Integrate Your Social Media Marketing with Data Science

Over 50 million small businesses use Facebook to connect with customers, Twitter hosts 336 active accounts, while YouTube has 1.8 billion logged-in monthly active users. Social media dominates the space as a tool that has extensive reach and an enormous audience, most of who access their accounts on a personal device. Considering apps are the main source of user engagement on smartphones, social media is the perfect place to market your app.

Businesses recognize the potential engagement on these platforms and 34% of companies primarily focus their app marketing efforts on social media. Still, with so many users and businesses on social media, how do you best appeal to a target customer?

Data science allows businesses to analyze customer behavior and predict how consumers will act when certain images or words are presented in front of them.

Data science can provide important insights into your customer base through the analysis of engagement with your social media posts.

Implement these 3 tips to best implement data science into your social media strategy:

  • Use Cluster Analysis to Determine Your Customer Base

Social media provides a huge amount of customer information that can be overwhelming. Attempting to reach the best audience for your app can be daunting, especially when there does not seem to be an organized way to understand the data.

Cluster analysis allows you to make connections between different customers and filter the users who apply to your app and those who don’t. Specifically, Cluster analysis groups a set of users in the same group when they are similar to each other in some sense.

For example, say you created a gaming app, but are not sure what kind of people are interested in your game. You begin posting different content and incentives on your site and you see an increase in traffic.

Cluster analysis will group the visitors to these social media posts into certain categories so you can determine what potential app users are most interested in your game. If the analysis shows boys between the ages of 13 and 17 are clicking on your posts, then you should launch a social media campaign specifically tailored to that age group.

Cluster analysis can provide more concrete knowledge on who is interested in your app. By grouping strong interest parties and weak interest parties together, you can stop wasting time trying to appeal to everyone.

  • Create User Personas with Big Data

Data science can create in-depth explanations of who exactly is interacting with your social media. These detailed reports can assist your marketing efforts to more deeply relate to your consumer base. User personas are effective means of creating an detailed and insightful customer analysis.

A user persona is a fictional representation of your perfect customer based on behavioral patterns and research of your ideal audience. User personas can create a more comprehensive look into who uses your app.

A user persona should include:

  • Header
  • Demographic Profile
  • End Goal
  • Scenario

An example of a user persona template can be seen below for a gaming app:

https://www.interaction-design.org/literature/article/the-persona-template-for-gamification

The header should simply include the fictional customer’s name, image and quote. These features can be made up.

The demographic profile, however, needs to stem from real research. The profile would include your average customer’s personal background, professional background, user environment, and psychographics (interests, attitude, motivations, and pain points).

The end goal states why your ideal user is using your app and what they gain from their download.

Finally, the user persona should include a scenario that describes how a customer would interact with your app and when they decide to use it.

When creating a user persona from data acquired through social media, make sure you are asking the right questions and listening to industry conversations. You should follow trending topics and customer feedback within your site and those of your competitors. You can cross analyze who is using your app with users who choose other companies in the market.

Further, you need to track your customer’s conversations on your social media pages. For example, if your 13-year-old boy audience consistently references augmented reality or character customization, you can use these trends to feed your own app updates.

  • Visualize the Data

Finally, data science can provide a clearer presentation of user behavior than the mess of words and images seen on social media. The ability to carefully group and number customers enables you to create graphs and charts that tell a story. You should use a data science tool to generate an accurate presentation of your customer behavior.

Facebook created a big data map of the popularity of Facebook around the globe:

http://www.keywebmetrics.com/2013/07/big-data-visualizations/

The more intense the light on the map, the more popular Facebook usage is. As seen, the United States and Europe have the most Facebook usage.

The ability to transform numbers into a readable format allows you to experiment with more A/B testing and evaluate what social media campaigns were effective. You can see the different situations that made a user click a certain link or comment on a specific post.

Market Smart with Big Data

Businesses should integrate data analysis into their social media strategies to find the most marketing success for their apps. Big data provides the most accurate means of defining your target user and appealing to their interests.

Data analysis makes your marketing smarter, which saves time and increases productivity. By focusing your efforts on users who will respond to your app, you can decrease costs and increase the number of downloads.

Report

Written by Emily Clark

Emily is a writer for The Manifest, designing surveys and reporting about mobile app development companies, trends, and news.

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