Showing posts with label Data Analysis. Show all posts
Showing posts with label Data Analysis. Show all posts

Thursday, June 5, 2025

YOUR Social Media Brand Engagement Data Science?


Too many organizations maintain a Facebook page, at times without much thought about strategy..

Small business and non-profit social media managers typically squeeze in posts around many other job duties. Still, I think much can be learned from those developing the art and science of social business goals, objectives and tactics.



Brian Massey, founder and managing partner at Conversion Sciences, focuses on business website performance data analysis. “The Conversion Scientist” (complete with his lab coat seen in my recent interview and during an eMetrics Summit presentation last summer) explores the marketing funnel – from lead generation through the optimization of the conversion process.




“Quality leads,” he says, allow marketers to “use a combination of user testing and A/B testing to prioritize and refine those ideas.” Improvement is defined as those tweaks that increase business revenue. It involves a constant process of innovation to respond to market changes driven by social media and other forces.

As I have noted in earlier blog posts, mobile smartphones are a location-based sensor constantly measuring contextual consumer behavior. From inexpensive content testing panels to big data pools, entrepreneurs are developing new tools to help marketers.

We’re talking about someone who understands how to evaluate data, how to collect data, how to make decisions based on the data they’re collecting, and integrate that into their design process.

Facebook target advertising offers social marketers access to millions of potential customers based upon demographic and psychographic filters. For businesses, that translates into qualified prospects. For non-profit and local government organizations, targeting is an efficient way to reach interested citizens, raise issue awareness, and spark new community engagement.



Success on Facebook, though, requires advertising experiments and effective “landing experiences” on websites, Massey says. Instead of “spray and pray” blasts, “marketers have to embrace this experimentation culture.”

You may not be ready to wear a lab coat, but Massey makes a good point about Facebook targeting as, “interrupt advertising, as opposed to search, which is intent-driven based on the keywords that are entered.” A strategic campaign integrates words, site design and images, brand management and data. In short, we need to embrace granular, contextual data.

The beauty of testing is that it allows a creative team to respond to data by developing bolder campaigns, Massey says. “We can take those risks because we’re doing it with user testing and small experiments.”

A recent ObservePoint 2017 Analytics Summit made this clear. James McCormick, Forrester Research principal analyst, emphasized that strategic metrics should be coordinated through standards and best practices. Optimization of key performance indicators (KPIs), are grounded in digital intelligence platforms. Understanding “digital touch-points,” he has written, should lead to “optimizing and perfecting experiences delivered and decisions made by brands during moments of engagement.”


Meanwhile, Massey focuses on site personalized visitor touch-points that locate someone at a place within the marketing funnel. It makes a difference, if a person seeks information, brand engagement, or price discounts. Artificial intelligence (AI) and the use of chat-bots work better for some functions than others. Massey asks, “What is the experience once they click?”

"These devices can be used to manipulate rather than persuade. We want to persuade, not manipulate. So, the more people we have that take on experience experimentation culture, the more diversity we have. I think it will ensure that we have a higher ethical bar of people who are using this data."

Massey says the data trend should not “scare you away from getting excited about the creative part of the job.” Social media marketers will need AI training to do the job five years from now, he adds.

Consider an email subject line. Data scientists can help marketers improve results. “I’ve got to sit down and use it on a daily basis to answer questions.”



For now, email and Facebook continue to be the primary way to reach people. “Instagram is probably the next frontier,” Massey says. Likewise, Pinterest can be effective. Increasingly, Facebook and YouTube video also are in the mix.

To some extent, the traditional marketing approach distinguishes use of social media from effective Instagram and Snapchat brand influencer campaigns. These sites, along with Twitter, started behind Facebook in offering targeted marketing data. Massey also is keeping an eye on Amazon and its integration of products and user data. “Every campaign is an experiment,” he says. “If we can embrace that experimentation culture, we have the tools, we have the data. We just have to sit down and ask questions that we can answer with data.”

Guest Authored By Dr. Jeremy Harris Lipschulz. Jeremy is a professor in the UNO Social Media Lab, School of Communication, University of Nebraska at Omaha. He is author of Social Media Communication: Concepts, Practices, Data, Law and Ethics, second edition (2018, 2015). Dr. Lipschultz has published books and scholarly articles on media, law, new communication technologies, social media and education. He has been a frequent media source for outlets, such as WGN, NPR, the Chicago Tribune, the Los Angeles Times, the Omaha World-Herald, KFAB, and others. Follow Professor Jeremy on X.




