Social Media Insights: 10 Experts Share How to Leverage Your Social Data

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According to the Pew Research Center, the average American spends just over two hours each day on social media and uses an average of three social media platforms.

Every day, your customers are tweeting, engaging with video, and sharing their experiences over social media, creating valuable data for your brand. Data that can lead to a better customer experience, personalized content, and new products. However, data on its own can’t drive those decisions. What you really need is actionable social media insights.

How can you generate those insights?

The experts listed below have a few ideas. For advice on how you can turn your social data into actionable insights that drive greater business value, we compiled the top insights from today’s leading social data and analytics experts. See what they had to say down below.

Brian Solis

Principal Analyst, Altimeter Group


Brian Solis 1

Who is Brian Solis? Keynote speaker. Best-selling author. Principal analyst. Those are just a few of the titles that apply to Brian Solis. Brian’s main focus of research and expertise centers around disruptive technology and its impact on digital transformation and the customer experience.

“Customers are connected and mobile-first, and they’re in control of their journeys and experiences. The pace of change for consumers and technology has never been faster. Yet, brands are still chasing customer intent through traditional means. The good news is that because of digital, customer signals give away exactly how to better serve them in every moment throughout their journey. Furthermore, in an era of machine learning, marketers can finally shift from trying to keep up with customer intent and instead, predict it.”

The takeaway: Most brands are currently concerned with what customers want in the moment. However, the greatest opportunity lies in predicting what they’ll want in the future. To do this, brands need to take advantage of predictive analytics and machine learning in order to identify and adapt to trends in consumer behavior. For example, machine learning social data platforms can analyze past customer behavior over social in order to predict how they’ll react and behave in the future as well as what they will want.

Follow Brian on LinkedIn or Twitter.

Rebecca Lieb

Analyst & Founding Partner, Kaleido Insights


Rebecca Lieb

Who is Rebecca Lieb? Rebecca Leib is the founder of Kaleido Insights, a research firm that focuses on informing successful content marketing strategies. She’s served some of the world’s most recognized brands, including Facebook, Home Depot, Nestlé, Adobe, and countless others.

“The insights many platforms and lists offer amounts to tunnel vision: a narrow view across only a small cohort of specific channels or media rather than a 360-degree spectrum of behavior across not only digital experiences, but also offline stores and real-world actions.”

The takeaway: To truly understand your customers, prospects, and their behaviors, you can’t rely on social data alone. You need to combine your raw social data and analysis to include both online and offline experiences.

Follow Rebecca on LinkedIn or Twitter.

Mike Quindazzi

Managing Director, PricewaterhouseCoopers


Mike Quindazzi

Who is Mike Quindazzi? At PricewaterhouseCoopers, Mike Quindazzi is a visionary business development leader and management consultant. He is also a global keynote speaker who is well known for his thought leadership on digital transformation, artificial intelligence, blockchain technologies, and the customer experience.

“Well-managed data (from new and legacy sources) combined with AI is poised to drive product innovation, content creation and new engagement models that will define customer engagement disruptive to industries and profit margins in the future.”

The takeaway: Brands that combine artificial intelligence and machine learning with their social data have a greater ability to identify consumer patterns, market trends, and areas of risk. Through AI technology, brands are able to automatically take their wealth of social data and transform it into actionable social media insights that inform better business decisions.

Follow Mike on LinkedIn or Twitter.

Shelly Kramer

Principal Analyst & Founding Partner, Futurum Research


Shelly Kramer

Who is Shelly Kramer? In addition to being a successful entrepreneur and adept researcher, Shelly Kramer has been named by Forbes as one of the Top 50 Social Media Influencers. Beyond social media, she has also been named an influential expert in digital transformation, IoT, big data, and more.

“Before you start burying yourself in all that data, you have to complete one crucial step: Identify the question the data will answer. Knowing the why first will allow you to focus your data collection efforts so there’s less to sift through, and what is collected is more likely to be valuable.”

The takeaway: For data analysis to generate insights that are relevant and valuable, there needs to be a strategy and purpose behind the social data that brands collect. With clear objectives and goals, brands can be more specific in the types of data points they gather and how they choose to apply them to the overall business strategy.

Follow Shelly on LinkedIn or Twitter.

Marsha Collier

President, The Collier Company, Inc.


Marsha Collier

Who is Marsha Collier? Marsha Collier is an award-winning author offering best practices and strategies for superior online customer service and experiences. As President of The Collier Company, Inc. she consults with the world’s leading B2B and B2C brands on how they can improve their community building, customer service, and customer experience.

“By using customer data analysis, today’s in-store experience can be remarkably personal. When a customer goes to the register to pay for items; personalized suggestions for additional products can be at your team member’s fingertips.”

