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Five Steps to Prepare Your Web Analytics Data for CRM

Integrating online customer behavioral data from your web analytics tool into your CRM efforts is critical to communicating with customers in a timely and relevant fashion. Whether just beginning or having already completed a web analytics data integration, companies often find that their web analytics tools were not implemented to collect critical customer data. Web analytics solutions are traditionally website focused—built for measuring traffic and sales at the page and campaign levels. Special consideration must be given to ensure that a web analytics solution is also customer focused.

A customer-focused web analytics solution will enable you to identify the largest portion of your online traffic possible, gather the most relevant online data to build a rich customer behavioral profile, ensure accuracy with the confidence you need to power personalized marketing, and give customers control over how their data is used.

Here are five critical steps to developing a customer-focused web analytics solution:

1. Increase the collection of strong identifiers in your online data. 

A strong identifier is one that you can use to link an online user directly back to your customer file. Common strong identifiers include: a registration or profile ID collected when a user logs into his account on the website; an email ID collected when a user clicks through an email to the website; and an order ID collected at the point of purchase. These strong identifiers are essential, as they enable you to link otherwise anonymous web data to specific customers in your CRM database. 

Not only should you ensure that you are collecting those identifiers which are already available to the website, but you should also design website functionality that encourages users to log in or otherwise identify themselves. Some businesses inherently require users to log in to access the primary features of the website (e.g., banking or telecommunications) and therefore enjoy high visitor identification rates; businesses with relatively low identification rates, such as online retailers, can encourage customers to log in through features such as loyalty programs, personalized offers, and special functionality only available to authenticated users (e.g., wish lists, recommendations, etc.). 

Weak identifiers, such as cookie-based user IDs, are also important because they connect online activity across multiple page views and sessions to a single user. Then once a user is identified, all current and previously anonymous online activity can be associated to the customer.

2. Audit your web analytics implementation to ensure accurate data collection. 

In particular, ensure that you consistently collect any customer identifiers when they are available; check that page names are accurate and can identify the specific pages viewed; check for consistency in channel, content hierarchy values, product category values, and custom variables; and check that campaign identifiers and marketing channel data are collected accurately (particularly where these are managed through rules that may have become outdated). 

You may find that the integrity of the web analytics data has been seriously neglected—website developers often change the layout and functionality of the website with little thought to the impact on data collection, and the web analytics team is left to play catch-up to maintain the accuracy of the data.

3. Plan ahead to capture the most important behaviors on the website. 

Consider which online events would make good triggers for marketing communications. For example, if you would like to communicate with individuals who have downloaded documents from your support website, then ensure that those download events are tagged. Also, think about the accompanying data that should be collected with these online events in order to personalize your communications. For example, your web analytics team may have tagged the download event, but did they also capture a document identifier so that you can tell which document was downloaded to personalize a follow-up message? 

If you collect the right data, you will be able to build a rich view of the customer’s online activity, product interests, campaign interactions, and any pain points.

4. Track users across domains and devices. 

If you manage more than one related website domain, it is important to configure your web analytics tool to be able to track visitors as they move from one website to the next, ideally through the use of a common visitor ID. This way, once you have identified a customer on one of your domains, you can leverage this information as they interact with your other websites.

Increasingly, a customer’s online behavior is fragmented across many different devices, e.g., work computer, home desktop, laptop, tablet, smart phone, etc. The most important key to putting the pieces back together is increasing the collection of strong identifiers, as mentioned above. This will enable you to link activity across devices by identifying the user. However, strong tracking of users across devices involves a larger, coordinated effort. Inconsistent functionality, inconsistent user experience, or inconsistent data management across devices can hurt the ability to track users across devices. For example, an online retailer can encourage authentication on their mobile website by providing the same rich “my account” features on their mobile website as on their desktop website and keeping data consistent between devices, such as by maintaining a common shopping cart.

5. Respect your customers’ privacy. 

Be transparent about the data you collect and how it is used. Give control of the data back to the customers—allow them to opt out of personalized marketing driven by their online activity. Consider creating a customer preference center where users can select their privacy settings as well as voluntarily provide you with their product interests. This is often the difference between a customer finding your personalized communication creepy or brilliant.

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