What makes a successful Google Analytics strategy for enhanced user experience?

Maximising Data And Conversion

What makes a

successful Google

Analytics strategy

for enhanced user

experience?

Agenda

Introduction to iProspect

iProspect relationship with Frosmo

Successful Google Analytics strategy

• Hygiene/data robustness – 100% accurate set up

• Advanced configuration for better insights – custom tracking

• Analysis/activation of the data

Examples of activation with Frosmo tool

• Holland and Barrett – personalisation by user type

• Music magpie – relevant cross sell based on analytics data

• Manchester Airport – 1-2-1 website based on previous behaviour

Questions

3

Daniel Wigley

• 9 years’ web analytics and conversion optimisation experience

• Set up iProspect web analytics and conversion product offering

• comScore Digital Analytix Expert

• Google Analytics qualified individual

• Experience working with 100+ brands to improve their web analytics and

conversion rate

4

Joe Woodcock

• 7 years Conversion Optimisation experience and Web Development

Experience

• Google Analytics qualified individual

• Qubit, Optimizely and VWO Certified

• Google Analytics and Google Squared qualified individual

5

6

Lead Generation & Affiliates

Paid Search

Natural Search

Content

Generation

Performance

Display

Our

Products

Resourced to deliver across the

entire spectrum of digital

marketing channels

Social Media Management

Conversion

Optimisation

Data & Insights

Video

Structured

Data & Feeds

iProspect relationship with Frosmo

• Only UK based agency with partnership with Frosmo

• We use Frosmo for our agency clients to aid personalisation and optimisation

• We actively use data team to power insight, then Frosmo to activate onsite personalisation and optimisation

• We choose Frosmo because it offers flexibility of an enterprise tool for our clients at good commercial value

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Experts in the World of Data and Analytics

• One of only 8 in the UK

• Dedicated account

management team

• Stamp of quality for

technical implementation

and consultation

• One of only 8 in the UK

• Access to new beta &

product development

• Preferential rates

• Includes free version and

Tag Manager 360

support

• Access to new beta &

product development

• Request new features

• 500 qualified individuals

in the UK

• 10+ qualified individuals

Analytics 360

Suite PartnerGAIQ Qualified

Analytics 360

Reseller

Tag Manager

Partner

What makes a

successful Google

Analytics strategy

for enhanced user

experience?

100% robust set

up

Advanced

configuration

for better

insights

Analysis/

activation of the

data

10

A great Google Analytics strategy is broken down into three key areas

• Data hygiene – ensuring you

can trust all the data you see in

the account

• Critical to making decisions

around site optimisation

• Ensuring everything is tracked

appropriate for your business

• Advanced configuration –

ensuring all the new

functionality of Universal

Analytics (or GA 360) is set up

to understand your users better

• Leveraging site performance

into conversion activity

• Only trying to improve

conversion on the areas with

the biggest ROI

Each one is reliant on the other being completed – it’s a simply to follow approach to ensure you are making the most of the

tools that are available to you..

Data Hygiene

12

Why is Google Analytics data hygiene so important?

Can distort

performance of

key pages on the

website

Can lead to

misunderstanding

optimisation

activity

Can lead to

wasted

investment

PIIHostname

Filters

‘Fake’

Traffic

Query

Parameters

13

What are the common mistakes?

• It is against Google

Analytics terms and

conditions to collect

personally identifiable

information

• Fake or bot traffic can

distort bounce rates and

overall conversion rates.

• It could be pricing

crawlers, uptime

checkers or site

confidence tools

• It is against Google

Analytics terms and

conditions to collect

personally identifiable

information

• Apply hostname filters to

make sure the data is

robust

• Only capture visits from

hostnames that you want

There are 4 key common hygiene factors that are consistently not applied across the multiple clients we work with..

Fake traffic – how do I spot it?

14

Ensuring all fake traffic is taken out

of the GA account is imperative to

understand key performance

• Click on audience >

technology > Network

• Apply a advanced filter to only

show % new sessions greater

than 99.9.%

• Add city as a secondary

dimension

Fake traffic – how do I fix it?

Ensuring all fake traffic is taken out of the GA account is imperative to understand key performance

15

‘Fake’

traffic

Query parameters – what are they and how do I spot them?

Query Parameters can make analysis a lot harder to understand the performance of specific pages

16

• Query parameters are the

bit after the full URL

• /static/ArgosPromo3/includ

eName/3for2toys.htm?tag

=ar:home:banner:0:toys

• Click on Behaviour > Site

content > All pages

• Apply a advanced filter

box with a ?

