You probably own multiple smart objects for everyday use. You almost certainly have a smart TV and a smart phone. You may own a smart watch and run your household heating and lighting via a smart app. At minimum, you might own a washing machine that offers 20 functions for different complexities of laundry…
But how many of these devices’ ‘smart’ capabilities do you use? Typically, the answer is few. And most devices are set to default settings.
The same behaviour applies to market research technology. Now, with heightened pressure to answer client demands quicker and cheaper, while facing an unknown future, we simply don’t have the time to customise insight tools.
As the data and analytics world evolves, we must move away from what’s technologically possible and focus on business needs. This requires a mindset shift. Market research technology is now about catering to the new world ahead, not the skills needed to do so.
Designing for user need
Most of today’s market research technology tools are highly evolved and deliver complex, functionality e.g. highly specialised data collection, reporting and analytics.
These capabilities answer clients’ demands for faster, deeper and more actionable insight. But we must now be mindful that we’re not simply delivering technology for its own sake and develop technology primarily with human users in mind.
We must think one step ahead. Data science, analytics and insights are considered the new ‘power team’ for unlocking hidden truths in data. However, we must overcome this barrier: no matter how good the insights you uncover are, they’re useless if your clients can’t understand or act on them.
Be smart, not clever
Sometimes we design new data collection, analytics or reporting tools because clients want the ‘shiniest’ tool available. Those requests are often made by the clients being stretched most by their customers. However, these are often the people who lack the time or backing to put advanced, detailed capabilities into practice.
To ensure we’re designing tools for end users rather than the visionary few, we must ask some questions.
Who’s your research tool’s audience?
Knowing your audience is a prerequisite for ensuring we’re designing the right tools for the right people, in the right way.
For example, the population contains multiple generations: Millennials (born mid-1980s to mid-1990s), Generation X (born mid-1960s to early 1980s) and Generation Z (born between the mid-1990s and mid-2000s). All these generations use technology differently, as outlined in research by Pew. These dynamics are reflected both in research samples and research workplaces. Therefore, we must develop and design tools for consumers to respond to and researchers to use that are sensitive to generational behaviours.
We must also think about the changing channels consumers are using. Research by PWC reveals that over 50% of people in all age groups use voice technology daily. Siri and Alexa are normal features of our daily lives. So why ignore this as a data gathering approach?
We must remember we’re designing research tools to be used by humans, regardless of the complex capabilities we want to achieve. Questionnaire design highlights how important this is. Rather than creating multiple complex ways of asking questions through programmatic design, we must focus on using simple question types that come pre-loaded into survey platforms.
How can you ensure your research tools help, not hinder their audience?
It’s important to understand where technological capabilities can make a difference, and when they’re exciting but not necessarily delivering value. In short, we must get the right balance between ‘smart versus clever’. Especially now that AI’s advances are changing the technology landscape further. Ultimately, we must ensure we’re not so delighted with coming up with something new and clever, that we lose sight of its purpose and it becomes a distraction.
“Smart” technology is what helps in the creation of out-of-the box, repeatable solutions. It should:
- Support research requirements
- Benefit human teams by reducing repetitive, time consuming tasks
- Free people up for higher value, more complex work
The challenge comes when we get carried away with “clever” solutions. Just because a technology can or does exist, doesn’t make it automatically the right approach. While market researchers always strive to meet client demands, they must eventually ask:
- Does this create unwarranted complexity? or
- Will this generate unnecessary work for researchers instead of reducing it?
If the answer to either question is “yes”, it’s possible a solution won’t save time or cost and therefore make good sense. Niche client demands are one thing, creating unmanageable research tools is another. Think of some VR tools that’ve been created. Clever? Absolutely. Adding value to the research process? Less so.
What is your tool’s real, usable benefit?
Understanding any technology-based tool’s purpose, how its ROI will be measured and what its measure of success will be, is just as important as its technological capabilities. For example, will the tool reduce the speed of service delivery? What time and cost savings will be achieved? And which functions are responsible for delivering these benefits?
Knowing what needs to be achieved vs. what’s nice to achieve are two different considerations. It’s easy to jump on the bandwagon of the latest tools, technology and apps without considering how they’ll address specific business requirements – and critically, deliver business value.
Conversational technology, including social and text analytics, are great examples of automation meeting real business needs. Social and text analytics allow people to share views in their own way rather than via restrictive, closed questions. This can potentially provide researchers with robust and high quality feedback.
To ensure you understand what your tool’s ROI is and what it must return to be classed as successful, Key Performance Indicators must be put in place. Furthermore, you must establish clear objectives about what your tools are being developed to achieve (both short and long-term). This allows you to understand your tool’s immediate and lifetime value.
It’s all about balance
Within technology, the conflict is between:
- Wanting to create the latest, best, most advanced tool
and - Needing to generate revenue from something usable and beneficial
We understand the desire to develop high-profile technology tools to meet the ever-changing research challenges clients face. Speed to market is always a crucial factor in the development process.
But now, more than ever, we must take a step back.
We must take time to assess, plan and understand the real objectives behind any new tool’s development, and know its ROI in the real world. We must think about how the ‘new normal’, whatever that may be, will impact what’s practical and accessible.
Taking a measured approach will define whether research tools succeed or fail – and ensure that technology delivers results and value not just an all-singing, all-dancing solution that 1% of people may use.
