Welcome to the SiteCatalyst Finance Fundamentals blog series.  In this series we will discuss the implementation basics and example analysis of each fundamental solution that Financial Services customers should consider leveraging.  Stay tuned and please feel free to contribute your thoughts/experience as we discuss each solution.

Once most companies move beyond the web analytics basics of “what is my most popular content?” they start asking more advanced questions such as:

  • Is my site traffic made up more of customers or prospects?
  • What customer demographics are visiting my site most often?
  • Who is completing my online application – customers or prospects?
  • Which age group has a higher conversion rate for my online account application?

Luckily, these questions can be answered in a fairly easy manner by capturing just one data point and doing some JavaScript and SAINT magic. This is assuming you have a logged-in portion of your website where users have to authenticate before accessing, like what most online banks or brokerages have. Once we can identify who the user is, the rest is simple data manipulation in order to report on, say, checking account application fallout by age group:

Product by Age Group

Pretty neat report, and actionable data too.

Visitor Segmentation Implementation

To implement simple visitor segmentation, we’ll need the following variables:

  • Customer ID – eVar set to never expire, and a prop
  • Customer vs. Prospect – eVar set to never expire, and a prop

Capturing Customer ID

When the user logs into the secure portion of your website or otherwise identifies themself, populate your customer ID eVar and prop to the user’s unique customer ID. This customer ID should be:

  • Unique at the individual level
  • Non-personally identifiable (no email addresses or usernames)
  • Stored somewhere in a back-end system for future look-ups
  • Shorter than 100 characters

The ID could be some sort of account identifier that is meaningless outside of your business’s back-end system, or a hash of a username. As long as that ID will be the same from visit to visit and fits the criteria above, you’re safe to use it.

The code to capture this variable will be very simple. Once the user ID is known, set it in the eVar and prop on every page and link tracking server call. In this example, eVar1 and prop1 are the customer ID variables:


If the customer ID isn’t available on every page, Adobe Consulting can provide the getAndPersistValue plugin that will persist that value forward as long as needed. If the user isn’t authenticated, don’t set anything in these variables.

Capturing Customer vs. Prospect

Once the customer ID is being captured, a simple bit of JavaScript can designate if the user is a customer of your company, or a prospective customer. We will look at the presence of the customer ID eVar to indicate that this user is a customer, and put that designation in another eVar and prop:

if (s.eVar1){
} else {

Once we capture these two data points, we are left with two reports. One, a raw report of all our customer IDs and any associated success events attributed to them:

Customer ID report

And the second, a report of simple customer/prospect designation:

Customer vs Prospect Report

In our next blog post, we will work with this data and discuss how to pull effective and telling reports using SAINT classifications and segmentation.

Have a question about anything related to SiteCatalyst for the Financial Services industry?  Do you have any tips or best practices to share?  If so, please leave a comment here or send me an email at svertree (at) adobe.com and I will do my best to answer it on this blog so everyone can learn! (Don’t worry – I’ll keep your name and company name confidential).