The value of data is now commonly recognized, but many businesses still struggle to understand and leverage this information. Additionally, small data is often neglected or misunderstood, despite its potential to improve businesses. When PR professionals have access to and understanding of data, they can improve how they communicate internally and with their audiences.
This month’s collection of articles, including stories about brick-and-mortar retailers’ work with startups to track customer behavior and satisfaction, journalists working together to make data more accessible, and Netflix’s use of data to deliver better content to its users, provide examples of real-world applications of data.
These articles will help you better understand how to mine the universe of data and apply this information to make informed decisions for your brand.
The European Data Journalism Network received funding from a grant to produce data-driven news stories that are then translated into multiple languages and made freely available to partner and non-partner news organizations. The collaboration between news organizations across Europe and the data-driven stories give citizens access to meaningful reporting and allows them to compare information. The project organizers state that, “We saw the project as an opportunity to improve our capacity to cover journalism on European affairs in a meaningful way…It’s also a way to take advantage of all this open data…and maybe contribute to the development of a culture of public debate based on facts and data.”
Poynter has pulled together a database that organizes research done on fact-checking. The database does not aim to be comprehensive, instead it highlights studies that are most useful to journalists. With brief summaries underneath each of the curated academic studies, Poynter has made it much easier for practitioners to quickly get to studies relevant to reporting, rather than spending time searching through mountains of data that aren’t on-point.
Communications, Creativity, and Data
Despite fears that the creation of shows from Silicon Valley giants like Netflix and Amazon would be dictated by analysts rather than artistic minds, data is actually improving the delivery of creative material, and, “perhaps big data is fostering a new golden age of creativity.” Harvard Business Review explains that digital platforms collect mountains of data about their customers and explores how these companies use this data to deliver the content their users want.
A long article in Reason Magazine about the use of Big Data and predictive analytics as a means to protect abused children highlights both the problems and promise of using data for intervention purposes. Buried deep in the article was an interesting observation: Allegheny County in Pennsylvania is recognized as having a solid program of implementing predictive analytics for child protective services. One of the reasons attributed to their success is that the Department of Human Services has built “a high degree of trust” within the county, working closely with stakeholders on implementation. The combination of solid communications outreach work and the use of data established the foundation for a successful program.
Analytics and communications go hand-in-hand, according to a recent profile piece in Silicon Republic of Marie Taylor-Ghent, EY’s data analytics director. Taylor-Ghent cites her need to work with team members, key stakeholders, and clients as the reason why communications skills are a necessity, even in a data-heavy analytical field.
Data Brings About Better Business
Data about consumer interactions allows businesses to measure and make informed decisions to improve customer satisfaction. A Finnish startup, HappyOrNot, is simplifying the process of collecting this data. Their terminals, which have been installed in airports, gas stations, and retail stores worldwide, ask customers to rate their experience by pressing one of four buttons, which represent very happy, pretty happy, pretty unhappy, and very unhappy. The New Yorker details how HappyOrNot’s clients use the data to adjust their business decisions and improve their customers’ experience.
Modern businesses, whether B2B or B2C, must collect and leverage data to prove the effectiveness of their strategies and track success. Until recently, brick-and-mortar stores struggled to gather this information, while digital retailers could easily track online behavior and purchases, allowing them to customize and improve individual shopping experiences. Now, companies are introducing innovative ways for physical stores to gain insight about their customers’ habits. In particular, a start-up has introduced floor sensors that will allow stores to track and learn from their customer’s movements.
Once people get their minds around what Big Data is, the next question is: how does one use this information to improve or inform business processes? Keeping in mind that professional sports is a business, Dataconomy takes a look at how data is revolutionizing sports. As the piece points out, professional baseball was one of the first businesses to really zero in on how to use data to improve team outcomes and make trading decisions based on information, not intuition.
Many organizations are eager to capture and leverage big data sets, especially as part of machine learning and AI jobs, but professionals must have a solid understanding of small data before analyzing and integrating big data. insideBIGDATA defines small data and explains why these sets could be more advantageous to businesses.
The Conversation takes a look at how Big Data could improve our work lives—or make the workplace unbearable. In the plus column are companies that would use information to improve workplace systems, particularly to address employee health, wellness, and safety issues. In the minus column are companies that would use such information to modify the behavior of employees. The bottom line is that data collection in and of itself is fairly agnostic. It is how data will be used that presents the potential for impact on employee morale.
As AI continues to rise to prominence, businesses are beginning to look at how they can use this technology to extract value from data. VentureBeat explores three organizational changes needed to usher in this development, as well as examples of how different industries are already working to implement these changes to improve their businesses.
Collecting data isn’t much use unless you are analyzing it and asking the right questions to implement change. That type of analysis can be costly, and if you’re a smaller or mid-sized municipality that relies on taxpayer funding, sometimes the idea of spending more money to eventually improve services and efficiency doesn’t always fly. The Bloomberg Philanthropies What Works Cities Program provides some of those upfront resources, and facilitates information sharing between similarly situated cities. Collecting information and pooling data resources is allowing cities to solve previously intractable problems.
Ethical Data Usage
Data is an excellent business tool for creating better customer experiences, but companies across a variety of industries now collect more information on their customers than ever before. As businesses gather and store more personal information about their customers, CMSWire explores the ethics of data collection and outlines the three discussions marketers should have to “define the balance of power between businesses and the people they hope to serve.”
When is Big Data risky? When it delivers insight that is supposed to be secret. The recent news of how personal fitness trackers used by U.S. military and intelligence personnel revealed patterns of activity and secret base locations illustrates this risk very clearly. Typically, the larger the data set the more anonymized the information becomes—tracking a large number of automobile commutes on highways can show us where traffic slowdowns are, but doesn’t reveal much in the way of sensitive information. Not so in this case, as Wired reports one researcher claims that he was able to peer into Strava’s public data, zero in on a specific individual, and track that individual on a route.
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