For now, Instagram, email and Facebook continue to be the primary way to reach people. “Instagram is probably the next frontier.

Likewise, Pinterest can be effective. Increasingly, Facebook and YouTube video also are in the mix.."

    • Authored by:
      Fred Hansen Pied Piper of Social Media Marketing at YourWorldBrand.com & CEO of Millennium 7 Publishing Co. in Scottsdale, AZ. I work deep in the trenches of social media strategy, community management and trends.  My interests include; online business educator, social media marketing, new marketing technology, skiing, hunting, fishing and The Rolling Stones..-Not necessarily in that order ;)

    Friday, April 6, 2018

    Understanding YOUR Social Media Analytics?


    Social Media Analytics

    Social media analytics is the practice of gathering data from social media websites and analyzing that data using social media analytics tools to make business decisions.



    The most common use of social media analytics is to mine customer sentiment to support marketing and customer service activities.

    The first step in a social media intelligence initiative is to determine which business goals the data that is gathered and analyzed will benefit. Typical objectives include increasing revenues, reducing customer service costs, getting feedback on products and services, and improving public opinion of a particular product or business division.

    Once the business goals have been identified, businesses should define key performance indicators (KPIs) to objectively evaluate the business analytics data.



    Metrics To Track

    Business metrics derived from social media analytics may include customer engagement, which could be measured by the number of followers for a Twitter account and number of retweets and mentions of a company's name. With social media monitoring, businesses can also look at how many people follow their presence on Facebook and the number of times people interact with their social profile by sharing or liking their posts.

    More advanced types of social media analysis involve sentiment analytics. This practice involves sophisticated natural-language-processing machine learning algorithms parsing the text in a person's social media post about a company to understand the meaning behind that person's statement. These algorithms can create a quantified score of the public's feelings toward a company based on social media interactions and give reports to management on how well the company interacts with customers.



    Popular Tools

    There are a number of types of social media analytics tools for analyzing unstructured data found in tweets and Facebook posts. In addition to text analysis, many enterprise-level social media analytics tools will harvest and store the data.

    Some of these tools come from niche players, while more traditional enterprise analytics software vendors offer packages dedicated to social media intelligence.

    As more social media analytics rely on machine learning, popular open platforms like R, Python and TensorFlow serve as social media analytics tools.



    Importance of Social Media Analytics

    There is a tremendous amount of information in social media data. In decades past, enterprises paid market research companies to poll consumers and conduct focus groups to get the kind of information that consumers now willingly post to public social media platforms.

    The problem is this information is in the form of free text and natural language, the kind of unstructured data that analytics algorithms have traditionally. But as machine learning and artificial intelligence have advanced, it's become easier for businesses to quantify in a scalable way the information in social media posts.

    This allows enterprises to extract information about how the public perceives their brand, what kind of products consumers like and dislike and generally where markets are going. Social media analytics makes it possible for businesses to quantify all this without using less reliable polling and focus groups.



    Guest Authored By Margaret Rouse. Margaret Rouse writes for and manages WhatIs.com, TechTarget’s IT encyclopedia and learning center. She is responsible for building content that helps IT professionals learn to speak each other’s highly specialized languages.

    WhatIs.com has won many awards over the years and has been cited as an authority in major publications such as the New York Times, Time Magazine, USA Today, The Washington Times, the Miami Herald, ZDNet, PC Magazine and Discovery Magazine. Before joining TechTarget in 2000 when they acquired WhatIs.com, Margaret worked for New York State Model Schools, teaching computer science and technology integration. Follow Margaret Rouse on Twitter.





    "There is a tremendous amount of information in social media data.

    In decades past, enterprises paid market research companies to poll consumers and conduct focus groups to get the kind of information that consumers now willingly post to public social media platforms.." -MargaretRouse


      • Post Crafted By:
        Fred Hansen Pied Piper of Social Media Marketing at YourWorldBrand.com & CEO of Millennium 7 Publishing Co. in Loveland, Colorado. I work deep in the trenches of social media strategy, community management and trends.  My interests include; online business educator, social media marketing, new marketing technology, skiing, hunting, fishing and The Rolling Stones..-Not necessarily in that order ;)