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Breaking down the silos
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SAMPLE:

BusinessIntelligenceMeets Web

AnalyticsBreaking down the silos

Econsultancy London

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Copyright Econsultancy.com Ltd 2013

Published May 2013


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Business Intelligence Meets Web Analytics Breaking down the silos Page 3

All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording or any information storage

and retrieval system, without prior permission in writing from t he publisher. Copyright Econsultancy.com Ltd 2013

Contents

1. Who is this report right for? ............................................ 6

1.1. About Econsultancy .................................................................... 6

1.2. About the author ......................................................................... 7

1.3. Contributors to the report ........................................................... 7

2. Introduction ..................................................................... 8

2.1. Where business intelligence meets web analytics breakingdown the silos .............................................................................. 8

2.2. The growing customer expectations of a channel-neutral

approach ...................................................................................... 8

3. The Value of Web Data across Channels ....................... 10

3.1. Specific online business benefit examples ............................... 10

3.1.1. Fabric mini case study: online integration for widerinsight..................................................................................... 10

3.2. Online behavioural data ............................................................. 11

4. Moving up the Analytical Curve and What You

Require ........................................................................... 124.1. Classic web analytics maturity model ........................................ 12

4.2. Web analytics maturity maps across to businessintelligence maturity .................................................................. 13

5. Business Intelligence within the Analytics Tool ........... 14

6. Simple Business Analysis outside of the AnalyticsTool ................................................................................ 15

7. Advanced Business Analysis outside of the AnalyticsTool ................................................................................. 17

7.1. The web analytics supplier proprietary warehouse................. 17

7.1.1. Web analytics supplier warehouse features .......................... 18

7.2. The standalone warehouse .........................................................18

7.2.1. Standalone warehouse features ............................................. 19

7.3. Using your Enterprise Data Warehouse (EDW) ...................... 20

7.3.1. EDW supplier warehouse features ........................................ 21


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8. In-House versus Cloud .................................................. 22

9. Extracting Data from Web Analytics Platforms (APIs) 23

10.Preparing Your Web Data for Wider Consumption ...... 24

10.1.

Understand why your website exists ........................................ 24

10.2. Develop your KPI framework ................................................... 24

10.3. Align your data collection to support KPIs ............................... 25

10.4. Consistentuse of IDs ................................................................. 26

10.5. Accuratecollection of data ....................................................... 26

10.6. Relevantcollection of data ........................................................ 27

10.7.

Similar collection of data .......................................................... 27

10.8. Tagging your site or reviewing existing tags ............................ 27

11. Planning for Linking Multiple Data Sets acrossCampaigns and Channels .............................................. 28

11.1. Campaign (or media) identifiers (CIDs) ................................... 28

11.2. Unique identifiers (UIs) ............................................................ 29

11.3. Vouchercloud mini case study .................................................. 30

11.4. Universal unique identifiers (UUIDs) ...................................... 30

11.5. Data identifiers are used throughout the user journey ............. 31

12. Stitching Data to Complete the Picture ......................... 32

13.What Data to Extract ..................................................... 33

14.Typical Uses and Benefits of a Full View ....................... 34

14.1. Introduction to benefits ............................................................ 34

14.2. Enhancing segmentation .......................................................... 34

14.3. Media attribution ...................................................................... 34

14.4. Reporting and general business intelligence ............................ 35

14.5. Understanding broken journeys across channel and devices .. 35

14.6. eCRM and triggers..................................................................... 35

15. Managing Your Data ...................................................... 36

15.1. Typical basic data transfer methods ......................................... 36

15.2. Importing data into a warehouse .............................................. 36

15.3. The time value of web data ....................................................... 36

16.

A Final Word on Team and Project Challenges ............ 38

16.1. Your analytics team and getting it right ................................... 38


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16.2. Be ready for the change and gain senior buy-in ....................... 39


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16.2. Be ready for the change and gain senior buy in ....................... 39


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SAMPLE: Business Intelligence Meets Web Analytics Breaking down the silos Page 6


and retrieval system, without prior permission in writing from the publisher. Copyright Econsultancy.com Ltd 2013

1.

