Learn to Track Qualified and Won Leads in Google Analytics

Websites where the majority of conversions happen offline, often rely on leads generation for driving sales.

The most common type of leads is form leads. These are the leads generated through a form, which is embedded on a website.

Form leads can be classified into:

#1 Qualified leads – leads which meet your customers’ qualification criteria.

#2 Won leads – qualified leads which converted into actual sales.

There are two methods to track web form leads as conversions in GA:

#1 Traditional method

#2 Via CRM (client relationship management)

Customer Relationship Management (or CRM) is a tool which is used to track and manage leads, and store all of the information about the leads.

Traditional method for tracking Web Form Leads as conversions in Google Analytics

In the traditional method, a user fill out the lead generation form on your website, and then submit it.

You then track the ‘thank you’ page URL (or URL of the page which is shown to a user, on successful form submission) as ‘Destination Goal’ in Google Analytics (GA):

destination goal

This is one of the most common and widely used methods in GA.

But with this method, you won’t be able to track qualified and won leads, as well as the sales associated with each form lead.

Tracking Web Form Leads as conversions in Google Analytics via CRM

Here is how this system works:

  1. A user fill out the lead generation form on your website and submit it.
  2. As soon as the user hits the ‘submit’ button, all of the lead information goes straight into your CRM software (like salesforce).
  3. You or your staff, qualify and categorise the lead via the CRM. So if a qualified lead turns into sales then it is labelled as ‘won’ and a monetary value is assigned to it.
  4. Your CRM stores all the lead data along with the corresponding client/user ID values.
  5. You download (or submit a request to download) the web form lead data from CRM once a week or so.
  6. You import the leads data (along with qualified leads, won leads & monetary value attached with each lead) from your CRM into Google Analytics.

This is the best way to track web form leads in Google Analytics.

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Requirements for tracking qualified and won leads in Google Analytics

Before you can track qualified and won leads in GA, make sure:

  • You use CRM software like salesforce.
  • Your CRM software provides ‘web to lead‘ functionality.

You need a CRM software to qualify leads and add a monetary value to them.

You need ‘web to lead’ functionality, so that every form submission on your website, automatically creates a corresponding lead record in your CRM.

For example, Salesforce provides ‘web to lead’ functionality.

Decide the additional data you will send along with lead data to your CRM

It is important, that you at least send client ID (or user ID) along with the lead data, to your CRM. Otherwise later, you won’t be able to map web form lead to its correct user in Google Analytics.

In addition to client/user id, you should also consider sending data like campaign source, campaign medium, referral, etc, along with lead data to your CRM.

Capture the additional data you will send along with lead data

You can capture additional data in GA by writing a script. For example, in order to capture client ID, you can ask your developer to write a script that automatically captures the client ID from Google Analytics cookie and store in a custom dimension with a user-level scope, as soon as the user visits your website.

If you rely more on user id then capture user ID instead of client ID.

Similarly, you can develop a script that can capture, referral data.

Now in order to capture additional data in your CRM, you need to create one or more corresponding custom fields in your CRM.

For example, create one custom field for storing the client ID, another custom field to store campaign source and so on.

Send additional data along with lead data to CRM on form submission

Additional data (client Id, campaign source, medium etc) is usually not the one you ask your website users to provide to you, via web form. So in order to send this additional data along with form lead data, you need to write a script, which can send this data via form hidden input fields. These hidden fields won’t be visible to your users.

Depending upon the type of data you want to send, to your CRM, add one or more hidden input fields to all of your lead generation forms on the website.

For example, add one hidden field for sending client ID (on form submission) like the one below:

<form action=”” name=”myForm”>
Name: <input type=”text” name=”name”>
<input type=”hidden” id=”clientID_field” name=”clientID_field” value=””>
<input type=”submit” value=”Submit Form” name=”btnSubmit”>

Add another hidden field for sending campaign source, on form submission and so on.

Through hidden fields you can send additional data along with the lead data to your CRM on form submission.

Send CRM data to Google Analytics

Download data from your CRM once a week and prepare it for import into Google Analytics.

