How Big Data Analytics is Driving the Future of Social Business Success
What social business is and how big data analytics help those companies achieve their goals.
While a lot of people like to stick to the 3 V criteria to clarify whether they’re working with “big data”, I really like the idea of categorizing a big data project as one that necessitates big data technologies for project success. Whichever definition you prefer; You can be certain of one thing — that social data is big data. That’s because:
- Social media networks necessitate, and are fundamentally built on top of big data technologies like Hadoop. In fact, Apache’s Powered By Hadoop page sites listings documenting that LinkedIn’s Hadoop cluster has 4,100 nodes and Facebook’s contains 1,400 nodes.
- Social media networks produce data that is high volume, high-variety, and high-velocity. In other words, they generate big data.
Big data technologies belie social media networks and social media networks produce big (social) data. The true marvel of big (social) data, however, is in how and where that data is being used to rewrite the entire paradigm of success for business marketing. In today’s article, we’re going to explore how big data analytics is driving the future of business success on social.
Big Data and Social Listening for Business
In moments of supreme thrill or frustration at an exchange you’ve had with a retailer, have you ever tweeted at them to let your thoughts be known? Surely you’ve at least written a positive review on the Facebook page of some of your favorite companies. Taken incrementally, these small acts produce only a tiny data record that either signals problems needing attention or encourages others to try a good service or product for themselves. While these outcomes are significant and important, at first appearance few people could comprehend how these small transactions, taken en masse, are revolutionizing the way business is done.
You see, today’s tech-savvy businesses are “listening” and responding to what’s being publicly said about them and their competitors on social media networks. Listening, not in the traditional sense, but rather they’re listening in a social sense; They are collecting, aggregating, analyzing, and making data-driven decisions based on the who’s, what’s when’s, where’s, and why’s they gleamed from big (social) data.
What are they listening for? Although some businesses are just looking to make sure that customer satisfaction rates stay high, smarter businesses are looking for data on signals that help them understand and convert their prospective customers.
7 Smart Metrics to Monitor for Today’s Social Business
For businesses that want to use social media as a vehicle for increasing acquisition and revenue-generating conversions, there are at least eight metrics that they need to be using social data to track and monitor. First and foremost, such businesses need to develop a solid, and well-supported picture of their buyer personas. They also need to generate a clear picture of what’s converting well on each of the various social networks. Lastly, they need to be aware of what’s trending on these social networks and how that relates to the products or services they’re marketing.
- Individual Role – This metric helps establish your buyer persona. You can gauge a lot about a person, and their purchasing prospects, by knowing the name of the company where they work, their role there, and the company size.
- Company Size – This metric helps establish your buyer persona.
- Individual Location – Location is a buyer persona metric that you can use to time your campaigns or customize your marketing messages for higher conversions.
- Content Engagement Stats by Topic Area – Another buyer personas statistic, tracking the topics to which a person most frequently engages will allow you to custom-tailor content and content placement for better conversions among the buyer persona segment to which a user belongs.
- Purchase Behavior – One last buyer persona metric is purchase behavior. Some buyer personas belong to the “audience persona” group, meaning they engage often but seldom make a purchase. Identifying this characteristic helps you optimize marketing by signaling you to divert your efforts to people with higher converting personas.
- Conversion Rates per Social Network – Not all social networks are the same. In each network, certain content types perform far better than others. To see whether your offerings or verticals perform well on a particular social network, you can track and monitor how often your competitors are being mentioned there.
- Trending Product Features and Customer Needs – Mine social data from various networks to get an idea of what features or customer needs are trending. Then, to bolster conversions, be sure to demonstrate this understanding of the customer by addressing those features or concerns in your social promotion efforts.
Deciding Whether to Analyze Social Data Manually Or Via Paid Software Applications
If you have a data scientist on staff, you can have him or her develop highly-refined and customized algorithms to support your organization’s social listening and selling goals. Although it takes more time to develop these custom algorithms, it may be the only way for smaller businesses to get around the budget limitations involved with purchasing subscriptions to proprietary social selling software. An added benefit is that, by developing custom algorithms you can generate insights specifically from social data that’s directly related to your business (and not on insights that are based mostly on what’s happening with competitors in your same industry).
The other alternative for big (social) data analytics is to purchase a paid subscription to one of the many software applications available on the market. The benefit of these solutions is that you can be up-and-running in a matter of hours, and more staff members will be able to utilize and generate social selling insights when you take the custom algorithm development requirements out of the picture. Although some of these applications are proven to generate demonstrable results, they’re often more expensive than small- and medium-sized businesses can afford. Popular services for large businesses are Salesforce Social Studio, Adobe Marketing Cloud, and IBM’s Customer Analytics suite. In the alternative, Nimble, Salesforce Small Business Solutions, and InsightPool are known to provide cost-effective results for businesses that are working with a limited marketing budget.
Link:
https://dzone.com/articles/how-big-data-analytics-is-driving-the-future-of-bu
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