Who is this report right for?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.

This 38-page report explores the growing need for a fuller view of customer behaviour andcustomer segmentation and, practically, how to open up a closed web analytics solution to provide

a more expansive business intelligence tool.

1.1.

About EconsultancyEconsultancy is aglobal independent community-based publisher,focused on best practice digital

marketing and ecommerce, and used by over 400,000 internet professionals every month.

Our hub has 190,000+ subscribers worldwide from clients, agencies and suppliers alike with over

90% subscriber retention rate. We help our subscribers build their internal capabilities via a

combination of research reports and how-to guides, training and development, consultancy, face-to-face conferences, forums and professional networking.

For the last 10 years, our resources have helped subscribers learn, make better decisions, build

business cases, find the best suppliers, accelerate their careers and lead the way in best practice

and innovation.

Econsultancy has offices in London, New York, Sydney and Singapore and we are a leading

provider of digital marketing training and consultancy. We are providing consultancy and custom

training extensively across Europe, Asia and the US. We train over 5,000 marketers each year.

Join Econsultancytoday to learn whats happening in digital marketing and what works. Call us

to find out more on +44 (0)20 7269 1450 (London) or +1 212 971 0630 (New York). You canalsocontact us online.

Recommended reports and training from Econsultancy

Econsultancy / Lynchpin Online Measurement and Strategy Report

http://econsultancy.com/reports/online-measurement-and-strategy-report

Econsultancy / TagMan Big Data Trends Briefing

http://econsultancy.com/uk/reports/big-data-trends-briefing-digital-cream-london-2013

The Presentation Style of Web Analytics Data and Decision-Making

http://econsultancy.com/reports/the-presentation-style-of-web-analytics-data-and-decision-making

Customer Relationship Management in a Social Age Best Practice Guide

http://econsultancy.com/reports/customer-relationship-management-in-the-social-age-a-best-practice-guide

Web Analytics Buyers Guide

http://econsultancy.com/reports/web-analytics-buyers-guide

Web Analytics Statistics

http://econsultancy.com/reports/web-analytics-statistics

Web Measurement and Analytics Training

http://econsultancy.com/training/courses/web-measurement-analytics
http://econsultancy.com/http://econsultancy.com/http://econsultancy.com/http://econsultancy.com/joinhttp://econsultancy.com/joinhttp://econsultancy.com/contacthttp://econsultancy.com/contacthttp://econsultancy.com/contacthttp://econsultancy.com/reports/online-measurement-and-strategy-reporthttp://econsultancy.com/reports/online-measurement-and-strategy-reporthttp://econsultancy.com/uk/reports/big-data-trends-briefing-digital-cream-london-2013http://econsultancy.com/uk/reports/big-data-trends-briefing-digital-cream-london-2013http://econsultancy.com/reports/the-presentation-style-of-web-analytics-data-and-decision-makinghttp://econsultancy.com/reports/the-presentation-style-of-web-analytics-data-and-decision-makinghttp://econsultancy.com/reports/customer-relationship-management-in-the-social-age-a-best-practice-guidehttp://econsultancy.com/reports/customer-relationship-management-in-the-social-age-a-best-practice-guidehttp://econsultancy.com/reports/web-analytics-buyers-guidehttp://econsultancy.com/reports/web-analytics-buyers-guidehttp://econsultancy.com/reports/web-analytics-statisticshttp://econsultancy.com/reports/web-analytics-statisticshttp://econsultancy.com/training/courses/web-measurement-analyticshttp://econsultancy.com/training/courses/web-measurement-analyticshttp://econsultancy.com/training/courses/web-measurement-analyticshttp://econsultancy.com/reports/web-analytics-statisticshttp://econsultancy.com/reports/web-analytics-buyers-guidehttp://econsultancy.com/reports/customer-relationship-management-in-the-social-age-a-best-practice-guidehttp://econsultancy.com/reports/the-presentation-style-of-web-analytics-data-and-decision-makinghttp://econsultancy.com/uk/reports/big-data-trends-briefing-digital-cream-london-2013http://econsultancy.com/reports/online-measurement-and-strategy-reporthttp://econsultancy.com/contacthttp://econsultancy.com/joinhttp://econsultancy.com/


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1.2.

