Web Analytics Management

Metrics for Smart Content Management - Metric #5 - Navigation to Content Score (NCS)

NCS is a quick way to see if your visitors are spending too much time trying to navigate to content. The fewer pages it takes a visitor to content, or the more direct path, the better. NCS complements the Content Engagement Score (CES) which lets you know whether visitors are using the most important content on your site.

Navigation-to-Content Score: Compares number of navigation page views to all site page views.

Calculation: Percentage of navigation-type pages viewed compared with all content page views. This is derived from dividing navigation page views by all site page views. A lower percentage indicates a more efficient visitor interaction with the site.

Calculation Note: As with the other metrics in this series, you need to identify navigation pages and measure them separately. Pages include: 
o    home pages
o    portal pages
o    search engines
o    site maps
o    pages provided for navigational purposes

Example: There are 40,000 page views of navigation pages out of 150,000 total page views for the month. This equals a navigation-to-content score of 27%. Here’s how a report might look:

You can make this a much more valuable report by running this for different segments of visitors based on geolocation, domain, first time vs. repeat, as well as adding visit segmentation attributes such as acquisition source. If you use this with the segmentation, you’ll be able to see which visitor groups are having an easier time finding site content.
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If you're going to eMetrics Toronto, be sure to stop by Analytics in Real Life on Wed, 3/20. I'll be moderating a panel with Anuschka Van Dijke from KPMG and Nancy Duley, from American Society of Clinical Oncologists. They'll be sharing their stories on how to get resistant management to come around to the value of analytics. Hope to see you there...

 

 

 

 

Metrics for Smart Content Management - Metric #2 - Mission Critical Content Effectiveness (MCCE)

Let’s return to the topic of content as being a measure of success. In my last post on Task Completion, I said that only sites that sell advertising can consider content viewing to be a goal. I admit that I overstated this a bit…if you’re a non-profit or government site, this could actually be pretty important. 
For non-profits, content that leads to donor contributions, program funding, volunteerism, and advocacy is highly important. Government agencies, branches and divisions have clearly stated missions against which they are funded.  I think of this as Mission Critical Content.

What is Mission Critical content? Content that directly or indirectly supports funding and revenue. For example, showing donors the readership of articles that they’ve funded.

Defining mission critical content can be a tricky exercise because you have to draw a line…or else all content can be viewed as critical. Here’s a few ways to go:

• Conduct an analysis to determine the pages viewed before visitors go to top tasks.  These pages are influential enough to bring a visitor to the task completion.
• Review the site to determine the pages that were designed to communicate mission. On a government site this could include: About Us, Our Mission, News, or posts from the head of the agency.
• Review the results of the top 100 pages and downloads on the site, cull out the non-content pages (home page, search, portals, index, and so forth). Review the resulting list to determine which pages are central to mission.

Once you figure out the content that is mission-critical, calculating the metric is pretty straightforward.

Mission-Critical Content Effectiveness (MCCE): Measures the number of times mission-critical content, including video, is viewed or files are downloaded.

Calculation: Expressed as a percentage based on total views or downloads of the top content pages of the site that most relate to organization mission, divided by the total number of all site content pages (do not include portal, search, or navigation-based pages). A higher percentage indicates a better MCCE rate.

Example: During the month, there were 25,000 total page views and downloads of mission-critical content and 150,000 total page views of site-content pages, including downloads. This equals a mission-critical-content effectiveness rate of 17%.
 

Based on the data, it would make sense that you could run this report for specific segments, such as visitors from targeted geolocation, organization type, content interest and branded keyword acquisition.  It would also be highly valuable to run an analysis showing the impact of mission critical content views on tasks such as donation, article sharing, membership and other top tasks.

Metrics for Smart Content Management - Metric #1 - Task Completion Effectiveness (TCE)

Management of content proliferation is important of course, but in evaluating content effectiveness it is also important to consider the goals of the site. All too often we hear that “reading content” is a site goal. While that may be true if you’re selling advertising, it is generally not true for content rich sites. (For more on this, you’ll want to read next week’s post on Mission Critical Content)The purpose of content is to drive an action or a task, such as a purchase, event registration, donation, newsletter sign up, lead generation form completion, using a selection wizard and so on.

Measuring Task Completion gives you an initial sense on whether the web site is effective in getting visitors to complete the tasks on your site that are associated with business goals. Once you establish Task Completion Effectiveness, you can use this as a benchmark to determine whether you content management actions are working. The goal: raise the site’s Task Completion Effectiveness percentage.

