Better conversion with Intelligent Analytics

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Better conversion with Intelligent Analytics @pjeedai

Transcript of Better conversion with Intelligent Analytics

Page 1: Better conversion with Intelligent Analytics

Better conversion with Intelligent Analytics

@pjeedai

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Turn user behaviour data

into Value

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Understand causes of bottlenecks on key areas

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Think through factors that may impact results

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Think about YOUR Data

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What YOU can investigate

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What YOU can investigateExamples and Ideas

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Inspire

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Tag Manager

Makes all this MUCH easier to do

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Tags

Add Events, Scripts with Custom Triggers

Add Extra Dimensions, Metrics, Data to Pageviews, Events, Hits

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Variables

Collect Data as Variables

Use Variables for fields in Google Analytics

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Page Values

Collect Data from Page or from Back end Source

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Send to dataLayer

Collect Data to use in Tag Manager Variables

Variables can also be captured without dataLayer

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Event Variables

Variables Can Be Variable

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Lookup Variables

If Bike Stock Type = New then use New Stock Variables

If Bike Stock Type = Used then use Used Stock Variables

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Variables for Custom Dimensions

Custom Dimension Variables

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Tools & Stacks

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Google Analytics API Scriptor paid plugins like

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Google Analytics API to Excel, csv or databaseAlso API for Facebook, Twitter, AdWords, Search Console & more

Allows scheduled and batch data pulls

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Google Analytics API to Excel, csv or database

Also API for Facebook, Twitter, AdWords, Search Console & more

Allows scheduled and batch data pulls

Also has save to Drive or Cloud database options

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Combine Business & Web DataDeeper Analysis and visualisation

PowerBI also has native API link to Google Analytics API etc.

PowerQuery and PowerBI have REST JSON API (make your own query from any source API)

Also have csv folder source extract for batch processing

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Requires a little more work than just using the Analytics UI, more powerful than VLOOKUPThis is an example Data Model to split detail out

This lets you combine, calculate and filter as needed

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Bigger datasets, more powerful statistical analysisPowerBI cloud has real language querying

“What is the best performing product for revenue this Quarter?”

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Geo lookup or CRM for customer addresses (or combine both)Visualise on drill down map or overlay ArcGIS data

e.g. Conversions > Avg from Areas with Household income > average

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Average alone can mask opportunity & risksTableau, R or PowerBI to analyse distribution patterns

Best for your lowest value, least loyal customersMay be Worst for your big spenders

Often not a business wineven if it reports as a Test or Campaign win

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User & Session Recording

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Also, you know. Maybe talk to them

Ask Customer Services, Feedback form responses, BCC on Customer Service emails, Jump on a Live Chat

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Hit level – Measurement Protocol

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Gets a little spendy at the top end but Free Option is good to try out

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Metrics and Measurement

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Success Events

If [Good Thing] happens

Track [Good Thing]

Ideally [Type of Thing] | [Which Specific Thing] | [What Details]

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Success Events - Detail

Why this much Detail?

• Custom Segments

• Remarketing

• Event Goals

• Filters and Offline Analysis (Dealer ID & stockID)(need to be a bit careful of high cardinality on unfiltered or unsegmented data)

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Fail Events

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Fail Events

Common Issue for eCommerce, Appointments, Holidays

• Conversion Rate Affected by Stock Levels & Availability

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Fail Events - Detail

Don’t just send Event on Success; Also send on Fail

• IF it failed

• WHAT type of Failure

• WHERE it failed (WHICH use case)

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Stock Level Events

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Event Goals

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Event Goals

Goals are NOT just Sale Complete URL

Clicks, Add, Viewed, Video Play

Events are Ideal for segmenting Goals

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Exeter Any Day

Event Click To Book

Individual, Create Team or Join Team

Exeter – Any Day

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Exeter Saturday

Event Click To Book

Individual, Create Team or Join Team

Exeter – Saturday ONLY

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Exeter Sunday

Event Click To Book

Individual, Create Team or Join Team

Exeter – Sunday ONLY

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Clicks By Race Day

With 3 Event Goals – break down ways Total is reached

Compare Click Volumes per Race Day AND Total

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Buy to Click Ratios

Calculate Buy to Click Ratios by Day AND Totals

Sunday has higher drop-off between Click and Buy

1560 ÷ 3164 = 49.30% 466 ÷ 1041 = 44.76% 2015 ÷ 4067 = 49.54%

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Custom Dimensions

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Custom Dimensions

• Product SKU• Site ID• Visitor ID• User Lifetime Value• Product Availability• Previous Submit• Checkout Account Type

• Guest• New Account• Logged In

• Experiment ID and Experiment Variant

Practically almost any Dimension you might want to track (non PII)Limited to 20 on a standard account. 200 on GA Premium

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Custom Dimensions

Dealer ID to link back to Network CRM

Dealer Name varies (multi-franchise)

Report whole network performance but link back to Dealer Sales

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Custom Metrics

Dimensions Describe Data

Metrics Measure Data• User/Session of Described Type – Count

• Lead Value

• Original Price

• Displayed Price

• Product Level Discount Value

• Volume Level Discount Applied

• Finance Deposit

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Custom Metrics

Frequently eCommerce will pass either

• Original Price (even if discounted Price is applicable)

• Discount Price (but no idea how much discount vs. Original Price)

Custom Metrics allows you to record & calculate the differences

Reports can then show Value Lost in discount/promotions

This allows you to report real Revenue performance

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Calculated Metrics

Calculate Business Metrics not Web Metrics

Original Price – Discount Price Applied = Value Lost

Buy Exeter Tickets ÷ Click Exeter = Buy to Click Rate

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Calculated Metrics

Buy Exeter Tickets ÷ Click Exeter = Clicks to Buy Rate

But we can now use this in Custom ReportsBy Channel | By Campaign | By Device | By Gender | By Age etc.

