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Building a successful data science team with R at the heaRt!

Building a successful data science team with R at the heaRt!. Jeremy Horne Head of Data Science, RocketMill. EARL 2016: Automated deployment of externally driven demand for goods and services. A real-time and radical shift in media campaign planning EARL 2018:

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Building a successful data science team with R at the heaRt!

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  1. Building a successful data science team with R at the heaRt!

  2. Jeremy Horne Head of Data Science, RocketMill EARL 2016: Automated deployment of externally driven demand for goods and services. A real-time and radical shift in media campaign planning EARL 2018: The power of machine learning in segmenting CRM databases

  3. We are RocketMill.

  4. We are an independentfull-service digital marketing agency.

  5. Activate. Nurture people through the customer experience. Create. Craft and optimise the consumer experience. Strategise & Plan. Define overall framework and plan the tactics. Data. Collect and visualise insights for business and marketing optimisation. Technology Ensuring the plumbing is right.

  6. We putpeople first.

  7. We’re on our own data driven journey Data and Insight at RocketMill 2009: RocketMill established 2015: First analyst hired / tool launch 2016: Data team created 2019: Data science is born! 2020: Team and client growth

  8. Some of our clients

  9. Data science at RocketMill

  10. I’m scared!

  11. We use data to understand people, and deliver them valuable experiences by combining technology and insight.

  12. …so how to we build a function around this?

  13. Step #1:Identify Data access Current usage Potential opportunities

  14. Step #2:Educate Opportunity identification Focus on business challenges Jargon-free!

  15. Step #3:Secure GDPR! SFTP / sharing portals

  16. Step #4:Simplify

  17. Computer Science Mathematics & Statistics Machine learning Research & analysis Software development Business Knowledge

  18. Consider this service offering… Media measurement Media measurement  We use Markov chains to create a stochastic model of your conversion paths, generating a transition matrix of by-channel interactions, so that we can analyse the removal effect of each media channel • For longer term measurement, we build econometric models to create a decomposition of your business KPI’s by media and non media factors, analyse the presence of adstocks and assess if you are operating within diminishing returns We build attribution models so that you can analyse the performance of media channels in isolation Where longer term of more complex measurement is required, we use media mix modelling techniques to understand how channels work together to drive a given business KPI We build attribution models so that you can analyse the performance of media channels in isolation Where longer term of more complex measurement is required, we use media mix modelling techniques to understand how channels work together to drive a given business KPI We use Markov chains to create a stochastic model of your conversion paths, generating a transition matrix of by-channel interactions, so that we can analyse the removal effect of each media channel For longer term measurement, we build econometric models to create a decomposition of your business KPI’s by media and non media factors, analyse the presence of adstocks and assess if you are operating within diminishing returns NO!!!!!

  19. Our offering is based around five core service areas

  20. Step #5:Build

  21. Choose a tech stack that suits your needs SUPPORTING ANALYTICS TOOLS DATA GATHERING AND STORAGE

  22. Step #6:Deliver

  23. Database strategy & CRM analysis – tidyverse! • Organise • Understand %>% arrange filter mutate select summarise Variables • Explain Observations

  24. Segmentation From simple techniques, such as Recency, Frequency, Value (RFV) using the tidyverse and reshape2… • …to more complex clustering techniques: • fpc • mclust • dendextend • ggplot2

  25. Modelling • Machine learning algorithms to understand the customers most likely to: • purchase at full price • purchase with a discount • respond to a mailshot • e1071 • kernlab • randomForest • ranger

  26. Media measurement C1 Drop-off Start C3 C2 Conv • Arrtibution through Markov chains to measure short-term performance of digital channels: • ChannelAttribution • markovchain • reshape2 • tidyverse • Econometric modelling to measure the sales drivers per week: • car • darksky • lmtest • scales • tidyverse

  27. Step #7:Share Internal communications Create case studies Develop a marketing strategy

  28. Step #8:Learn New measurement strategies Technology evolution R package developments

  29. Becoming driven by data science Educate Build Share Deliver Identify Secure Simplify Help your peers spot opportunities Put systems in place to preserve data integrity Explain your offering in a tech friendly way Create solutions to business problems Talk about the work you are proud of! Datasets and the opportunity Identify and implement your tool stack Learn – the market evolves all the time: move with it!

  30. Thank you!Questions? Source: https://unsplash.com/@picsbyjameslee

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