Shuki Mann - LIXFIX (All Things Data 2015)

#ATDconf
Google Tag Manager
Awesomeness
Shuki Mann!
!
@ShukiMann!
shuki@allthingsdata.co.il

#ATDconf#ATDconf shuki@allthingsdata.co.il
What is Google Tag Manager?

source: builtwith.com
GTM market share VS. other vendors

GTM Corner Stones:
what to do
when to do

#ATDconf
#ATDconf shuki@allthingsdata.co.il
–Avinash Kaushik
I.T.

Business Question
First of All - Implementation Process
Deﬁning KPIs
Requirements
Implementation-
QA
Implementation-

#ATDconf
!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

weeks passed since the date stored in the
cookie

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

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.

#ATDconf
DONE

#ATDconf
!
The Second Magic: Optimizing Internal Site
!Search
Difﬁculty: 3

Search Terms report in GA - we have lots of users
that 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” you
would 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 with
class “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”

#ATDconf
Thank You :)
!
All Things Data Rocks!
!
shuki@allthingsdata.co.il

#ATDconf
The Third Magic:!
Fight with Gibberish URLs!
!
Difﬁculty: 3

#ATDconf
As seen on…

#ATDconf
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

Shuki Mann - LIXFIX (All Things Data 2015)

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