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Segmentation by user acquisition source

NOTE
The process below does not support Google Universal Analytics.

The ability to segment your data by user acquisition source is critical to effectively managing your marketing plan. Knowing the acquisition source of new users shows which channels yield the top returns, and allows your team to allocate marketing dollars with confidence.

If you are not already tracking user acquisition sources in your database, ÃÛ¶¹ÊÓƵ Commerce Intelligence can help you get started:

Tracking user acquisition source

ÃÛ¶¹ÊÓƵ recommends two methods to track referral source data based on your setup:

(Option 1) Track order referral source data via Google Analytics E-Commerce

If you use Google Analytics E-Commerce to track your order and sales data, you can use the Google Analytics E-Commerce Connector to sync each order’s referral source data. This allows you to segment revenue and orders by referral source (for example, utm_source or utm_medium). You also get a sense of customer acquisition sources via Commerce Intelligence custom dimensions such as User's first order source.

(Option 2) Saving Google Analytics’ acquisition source data in your database

This topic explains how to save Google Analytics acquisition channel information into your own database - namely the source, medium, term, content, campaign, and gclid parameters that were present on a user’s first visit to your website. For an explanation of these parameters, refer to the . Then, you explore some of the powerful marketing analyses that can be performed with this information in Commerce Intelligence.

Why?

If you are just looking at the default Google Analytics conversion and acquisition metrics, you are not getting the whole picture. While seeing the number of conversions from organic search versus paid search is interesting, what can you do with that information? Should you spend more money on paid search? That depends on the value of customers coming from that channel, which is not something Google Analytics provides.

NOTE
mitigates this problem by storing transaction data in Google Analytics, but this solution does not work for non-eCommerce sites. Also, certain tools like cohort analysis are not easy to do in the Google Analytics interface.

What if you want to email a follow-up deal to all customers acquired from a certain e-mail campaign? Or integrate acquisition data with your CRM system? This is impossible in Google Analytics - in fact, it is against the Terms of Service for Google Analytics to store any data that identifies an individual. But, you can store this data yourself.

The Method

Google Analytics stores visitor referral information in a cookie called __utmz. After this cookie is set (by the Google Analytics tracking code), its contents will be sent with every subsequent request to your domain from that user. So in PHP, for example, you could check out the contents of $_COOKIE['__utmz'] and you would see a string that looks something like this:

100000000.12345678.1.1.utmcsr=google|utmccn=(organic)|utmcmd=organic|utmctr=rj metrics

There is clearly some acquisition source data encoded into the string. This is tested to confirm that this is the visitor’s latest acquisition source and associated campaign data. Now you need to know how to extract the data.

This code was translated into a . To use the library, include a reference to ReferralGrabber.php and then call

$data = ReferralGrabber::parseGoogleCookie($_COOKIE['__utmz']);

The returned $data array is a map of the keys source, medium, term, content, campaign, gclid, and their respective values.

ÃÛ¶¹ÊÓƵ recommends adding a table to your database called, for example, user_referral, with the columns like: id INT PRIMARY KEY, user_id INT NOT NULL, source VARCHAR(255), medium VARCHAR(255), term VARCHAR(255), content VARCHAR(255), campaign VARCHAR(255), gclid VARCHAR(255). Whenever a user signs up, grab the referral information and store it to this table.

How to use this data

Now that you are saving user acquisition source, how can you use it?

Suppose you are using a SQL database and have a users table with the following structure:

ID
EMAIL
JOIN_DATE
ACQ_SOURCE
ACQ_MEDIUM
1
john@abc.com
2012-01-24
google
organic
2
jim@abc.com
2012-01-24
google
cpc
3
joe@def.com
2012-01-25
direct
-
4
jess@ghi.com
2012-01-26
referral
techcrunch.com
5
jen@ghi.net
2012-01-30
other
organic
…
…
…
…
…

For starters, you can count the number of users coming from each referral channel by running the following query against your database:

SELECT acq_source, COUNT(id) as user_count FROM users GROUP BY acq_source;

The result looks something like this:

ACQ_SOURCE
USER_COUNT
google
294
direct
156
referral
55
other
16

This is interesting, but of limited use. What you would really like to know is:

  • The growth rate of these numbers over time
  • The amount of revenue generated by each acquisition source
  • A of users coming from each source
  • The probability that a user from one of these channels will return as a customer in the future

The queries required to do these analyses are complex. Armed with this information, you can determine your most profitable acquisition channels and focus marketing time and money accordingly.

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