5 Ways to Use Data Science for Social Media Marketing

  • Date: 30 October 2020
  • reading time: 3 Minutes
  • Blogger: Jolene Rutherford


 


social media

 

We live in a world driven by social media, which for business leaders means that investing in social media is paramount to success. Now, you might think that social media marketing requires nothing more than publishing a few posts a month, but doing that won’t get you very far. This is because social media marketing is a complex process and a big financial investment for those who want to capitalize on it.

What’s more, there are always new and upcoming social media trends that you need to follow in order to stay ahead of the game. This means more money poured into SM marketing, and dedicating more time and resources to social media management.

Needless to say, with so many networks accommodating billions of users around the world, SM marketing is becoming more complex every day. To make it worth your while in 2020 and beyond, you need to use data science to your advantage.

Today, we’ll be talking about why data science matters for social media marketing and how you can apply it to take your company forward. Here’s what you need to know.

1. Using data science for social media listening

The social media world is teeming with useful information, and brewing with hot topics that may or may not concern you. With so much information flowing around daily, it can be extremely difficult to discern between the data you should and should not care about. Mind you, the valuable data could take your sales, marketing, and branding to the next level.

This is why you need to invest in social media listening. This is the not-so-simple act of monitoring SM activity to find out what your audiences are talking about. Without the use of data science and its tools, global social media listening is next to impossible. After all, nowadays it is estimated that 1.7MB of data is created every second for every person on earth.

With the use of social media listening platforms and tools and the contribution of data scientists, collecting and collating this data can be worth your while. Keep in mind that it’s not just about gathering the data, it’s also about making sense of it all and applying it towards the right marketing strategies.

 

2. Learning about customers’ likes and dislikes

One of the biggest challenges of social media marketing is appealing to as many followers as possible while attracting a broader worldwide audience. Needless to say, you can’t please everyone, but that doesn’t mean that you shouldn’t strive to affect as many people as possible. To do this, you need to find out about the unique likes and dislikes of your audience, followers, and customers.

This allows you to segment your social media audiences and personalize your approach to engage more people than ever before. What’s more, you can do this while better managing your marketing expenses and social media budget. Before the use of data science and big data analytics, you would need to send out extensive surveys and run focus groups to gain these valuable insights.

Data science allows you to gather important information about your social media audience without actually engaging them in conversation. Most importantly, this avoids the problems of low response rates that lead to subpar survey results and incomplete data pools that you can’t use. 

3. Contextualizing data for effective word clouds

The context in which people are talking about your brand is equally, if not more important than gathering volumes of data. Your data scientists need to make sense of the information and define the right contexts in which it was used in order to generate relevant and complete insights. This is one of the best ways to build a strong brand in the social media realm.

Contextualizing vast amounts of data through social listening and other methods requires you to find a comprehensive data scientist course for your marketers, IT crew or data analysts that includes advanced techniques in data sourcing, management, and contextualization. Contextualizing data allows you to, among other, generate better word clouds for your SM strategy, and tackle the challenges with the highest ROI potential.

4. Researching customer personas to build better SM strategies

Building a better overarching social media strategy requires rigorous and extensive research. This, of course, is not a one-time thing. Rather, social media research is an ongoing process that helps you learn about your online audience over time to keep updating and improving your SM strategies. 

One of the most important things to keep in mind about SM marketing is that it only works if you know whom you’re speaking to. In other words, you can’t just post stuff without addressing the person and their unique problems. 

To create the most detailed customer and audience personas, you need to monitor the relevant topics and the conversations surrounding them. You will achieve this using data science, after which you can put the information into context by creating listening dashboards where you will group customer types and use a data-driven approach to create comprehensive customer personas. This will allow you to build truly detailed and hyper-targeted social media strategies that convey the right messages, reach the right people, and evoke the right emotions.

5. Using data science to boost influencer marketing

Influencer marketing is a growing industry, one that dominates the digital marketing world. In 2020 and beyond, it is expected that 65% of influencer marketing budgets will increase dramatically, meaning that companies are spending more than ever before on this lucrative marketing channel.

The reasons behind it are numerous, but the conclusion is the same – the more influencers promote your brand, the bigger your brand awareness, visibility, and trust will be. There is no denying that you should invest in influencer marketing as well, but you should preferably do it without breaking the bank.

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This is why using data science to gather data on influencers can be an invaluable part of your strategy. You can use data science to identify the ideal audience for your brand and cross-refence that data with complementary influencers in the field. The data scientists can further narrow down the search for the perfect influencer by comparing the results with the business model, overall effectiveness, and personality traits of SM influencers across multiple networks.

Wrapping up

Data science has a valuable role to play in modern social media marketing. Be sure to use it to your advantage and skyrocket your success on social media in 2020 and beyond.

  • Blogger: Jolene Rutherford
  • Marketing Specialist - turned blogger at Technivorz
  • Jolene Rutherford is a marketing specialist - turned blogger, currently writing for technivorz.com. Interested in digital marketing and new technology trends. Love sharing content that can help and mean to people
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