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Machine Learning for Marketers - CTAConf 2019

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Explore CTAConf's Marketing IQ theme with a layer of AI.

You don't have to be a data scientist to think of the next genius ML application!!! ANYONE CAN!

Machine Learning is power at your fingertips! Learn more about how you can apply Machine Learning to your day to day life here.

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Machine Learning for Marketers - CTAConf 2019

  1. 1. Machine Learning for Marketers @BritneyMuller Senior SEO Scientist
  2. 2. Our journey from data to insights has traditionally looked like this:
  3. 3. To do better, we must think differently
  4. 4. Machine learning & data science tools can be your laser beam!
  5. 5. All ML solutions have one thing in common…data
  6. 6. Adequate training data fuels ML models Finance Driving Surgery
  7. 7. Teachers Nurses Childcare ML doesn’t solve well for soft/people skills
  8. 8. You don’t have to be a Data Scientist to think of the next brilliant ML application!
  9. 9. bit.ly/rand-b @BritneyMuller
  10. 10. codelabs.developers.google.com
  11. 11. What is Machine Learning? Intelligence IQ + ML Tools & Resources What We’ll Cover:
  12. 12. What is Machine Learning? Machine Learning is a subset of AI that combines statistics & programming to give computers the ability to “learn” without explicitly being programmed.
  13. 13. 10 Year Challenge?
  14. 14. Training data will get better & Machine Learning will free us up to do more strategic work.
  15. 15. What is Machine Learning? Intelligence IQ + ML Tools & Resources What We’ll Cover:
  16. 16. @BritneyMuller
  17. 17. Uncover the ONE keyword/topic with the highest ROI potential (rolling analysis)
  18. 18. pair-code.github.io/facets
  19. 19. pair-code.github.io/facets
  20. 20. Navigate via rolling business & market data
  21. 21. Source: news.efinancialcareers.com/ca-en/285249/machine-learning-and-big-data-j-p-morgan “Machines have the ability to quickly analyze news feeds and tweets, process earnings statements, scrape websites, and trade on these instantaneously.”
  22. 22. Add deep insights to your current processes
  23. 23. Rich customer understanding.
  24. 24. + +
  25. 25. Amazon’s Review API Use NLP to parse out pain points and areas of opportunity @BritneyMuller
  26. 26. Automate meaningful content
  27. 27. @BritneyMuller
  28. 28. @BritneyMuller
  29. 29. Automate Meta Descriptions searchwilderness.com/mozcon-2019
  30. 30. Automate visual content and image understanding
  31. 31. Video Generation
  32. 32. Automate Image Understanding @BritneyMuller
  33. 33. Machine Learning is becoming more accessible & will free us up to work on higher level strategy.
  34. 34. @BritneyMuller
  35. 35. What is Machine Learning? Intelligence IQ + ML Tools & Resources What We’ll Cover:
  36. 36. @BritneyMuller
  37. 37. Use Google's own NLP to know how G is understanding your content (vs your competitors)!!!
  38. 38. Automate Transcriptions
  39. 39. Automatic 301 Redirects searchwilderness.com/mozcon-2019
  40. 40. CPU > GPU > TPU
  41. 41. We have only scratched the surface title tag optimization deduping questions (Quora, Stack Overflow) log file analysis parsing text into entities (ex. insurance forms) traffic predictions deeper user engagement insights website audit insights automatic website fixes
  42. 42. Getting Started • Search ‘Harvard CS109’ in GitHub • Google CodeLabs – Break things!!! • MNist --The “Hello World!” of Machine Learning • Colab Notebooks OR Jupyter Notebooks • Learn With Google AI • Image-net.org • Kaggle • MonkeyLearn
  43. 43. • Yearning Learning (free book preview by Andre Ng) • Neural Networks & Deep Learning • Correlation vs Causation (by Dr. Pete!) • Exploring Word2Vec • The Zipf Mystery • BigML • Targeting Broad Queries in Search • Project Mosaic Books • Algorithmia • How to eliminate bias in data driven marketing • TensorFlow Dev Summit 2018 [videos] • NLP Sentiment Analysis • Talk 2 Books • The Shallowness of Google Translate • TF-IDF • LSI • LDA • Learn Python • Massive Open Online Courses • Coursera Machine Learning • RAY by Professors at UC Berkeley Advanced Resources
  44. 44. ML for Marketers Takeaways: 1. ML can shorten the path between data -- insights 2. An ML model is only as good as its training data 3. Consider the data you have & what you could do with it 4. YOU can create an ML model today 5. ML will help us level up as an industry
  45. 45. The Data Science Team at Moz is innovating in this space to make your journey from data to insights more efficient
  46. 46. think differently
  47. 47. What will you solve for?
  48. 48. Thank You!
  49. 49. Uncovering highest ROI keywords, links & social platforms Navigation via predictive business & market insights Understanding customer’s needs & pain points Crafting desired / helpful copy Decreasing friction to optimize customer satisfaction & conversions Amplification Promoting content & engaging with customers on highest ROI platforms.

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