Social media has become one of the most effective platforms for brands to reach their target audience. Over 22% of the global population is on Facebook. Among global Internet users, the figure is 79%. The proportion of the population on any social media platform is even higher.
The ROI of social media marketing can be very high. According to one MarketingSherpa study on social media marketing, brands receive $1.95 in revenue for every dollar they invest on social media. While this figure is very encouraging, there is a lot of variability and it is important to understand the multitude of factors that play a role.
Fortunately, big data has made it easier for brands to assess and forecast the ROI of their social media campaigns. Here are some ways that it is beneficial.
Matching social media networks with your target audience
There are over 350 popular social media websites across the Internet. Counting all known social media websites is challenging, because there are many sites that are specific to small countries and specific niches. Every site has its own unique demographic composition. This means that some sites may be more ideal for reaching your target audience than others.
Hadoop tools and user surveys enable marketers to understand the demographics of every social media website. This enables them to target websites that best align with their target audience.
Projecting potential revenue from individual demographic groups
It is not uncommon for brands to target a variety of demographic groups. There are two important factors that brands must take into consideration when estimating the revenue that they can generate from each group on a given social media network:
- The average revenue generated from an individual lead in a given demographic group. This figure is different for every industry. A clothing company may determine that the average female customer spends 2.5 times as much as a male customer.
- The number of customers in a different demographic on a particular social media website. Around 51% of Facebook users are females, while the remaining 49% of users are males. You would obviously have access to a slightly larger base of potential female customers and earn a little more money from them, provided the value of leads was the same for each gender. The difference on Pinterest would be much more significant.
Only 7% of all pins are placed by male users. Brands would be better off targeting Pinterest if they were focusing purely on female customers.
The demographics of social media websites are frequently changing. Big data makes it easier to keep track of the demographics and focus on the right platforms.
Choosing the Right Engagement Approach
There are different ways to engage with your audience on social media. You can consider using paid traffic or focus on organic reach. According to SocialStore, organic traffic may ideal for some marketing strategies.
Monitor engagement to identify campaign burnout
When you are advertising with search engine marketing, your campaigns can last for months or even years. You are constantly attracting a fresh new source of potential customers and only pay for ads that are clicked.
This is not the case with social media marketing. Your ads are going to burn out rather quickly. You may have a campaign with a 150% ROI that will be losing 30% in three weeks. You want to identify campaigns that are collapsing to protect your budget.
Big data makes it easier to track the performance of your campaigns and identify gradual changes in ROI. You can use predictive analytics tools with data from previous campaigns to know when to pause a campaign to avoid losses. Most social media platforms have automated controls that you allow you to set a date to pause your campaigns. If your predictive analytics tools predict that your average campaign burns out after six weeks, you can assign that as your end date.
Identifying the right target audience is only the first half of the equation. You also need to find advertising creatives that convert well.
There are a number of predictive analytics tools that can help you measure the ROI of your correct creatives and predict the performance of other creatives based on previous campaign data.
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