Task Completion Effectiveness (TCE): Measures completion of site tasks associated with your goals and mission

Calculation: Expressed as a percentage based on the total number of task-completion page views divided by total number of site page views. A higher percentage indicates more successful task completion.

Calculation Notes: The completion page for each task will need to be identified, such as a “thank you” page or a submission confirmation.

Example: During the month, there were 500,000 total page views. Of this total number, there were 10,000 task-completion page views. This equals a task-completion effectiveness of 2%.

In the chart below, you’ll notice that we’re using “visits” and not “page views” as a baseline metric. Why? This report was done in Google Analytics. GA bases its metrics on visits and can not correlate events to page views. While we could have created filters to obtain the page view data, we opted to go with what GA does best. Using visits as an alternative still provides a reliable measure of task completion effectiveness. If we had done this in SiteCatalyst, we would have been able to correlate the events to page views.

 

 

In this example, the TCE has gone down slightly over a 3 month trend. Next steps should include reviewing the page view totals of the task confirmation pages to see which ones are experiencing declines, and then determining what factors are influencing the drop. Is it because there has been more content added to the site, thereby “diluting” the completion page views? Less marketing and acquisition driving towards task completion? Or, perhaps tasks are seasonally driven? Like any good high level “health” report, the TCE will drive additional questions that require you to do some analysis and investigation.

As I mentioned in my first post, this metric becomes even more effective through segmentation of audiences by geolocation, subdomain, visit frequency, and acquisition source.

Metrics for Smarter Content Management

In your organization, what stakeholder group is most under-served by web analytics?

Certainly not marketers and product managers…they are an analysts’ best set of friends because the reporting can show real ROI.

The user experience designer or information architect? No, they get data that can really help with site optimization that brings visitors to the marketing and product focused site sections. 

I’m thinking it’s the content manager…the operations guy/gal whose job it is to manage the production, updating, archiving and retiring of content. Is there someone in this role where you work? Maybe they are a subject matter expert who has control over a particular site section. Maybe they manage a team of writers whose job it is to crank out the content. Maybe they are your intranet managers…a part of the site that generally flies beneath the radar when it comes to analytics. Maybe it’s the overall site manager. And maybe it’s you.

In much of my work with US Federal government agencies, financial services, pharmaceutical companies and non-profit organizations, the content managers and intranet managers tell me that they just don’t get metrics that help them determine when it’s time to clean up, spruce up or get rid of content that is old and in the way.  As one weary content manager told me, “The goal is to publish, publish, publish…not analyze whether anyone looks at the content or what they do with it.”

While I hear some content managers say with pride that they simply whack all the pages that don’t get page views, I don’t think this is the whole solution to the pruning problem.  I think it makes more sense to first get an understanding around relative site performance based on goals as a first step, and then take a more surgical approach that’s based on prioritization. This may indicate that certain areas of the site need more than just an elimination of pages and in fact may need a new content strategy. This seems like a more constructive approach.

Over the last few years, I’ve been working with clients who want to go this route.  I’ve developed six metrics that you can start using to evaluate site performance and direct your content management efforts.  I’ll be sharing them over the next six weeks in a series of posts that I’ll be publishing here. 

Let me say up front, that creating these metrics requires some prep work, like categorizing content pages vs. navigation pages. It's actually a good exercise...like doing an inventory. The goal: Do the analysis, create the metric and develop benchmarks that provide you with a good idea of overall site effectiveness that can be tracked and explained over time.

…But First a Word About Segmentation

While the metrics stand on their own, it makes sense to create a series of visitor/visit segments based on Semphonic’s two-tiered segmentation methodology. After an extensive review of site objectives, goals, top tasks and target audiences, you can create key segments. The metrics that you develop can be applied to these segments to understand whether each of these segments may use content that others don’t. This helps you understand immediately whether specific content types that do not get a high number of views, may in fact be content that is important to a highly valued segment. In the table below, we have some examples of segments developed for a site that reaches health care professionals, researchers and the general public.

As you can see from these categories, combining the known visitor data with site behavior gives you an opportunity to amplify meaning from the basic elements of data you’d be collecting.

OK…so categorizing pages and segmentation... two keys to making these metrics work. If you can do that over the next week, you’ll be on your way to applying the first metric I’ll be talking about next Tuesday…Task Completion Effectiveness. 

