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Leveraging Insights with Creative Segmentation

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Leveraging Insights with Creative Segmentation

  1. 1. #NYKLondon Leveraging Insights with Creative Segmentation
  2. 2. #NYKLondon Agenda Objective: Learn what rules, categories and tags are, and see creative ways Brandwatch Data Analysts have leveraged these tools to find compelling insights. Section One: Definition • What are rules, categories and tags? Section Two: Best Practices • Rule writing tips • Discovery and inspiration for segmentation ideas Section Three: Use Cases • Competitive rules • Owned vs. earned content • Selectively excluding data
  3. 3. #NYKLondon Definition
  4. 4. #NYKLondon Rules, Categories & Tags
  5. 5. #NYKLondon Rules, Categories & Tags
  6. 6. #NYKLondon Best Practices
  7. 7. #NYKLondon Best Practices: Context
  8. 8. #NYKLondon Best Practices: Inspiration Work Backwards • What is my company/team strategy? • What are my goals? • What are the business outcomes I need to create? • What problems do we currently face? • How can smart segmentation address these needs and gaps?
  9. 9. #NYKLondon Best Practices: Inspiration
  10. 10. #NYKLondon Best Practices: Inspiration
  11. 11. #NYKLondon Best Practices: Inspiration Let the data guide you
  12. 12. #NYKLondon Best Practices: Inspiration Let the data guide you
  13. 13. #NYKLondon Best Practices: Inspiration Let the data guide you
  14. 14. #NYKLondon Best Practices: Inspiration Let the data guide you
  15. 15. #NYKLondon Best Practices: Inspiration Let the data guide you
  16. 16. #NYKLondon Best Practices: Inspiration
  17. 17. #NYKLondon Best Practices: Inspiration
  18. 18. #NYKLondon Best Practices: Inspiration
  19. 19. #NYKLondon Best Practices: Inspiration
  20. 20. #NYKLondon Use Cases
  21. 21. #NYKLondon 1. Competitive Segmentation
  22. 22. #NYKLondon Why? • You can compare a share of voice with a competitor based on query volumes, i.e. how many times has my brand been mentioned online vs. how many times my competitors have been mentioned online? • Sometimes it may be more accurate to compare the number of mentions a competitor has within your own brand query, i.e. which competitors are being mentioned the most within the conversation about your brand?
  23. 23. #NYKLondon 1. Competitive Segmentation Competitor Share of Voice by Query Volume
  24. 24. #NYKLondon 1. Competitive Segmentation • Question: Across all Ben & Jerry’s conversation, which competitor is most commonly mentioned? • Solution: Competitive Rules + Category overlaid on Ben & Jerry’s Brand Query
  25. 25. #NYKLondon 1. Competitive Segmentation Competitor Share of Voice Within Query
  26. 26. #NYKLondon 1. Competitive Segmentation Competitor Share of Voice Within Query
  27. 27. #NYKLondon 2. Owned vs. Earned Categories
  28. 28. #NYKLondon Why? • Owned content: Content online written by you, either from your social accounts or on your own website • Earned content: Content online written by other people, excluding any content written by you, i.e. all of your mentions excluding your owned content • This allows you to compare topics from your owned channels vs. your audience, or whether your owned channels are effective in generating engagement for example
  29. 29. #NYKLondon 2. Owned vs. Earned Categories
  30. 30. #NYKLondon 2. Owned vs. Earned Categories
  31. 31. #NYKLondon 2. Owned vs. Earned Categories
  32. 32. #NYKLondon 2. Owned vs. Earned Categories
  33. 33. #NYKLondon 2. Owned vs. Earned Categories
  34. 34. #NYKLondon 2. Owned vs. Earned Categories
  35. 35. #NYKLondon 2. Owned vs. Earned Categories
  36. 36. #NYKLondon 3. Selectively Excluding Data
  37. 37. #NYKLondon Why? • You may wish to exclude a particular topic from your data temporarily, or just in one section of your dashboard • The best way to do this is to exclude a tag or category as a filter from your component, tab, or dashboard
  38. 38. #NYKLondon 3. Selectively Excluding Data
  39. 39. #NYKLondon 3. Selectively Excluding Data
  40. 40. #NYKLondon 3. Selectively Excluding Data
  41. 41. #NYKLondon 3. Selectively Excluding Data
  42. 42. #NYKLondon 3. Selectively Excluding Data
  43. 43. #NYKLondon 3. Selectively Excluding Data
  44. 44. #NYKLondon Now You Know
  45. 45. #NYKLondon Questions?

Hinweis der Redaktion

  • Enter the data with no preconceptions and conduct some open listening to find underlying themes
    Ok so the topic is on segmentation and that slide is if you know you want to get more granular with your data/analysis but don't know where to begin and need inspiration you can let the data guide you. So start with your query, enter the data with no preconceptions and conduct open listening to find underlying themes.

    The images are examples of what you might see in a ben and jerry's dashboard.. so maybe you see there are alot of topics about different flavors in the cloud. Create a category to break down the flavor preferences further.

    Or we see there's lots of conversation around "dairy free" maybe create a tag and see if that convo is negative/positive etc

    to the right if you see specific influencers emerging, create segmentation to visualize them separately or compare them and the engagement they raise for the brand
  • A better way to benchmark?
  • Dairy Queen has the highest Conversation Volume across the competitive set, but does that mean they are Ben & Jerry’s biggest competitor?

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