Last week, I attended the eMetrics Summit in Santa Barbara, CA. I spoke and helped facilitate a number of round tables. For readers on the other side of the pond, the summit’s European version takes place this week in London.
In one session, all conference participants were divided into discussion groups and asked to identify the top 10 Web analytics problems for the group. After an hour, each table nominated a representative to share their items.
The following is a master list that outlines the 22 issue themes that came up:
- Hiring people.
- Data proliferation: multiple sources, reports, and integration.
- Lack of standard definitions, benchmarks, templates, and expectations (see the new white paper on this that I coauthored with Guy Creese for the Web Analytics Association.
- Political issues: management buy-in; IT vs. business unit objectives; resources and reporting vs. analysis.
- Silos: multiple resources going in different directions.
- Accuracy: tool limitations (or perceived limitations), cookies, data misinterpretation, and defining acceptable discrepancies.
- Lack of actionable metrics.
- Identifying a few critical Web and success metrics.
- Understanding business goals well enough to know what to measure; and connecting Web metrics to business key performance indicators (KPIs).
- Measuring income/revenue versus loyalty metrics, or conversion versus lifetime value.
- Branding metrics.
- Segmenting customers online.
- Prioritize and determine the best opportunities to pursue.
- Having a process to create dashboards.
- Education for all team members throughout the organization.
- Defining functional roles for managers, analysts, and consumers of data.
- How much data should be kept.
- Six Sigma.
- Integrating with marketing and consumer data.
- Vendor and implementation over-promising.
- Inability to make incremental changes.
- To be successful in analytics is hard work.
Participating in this event got me thinking again about the common challenges people face, so I created a prioritized list of the top issues we see when we begin working with new clients.
Top issues that prevent organizations from getting the most value from their analytics tools are:
- Not focusing on the key business goals and KPIs when analyzing site performance and identifying opportunities
- Not having a framework or process to act on data
- Not understanding how to monetize and prioritize opportunities with the greatest potential to improve the bottom line
- Finding, hiring, and training qualified people on the correct use of Web analytics data (including training internal resources and team members on how to use the data to make decisions)
- Sharing and integrating meaningful data throughout organizations
I asked conference organizer Jim Sterne about the biggest difference he’s seen in questions and hot topics from last year to this one. His reply:
People are not as focused on why this is important as they are on how to be successful with analytics. The buy-in to Web analytics is so much more assumed this year. In years past, people’s questions and issues were more technically oriented. Now, people are more interested in how to make it an integrated part of their business and really use the data to improve the way their site is performing.
It will be interesting to see if these same issues are also the topics on the top of the minds of European attendees. I’m attending the London event and will write a follow-up column on the differences between North American and European participants’ concerns.
When measuring the effectiveness of discount codes, retailers often get it wrong. In this article, we'll look at how data-driven attribution can help businesses better understand where discount codes produce the best ROI.
Many businesses invest a great deal of time and effort into knowing their customers - but too few focus on understanding them.
Data. It’s the latest ‘buzzword’ in the digital marketing world when it comes to content.
Digital has quite forcefully overturned the entire media industry, causing even the most traditional companies to adapt or be left behind.