About the authorJulian Brewer worked as the Head of Digital Commercial at Barclays Retail Bank for six years,

driving the development and innovation of digital commercial in one of the UKs largest online

banking platforms. Latterly, Julian has joined Lloyds TSB as Head of Digital Product & Sales.

Julian is the founder of Trackz, a blog and business intelligence consultancy that focuses on

extracting business intelligence from the digital experience and employing this to optimise thecustomer experience and commercial return across channels.

This is the first report written by Julian for Econsultancy. He can be followed on Twitter

@julianbrewer.

1.3.

Contributors to the reportJulian Brewer and Econsultancy would like to thank the following people for their input into this

report:

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
https://twitter.com/JulianBrewerhttps://twitter.com/JulianBrewerhttp://econsultancy.com/reports/business-intelligence-meets-web-analytics-best-practice-guide?utm_campaign=sample-report-page&utm_medium=report&utm_source=sample-reporthttps://twitter.com/JulianBrewer


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2. Introduction

2.1.

Where business intelligence meets web analytics

breaking down the silosFor a decade or more, the primary method for analysing website traffic and behaviour has been

through web analytics tools using the data that they collect from site traffic and visitor paths.

These tools in isolation have delivered enormous insight into the usage of sites and devices.

The convergence of digital and physical channels, and increasing cross channel customer

behaviour, calls for a fuller and more integrated view of customer behaviour and customer

segmentation from online business intelligence systems. The web analytics data silo is no longer

an acceptable state for either online or offline marketers.

Marketing directors already need to be focused on the need for...

In this guide, youll learn the following:

To understand the restrictions of the siloed 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.


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3. The Value of Web Data across ChannelsAs channels and touch points proliferate, a more rounded business view of customer interactions

delivers service benefits that avoid the grinding of gears as one side of the organisation fails to

see the online activity. Pooling the full data within an organisation across all touch points

delivers both immediate commercial benefits to the organisation and insight to develop a

strategic roadmap.

The ability for your organisation to understand this landscape provides an opportunity to

compete, using information management as a core competency and delivering the following

benefits:

Understanding changing consumer behaviour faster than...

...

3.1.

Specific online business benefit examplesThere are a number of good point solution examples of the benefits of integrating customer data

with web analytics, or web intelligence bringing data together and giving a broader breadth of

intelligence, buying behaviours, patterns and decisions.

There are, however, few large organisations that have truly integrated the full view of thecustomer across channels. The lack of a wide set of examples for full integration highlights the

challenges of this approach both technically and politically.


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4. Moving up the Analytical Curve and

What You RequireThe explosion in analytics in all its forms is dramatic and the volume of data that the digital

channels are producing continues to be a key business trend.

Saugatucks 2012 SAAS survey shows thatbusiness information and analytics will be...

4.1.

Classic web analytics maturity modelThe diagram below shows the evolution of organisations from basic web metrics to a more joined-

up and multichannel approach to data and business.

With increasing web analytics maturity comes integrated analytics and increased business

intelligence as part of the multichannel view


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5. Business Intelligence within the

Analytics ToolFor many companies that are trying to develop business intelligence from their web analytics

solutions, taking steps to integrate the data within their platform to yield insight is a great start,

either at an aggregate or granular level.

If your analysis is more at the aggregate level then you may wish to conduct the analysis within

the...

Top tip


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6. Simple Business Analysis outside of the

Analytics ToolFor simple business-driven analysis focused on decisions to improve process, there are distinct

advantages in taking data outside of a web analytics tool to join it with other online and offline

data.

For the purposes of business intelligence for process improvement at an aggregate level there is

probably no need to incur the cost and effort of a customer-level warehouse.

Introducing a business intelligence tool into the set-up will...

Top tip

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