Add Multi-Channel Data Warehousing to Your Toolkit

In recent newsletters I’ve referenced the Marketer’s toolkit. The kit often contains tactics such as one-to-one marketing, online strategies, old and new distribution channels, crisis management, database marketing, direct marketing, branding, niche and segment marketing, as well as CRM. The Marketer’s toolkit continues to expand as new technologies and ideas come to fruition, and the role of the tactics within this toolkit is to help the Marketer better understand the lifecycle of their visitors. This lifecycle can involve more than one channel; be it online, call centers, sales team execution, etc. For now, let’s focus on a trend that has become much more common in recent months - sending data from an analytics solution into a data warehouse. 

Data Warehousing

Many of our clients utilize some form of data warehousing methodology. In many cases, this warehouse is simply used to store customer data, sales data, or something other than the behavioral web data that you’d see within your analytics solution. However, a subset of our clients has begun to adjust their data models to include segments of their online behavioral data as well. The following is an illustration of what the data model might look like:

A few common options for data warehousing are Oracle®, Teradata®, or a home-grown solution. Teradata® has been very active in the data warehousing space. Their Integrated Web Intelligence (IWI) platform includes pre-built data models to connect directly with the major analytics vendors. 

As with any data integration, there needs to be a common key within the datasets. A typical starting point for an integration like that of the above diagram could include purchase information (i.e. order ID, etc.) or personal information (i.e. email address, subscriber ID, etc.).

Data Feeds

When looking at data warehousing options, you also need to consider the methods for getting data out of your analytics solution.  All of the analytics vendors, including the free vendors, allow for you to export your data in a CSV format.  For some of your standard, external reporting, the CSV export method will suffice.

A few common options for data warehousing are Oracle®, Teradata®, or a home-grown solution. Teradata® has been very active in the data warehousing space. Their Integrated Web Intelligence (IWI) platform includes pre-built data models to connect directly with the major analytics vendors. 

As with any data integration, there needs to be a common key within the datasets. A typical starting point for an integration like that of the above diagram could include purchase information (i.e. order ID, etc.) or personal information (i.e. email address, subscriber ID, etc.).

Data Feeds

When looking at data warehousing options, you also need to consider the methods for getting data out of your analytics solution. All of the analytics vendors, including the free vendors, allow for you to export your data in a CSV format. For some of your standard, external reporting, the CSV export method will suffice.

Application Programming Interfaces (APIs) and products such as the Adobe® DataWarehouse, powered by Omniture® or Webtrends™ Visitor Data Mart also allow for access to the raw data, which brings in much more granular data to merge with your existing data models for the warehouse. You can also set up data feeds from Adobe® SiteCatalyst®, powered by Omniture® that feed directly into your existing data warehouse.

As the analytics industry continues to head in this direction at a rapid rate, many of the analytics vendors are developing an “open” model for their data to be exported or fed from. The first step to designing an efficient data warehousing model is to decide what data you want to merge with your analytics solution. After you know what data you want to be integrated, you’ll need to make the appropriate tagging adjustments to your site if needed. These initial decisions will help you determine the best method to export the information.

How is the data used?

Simply bringing the data together is not enough. You will have a very rich dataset to interact with, and need to align resources against it to conduct analysis. From a design standpoint, you’ll have a marketing tool (analytics vendor) and a Business Intelligence environment (data warehouse).  As a result, the analysis tasks typically get broken out as follows:

  • Reporting and Basic Analysis
  • Deep-Dive Analysis

The reporting and basic analysis usually happens within the analytics solution, while the deep-dive analysis is typically performed on the data within the data warehouse. Using the data warehouse environment, business analysts will perform ad-hoc analysis in order to answer the more complex questions being asked by the business. 

Considering all of the tactics marketers execute, the proper analysis of these efforts needs to take place to determine their effectiveness and the subsequent business direction based on those findings. Utilizing a data warehouse with the appropriate data feeds is an efficient approach to gathering all of your data in one place. Essentially, adding data warehousing to your already expanding toolkit is an effective means to ensure a competitive advantage for your organization.

 

Please feel free to contact me directly if I may offer some guidance in your data warehousing efforts. Also, if you’d like to see a specific topic covered in an upcoming WebSight Newsletter, just let me know and we’ll work it in!

On a side note, I wanted to take a moment to point out the great things happening lately on the Stratigent Blog, Analytics Insights.  While the newsletter is a monthly occurrence, members of our client services team are sharing their thoughts, ideas, and case studies with the industry on a bi-weekly basis.  I urge you to take the time to check out the topics, and please feel free to comment and ask as many questions as you’d like.

 

 

By Bill Bruno
About the Author:

Bill Bruno is the CEO - North America, Ebiquity.

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