We're drowning in data. We generate it from our own activity or research; we collect and capture tons more from external sources. And, by now, all of us have been exposed to the conversation about Big Data—the voluminous unstructured data that is collected from nontraditional sources such as blogs, social media, email, sensors, photographs, video footage, and so on.
As the number of channels and customer touches expand, so does the amount of data coming from them. Every day, there are more than a billion posts and 3.2 billion likes and comments on Facebook, and 175 million tweets on Twitter. According to Stephanie Miller, VP of member relations at the Direct Marketing Association, "data is big, getting bigger, and more complex (and expensive) to manage."
Data vs. Insight
In today's data-rich and data-driven environment, we are predisposed to gain our insights from data. But action doesn't always follow collection. A survey of 600 executives by the Economist Intelligence Unit found that 85% of the participants thought the biggest hurdle to unlocking value from data was not grappling with the sheer volume, but analyzing and acting on it. And gleaning the insights from the data is what makes the data valuable.
Merriam-Webster defines insight as the power or act of seeing. Keyword: Seeing. We must use the data to identify and see—to see patterns, trends, and anomalies. And once we gain this insight, its value is proven by the actions we take as result. Data that doesn't help you see isn't useful. So, in this instance, more does not always translate into better insights. In fact, according to the recently released 5th annual Digital IQ Survey, consulting firm Pricewaterhouse Coopers (PwC) found that 58% of respondents agree that moving from data to insight is a major challenge.
In 1990, Stephen Tuthill at 3M helped make the connection between data and wisdom. His The Data Hierarchy outlines four important concepts: data, information, knowledge, and wisdom, with data being the raw items or events. Once we have the data, we can sort and organize it into information. Knowledge is then derived from the patterns that result from understanding the relationships between the data and other factors. Wisdom comes when we understand what to pay attention to—what has meaning for us.
So, rather than focusing on more data, we need to focus on capturing the right data and then analyzing it in a way that gives us the power to see (knowledge) and act (wisdom). Bernard Marr from UK-based Advanced Performance Institute reminds us that to get the most out our data "you need to know what you want to know." Once you know what you want to know, collect and organize the data.
Getting From Data to Insight
- Having the data is one thing, analyzing and synthesizing it is another. Synthesis is where we begin to see the patterns. Once the synthesis is completed, you will need a way to bring the data to life. Data visualization greatly aids in this part of the process. Data visualization presents analytical results visually so we can more easily see what's relevant among all the variables, capture and communicate important patterns, and even support predictive models. Visualization is an important step for exposing trends and patterns that you might not have otherwise noticed.
- Not all patterns are germane. Take the time to review and discuss each pattern and its potential implications. Talk about why you think each pattern is important and what it means. This is an essential step for going from information to knowledge.
- In one simple statement, articulate the insight that emerged out of each pattern or point of synthesis. We find it is helpful to capture insight on a Post-it Note and place it on a wall or flip chart to easily track each insight and see the "big picture" that may be emerging as we go.
- Incubate the insights. Give yourself and your team at least a day away from the "board." When you and the team return you can take a fresh look and decide whether to make any changes.
- Do the insights resonate? Once you are comfortable with the conclusions/insights you've captured, involve other people who were part of the initial steps to gain their reactions. Be sure to give them the context. The point of this step is to decide if the insights resonate and are compelling enough to make or affect key decisions. That is, to determine whether you have acquired the wisdom you need to act.
The success of this approach is contingent on the quality (not necessarily the quantity) of the data set, then following a process proven to identify core insights to support strategic decisions.
Continue reading "More Data Does Not Equal Better Insights" ... Read the full article
MarketingProfs provides thousands of marketing resources, entirely free!
Simply subscribe to our newsletter and get instant access to how-to articles, guides, webinars and more for nada, nothing, zip, zilch, on the house...delivered right to your inbox! MarketingProfs is the largest marketing community in the world, and we are here to help you be a better marketer.
Sign in with your preferred account, below.
You may like these other MarketingProfs resources related to Metrics & ROI.
So much of marketing is data-driven. But what makes data high-quality, and what are the advantages of vetting the data you use? This article covers the basics.
Industry events were famously difficult to measure ROI for... until they went virtual. Now, marketers can use the lessons learned from those virtual events to improve ROI measurement on hybrid and in-person events as well as digital ones.
Marketers are collectively sighing in relief at having two more years before the death of third-party cookies takes effect. So what should they do with that time? Prepare to fully use first-party data.
Tracking email KPIs goes far beyond simply monitoring your open rates. This article outlines other important metrics to use, and how to track them.
Marketers love metrics, but they don't always track the ones that bring the most value to their company. Here are three examples of metrics that should be retired, and three that should replace them.
Rajkumar Venkatesan, co-author of "The AI Marketing Canvas: A Five-Stage Road Map to Implementing Artificial Intelligence in Marketing," gives us a sneak peek at the road map and offers insight into how marketers can get started using AI.