Intelligent Enterprise

Better Insight for Business Decisions

RSS
Webcasts
Whitepapers
Subscribe
Home

February 1, 2003

Actionable E-Metrics

An actionable online analytics framework is a key ingredient in any intelligent enterprise

by Allen S. Crane

Continued from Page 1

Because of their complexity, deep dive metrics are often prototypes for technology projects. You must carefully balance these requests so that the result analysis is actionable in its final scope, yet deliverable in the required time frame. Deep dive analyses frequently drive significant business changes because of their ability to quantify formerly invisible cause and effect behaviors.

An example here would be to determine specific opportunities for your customers by developing a report that shows the number of purchases for a specific product or stock keeping unit, divided by the number of visits to that product, and then plotting the results:

Low visits/low conversion: low interest or difficulty in finding these products on the site. If the path to purchase is easy to navigate and awareness is there, low interest could be a candidate for removal from the site.
Low visits/high conversion: the "surgical shoppers" who know what they're looking for. Consider bundling these items with other top-selling products.
High visits/high conversion: hot products, hot sellers. No need to waste promotion dollars here, because everything is selling so well already.
High visits/low conversion: opportunities galore. Better merchandising, competitive price position, and aggressive promotions should be seriously considered here.

Highly integrated and automated reporting. These metrics are known for their long-term/high integration effort. They derive from deep dives as well as the result of complex integrated reporting, which essentially says that the data would otherwise represent an incomplete picture unless reported in the context of multiple types of data (for example, clickstream data combined with financial and customer data such as online product conversion — units sold online as a ratio of online visits).

The development of highly integrated and automated reports is a collective effort among online analysts, business users, and the IT infrastructure necessary to deploy them. (See the sidebar "The Online Analytics Team.") Because these highly integrated and automated reports take so much effort, build as much data into the them as you can in order to answer as many questions as possible.

As I stated earlier, the ideal reporting of such data should be managed and developed together, and accessed by flexible reporting tools that can accommodate technical and nontechnical users. To that goal, flexible reporting tools such as Excel Pivot Tables and online analytic processing can accommodate both high- and low-level decision reporting. These tools make drill-down reporting easy, allowing significant insight to be distributed widely on a regular basis, while complex data can be synthesized into a presentable format that's as readily available as quality e-metrics. (See Figure 2.)

With the basic framework for online analytics in place, you now have a method for measuring the critical business drivers of online behavior.

Survival Instinct

A robust online analytics framework must be in place to provide quality analytic solutions to problems that would otherwise be invisible and unquantifiable: the integrated analysis of online and transactional data.

Inventing and building the framework is only the first step, however. Sustaining the process via quantitative management in the form of education, delegation, and evangelization is key to doing more with less, by improving processes, increasing analytic efficiencies, and leveraging resources wisely.

The ability to make visible and measurable that which is of utmost importance is crucial to e-commerce success and a critical component of e-business survival.

Allen S. Crane [allen_crane@yahoo.com] is senior manager of business process improvement for Dell Computer Corp. He has been involved in Web-based data mining and database marketing for more than seven years.

THE ONLINE ANALYTICS TEAM

Now that we've identified the various types of analyses, we can focus on the processes for getting the most out of the online analytics team.

The quantitative management approach is best implemented in phases, focusing first on inventing and building processes for getting the right metrics to the right people at the right time, and then on sustaining them:

Phase I — Inventing and Building

Rate This Article

Comments:

Optional e-mail address:

Consulting: Engaging with the business users to identify opportunities for analysis that can answer, "What do we know to be of utmost importance, but are unable to measure?" Such engagements lead to ...
Development: Creating a systematic, reliable, and repeatable process that will deliver the desired results of the consulting engagement, which will eventually need ...
Automation: This is the number one ingredient for doing more effective work with fewer people, in order to sustain world-caliber metrics with an ultra-lean staff. As much as possible, every process should be automated to minimize human intervention, process dependencies, and make increased use of communication and distribution channels, so as to prepare the way for ...
Education: Now begins the process of educating users on the data, where to find the results of the analysis, and how to approach online analytics in general.

Now that we've delivered on our promise of better data, we're ready to exploit the second phase of quantitative management to maximize individual efficiency and increase overall process speed.

Phase II — Sustaining

Education: As just stated, you begin with the education of users on the how, what, when, and where of the data. When you give the business users the tools to access the data, you increase their responsibility through ...
Delegation: At this time, users are familiar enough with the basic processes to get at all necessary quality e-metrics and reports: some may even run their own projectcentric metrics. These users understand how to find, access, and navigate reports and are versed in the process by which they can charter and prioritize (for the online analytics team) future deep dives and integrated reports. The best business users may even become mentors to others in their own groups on how to use the data, taking ownership of the process themselves to fetch and analyze the data and contributing to ...
Evangelization: The work to date has become so thoroughly instilled in the company that the business uses the data on a regular basis. At this point the self-serve nature of analyses and reporting is clearly understood in the organization, and the online analytics team can focus on further enhancements and next-generation analyses.

RESOURCES

Related Articles at IntelligentEnterprise.com:

"Beyond the Shopping Cart," March 8, 2000

"Bringing Them Back," July 17, 2000

"In the Bag," April 16, 2002