Question 1

What is data analysis in market research?

Accepted Answer

Market research involves acquiring data about a market and turning it into insights that help improve your interactions with the market. Data analysis lands in between data collection and insight development and can take many forms depending on the data, the issue to be addressed, and the resources you have to invest in it. Its complexity can range from reading a published table of numbers and deciding what it means for you to building an enterprise-wide system for integrating, housing, and analyzing different kinds of data using sophisticated algorithms with flexible user tools and dashboards that can stimulate insights after only a quick scan. Data analysis can be a finite step in a defined project or a living process that continuously feeds on new data and may even adapt itself automatically as it learns. Data analysis can turn your survey data into product and positioning decisions or apply sales data to decisions about advertising and positioning. It can take live web traffic data and determine how to optimize a given user’s experience or apply results of web searches to help you optimize your online content. Whether is it performed manually by an analyst using a statistical package or automatically by a machine following and optimizing an algorithm, data analysis provides the bridge from market attitudes and behavior to actionable business decisions.

Question 2

What types of companies provide data analysis for market research?

Accepted Answer

The GreenBook Industry Trends (GRIT) Report segments insights suppliers into five major types. Although companies who primarily offer data and analytics services make up only about 13% of suppliers, three times that number say data and analytics are a significant source of revenue for them. The biggest overlap is with technology providers (39%), and data and analytics are offered by just over one-quarter of strategic consultancies, full service research agencies, and field services providers. You can find data and analysis services offered by suppliers of any type, and this gives you a wider selection of complementary services and levels of expertise from which to choose. According to GRIT, more than 60% of data and analytics and full service research providers offer “analytical services,” as well as most strategic consultancies and technology providers. Data and analytics providers are the most likely to offer research or analysis of unstructured data, followed by strategic consultancies and full service research providers. Technology providers stand out because they offer tools or platforms for basic or advanced analytics, and nearly half of data and analytics providers offer an analysis platform. Both of these types of providers are nearly as likely to offer tools or platforms for collection or analysis of unstructured data, and both are well ahead of full service research providers, strategic consultancies, and field services providers with respect to offering analysis platforms. Many different options for data analysis support are out there, and they will differ by degree of focus, expertise with structured versus unstructured data analysis, and use or availability of technology or tools. While DIY platforms offer analysis capabilities for data you can upload to or collect on the platform, other kinds of data analysis can be performed within your own data warehouse or knowledge management system. Providers of these services help you to identify, integrate, manage, and use data you currently have or may acquire in the future. This enables more powerful analyses because you can see an issue from multiple perspectives, more available data because more of your staff can access it, and more effective application of insights because data visualization and dashboarding tools may be included. You have a great variety of data analysis providers available to you, making it more likely you will find the right match to your initiative.

Question 3

What are the 7 key steps in data analysis?

Accepted Answer

Any kind of data analysis involves seven steps: problem definition; data selection; data acquisition; data cleaning; data analysis, interpretation; and data visualization, storytelling; and communication. While only some steps may need to be optimized for a given analysis, they all need to be effective. Problem definition is fundamental to any initiative, and it’s important that the data analyst understand the objectives and scope of the effort. Before you can have meaningful insights that address your issue, the issue will be translated into data needs, designed into analysis plans, and be used to guide interpretation. It’s critical that your needs are properly represented throughout the process, whether that means constantly checking on the progress or leaving it to the experts, and a robust problem definition will buttress success in either case. The next steps are to identify the appropriate data to address the problem, then to acquire it. This could end up as simple as accessing syndicated data to which you already subscribe, as involved as conducting qualitative research and designing a survey instrument based on its findings, or even as complex as merging different data sources and building a data warehouse. These steps need to be executed by someone who understands the problem you are trying to solve and the success criteria for solving it. Once the data is collected, it needs to be cleaned or processed (unless it is prepackaged, for example, in a syndicated report for which someone else has done the data processing). It is critical that the data you analyze matches the scope and criteria you have defined and to exclude any that doesn’t. Even after data is cleaned, it generally needs to be processed. Data measured in certain ways may need to be transformed or rescaled to fit the analysis method, and variables need to be combined to create more useful variables. Regarding surveys, for example, many people fail to realize that the best way to ask a question often is not the best way to analyze it; those are two completely different situations. At this point, the main analysis and interpretation can begin. The method of data analysis needs to be selected based on its appropriateness for the kind of data you have and the specific question you need to answer. Equally important, the analysis needs to be interpreted by someone who understands not only the business issue but the data and the method used to analyze it. Identical results might have completely different meanings if they came from different data sources or if the assumptions behind the method used differed significantly. Perhaps a take rate for a new product concept of 20% might be great if it was based on the general population but awful if it included only your core customers. A data analyst who understands your business can add value, but don’t underestimate the need for critical thinking and objectivity. Finally, if the process has run through all these steps while remaining true to the objectives and scope, now the results and interpretations must be communicated effectively to the intended audience. This requires some combination of skill in storytelling, data visualization, and, of course, understanding both the significance of the work and the biases of the audiences. In some cases, the proper mix of courage and tact are also needed. A provider of data analysis services may be able to manage any or all steps of this process for you, and they may be able to advise you on steps in which they are not directly involved.

Question 4

Can unstructured data be analyzed in market research?

Accepted Answer

A recent GRIT report shows that 40% of insights suppliers offer research and analysis based on unstructured data, such as text, social media posts, images, audio, and other data that is not organized in a pre-determined way. Further, nearly 30% offer platforms and tools to aid in the collection or analysis of such data. In another recent GRIT report, more than half of insights buyers said that automated social media analysis either plays or will play a key role for them in the future, including about one-third who said it already plays a key role. Nearly half said automated text analysis plays or will play a key role for them, and one-third said the same for automated analysis of image and video data. Unstructured data can and is being applied to market research and is available as a service or as technology.

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