shuki mann - lixfix (all things data 2015)

#ATDconf

Google Tag Manager Awesomeness

Shuki Mann!!

@[email protected]

mailto:[email protected]

#ATDconf#ATDconf [email protected]

What is Google Tag Manager?



source: builtwith.com

GTM market share VS. other vendors


http://builtwith.com


GTM Corner Stones:

what to do

when to do


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#ATDconf [email protected]

–Avinash Kaushik

I.T.



Business Question

First of All - Implementation Process

Defining KPIs

Requirements

Implementation-

QA

Implementation-


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!The First Magic: Cohort Analysis by The Last Seen Post!

(in other words: how the last seen post affects the FTD!amount)

! Difficulty: 2



What is “Cohort”Cohort analysis divides website users into groups (=cohorts) based on a common characteristic, and compares behaviour over time across those groups. !Cohort Types: • Date of first visit (retention by…) - default • Date of registration (churn rate by…) • Acquisition Campaign (sign ups by…) • App download date (in-app purchases by…) !and… • Last blog post they read (Avg. FTD amount by…)



conversion rate by acquisition week

Problem: GA presents only “acquisition date” as the common characteristic.



Our Business Question:!!

Whats the effect of the last post the user has read on the FTD amount by the number of days

passed since reading that post



FTD

!Implementation Plan!

1. While the user reads a post - save this post name to a cookie 2. …and also save the current date. 3. When the user is performing his FTD - take the date that was

stored to the cookie, calculate the days/weeks/months passed since that date and send that with GA transaction tag.

!4. What would happen if the user reads another post? It will overwrite

the stored information in the cookie, aka last click attribution. (It can easily be adjusted to first-click-attribution)

PostA PostB



1. Create cookies with the post’s URL and its reading time



2. Create variables to get these values from the cookies when the FTD occurs



3. Create Custom JS Variable that calculates the days passed since the date stored in the cookie



3. Create Custom JS Variable that calculates the weeks passed since the date stored in the

cookie



3. Create Custom JS Variable that calculates the months passed since the date stored in the

cookie



4. Create session-scoped custom dimensions in GA



4. Write down their index numbers…



5. Send transaction with the calculated

CDs values



Debugging with WASP inspector - all CDs are sent!

download chrome ext. from: bit.ly/wasp-inspector


http://bit.ly/wasp-inspector


Create Custom Report in GA! (in our case use only Average Order Value)



Export to Excel



A little bit of Tableau work and…

Business insights (here comes the money): !1. After reading post3 you have an

opportunity window of 3 days to bring high valued FTDs

!2. Something interesting happens in the

second week after reading post1… We should investigate it further



Another example: save the affiliate name (instead of post name) and monitor his traffic deposits across the

following weeks

FTDAff 1 Aff 2



So what did we have?!1. We wanted to see how different groups of the same users

behave across the timeline. !2. What defines “the same user”? In our case we are referring to

users that originated from a specific affiliate or read post X before their FTD.

3. When a user reads a post, we store the post name and reading date to a cookie.

4. When the user performs an FTD we retrieve the days+weeks+months since the last post reading date, and send it through custom dimension to GA (plus the post name of course).

5. We create a custom report in GA, export the data and visualise it in Tableau (or any other software).



More examples !!

1. e-Commerce - Store the registration date and see how these users convert through time. Maybe you will find that users that registered because of X converted less than users that registered because of Y.

!2. Apps - in-app purchases by installation date.


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DONE


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! The Second Magic: Optimizing Internal Site

!Search

Difficulty: 3



Search Terms report in GA - we have lots of usersthat didn’t find what they’ve searched for

#FAIL



Action Plan!!1. Grabbing the search term query from the URL !2. Return an HTML and inject it to the post’s feed code

for each search query

Business Goal!!

We want to provide more relevant search results or promote certain items that would of not been showed organically.



When searching for “adwords” youwould see a boring post:



…but after the injection, you can see a promoted post for my

AdWords Workshop



Step 1: grab the search query from the URL



Step 2: return a specific HTML code to inject for each search query:



Step 3: When the user is in the search results page - inject the returned

HTML to the main post feed (div withclass “columns” in our case)



<div class=“columns”>…



Try it yourself: search for “adwords”



Try it yourself: search for “google analytics”



But…!Lookup Table works only with “equals” operator. If someone is searching for “google adwords” and

not “adwords” it won’t work :-/



until…



RegEx Lookup Table

take the search look if the phrase in return the right cell



Take the returned value from our RegEx lookup table, and return the promoted

post HTML we want to inject



What did we have so far?



Try it yourself: search for “adwords”



Try it yourself: search for “google analytics”


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Thank You :) !

All Things Data Rocks! !

[email protected]



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The Third Magic:!Fight with Gibberish URLs!

!

Difficulty: 3


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As seen on…


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How will these URLs look in the GA reports?!



The problem:!Ecommerce shop with gibberish URLs - no way to analyse

with GA

alternatives before GTM:!!

1. 301 redirects (very risky) 2. Search & replace filters in GA (no way. thousands of products)



What are we going to do? - Solution #1

We want to be able to see more meaningful URLs in GA reports !1. Grabbing the “ugly” parameter from the original URL with a

GTM variable (macro) !2. Replace this old parameter with a new and more

meaningful one !3. Send virtual pageview to GA with the new parameter



Grab the itemId parameter with URL-Query variable



Return a new itemId for each ugly itemId!for example: “{8317F274-701D-46A3-A8D1}” >>> “Blue T-shirt -

Men”



Solution #1: Lookup Tables

The lookup table takes the value from the {{Old Item Id}} variable, and returns a new value to the {{New Item Id}} variable. !“if {{Old Item Id}} value is “ItemA” return “NewItemIdA” to the New Item Id”



Create Custom JS Variable that returns the {{New Item Id}} !only if the ItemId is in the URL



Send the New Item Id with virtual PV within the GA tag



But wait, we have 10,000+ products!!!

How can we create 10,000 rows more easily?

bit.ly/lookup-table-builder



Paste the code in the console and… hopa!

bit.ly/lookup-table-builder



Still - it takes a lot of time to create the lookup table, so I’ve looked for

an easier way



Solution #2: DOM scrapping

I need this part



(Houston, you have duplicate GA tag)



Step 1: Custom JS variable to get the last element on the breadcrumbs



Step 2: Fire GA tag with virtual PV


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DONE


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Thank You :) !

All Things Data Rocks! !

[email protected]



shuki mann - lixfix (all things data 2015)

Marketing

acquisition date

current date

seen post

app download date

custom js variable

stored information

ga transaction tag

implementation plan