 

42 Rules for a Web Presence that Wins

42 Rules for a Web Presence that Wins by Philippa Gamse is a slender tome that gets right to the point on developing practical web site strategy.  Targeted primarily to the SMB market, I think there’s a lot in the book that larger organizations, as well as non-profit and government web site managers could very well be reminded of when it comes to web site management best practices. Specifically, as my paraphrasing of Philippa puts it:

• 95 percent of web presences leave money on the table, and usually the owner has no idea.
• Most websites fail to make the emotional connections with visitors who are crucial to creating and sustaining meaningful…and profitable…online relationships.

Having been working in the internet space since 1991, Philippa knows what she’s talking about and has a great historical perspective that transcends “flavor of the day” points of view that tend to proliferate in the online world.

What I like about Philippa’s point of view as a web strategist is that she is really focused on the bottom line and results, so she’s a natural fan of digital analytics, dedicating an entire section of her book to “Measuring Results.” Not only is she an advocate for using analytics, she continually and consistently ties it back to deriving intelligence that can be acted on. I can think of more than a few digital analytics managers who could use some of what’s here for ammunition to use for convincing stakeholders and senior leadership that there’s more to life than high level traffic reporting.

You can find out more about 42 Rules for a Web Presence that Wins or order the book from Philippa’s site Websites that Win International. I definitely think you should check it out.

So, will Web governance make your digital analytics program run faster, jump higher and make you smarter?

To conclude this year's Profiles in Analytics - Does Web Governance Drive Analytics, I wanted to leave you with some general takeaways on how to move towards a better Return On Investment on your program...regardless of whether your organization is driven by a solid governance model or not.

So, will Web governance make your digital analytics program run faster, jump higher and make you smarter?

Like any programmer will tell you “it depends.”

The Profiles in Analytics research indicates that enterprise-wide Web governance is generally a good thing. The operational processes, the roles and responsibilities, and the overall standards that come out of governance help get everyone in an organization on board with implementing strategy. This appears to help the institutionalization of digital analytics throughout the organization.

There does appear to be a gap between where enterprise-wide governance ends, and where digital analytics governance begins. Whereas Web governance creates a space for digital analytics to grow, the depth of influence and making real change is only beginning.  The dichotomy between the considered priorities of digital analytics teams and the time spent on tasks shows that there are constraints that detract from analytics reaching its full potential as a way for organizations to learn from their experience in the digital channel.

How to clear the constraints?

• Invest in a Web governance process that provides insight on where digital analytics should sit in the organization. The level of influence that digital analytics has within the organization is tied to the office or department in which it resides and the influence of an executive champion in fostering cooperation.
• Conduct an audit of digital analytics operations to understand priorities, roles, responsibilities, tasks and processes. Senior management and digital analytics management need to be on the same page. There needs to be frank and open discussions about constraints and roadblocks that prevent digital analytics in being an effective voice in providing insights throughout the organization.
• Facilitate cooperation between digital analytics team and potential partners within the organization where there are opportunities to complement and leverage resources. Digital analytics programs that succeed depend on a network of resource support beyond the direct team. IT, Procurement, Marketing, Content Management, Business Intelligence, Finance and Operations are among the groups that a Digital Analytics team must interface with and work with to operate effectively. It helps to have these relationships facilitated by senior leadership so it is clear to all that analytics are recognized as a management priority.

This year’s Profiles in Analytics research suggests that it isn’t enough for organizations to pronounce that they are “data driven.” There is a lot more work to do around overall Web governance, development of analytics management expertise, and figuring out the best place in the organization for digital analytics so that it can have real influence.

Interested in continuing the conversation? Email me at [email protected].

 

Has Digital Analytics Made it into the Digital Production Lifecycle?

Continuing on with Part 5 of this year's Profiles in Analytics - Does Web Governance Drive Analytics...or get the whole analysis, survey data and digital analytics profiles at Semphonic.

Has Digital Analytics Made it into the Digital Production Lifecycle?

For all of the aspirations on how to create digital cultures and data driven organizations, when it gets down to basics, simply making sure that data collection occurs is a back burner issue. While Web governance oriented organizations may have processes in place and top down commitment to ensure that analytics is part of the development cycle, that it is only at around 60 percent says that there is room for improvement.

While non-governance organizations have roughly the same compliance, that there is such a high level of dissatisfaction with the process of implementing code changes, tells you something about an underlying issue that can sabotage whether accurate data is available when senior leadership wants to use it for appraising the role of the digital channel.

The Details

It stands to reason that organizations with established Web governance have more formalized processes around production of new content and applications for the digital channel, than organizations that don’t have strong governance.

Web development process. Nearly twice the number of organizations with governance includes digital analytics in the process “all the time” versus those that don’t, as seen in the chart below. Still, at 25 percent, there is clearly more work that needs to be done in this area. Interestingly, once you combine “all” and “most” of the time responses, you get roughly 60 percent in all organizations.

