Big Data
Yes, “Big Data” is the catchphrase of the day in many industry sectors. In market research it has been around for some time, but the increasing use of data with better and faster software and growing levels of expertise has never been higher. Looking at Big Data is a scientific way to get customer insights. There may be answers to your marketing questions already sitting in your database—why not pull them out?
Nova Insights has been providing analytic services to firms with large or live databases to help them understand behaviors of the people their records represent.
If you have a database of customers or members that includes some basic information on each record along with their behavior as it relates to your organization, you may have the opportunity to better understand the variables that influence behavior, and perhaps develop a segmentation scheme for more meaningful communications and offerings that will resonate more effectively.
Analyzing your Big Data can be very valuable, but it should not be seen as a substitute for primary research that can create a depth of understanding only gained through attitudinal and psychographic measurements. Before we embark on a Big Data project, we communicate clearly what can be expected from the dataset and what is beyond the scope.
We always keep in mind that behind every record is a human, and we make emotional decisions. As the Harvard Business Review notes, "Human behavior is nuanced and complex, and no matter how robust it is, data can provide only part of the story. Desire and motivation are influenced by psychological, social, and cultural factors that require context and conversation in order to decode. Data...reveals what people do, but not why they do it."
To maximize value from Big Data, there are two key considerations:
1. Sources of data
Many organizations struggle to get data about their customers. We need to know the quality and depth of the data as well as the ability to have it exported for analysis. We can also help with the cleaning and integration of databases as is necessary.
2. Insights
To generate insights from large amounts of data we must have the right questions. It is important we meet with the client to discuss the objectives of the analysis--What questions need to be answered? What hypotheses should we test?
Analyzing the data you already have is often a good first step to understanding your customers or members. It may also raise more questions that can be answered through further exploration using primary research methods.