Smart Ideas for Big Data in Social Media
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Aleksander from Sotrender Research Team shares ideas for using Big Data in Social Media Marketing: Benchmarking with Trends Reports, Facebook Fans Interests, Paid Posts Prediction & Online Marketing Trainer Sombrero! Presentation from GOmobile Academy, Warsaw, 10.02.2016.
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Smart Ideas for Big Data in Social Media
- 1. The Bigger The Better: Smart Ideas for Big Data in Social Media Aleksander Zawalich Analyst Sotrender Research Team aleksander@sotrender.com Go Mobile #10, Warsaw, 10.02.2016
- 2. About Sotrender 5 20 800 16 3 Team Members Years Marketers Countries Research Team • Research company specializing in measuring social media, as well as developing it’s own analytics software with usage of big data technologies. • Founders: Jan Zając (CEO), Paweł Kucharski (CTO), Dominik Batorski (Chief Scientist).
- 3. Our Software
- 4. Our Software
- 5. How are we doing it? • Apache Big Data: Hadoop, Hive, Spark, HBase • R-software Analyses: R-Studio, own algorithms, machine learning, decision trees and random forests, open-source packages (e.g. dplyr, ggplot2)
- 6. Data statistics 35 4 30k PlatformsTB of data Profiles
- 7. We have BIG DATA. What else do we need?
- 10. Trends Reports • Monthly reports for marketers • Facebook, Twitter, YouTube • 3 countries (PL, UK, Indonesia) • Have been published, developed and improved since 4 years. sotrender.pl/reports
- 11. PL Fanpage Trends Report – 03.2011 Rank Name Fans Growth Growth %
- 12. PL Fanpage Trends Report – 01.2016
- 13. PL Fanpage Trends Report – 01.2016 % of Engaged users Engaged users
- 14. PL YouTube Trends Report – 01.2016 Ratings number % of positive ratings
- 15. PL Twitter Trends Report – 01.2016 Most often mentioned profiles
- 16. Idea #2 Facebook Fans Interests
- 17. Facebook Fans Interests • On-demand analysis about your fans: where else are they active and what are their interests. • Useful for planning communication strategy and choosing brand ambassadors.
- 18. Facebook Fans Interests Hey, which cars do you like apart from Honda?
- 19. Facebook Fans Interests Example data
- 20. Facebook Fans Interests Example data Coactivity with categories
- 22. Idea #3 Paid Posts Prediction
- 23. Facebook Paid Posts Prediction • Estimation of paid posts on fanpages made with machine- learning and random forests algorighms. • Based only on public data derived from 14 000 profiles. • >90% accuracy of the model. $$$
- 24. Facebook Paid Posts Prediction Example data The share of paid communication vs reach per postNumberofallposts Number of paid posts
- 25. Facebook Paid Posts Prediction Example data Non-paid Paid Paid vs non-paid communication usage
- 26. Facebook Paid Posts Prediction Example data Non-paid Paid Efficacy of paid posts – mean number of activities
- 27. Idea #4 Personal e-marketing trainer
- 28. Sombrero App – personal E-marketing trainer • iOS and Android app aimed at helping beginners at the beginning of their social media adventure. • Big-data and experience-based everyday simple tasks. sombreroapp.com
- 29. Sombrero App – personal E-marketing trainer Add profiles Complete tasks See results
- 30. Thanks for your attention Let’s stay in touch! Aleksander Zawalich Analyst Sotrender Research Team aleksander@sotrender.com sotrender.com facebook.com/Sotrender twitter.com/Sotrender slideshare.net/FanpageTrender Go Mobile #10, Warsaw, 10.02.2016