The research shows that there is still a great deal of work that needs to be done in the area of integrating analytics to the digital development process. While there is an increasing amount of project management best practices aligned with enabling analytics, analytics itself is often implemented after a project has launched. With the advent of mobile applications and social media initiatives, there are new opportunities for using analytics, and at the same time a repeat of the poor practices that have left analytics out of the fixed Web development process.

Implementing data collection code changes. The research showed the biggest difference between governance and non-governance when dealing with the process for implementing changes to data collection code, as seen in the chart below.

Anecdotal research tell us that the application of data collection code, considered to be the least glamorous element of analytics, to be a universal and significant hold up in the analytics process.  Because there are often other projects in the queue ahead of analytics, or analytics is considered expendable if content or applications need to meet a deadline for launch, data collection coding may be held up for weeks and even months in certain organizations.  

The “not acceptable” level of satisfaction among organizations without governance is a situation that if addressed, could show immediate improvements to the availability of analytics and potential value of metrics created with the data.

Next week: So, will Web governance make your digital analytics program run faster, jump higher and make you smarter?

Get the entire research at Semphonic.

Are Web Governance Oriented Organizations “Better” at Using Digital Analytics?

Continuing on with Part 4 of this year's Profiles in Analytics - Does Web Governance Drive Analytics...or get the whole analysis, survey data and digital analytics profiles at Semphonic.

Are Web Governance Oriented Organizations "Better" at Using Digital Analytics?

Enterprise Web governance may contribute to high quality digital analytics for the enterprise, but it does not guarantee success. At the same time, lack of enterprise Web governance doesn’t necessarily doom an analytics initiative to failure. However, programs seem to stop short on delivering all that they can deliver. 

In both cases, analytics programs appear to be primarily centralized entities that focus on dashboard development, reporting, providing analysis and recommendations.  While there is service to multiple stakeholders, the lack of time dedicated to training, encouraging self service and creating analytics standards that may be used throughout the organization fosters a somewhat isolated digital analytics culture. So, while multiple stakeholders are potentially served through distribution of reports, the value of what’s being conveyed in the reports may or may not be understood.

The Details

If you serve more stakeholders more efficiently does this mean that you are providing a high quality analytics product? Perhaps, but not necessarily. This is like saying that a Super Size meal is better than a 4 oz filet mignon. Quantity doesn’t mean quality.

To determine the level of quality, the research focused on three elements:

• Digital analytics program priorities of digital analytics managers
• Whether the program priorities were in line with senior management
• Priority tasks of the digital analytics teams

Top priorities.  In looking at alignment in priorities between digital analytics managers and their management, it appears there is actually more alignment among those in organizations without Web governance councils.

 

 

It is altogether positive that there is fairly strong agreement between digital analytics managers and senior management that the primary mission is delivering recommendations and analysis, even if it is not completely equivalent.

There is a fairly strong sentiment among senior leadership around the importance of developing dashboards and reports in organizations that have Web governance. This suggests that there are a number of senior leaders who believe that success in analytics is based on getting reports into as many peoples’ hands as possible. 

But there is more to this story…

Top tasks. When asked about the tasks the analytics team spends the most time on, there is an interesting disconnect from the goals and perceptions described previously…the prominence of implementation and maintenance of the analytics tools, as seen below.

 

Neither Web analytics managers nor senior leadership wants to consider that this is a top priority. However, lack of recognition of the importance of this task is akin to driving a car and not wanting to get it serviced regularly. Negligence can catch up in a number of ways. In the scenario of mutual denial, analytics teams may not have sufficient resources to provide more valuable insight from analytics.  However, the question is whether they make the business case to request these resources. Conversely, senior leadership may not be aware of the amount of time and effort required to maintain and improve the Web analytics implementation.

Finishing among the top three tasks analytics teams spend their time on, and what also doesn’t show up as a priority is “conducting ad hoc analysis.”

Like implementation and maintenance tasks, there would be agreement that this would not be a priority; however, because so much time is spent on this task, it takes away from potentially other more valuable tasks. It is worth noting that organizations without Web governance indicated that their team spends more time on this than any other task. However, this activity actually occurs more often as a second and third task than non-Web governance organizations.  Reasons for this can range from positive to negative: a focus on conducting deep dive analyses, “drive by” requests, weak or non-existent request management and evaluation process, or a need to improve quality and distribution of dashboards.

