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Orchestrating Data to Increase Sales & Reduce Costs

Mark Edmondson, Senior Data Strategist, IIH Nordic

Data Strategy Executive Morning Briefing

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Orchestrating Data to Increase Sales & Reduce Costs

  1. 1. Orchestrating data to increase sales and reduce costs Morning Brief: Data Strategy - IIH Nordic Aug 2019 Mark Edmondson, Senior Data Strategist, IIH Nordic
  2. 2. The problem Company Bonnier Publications is a Copenhagen-based media company that focuses on special interest magazines primarily for the Nordic market. It has won a loyal following with some of the region’s most famous brands, and is part of Swedish media group Bonnier Holdings. Context A global magazine industry that is shrinking every year, the Copenhagen-based company with 500 employees knew that moving from a print to a digital multi-format business model was critical to survival and growth. Problem statement A six-month deadline to achieve digital transformation. The challenge was a complete overhaul of the way Bonnier engaged with customers online to maximize e-commerce conversion rates, setting an initial target of 25,000 new subscriptions.
  3. 3. Challenges deep-dive Challenge 1 Single Customer View Consolidate customer activity across hundreds of websites, CRM databases and digital media sources to create more efficient marketing Challenge 2 Digital transformation Update internal systems so they can handle cutting edge data activation, such as machine learning and democratic data access, despite not being IT experts Challenge 3 Increase conversion Use data to predict user behaviour, so as to more efficiently target marketing spend and activity
  4. 4. Solution DataLake + Google Analytics 360 on Google Cloud Platform Build a machine learning algorithm on GCP that would leverage the power of Google BigQuery to model consumer predictions in a granular way. The algorithm was developed using GCP solutions such as Google Cloud Functions, Google Kubernetes Engine and Tensorflow. One reason Bonnier chose GCP for the data project was familiarity with platforms such as Google Analytics 360 and Google Ad Manager. The key factor was Google BigQuery’s massive processing power, which allowed aggregation of historic and real-time data from 15 million consumers in one location.
  5. 5. Implementation
  6. 6. Sep 2018 Consolidate GA web properties under one GA360 Rollup Oct 2018 Set up data transfers from GA360, on- prem servers and digital media into BQ Nov 2018 Create machine learning models for conversion prediction Jan 2019 Upload consolidated data and ML segments back into GA360 Feb 2019 Export GA360 segments into AdWords and other data activation channels
  7. 7. Impact ● E-commerce conversions up 18% + 50,000 new subscribers ● Doubles checkout conversion with data overhaul ● Maintains new subscription rate while reducing banners by 90% ● Motivates employees and attracts tech talent through data transformation max growth
  8. 8. Nominated for awards in Copenhagen, Stockholm, Dublin and New York (so far)
  9. 9. Four Point Process for your business Step 1: Find your Use Case Cloud Use Case Workshop Auditing your data sources and activation channels, finding your KPIs Step 2: Import your data Data Lake service Optimise data streams such as GA360, Google Ads, Facebook into Google Cloud Platform Step 3: Data Modelling Data Modelling Engine Turn raw data into useful output using sophisticated statistical modelling and machine learning techniques Step 4: Data Activation Data Activation API Integrate model data to where you need it

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Mark Edmondson, Senior Data Strategist, IIH Nordic Data Strategy Executive Morning Briefing


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