Research departments are under pressure. They are expected to deliver faster, cheaper and more impactful insights than ever before. Instead of doing more and faster research, insight departments are also able to revisit existing data sources. Often, companies have plenty of valuable data sources at their disposable, without being aware of their full potential. Moreover, relevant databases are often publicly available via APIs or sold via data brokers. Yet, the biggest hurdle lies in making sense of this abundance of data. Companies are struggling to connect different sources due to different structures, missing values and other complexities. In the last years enormous advancements have been made in machine learning and data science. Although demystifying is needed in order to better understand this discipline in context. With a creative and pragmatic mind-set, the problem can be solved by borrowing techniques from this field of data science. We show a case – in the beverage industry – where we exploited existing data sources to uncover a hidden layer of insights.
Here are some key strategies and tools to drive speed, extract value and quality by employing the most relevant skills and technology tools.
Discussion in conferences, webinars and articles about the future of market research often highlights the implications for research agencies and the efficiencies generated by new technology. These efficiencies including automation and standardisation of research, agile research, VR and AI-applications, enable research projects to be delivered faster and cheaper. But what does this mean for the insights departments of companies? How should they prepare for and adapt to a demand for cheaper, faster and better and what are the organisational and skills implications for them?
Companies are preaching that they are consumer centric. Listening to their consumers is the most important business driver. This was recently confirmed by the PWC study “What the Top Innovators get right”. All of the survey respondents indicated they value deep customer and consumer insights in their innovation programs. They ranked consumer and client insights as the most important capability during the ideation stage.
But when consumer insights (CI) is the most important business driver, and a strategic CI function adds business value, why do we see that CI-departments are under pressure?