The takeaway: Analyzing customer social data can generate insights for both the digital and in-store customer experiences. If a customer engages with a branded tweet before coming into a physical store, that data can be used to create a more personalized shopping experience with tailored product recommendations or promotions.

Follow Marsha on LinkedIn or Twitter

Tamara McCleary



Tamara McCleary 1

Who is Tamara McCleary? If you follow social media, AI, or big data trends, you’ve likely already heard of Tamara McCleary. In fact, Klear ranks her in the Top 1% of Global Social Media Influencers. She’s also been named the No. 1 Most Influential Woman in MarTech by B2B Marketing.

“In order to create value-adding autonomous systems, we have to feed those systems with massive amounts of data about ourselves. So much information about us that they can begin to predict what we will want before we actually realize we want it. To say it a different way, we are creating artificially intelligent algorithms, (AI), to predict our needs, each and every one of us, before we realize what those needs are.”

The takeaway: AI-powered marketing is our future. However, if we want AI to produce automated, personalized, predictive campaigns and experiences, we first need to collect, store, and analyze massive amounts of customer social data.

Follow Tamara on LinkedIn or Twitter.

Kristin Luck

Growth Strategist, Luck Collective


Kristin Luck

Who is Kristin Luck? Kristin Luck is a successful entrepreneur and consultant with over 20 years of experience in developing nontraditional growth strategies for data-driven technology companies, CPG and direct-to-consumer brands, and market research firms.

“Whenever you’re working with disparate data sources it can be challenging to understand how to combine them in meaningful ways. This isn’t so much a data processing skill as it is a data architecture skill- something that researchers haven’t been traditionally trained to tackle.”

The takeaway: Regardless of how skilled your data analysts or consumer insights team is, collecting data in disparate sources creates confusion and makes it difficult to perform a valuable analysis. Brands need to make it easy for their team to draw meaningful conclusions from social data by centralizing their data sources into a single platform or tool (e.g. the Meltwater social media analytics tool).

Follow Kristin on LinkedIn or Twitter.

Rei Biermann

Senior Social Media & Community Manager, Amazon Web Services


Who is Rei Biermann? With over a decade of experience in digital media, marketing, and community management, Rei Biermann is an expert in using data insights to improve user engagement and brand sentiment over social media.

“There’s always an element of risk when taking an idea to market. To minimize that, conduct the right market research so you know you’ve got a large enough audience for your product.”

The takeaway: Social data and insights help brands create custom content, personalize user experiences, and engage customers at the right time and in the right place. However, one opportunity that isn’t as easily seen is in research and development. Before launching a new product or service offering, make sure you dig into your social data and perform market research to ensure your solution is solving a real pain point.

Follow Rei on LinkedIn or Twitter.

Annie Pettit

Market Research Trainer and Advisor, Annie Petit Consulting


Annie Pettit

Who is Annie Pettit? Annie Pettit is a leading market and social research methodologist helping brands leverage today’s digital landscape to drive differentiation. To date, she’s helped top research companies reach their potential and written countless white papers, case studies, and research reports.

“Social media monitoring isn’t the most useful things for clients. It’s just not enough to know when the mentions of a brand name increase or decrease. You need to know exactly why the change happened and how much it affected perceptions of the brand. And, this needs to happen in a way that is valid and reliable. This is what social media research provides.”

The takeaway: Social media is how many customers choose to communicate and interact with brands today, providing us with plenty of data and insights. However, it’s not enough to just monitor and measure your social interactions. There needs to be a scientific process behind your social data analysis, including sampling, weighting, and scaling in order for your findings to be valid and actionable.

Follow Annie on LinkedIn or Twitter.

Mike Delgado

Director of Social Media, Experian


Mike Delgado

Who is Mike Delgado? Podcasts. Live streaming. Community building. Social media. Mike Delgado, Director of Social Media for Experian, is a master in communications and digital media. In his spare time, Mike even teaches social media strategy at the University of California, Irvine.

“I think one of the difficulties when it comes to data and the art of data science is you don’t have the right data. You may have a ton of data, but if you’re not looking at the right data, or finding the right data, it’s not going to be providing you with much help.”

The takeaway: Having plenty of social data at your fingertips is great. But with so much to analyze, it’s easy for opportunities to get lost in the weeds. Before beginning an analysis, you need to make sure you’re asking the right questions of your social data and seeking the right answers.

Follow Mike on LinkedIn or Twitter.

A Method to the Madness

There is more social data today than ever before, creating a paradox of choice. With data overload, brands and marketers struggle to identify the data worth analyzing and to generate social media insights worth acting upon.

If you want to simplify your research and data analysis and produce more meaningful results, you need to collect, store, and analyze your social data with the advice above.

For more ways to turn your social data into actionable social media insights, check out our latest ebook:

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