A day in the life of a project at John Lewis

A day in the life of a project at John Lewis
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  • SAS modelling Campaigns GDPR operations on data Production errors Customer Product Channel interactions
  • Joined up data (we dont have)
  • I want to predict which skincare brand Customer wants to buy (email)
  • I want to predict which reward to give to a customer (DM)
  • Customer Datawarehouse
  • I want to predict which menswear brand Customer will like (online)
  • I want weekly emails to contain top most likely brands and products types 
  • I'll create a predictive model!
  •  Lots & Lots of data
  • I will ask the customer what they prefer
  • I'll create a predictive model!
  • I'll create a predictive model!
  • I'll create a predictive model!
  • Algorithmic-driven predictions
  • Design and content (assets)
  • Cut lists of customers with propensities
  • Online personalised content & producs
  • Outbound Email Comms
  • Outbound Direct Mail
  • personalised banners online
  • instore personal consultancy recommendations
  • weekly marketing emails
  • CUSTOMERS
  • transactional emails
  • You're bombarding me with so much messages/ I would read these messages if they were more relevant to me / I love these messages, I wish I had daily ones.
  • product recs online
  • quarterly rewards in mail
  • novel marketing campaign email
  • Cloud Data Platform (not here yet)
  •  beauty fashion nursery email instore 
  • ask cust about their prefs target 3 things a cust most will buy all channel msg frequency & content personalised know prod type, brand, price cust likes 
  • what technical features are built first to enable cross category and channel personalisation? 
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