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Custom Reports

Extremely useful: within the limits of the User Interface

For complex reports use API

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Custom Reports

Clicks to Book – By Ticket Type (from Event tracking)

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Custom Reports

Drill down to Individual Tickets – Exeter Saturday has most Clicks

Compare performance of Exeter Saturday 2016 vs Exeter Saturday 2017

Are sales behind schedule? Traffic growth but lower Clicks to Buy Ratio?

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Annotations

Record Changes to Tracking

Record Campaign and Promotion Periods

Highlight ‘odd’ data to investigate

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Lots of Data

Pull data via API

Match against Business Data

Automate

Crunch Segments, Dimensions, Metrics

Take Action

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PowerQuery > Data Model > PowerPivot Measures > Excel visualisationSame Data Model, Measures and Query could also be used in PowerBI

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Manual: Pull data via API to Sheets and Download. Download csv from GA UI

Automate: Next Analytics, Analytics Edge, Supermetrics, Power Query, PowerBI

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Calculated Metrics

Custom Filters

Visualisations

Links to:

• Google Analytics

• AdWords

• Sheets

• BigQuery

and more

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• Automatic Refresh

• Custom Filters

• Date Range

• Dimension Filters

• Custom Segments

Up to 20 Pages per Report

Unlimited Reports

Free!

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Distribution matters• 2 users off the scale of this chart• 130+ items per purchase

“Average” is misleading if you don’t know how it is distributed

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Custom Segments

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Custom Segments

User has Clicked Enquiry on Used Motorcycle

Label of Event Contains Year: Segment to 2015

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Channels Report

Segment can then be applied to other Reports: e.g. Channels

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Segment Share of Contribution

Share of Sessions or Event Clicks easily compared

Or Targeted. Or Reported against # Stock of each Year being advertised etc.

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Shortcuts

Create shortcuts to quickly re-apply Segments/Filters

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Referrers

Advertising Stock

Costs Money

Different Portals

Different Audiences

Different Stock

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Referrers

“Price To” from ?= Search string from Referral Path

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Regular Expressions

“Price To” from ?= Search string from Referral Path BUT

Different format for “Price To” Search on EVERY Referrer site

Expresso http://www.ultrapico.com/expresso.htm (Windows Only)

http://regexr.com/ (Browser)

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Custom Channel Groups

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Custom Channel Groups

Default Channels are ok if you tag inbound links and adverts accurately

But Custom Channel Groupings are better

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Custom Channel Groups

Start with Default as Template

Divide Channels more precisely

Rules apply top to bottom

Different Groups

Different Levels of Detail

Paid Search is a good exampleBy Type: • Shopping• Display• Text• VideoBy Spend: • High Cost• Medium Cost• Low Cost

Buying Cycle, Competition, Volume etc.

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This is a Top line Channel splitting – slightly more detail than Default Channels:

• Paid: Main Ad types, Top Funnel, Middle Funnel, Bottom Funnel

• Organic Search: Google or Other – Keyword Known/Not Provided

• Email: Which Mailing list (Mailchimp or EventBrite)

Custom Channel Groups

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Custom Channel Groups

More detail on Paid Campaigns

• Paid Search

• Paid Social

2nd Dimension of Keyword

Exeter Race promotion

• Keywords mostly Exeter

• Some Top Funnel generic

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Demographic Reports

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Demographic Reports

Make sure Privacy Policy is compliant

Make sure this option is legal in your territories

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Age Bands

User Volumes By Age Band

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Gender

User Volumes by Gender

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Affinity & InterestsInteresting? Useful?

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Affinity & Interests

Combine with a Segment of Users Who Clicked but didn’t Enquire

…can be Targeted with appropriate Stock

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Content Grouping

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Content Grouping

Must have Edit Permission for the View

• Template

• Type

• Categories

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Content Grouping

Tag Manager makes it easier

dataLayer makes it simple

Page Template: Used Bikes > All Used Stock Page Titles

Makes: Ducati > Ducati Models

Models: Multistrada > Multistrada Variants (S, Enduro etc.)

Model Year: 2009, 2010, 2011 etc.

Price Bands: £5,000 - £7,499 | £7,500 - £8,999 | £9,000 - £10,499 etc

Up to 5 Groupings

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Content Grouping

Pages Report – lots of detail

Hard to see which Categories work best

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Content Grouping

Categories Content Group Applied:

Apparel clearly more popular than Brands and Bags

Can also be used to create Segments

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Think about YOUR Data

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What YOU can investigate

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@pjeedai

Data is one thing

Intelligent use of data is everything

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Thank you for listening

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ResourcesGet Started With Tag Manager & Google Analytics

https://analytics.google.com/analytics/academy/

Learning Resources

https://www.simoahava.com/

http://www.lunametrics.com/blog/

http://www.analytics-ninja.com/blog.html

Demographics and Advertising Tools Policy Requirements

https://support.google.com/analytics/answer/2700409?hl=en-GB&utm_id=ad

Regular Expression Tools

http://regexr.com/ (Online)

http://www.ultrapico.com/Expresso.htm (Windows)

Data Studio

https://www.google.com/analytics/data-studio/

API Tools

http://www.analyticsedge.com/

https://supermetrics.com/

http://www.nextanalytics.com/

https://powerbi.microsoft.com/en-us/

https://www.scitylana.com/

Connect on Linked In https://www.linkedin.com/in/timstewart/

Or ask me a question on Twitter @pjeedai