Regardless of whether the organization is driven by Web governance or no not, the tasks that could potentially drive high value throughout the enterprise are given the lowest priority among both Web analytics teams and senior leadership. These tasks also get the least amount of analytics team attention:

• Train and educate on the use of analytics
• Provide strategic direction on the use of analytics
• Create organizational analytics standards
• Developing culture of self-service analytics

Next week: Has Digital Analytics Made It into the Mainstream of the Digital Production Lifecycle?

Get the entire research at Semphonic.

Does Web Governance Encourage More Efficient Operation of Digital Analytics?

Continuing on with Part 3 of this year's Profiles in Analytics - Does Web Governance Drive Analytics...or get the whole analysis, survey data and digital analytics profiles at Semphonic.

Does Web Governance Encourage More Efficient Operation of Digital Analytics?

Digital analytics teams in organizations with Web governance appear to be more efficient in serving a larger stakeholder base than those that are in organizations without Web governance. While staff size appears to be somewhat smaller in Web governance oriented organizations, there appears to be slightly more management expertise.  The experience of digital analytics team management coupled with overall organization Web governance could contribute to a more process oriented approach to serving stakeholders. This would enable more stakeholders to benefit from the use of digital analytics services.

In addition, stronger management of digital analytics teams could also lead to a tighter definition of roles and responsibilities within the team. This could foster greater specialization among team members that could be manifest in more efficient completion of tasks.

The Details

Digital analytics teams in Web governance-oriented enterprises appear to serve more stakeholders than those organizations without Web governance.  As indicated in the chart below, digital analytics teams in organizations with governance appear to serve more stakeholders in all categories except one.

Of course, some of the difference in stakeholders served can be attributed to organization size…larger organizations have more stakeholders. However, the research suggests that the influence of Web governance on staff size and management experience also plays a role in how many stakeholders are served.

Analytics staff size. Organizations with Web governance had twice the percentage of large staffs with 10 or more people. However, these enterprises actually had smaller staffs than did organizations without Web governance in the mid-range (2-10 staff size).

Digital analytics management experience. From a title perspective, managing a digital analytics team is largely a middle management function, with Director and Manager the most frequently indicated titles.

However, it is in the area of both analytics and management experience where there are potentially significant differences between teams in organizations with and without Web governance.

Organizations with Web governance tend to have managers with more management experience than analytics experience. Organizations without Web governance tend to have managers with more analytics experience than management experience.  A significant plurality of organizations, 30 percent, has managers with both ten and more years of analytics and management experience.

This overweighting of technical and management experience appears logical in context with the characteristics of the types of digital analytics teams one finds in large and Web governance-oriented organizations vs. those that are smaller and not inclined to Web governance. Managers in large organizations appear to be more involved with  strategic and operational functions; in smaller organizations with less staff, managers are in a more practitioner/manager role.

Is there an approach that works better? If there is an organizational strategy to scale analytics across the enterprise, than having more experienced managers who know how to manage programs and staff and are comfortable interfacing with senior leadership makes sense.

 

Next week: Are Web Governance Oriented Organizations "Better" at Using Digital Analytics?

Get the entire research at Semphonic.

Does Web Governance Drive Digital Analytics?

Continuing on with Part 2 of this year's Profiles in Analytics - Does Web Governance Drive Analytics...or get the whole analysis, survey data and digital analytics profiles at Semphonic.

Larger Organizations Invest in Web Governance

By their nature, large organizations recognize the need to invest in operations governance as a means to manage processes and people efficiently.  Web governance is a natural extension of a governance culture that already exists.  Smaller organizations tend to have less process and a flatter management structure. The concept of Web governance may run counter to how the organization approaches overall operational processes. In addition, as smaller organizations tend to run leaner from a staff perspective, they may not have the resources to dedicate specifically to Web governance.

The Details

There is a relationship between investment in Web governance and an organization’s size and annual revenues. Larger organizations tend to be more inclined to have Web governance councils than smaller organizations, as seen in the charts below.

51 percent of the organizations with over $501 million in annual revenue have Web governance councils compared to 17 percent that do not. On the other end of the spectrum, 77 percent of the organizations with less than $500 million in revenue do not have Web governance councils compared to 24 percent that do.

The trend towards Web governance is also borne out based on number of employees. 66 percent of the organizations with over 1,000 employees have Web governance councils compared to 25 percent that do not and 44 percent of the organizations with 100 or fewer employees do not have Web governance compared to 11 percent that do.

 

Next week: Does Web Governance Encourage More Efficient Operation of Digital Analytics?

Get the entire research at Semphonic.