Social media is one of the most widespread technological advances to occur in the last ten years. For business, social media has been one of the great levelers, allowing small companies to go toe-to-toe with massive corporations. Even for users, social media interests have allowed them to find products they’re interested in much easier. PWC notes that 37%of consumers use social media to gain inspiration for a purchase. Businesses can learn a lot from the collected data of their consumers if they know where to look and what they’re looking for.
Predictive Metrics Algorithms
To determine how well a particular social media marketing post does, one can rely on the analytics relating to that specific network. Emarsys mentions that as much as 42% of the world uses social media, which works out to over three billion users in all. There are a handful of metrics that a company can track through collected data to determine whether a social media post will get the engagement they want.
Timing and Audience
Social media marketing depends heavily on timing to succeed. For example, Sprout Social states that the best time to use Facebook as a company is during the week between 10 AM and 3 PM, while the worst time to engage on Facebook would be Sunday evenings. While this is true for the general population, specific demographics have different active times. Tapping into Big Data to provide information about a specific demographic can help the business tailor their posts to meet the desired audience.
Competition and Using Slow Hours to the Company’s Advantage
While the activity for a particular demographic may be lower during certain times, there is another critical factor that a business should consider. The engagement that a competitor gets when they are online will fall to the company if their competitor isn’t utilizing their social media efficiently. If a demographic that is concerned with a particular type of product tends to have a lot of posts at a specific time, then all other times when the competition isn’t posting is ripe for a business to put their products in front of the smaller audience. The lowered level of competition is perfect for smaller brands trying to compete against larger corporations.
Analysis of Market Trends using Data
Insights are the bread and butter of Big Data analysis. By taking Big Data as a whole and running it through algorithms to strip useless data from the pool, a data scientist can potentially provide insights that help a company operate more efficiently. However, Big Data serves another purpose in the realm of social media marketing. By using algorithms, a business could utilize the data collected from its social media channels to raise engagement on those channels.
Marketing Reports are Important Glances
A marketing report takes information that a business already has and puts it into a visual format making it easier to digest. By comparing social media analysis from the industry leaders, a company, such as Smith’s Tree Removal, can pattern itself to do some of the same things those at the top of the chain have done. Additionally, the business can streamline its approach based on its own marketing numbers and the preferences of its existing customers.
Competitor Data Aids Decision-Making
As explored before, the times a competitor is less active on social media are the best times to cut into their market dominance. Competitor data is vital in determining the metrics that competitors are using to promote the growth and expansion of their own business. It also allows the company to visualize where their weak points are to target them in the company’s own marketing strategies better. Smart Data Collective mentions that Big Data is instrumental in helping businesses conduct comparative analyses on social media.
Customer Feedback Through Interaction
Everything a person posts on social media forms part of their data set. Users are continually flicking through social media, either browsing or researching products and their reviews online. Global Web Index mentions that each person spends an average of 2 hours and 22 minutes on social media during the day. Never before have businesses been able to get in contact with their consumers so quickly. But to fully benefit from the technology, a company needs to pay attention.
Product Testing Through Social Media Responses
Market research forms a significant part of a company’s attempt to develop a new product. The same can be done for marketing content. By engaging with social media and using the feedback as a basis for rolling out new advertising, a company can potentially avoid any hassles in advertising that could lead to a social media debacle. Additionally, the business can use A/B testing with different ads promoting the same product or service. The ad that has the best engagement would be the one that gets the nod.
Finding Issues in the Business
One of the less highlighted but critically important aspects of utilizing Big Data Analytics is the ability to use that data to find inefficiencies in the business’s marketing plan. The goal of a marketing plan should be to get the most engagement while spending the least amount of money. Big Data offers insights that allow the business to target its core demographic and interested users better. The result is that more users opt to but from the company. Analytics can help to locate where a business is wasting its marketing budget and help it tighten up those loose areas and conserve marketing funds for more impactful campaigns.
Growing a Business Using Analytics
Data analytics drive business successes around the globe. Even before computers and the internet existed, statisticians and marketers would spend hours, even days poring over rolls of numbers and trying to make sense of them. The adoption of computers has made that task a lot simpler. Today’s analytics systems utilize predictive analytics and machine learning to help the system produce more relevant results. Because of the increased power of computers today, coupled with the use of cloud data processing and storage, even smaller businesses can benefit from the growth potential offered by Big Data analysis.