We studied and analyzed more than 20,000 posts and comments, and 6,000,000 profiles of potential customers

For this research, we analyzed more than 20,000 posts and comments about AB InBev and its various brands published on the Vkontakte and Facebook social networks. Our analysis covered the period between January 1, 2016, and December 12, 2016.

About the company

AB InBev Efes is a leader in the Ukrainian brewing market and a joint venture of the world’s largest brewing company, Anheuser-Busch InBev, and Turkey’s largest brewery, Anadolu Efes. More than 180,000 people work for the company, and its products are sold in 100 countries.

The company is known for global beer products branded as Bud, Corona Extra, Stella Artois, Hoegaarden, Leffe, Beck’s, Lowenbrau, Franziskaner, Spaten, Staropramen, Taller, etc.

The goals of brand monitoring

As a part of a marketing strategy improvement initiative for AB InBev, Singularex was tasked with an analysis of social media profiles and posts in order to:

  • Discover the target audience structure and interests
  • Identify influential persons and groups
  • Build social graphs to examine user relationships
  • Find out what people associate the brands with
  • Analyze sentiments by regions and target groups over time
  • Discover new industry trends

Technologies and tools we used

Social Media intelligence tools, neural networks, clustering, social graphs, user behavior analysis, learning associations, and sentiment analysis.

Some insights from our AB InBev brand monitoring

Associations with the brand and its products

After studying thousands of references and analyzing word frequency correlations, we managed to detect a number of right/desirable and wrong/undesirable consumer associations regarding AB InBev’s brand positioning:

Most of the proper associations were connected with the brand’s story or some characteristic of the product (such as ascorbic taste, alcohol-free, etc.).

While studying wrong brand associations, we discovered a number of dependencies with private trader ads, sushi-bar promos and football games.

Sentiment analysis by region, over time

We analyzed brand and product references on social networks according by regions in Ukraine.

In the following graph, the more positive sentiments in posts are the more green; the region is scored according to our sentiment scale.

With the help of sentiment analysis over time, we could detect attitudinal changes toward the brand and the influence of promos and other events on these changes.

For example, the brand got lots of positive comments and posts after opening the bar “Lemo” or its promo at the “Падишах” club.

Sentiment analysis over time could be a great help in monitoring the results of marketing activities.

Opinion leaders and target groups detection

After analyzing brand mentions on Facebook, we identified 8 groups, 8 opinion leaders and 7 pages of the HORECA companies with the highest number of posts and comments where AB InBev or its products were mentioned.

The detection of groups, influencers and companies like this can be a powerful tool for brand promotion and partnership.

Relationships between post authors

In our user behavior analysis, we were trying to detect strong connections between users, identify opinion leaders and the number of friends they had and products they were talking about.

We detected that most of the activity on VK came from users in Kharkiv and was connected to AB InBev as an employer: the comments/posts consisted largely of employee feedback, recruitment posts, and information on university collaborations.

Target audience analysis

We analyzed 6 million profiles of potential customers on VKontakte and gained new insights into the company’s target audience in terms of their personal priorities, what inspires them, their most important things in life, and their views on alcohol and smoking.

Such graphs are useful for creating new company ads and promos and a better understanding of potential customers.

The top research insights

  • In two weeks of work and with a team of 2 data scientists, we managed to conduct brand monitoring on social networks for one of the largest brewing companies in Ukraine.
  • We studied and analyzed more than 20,000 posts and comments, and 6,000,000 profiles of potential customers.
  • In general, AB InBev company has strong and proper brand associations connected to its history and product characteristics. There are also some improper associations as a result of third-party promo activities or football events.
  • Our sentiment analysis by region and over time detected the territories with the most positive attitude toward the brand and identified dependencies between certain events and growth in the number of comments.
  • We detected thematic groups, influencers, and HORECA to support the company’s future marketing activities.
  • User behavior analysis helped us gain many useful insights about the target audience and the relationships among its members.

Similar brand monitoring studies could become an effective foundation for any brand strategy or marketing activities.

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