The ‘now economy’ and consumer technology advances which allow a “faster-than-light” value chain are just a couple of things driving the need for speed across all industries. Market research is no exception. In this new reality, our task has shifted. We must deliver crucial, game-changing insights quickly, overlaid with best-in-class intelligence and context from multiple data sources. Fortunately, with smart implementation of automation, we can start to forge a path to accomplishing these lofty goals.
Automation can help us meet our goals by handling more manual, mundane and (let’s face it) boring tasks. When we let the machine take care of data collection, data cleaning, charting and analysis, this frees us up from staring at tables, making mistakes and other frustrations. How many of us have spent hours poring over SPSS files, formatting data tables and PowerPoints, manually cleaning data and, for example, sending IDs back to multiple suppliers cobbled together for one multi-country project? These are the places where automation can do the heavy lifting.
Current sample fielding models in market research
Unfortunately, the path to automation is often wrought with false starts or insufficient implementations. As we experience growing pains and the shift to greater use of technology, we find many processes that are “semi-automated.” These stopgap approaches to achieving faster insights have developed a whole new set of challenges. In some cases, organisations end up over-engineering solutions, with people and technology, and deal with unexpected pitfalls. It’s difficult to scale because there are still people involved in portions of the process that should be automated, and this slows down delivery times. One solution is to take a staged or scalable approach that offers more options.
The golden path to sample automation
Implementing the right tech stack that utilises best-in-class APIs, alongside existing tools and integrations, is the only answer. When you couple this with streamlining operations for maximum efficiency, fast adoption and flexibility, you uncover the right way to use automation. Ultimately, this makes the role of the market researcher more valuable, more strategic and more important to your business. Implementing a professional, built-for-purpose SaaS platform to achieve your automation needs equals time savings, cost savings and high quality.
This doesn’t mean you have to jump in both feet first and take the plunge, possibly disrupting workflows. There is a smart path to automation, which includes a staged approach that is flexible enough to fit any business model and grow with any size company. There are options that can work as a pathway to automation, with an eye to future, more complete implementation. If you work with a technology supplier that has a wide array of options, you have the opportunity to scale.
For example, some companies may have a business model that best works with a fully managed service that includes things like survey scripting, hosting, data processing, language translation and project management. Others may be interested in taking greater internal control with a DIY model. This self-service model can work well if it allows access to a large supply chain that can effectively represent global audiences. From there, some may choose to utilise an API and quickly connect to their own proprietary software, accessing the right sample. The key to success is finding a technology solution that can offer multiple options. Eventually, as companies grow and need a more holistic approach, the adoption of a more fully automated model, such as a full enterprise implementation, can be streamlined.
This is a model that can digitally transform a business to prepare for the future. Taking this approach gives companies control and flexibility, ability to blend sample and achieve data continuity, and realise fast value at a low cost. Full implementation is the perfect way to future-proof market research businesses.
Automation is essential as market researchers strive to meet demands for speed, efficiency, quality and cost savings. Implementing it to handle steps in the process where it can provide the most benefit leaves us free to do the strategic thinking, add our expertise and discover the insights that are relevant to the business.
Written by: Greg Dunbar (EVP, Enterprise at Cint)