Value Creation Tactics for Web Analytics and Marketing Optimization

The holy grail of web analytics is to optimize the value derived from the technology, people, marketing and other investments that an organization makes in web. The following outlines the most important sequence of value creation tactics within web analytics.

 

KPI's are the quantitative measurements which reflect critical success criteria as defined by the stakeholders of a website. KPI's, if used correctly, will often act as the critical bridge connecting the abundant data and reports that web analytics tools generate with the ability to succinctly evaluate the performance of the web site, business process or marketing campaign that is being evaluated. Without KPI's it can be an overwhelming task to share relevant and actionable data with various stakeholders within an organization. Additionally, KPI definition acts as a critical enabler for the other value creation tactics listed below and many other advanced analytics techniques.

 

A web analytics dashboard is an instrument used to display and organize data in an easy to understand format. Making dashboards accessible outside of the web analytics application for executives is an important step. The most effective means of consuming web analytics dashboards for many stakeholders is to bring the data into a format that the stakeholder is already accustomed to utilizing. Most commonly, this is Excel but we have also been successful integrating this data into Intranet portals or even formatted for consumption via blackberry. Additionally, it is important to note that dashboards for this audience should be concise, containing only the absolute minimum of the most important KPI's. In addition, these reports should be accompanied by a succinct analysis of the data.

 

Proactive data analysis is a critical factor in gaining a consistent return on investment from web analytics. Without it, an organization will find itself perpetually in reactive mode and relying on static reporting to provide insights. Alternatively, organizations should proactively look for data that is needed to inform and guide the decisions of the organization with regards to marketing campaigns, site design, and business process.

One of our clients, an online retailer, is able to cite a very specific example. As part of its efforts to optimize conversion, the organization observed that conversion rates fluctuated greatly during the course of the day. Upon further investigation, the retailer was able to identify subtle technical errors as the root cause of this problem, impacting a significant amount of traffic and conversion. Without this proactive analysis of the data that focused on solving a problem that directly impacted the bottom line, this retailer may have never learned that this issue had existed nor been able to promptly address it. In gathering data for our recent research paper we found proactive data analysis as a fundamental building block of a strong web analytics program. For additional information on proactive data analysis and Stratigent's research see recent whitepaper click here. 

 

Adapt Continuous Improvement Process.

The final value creation tactic is one of the most important for the long term success of web analytics within an organization, the continuous improvement process (CIP). Organizations that can fully adopt the CIP become data-driven organizations and can reap the benefits of being able to guarantee incremental improvements to their sites, marketing campaigns, and online business processes. Below is a graphical representation of the CIP. 

 

 

The most important aspect of the CIP is that data must be acted upon and the results measured. Next, results must be analyzed to determine the effectiveness and future actions to test identified. Acting on the data should be an ongoing process towards continuous improvement of the website.

One residual benefit of adopting the tactics outlined above is that rapidly delivering measurable ROI on web analytics initiatives will help to achieve the needed buy in at an executive level. The executive level buy in will only help to achieve the funding and resources necessary to progress the use of analytics to include some of the commonly publicized techniques such as multi-channel data integration, controlled experimentation, and automated personalizing. So, resist the temptation to jump over the basics into the most exciting and cutting edge techniques until the right foundation is in place and current opportunities have clearly been maximized with these basic techniques.