There are two methods you can use to send CRM data to Google Analytics:

  1. Data import (user data). This is an easy method.
  2. Measurement Protocol.

If you want to use the data import feature, then follow the steps below to send CRM data into Google Analytics:

  1. Create a custom dimension for storing ‘client ID’ (or user ID).
  2. Create a custom dimension for storing the ‘form lead type’ (qualified lead, won lead)
  3. Create a new user data set in GA.
  4. Use the ‘client ID’ custom dimension as key and ‘form lead type’ custom dimension for imported data.
  5. Set ‘overwrite hit data’ setting to yes
  6. Download the data set schema template.
  7. Prepare the downloaded CRM data for import, according to the data set schema template.
  8. Upload the CRM data and create custom reports.

If you are brand new to data import, then read this article: How to correctly measure Conversion Date & Time in Google Analytics where I have explained data import features in great detail.

If you want to send CRM data via measurement protocol, then follow the steps below:

1: Convert your CRM data into payload data i.e. format your CRM data according to measurement protocol.

2: Send the payload data to Google Analytic server via GET or POST HTTP request.

Note: There is one big downside of using measurement protocol and that is measurement protocol does not allow you to upload aggregated data (like tables). So implementation is pretty tricky.

To learn more about using the measurement protocol, read this article: Understanding Universal Analytics Measurement Protocol

Other articles on specialized tracking in Google Analytics

  1. Ecommerce Tracking in Google Analytics – Tutorial
  2. Event Tracking via Google Tag Manager – Tutorial
  3. Event Tracking in Google Analytics – Tutorial
  4. Guide to Google Analytics Store Visits Tracking
  5. Offline Conversion Tracking in Google Analytics – Tutorial
  6. Implementing E-Commerce Tracking via Google Tag Manager
  7. Tracking Virtual Pageviews in Google Tag Manager – Tutorial
  8. YouTube Video tracking via Google Tag Manager
  9. How to Use Keyword Hero to Reveal Not Provided Keywords in Google Analytics
  10. Virtual pageviews in Google Analytics – Tutorial
  11. Google Analytics and YouTube Integration Tutorial
  12. Google Analytics for Facebook Tutorial
  13. Google Analytics Cross Domain Tracking Explained Like Never Before
  14. Using multiple Google Analytics tracking codes on web pages
  15. The one thing that you don’t know about PayPal.com and the referral exclusion list
  16. Calculated Metrics in Google Analytics – Tutorial
  17. Creating your own Google Analytics Tag Auditing System
  18. Tracking Site Search without Query Parameter in Google Tag Manager
  19. Tracking true referrals in Google Analytics when using PayPal and other payment gateways
  20. Phone Call Tracking in Google Analytics and Beyond
  21. Learn to Track Qualified and Won Leads in Google Analytics
  22. Introduction to Postbacks in Google Analytics
  23. Google Analytics Recurring Revenue and Subscriptions Tracking Tutorial
  24. How to track the impact of cookie consent on website traffic in Google Analytics
  25. Tracking Offline Conversions in Google Ads
  26. Implementing Scroll Tracking via Google Tag Manager
  27. Scroll Tracking via Scroll Depth Trigger in Google Tag Manager
  28. Site Search Tracking In Google Analytics Without Query Parameters
  29. Video Tracking via YouTube Video Trigger In Google Tag Manager
  30. How to Correctly Measure Conversion Date & Time in Google Analytics
  31. Google Analytics Social Tracking – Twitter, Facebook, Google Plus and LinkedIn
  32. Google Analytics Cross Domain Tracking (ga.js)
  33. Tracking Twitter and Linkedin Social Interactions in Google Analytics
  34. Creating Content Group in Google Analytics via tracking code using gtag.js
  35. Tracking Site Search in Google Analytics with Query Parameters
  36. Understanding site search tracking in Google Analytics
  37. Creating and Using Site Search Funnel in Google Analytics
  38. Learn to Setup Facebook Pixel Tracking via Google Tag Manager
  39. Setting up & Tracking AMP Pages in Google Analytics
  40. Setting up Sales Funnel across websites in Google Analytics
  41. Regular Expressions (Regex) for Google Analytics & Google Tag Manager – Tutorial

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Himanshu Sharma

Digital Marketing Consultant and Founder of Optimizesmart.com

Himanshu helps business owners and marketing professionals in generating more sales and ROI by fixing their website tracking issues, helping them understand their true customers' purchase journey and helping them determine the most effective marketing channels for investment.

He has over 12 years of experience in digital analytics and digital marketing.

He was nominated for the Digital Analytics Association's Awards for Excellence. The Digital Analytics Association is a world-renowned not-for-profit association that helps organisations overcome the challenges of data acquisition and application.

He is the author of four best-selling books on analytics and conversion optimization:

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