The Business Intelligence Meets Web Analytics Best Practice Guide is aimed at data and web analysts, marketers, executive management and agencies that work with web analytics data and aspire to deliver more business intelligence from their investment. The report explores the growing need for a fuller view of customer behaviour and customer segmentation and, practically, how to open up a closed web analytics solution to provide a more expansive business intelligence tool.

This best practice guide will help you understand the following: 

  • The restrictions of the silo measurement approach and the benefits that a fuller business intelligence view provides for both on and offline marketers.
  • How leading marketers are successfully incorporating offline data to improve business intelligence and target their customers online and offline.
  • How a range of new and existing suppliers are enhancing their offerings to accommodate external data.
  • What types of data are proving valuable and how they are being used.
  • How businesses can move towards a fuller view and some of the challenges you are likely to encounter along the way.


This guide has been put together by Julian Brewer, an experienced digital marketing consultant working for Lloyds TSB and founder of Trackz, with the assistance of the following:

  • Neil Miller, Joint CEO, Fabric Worldwide – London
  • Paul Muret, Director of Engineering for Google Analytics, Google
  • Ellie Fields, Director of Product Marketing, Tableau
  • Holger Marsen, Senior Solutions Consultant, Adobe
  • Barry Parshall, SVP Product Management, iJento
  • Steve Dalgleish, Director, Lynchpin Analytics
  • Neil Mason, SVP Customer Engagement, iJento
  • Nick Willis, Head of Analysis, Seren
  • John Dumas, Practice Director – UX Research, Seren
  • Richard Wright, Senior Marketing Manager, Tealium
  • Rob Hick, Chief Data Scientist, Bright North
  • Lindsay O’Gorman, Marketing Director, TagMan

Table of contents

  1. Who is this report right for?
    1. About Econsultancy
    2. About the author
    3. Contributors to the report
  2. Introduction
    1. Where business intelligence meets web analytics – breaking down the silos
    2. The growing customer expectations of a channel-neutral approach
  3. The Value of Web Data across Channels
    1. Specific online business benefit examples
      1. Fabric mini case study: online integration for wider insight
    2. Online behavioural data
  4. Moving up the Analytical Curve and What You Require
    1. Classic web analytics maturity model
    2. Web analytics maturity ‘maps’ across to business intelligence maturity
  5. Business Intelligence within the Analytics Tool
  6. Simple ‘Business Analysis’ outside of the Analytics Tool
  7. Advanced Business Analysis outside of the Analytics Tool
    1. The web analytics supplier ‘proprietary’ warehouse
      1. Web analytics supplier warehouse features
    2. The standalone warehouse
      1. Standalone warehouse features
    3. Using your Enterprise Data Warehouse (EDW)
      1. EDW supplier warehouse features
  8. In-House versus Cloud
  9. Extracting Data from Web Analytics Platforms (APIs)
  10. Preparing Your Web Data for Wider Consumption
    1. Understand why your website exists
    2. Develop your KPI framework
    3. Align your data collection to support KPIs
    4. Consistent use of IDs
    5. Accurate collection of data
    6. Relevant collection of data
    7. Similar collection of data
    8. Tagging your site or reviewing existing tags
  11. Planning for Linking Multiple Data Sets across Campaigns and Channels
    1. Campaign (or media) identifiers (CIDs)
    2. Unique identifiers (UIs)
    3. Vouchercloud mini case study
    4. Universal unique identifiers (UUIDs)
    5. Data identifiers are used throughout the user journey
  12. Stitching Data to Complete the Picture
  13. What Data to Extract
  14. Typical Uses and Benefits of a Full View
    1. Introduction to benefits
    2. Enhancing segmentation
    3. Media attribution
    4. Reporting and general business intelligence
    5. Understanding broken journeys across channel and devices
    6. eCRM and triggers
  15. Managing Your Data
    1. Typical basic data transfer methods
    2. Importing data into a warehouse
    3. The time value of web data
  16. A Final Word on Team and Project Challenges
    1. Your analytics team and getting it right
    2. Be ready for the change and gain senior buy-in