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Metrics for Success

Part 1 of 2
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There are many areas within an organization that interact with customers, suppliers, partners, manufacturing and management. Each interaction, communication, or process is an opportunity to collect data regarding the organization’s success, efficiency, performance or failure. In fact, the availability of sufficient data is not usually a problem; the challenge lies in the ability of the organization to format, analyze and understanding the available information in order to make proper use of it (Web Analytics, 2010).

There are two basic approaches to web analytics – web metrics, commonly used to measure the technological efficiencies of the web site and its associated hardware and software and web analysis used to determine the best customer relationship experience.

One specific area where a large amount of useful data can be obtained is the organization’s web site. Mark Volpe (Volpe, 2007) states that web analytics can capture information about your customer and their behaviors, the pages and products in which they are interested, where the customer is geographically located and how they were referred to your site. The number of visitor’s to a particular product may be an indication of a successful advertising or marketing campaign, or the result of sales interaction at a recent trade show event.

On the surface, generalizations can be made from this data with regard to customer traffic or exposure to your product or brand. But, with a deeper analysis (Mott, 2010) you can begin to develop a clear keyword strategy, use cloud tags to ensure the proper message is presented to your customer, check back-links and fully utilize social media to improve your reach. Understanding this level of information will enable you to fine-tune all aspects of your web presence to ensure you are getting the most value from your web investment. Effective web analysis will help management to make better decisions. Here, Gary Smith (Smith, 2010) outlines a seven-step process to apply analytics to decision-making:

  1. Define the problem
  2. Identify relevant factors
  3. Focus on data collection
  4. Model the solution
  5. Report the results
  6. Implement the decision
  7. Follow up

He continues, analytics provide a methodology for good decision-making and simulation can demonstrate the impact of those decisions before they are actually implemented (Smith, 2010). Based upon my experience, I would add three more steps to Smith’s process – 8. Analyze the outcome, 9. Adjust the Solution, 10. Repeat.

Hubbard Jordan LogoIt is important to note that there are many good tools available on the internet to help you to accomplish the task of collecting and analyzing your data; these include tools to measure inbound marketing, lead generation, public relations analysis, social media marketing, search engine optimization, web site design, and web analytics (Hubspot, 2010). Look for unique ways to turn your customer engagements into useful interactions and in part 2 of this article we’ll examine how Dashboards, APIs and Mashups can be used to improve accessibility to your metrics.


Hubspot, . (2010). Comprehensive web/marketing analytics resources. Retrieved from http://www.hubspot.com/web-analytics-marketing-hub

Mott, A. (2010, February 15). 4 simple ways to integrate analytics into your daily internet marketing efforts. Retrieved from http://blog.hubspot.com/blog/tabid/6307/bid/5499/4-simple-ways-to-integrate-analytics-into-your-daily-internet-marketing-efforts.aspx

Smith, G.. (2010, May). 7 Steps To Better Decisions. InformationWeek,(1265), 36.  Retrieved June 5, 2010, from ABI/INFORM Global. (Document ID: 2037029771).

Vaolpe, M. (2007, August 30). Marketing metrics: what to measure. Retrieved from http://blog.hubspot.com/blog/tabid/6307/bid/2178/Marketing-Metrics-What-to-Measure-in-Marketing-Part-I.aspx

WEB ANALYTICS: Success Stories. (2010, April). B to B, 95(4), S20.  Retrieved June 5, 2010, from ABI/INFORM Global. (Document ID: 2017006371).

Posted in Analytics, MROI, Web Technology.

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