles to research tasks and projects?
Design helps us visually communicate messages, establish theories and present data, grab attention and create lasting cognitive connections. To effectively use and present insights, we too need to organise information effectively and guide viewers to take action. So here are five design principles you can use to help benefit your market research and insights:
1. Ideation
Ideation is a key part of the design process and, as the name suggests, is concerned with the generation of ideas and solutions. It's about having your team pull together to think and conceptualise ideas that will ultimately create the end product.
Within ideation, the main goal is to generate as many ideas as possible, and as you’re coming up with these ideas, remember to focus on the business's key objectives. When engaging in this principle, it is a good idea to ask yourself; what mediums can I use to solve this problem? For example, videos, AI, interactive surveys? How do I tell a story with the data output? What is the story the data is telling us? How can we create a compelling narrative for stakeholders? Are we able to communicate the insights in an exciting and purposeful way?
In design thinking, the ideation stage often references the design team as a whole generating new, and sometimes slightly wacky, ideas. But for researchers, your participants are your team. This means that you need to treat your consumers in a way that not only engages them, but also inspires them to generate options. Focus groups, online video discussions, forums and collaborative tasks can all be utilised well for this purpose, but you as the researcher must create an exciting environment to generate results worth pursuing.
 |
Tweet This |
|---|---|
| Design is a crucial factor in many market research processes, from research design to insight communications. |
2. Storytelling
From reading books to watching films and perusing art galleries, we consume stories in a variety of mediums every day. Stories entertain, educate and solve problems. As humans, our brains are hardwired to hook into and engage with stories as they fuel our imagination and spark new ideas. We need to use this principle to present data in the same stimulating way to hook in and engage stakeholders.
Insight professionals need to learn to find the story within the data, and then weave the insights into that memorable story in a comprehensive way to inspire stakeholders into action. This could be through storytelling techniques such as anecdotes, relevant imagery, hierarchical typography or real-life examples, and then using these to share your insights, making them more trustworthy and relatable. You can also use storytelling techniques such as tension or a surprise twist to share your insights and make them more impactful and memorable.
When presenting your research, storytelling can help you and your stakeholders better understand your target audience, thus creating more effective insight reports and marketing campaigns.
3. Visual Intrigue
Regardless of which format you choose, it's always important to use effective techniques when communicating your research findings. As mentioned briefly within storytelling; visual communication through relevant, clear, unique imagery is one way to engage your audience but it doesn’t stop there.
We have a predisposition to grasp ideas more easily when the information is given to us with the right visuals. Just pure data without visual aids tends to be harder to consume.
Visual aids such as infographics, charts, iconography, video explainers, interactive gaming, and more can all help to present data in a more appealing and understandable way. They can also help you highlight the key points, trends or relationships that you want your audience to take particular note of and remember.
Intriguing visuals can also make reporting look more attractive and professional, which overall helps people to trust the data you are giving them. However, visual aids are not a substitute for clear and concise writing. You cannot leave out the story or core elements, and you will still need to explain and interpret your data as this provides much-needed context for your visuals. Furthermore, be mindful that too many visuals may overwhelm your audience or cause it to seem repetitive. To avoid this, make sure the type of visual aid matches your data and purpose.
4. Alignment
When referencing design, alignment usually relates to the positioning of various items on a page relative to one another. Or to show a relationship between items, giving them a sense of balance. Alignment is the foundation of design as it declutters and frees it from becoming chaos.
But when we think of research, alignment can be taken a step further and not just aligning your data within the confounds of, say, a webpage or PowerPoint, but also aligning your goals and data with the target audience and consumers. For example, your questions should be aligned with your key objectives, as well as the research methods you have chosen. Your questions should be clear, specific, and relevant to your target audience and market, and also must be answerable, measurable, and actionable.
Alignment provides structure, thus creating balance, be it in a logo of your research, a survey design, or a report-based newsletter or debrief.
|
Tweet This |
|---|---|
| From alignment and visual intrigue to a balanced use of technology, there are many design principles that insight experts benefit from incorporating into market research. |
5. Balance of Technology
We can see today’s world being driven forward by advances in artificial intelligence, machine learning and the rise of Chat GPT, and it’s easy to become enamoured by technology. However, I believe that a human element is still critical to successfully understanding your consumers, making informed business decisions and presenting your data.
Whilst technology can be a great tool for automating lengthy processes and easier tasks, the nuance and stories behind the data are still needed and require experience to accurately find. For example, AI can provide valuable insights, just like it can create art, but the output is often devoid of any understanding and consumers are left wanting an answer to the “why” behind the output. And this is why experienced researchers are needed to transform the data into actionable results and to really understand the motivations behind the data.
This being said, there is definitely a balance that can be struck between technological and human interaction. For example, AI is often a great start for design clients who can use it to create a rough outline of what they need, without having prior design experience. Much like auto-generative AI that can now analyse qualitative text data to a high standard, this allows for easy understanding of insights and frees up time for researchers to continue with more in-depth analysis.
Achieving an equilibrium between creativity and technology is essential in today’s world. While human creativity can fuel innovation, understanding and intuition, technology can provide efficiency and scalability. By combining the power of new automated processes with the expertise of experienced researchers, businesses can end up with the best of both worlds.
