March 17, 2017

Read time: 3min

End-to-end research automation efficiency: 2018 and beyond

Market Logic Team

The automation of market research continues to evolve at breakneck speeds. In 2016, automation was widely used in the analysis of survey data and charting and infographics. And the 2017 GreenBook Research Industry Trends (GRIT) report found that “69% of clients and 75% of vendors view market research automation as a positive trend or game changer.” We’ll look at the real-life impacts research automation is having on the insights industry now, and what the future will hold.

Automated research tasks deliver higher efficiency

Research methods, such as sampling and survey design, require many manual steps that are time-consuming and demand research expertise. Around 30% of GRIT respondents use automated sampling and survey design tools to pull optimized samples themselves, design the survey by simply selecting a scratch template, and analyze results in real-time, saving precious time and money.

Holistic research automation for increased efficiency

Research generates tons of valuable data, which can be a big challenge to analyze, summarize and visualize in a comprehensive report. When it comes to the final phases of the research process, results need to be robust and easy to read, for example in charts, video snippets and graphs. Forty percent of GRIT survey respondents use automated charting and infographics, such as the data search and visualization capabilities in our search experience, to create insightful reports that are instantly available online. Though compelling, these applications can sometimes be isolated solutions for individual research tasks. At Market Logic, clients adopt a more holistic approach to research automation. They’re looking to achieve end-to-end efficiency with standardized best practices from the right research brief for the project type to the best-accredited vendor for the fieldwork. That’s why they opt for holistic research automation, starting with an online research request the brand manager can submit to the research team, which is reviewed and transformed into the business objectives at the core of a best practice research brief, automatically checked for any prior knowledge to prevent duplication, and pushed through end-to-end supplier management (selecting and commissioning a supplier, uploading results and evaluating performance). Most importantly, the entire process and the final results are seamlessly integrated into a marketing insights engine to ensure that the research asset is used again and again.

Handling social media and video data in a quantitative way

When it comes to results analytics, only 35% of GRIT survey respondents use automated solutions for analytics of social media and text data, and 20% use them to analyze images and video content, as these two areas have traditionally been handled qualitatively. New cognitive video, face and image recognition technologies from partners like LivingLens offer unique solutions for analysis of image and video content. Here, automation helps clients get the most from their video data – end users can enter a search term on their insights platform to jump straight to the part in the video where the respondent enacts or discusses their topic of interest.

Multi-dimensional text analysis to quantify the qualitative

Machine learning can help bring quantitative analysis to traditionally qualitative data. With social and text analytics in place, Market Logic uses machine learning in our AI-driven platforms to provide companies with the ability to explore large amounts of unstructured data with advanced, multi-dimensional text analytics. If the exponential increase in research automation in 2016 and 2017 is any indicator, 2018 is set to be another exciting year.