Was Napoleon right? – 4 tips for succeeding with DIY research

In recent years market research has been transformed by automation. The original pioneers like SurveyMonkey and Zappi are now big, established businesses and in their wake, we’ve seen a whole host of research tech start-ups entering the market and also big agencies such as Kantar and Ipsos automating their key methodologies to make them available for clients to self-serve. Clients in turn, attracted by the cost savings and speed, have turned to research tech platforms to conduct more of their insight work in house.  

The trend to automation is set to continue to disrupt the insights landscape for years to come. Already we’ve seen sophisticated research methodologies that used to take weeks to conduct becoming automated and available to complete in days (e.g. conjoint analysis from Conjoint.ly), emotion and behaviour measurement available as SaaS (e.g. facial coding from Element Human) and AI removing the need for respondents altogether (e.g. visual attention measurement from Dragonfly AI).

These developments and numerous others mean that the shift in how businesses access and use insight will continue to accelerate with an increased focus on ‘DIY’.

But when it comes to insight can we really use the maxim of Napoleon Bonaparte, “if you want a thing done well, do it yourself”? Well, here are 4 tips for how to succeed with DIY platforms.

Napoleon Bonaparte
Credit: Image by WikiImages from Pixabay

Tip 1: Think about what you need in your toolbox

With the number of methods and applications of automated tools proliferating all the time, the research tech landscape can seem bewildering. Mike Stevens, Insight Platforms Founder, says that at last count there are over 1000 research platforms. But with so many choices out there, selecting the right tools for your DIY toolbox can be difficult.

Some businesses have consolidated a lot of their research in 1 or 2 platforms and benefited from reduced cost, increased agility and better decision making from using consistent metrics across teams and markets. Yet there is a risk that if you only use a hammer then every problem looks like a nail and other businesses might benefit from a portfolio approach, using different tools for different needs in much the same way that research teams would historically have a roster of agencies.

There is no ‘right’ approach to selecting what should be in your toolbox, it depends on a range of factors including but not limited to the size of the business, its insights needs and priorities, budget, insights team strength and capacity and whether the users of DIY research will extend beyond insight teams.  

Tip 2: Success comes from how you use your tools

As any artisan will tell you, more important than what tools you use is how you use them and the same applies to DIY research. Maximising the potential of research tech platforms requires a different way of working and a mindset shift across the organisation. And this can be much more difficult to achieve than buying some new tools.

Agile ways of working will facilitate the adoption of research tech and ensure that its impact is maximised. For example, in creative or product development, research platforms should be incorporated in iterative test and learn sprint cycles to ensure that consumer insight informs decisions and, consequently, increases the likelihood of successful outcomes.

Tip 3: Don’t be afraid to get some expert help

I recently put up some floating shelves in my son’s bedroom. Whilst I took a certain satisfaction from completing the job, the fact it took most of my Sunday and the shelves weren’t quite straight when I finished left me frustrated and wishing I’d paid someone else to do the job. Similarly with DIY research it can pay to enlist some expert help for a number of reasons.

Whilst some methods and platforms are relatively simple to use, others are more complex and even the more straightforward platforms require time to run the research. With insight and marketing teams often under pressure to do more with less resource, that bandwidth can be hard to access internally. But it’s not just a case of resource, insights expertise is still needed to maximise the value of the research. For example, deciding what sample you should recruit, whether you need any additional questions to address the objectives and identifying if you can maximise insight by bringing in other data and knowledge to complement the learnings from the DIY tool.

Most importantly, without insights expertise to interpret the results there is a danger that the business doesn’t take the correct actions and makes expensive mistakes or fails to spot opportunities. Fortunately enlisting this expertise needn’t cost the earth or act as a brake on agility. Think of it as a shift from the traditional full service agency model to a guided service with a consultant using automated platforms to deliver insight and advice to the business.

A research platform plus consultant approach isn’t just a route to maximising value from relatively straightforward research approaches like copy testing or concept testing. Research tech advances in areas like survey design, sample selection and analytics have removed the need for big operational agency infrastructures, meaning that an experienced insights consultant can also deliver more complex insight programmes in areas like brand strategy, positioning and segmentation.  

Tip 4: Discovery from learning

As already mentioned, the speed and reduced cost from research tech platforms enables iterative test and learn sprint development cycles. The learning gained during these projects should increase the chances of success compared to a previous era where the higher cost and longer timelines of consumer research meant that consumer input came too infrequently or too late in the process.

However, there is a huge missed opportunity if learning is restricted to within project and not also across projects. A client once described this to me by saying, “we seem to do a lot of testing and not enough learning”. Lower cost research platforms mean businesses have the opportunity to do a lot more testing and this should be used to create a first party data lake into which we can deep dive to discover new learnings that are a source of unique advantage for the business. These learnings could come from regular sessions to identify themes behind successful vs. unsuccessful product or creative development, by conducting drivers analysis against a dependent variable such as uniqueness or modelling to commercial data such as CTR, sales etc. to identify variables that are predictive of success.

I suspect that where this learning is not captured, it is a result of a need to focus on the urgent over the important. This is another area where external support can be invaluable, providing both the resource to look across projects and a fresh perspective to those who are focussed within projects. As well as generating this learning, a good consultant can bring the story telling skills to package it to deliver impact across the business and act as a springboard to develop new opportunities.

If you’d value a discussion about how you can maximise the value from DIY research, please visit us at www.tripleirc.com and get in touch.

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