Query parameters – what are they and how do I spot them?

Query Parameters can make analysis a lot harder to understand the performance of specific pages

17

Click on filters in the

admin section

Selection custom

Apply regex (\?+.*$)

Have the data

cleansed!

PII – what is it and how do I spot it?

Collecting personally identifiable information is against Google Analytics terms and conditions

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• Google Analytics can capture PII by default – need to make sure data is cleansed

• Click on All pages > add and @ symbol into the advanced filter

• View results and then take steps to cleanse the data

Advanced

Configuration

Custom

Dimensions

Full Enhanced

Ecommerce Set

Up

Form Field

Abandonment

Tracking

20

The account can also be customised for enhanced insights.

• Utilising more custom

dimensions can give you

greater insight into visitor

behaviour.

• Allowing you to really target

the real problem areas of the

site

• Need to configure the funnel

so that it captures virtual

page views to understand

progression between each

step for optimisation

purposes

• Additional insight can be

captured around fields:

• How long was spent in each

field?

• Does progression differ by

traffic source?

20 custom dimensions (compared to 5 custom variables with classic GA)

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Weather Gender Age Login in vs logged out

Products viewed Submitted a lead or not Always uses promotions Lead ID/customer number

Custom dimensions give you bespoke insight and allow you to understand visitors in a way that is tailored to your business

Enhanced ecommerce reports to provide granular data

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Answer questions about your user behaviour

you’ve not been able to answer before

You will be able to answer the following

questions:

• What products cause the highest

abandonment rate?

• Funnel conversion rate by any

dimension

• What is the most viewed item on the

website?

• Add to basket by order item appears

in a list

• What is the main cause of users not

completing the checkout process?

• How many users added to

basket, what is the add to

basket rate of my products?

Form field abandonment

23

Answer questions about your user behaviour

you’ve not been able to answer before

You will be able to answer the following

questions:

• Which field causes users to

abandon?

• How many seconds are spent in each

field?

• Are fields entered twice by the user?

• How far do users progress down the

form?

Activation of

the data..

Analysis and activation

• After you’ve found out what happened/trends focus on the

why?

• Utilise things that have been set up, or think about additional

thing that’ll add another layer on insight into findings

• Think about what you’re going to do with the data and

how it can be activated into something meaningful

25

Google Analytics integration with Frosmo

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Out of the box

integration

Bespoke Manual

Tracking Script

Music Magpie

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Used Google Analytics after accurate

set up to analyse the average number of

products purchased has declined and the

percentage of customers removing items

from the bag was high YoY

We were able to add in a number of

messages across the site highlighting

recently viewed products to try and

increase the number of products the user

adds to the basket.

Implemented this change site wide

improved the average quantity by 33%

and improved AOV by 37% YoY

Holland and Barrett

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Large proportion of users purchasing, then

returning to browse the site and not buying

products – creating dynamic

recommendations based on insight from

enhanced ecommerce

Using enhanced ecommerce we were

able to understand the relationship with

users removing products from their basket

dynamically recommending products

associated with them or ones they had

bought

Using Frosmo tool my team implemented

dynamic recommendations on the

homepage increased add to basket by

4.5% and conversion rate by 7% for

returning users

Holland and Barrett

29

Large proportion of users purchasing, then

returning to browse the site and not buying

products – creating dynamic

recommendations based on insight from

enhanced ecommerce

Using enhanced ecommerce we were

able to understand the relationship with

users removing products from their basket

dynamically recommending products

associated with them or ones they had

bought

Using Frosmo tool my team implemented

dynamic recommendations on the

homepage increased add to basket by

4.5% and conversion rate by 7% for

returning users

Manchester Airport Group

30

95% abandonment rate from the flight

information pages on the site - Advanced

personalisation based on insight from

custom dimensions

We captured lots of additional information

about the visitor, their gender, what they’d

bought previously, shops they’d browsed,

abandonment rate of booking processes

Implemented this on flight information

pages and reduced abandonment rate

on this page by 12% and increased

average pages view by 13.5%

Manchester Airport Group

31

95% abandonment rate from the flight

information pages on the site - Advanced

personalisation based on insight from

custom dimensions

We captured lots of additional information

about the visitor, their gender, what they’d

bought previously, shops they’d browsed,

abandonment rate of booking processes

Implemented this on flight information

pages and reduced abandonment rate

on this page by 12% and increased

average pages view by 13.5%

Any Questions?