Jim Sterne and the Web Analytics Association Need Our Help!

Jim Sterne the president of Target Marketing as well as the Chairman for the Web Analytics Association (WAA) is looking for some help from the analytics community at large.

Jim has posted a survey and is attempting to find out which channels marketers and analysts are measuring as well as how they plan to use the data for optimization. As this information is being collected by the WAA Chairman, you can bet that it’ll be used for good! I’d even expect seeing the WAA using the data collected to optimize their offerings to members in 2008!

I’ve personally taken the survey and it used all of maybe 2 minutes of my time.

Click here to take the 2 minute survey!

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The KPIs of SEO

SEOMany companies are taking a much more serious look at Search Engine Optimization as an effective growth technique for their websites. But after investing in an SEO exercise, how will you determine if your efforts paid off? SEO engagements with top firms can be very pricey so when someone finally asks, “Hey – that Google thing we did back last month…how did that work out?” wouldn’t you love to be ready with a detailed 1-page report? :) Of course you would!

My SEO expert colleague Nima Asar Haghighi (check out his blog) and I have been trying to determine what are the Key Performance Indicators for measuring Search Engine Optimization and here’s what we’ve come up with:

Percentage Change in Visits/Visitors from Organic Search

Although probably the most obvious indicator, this metric is by far the most important. After all, if your SEO efforts didn’t permanently end up in an increase in the number of visits or unique visitors (depending on your analytics tool’s abilities) then those efforts weren’t worth all that much!

Percentage Change in Number of Organic Search Keywords

By measuring the percentage increase in the total number of organic search keywords to your website, your essentially evaluating if your SEO efforts resulted in search engines assigning a broader set of keywords to your content. The benefit of this? A broader set of keywords means your visitors have to be less precise when trying to find your site and what you offer.

Where to find organic keywords in Google Analytics

This is actually a good time to re-examine the concept of the long tail again for those who are unfamiliar as this metric and ones to follow measure the effectiveness of lengthening the long tail.

The Long Tail

The long tail in our case, measures those many, many, many organic search keywords that drive a fairly low number of visits or unique visitors to your site. This is a pattern that happens naturally as for most sites, the keywords that really drive traffic to your site are branded, outside of those though there are a number that drive traffic with many variations. Consider the article I have on installing Google Analytics. Google and Yahoo both drive a fair number of visits to this page, but take a look at the many subtleties in terms of the keywords visitors use to access the same content:

  • google analytics install
  • google analytics installation
  • installing google analytics
  • google analytics cross domain
  • google analytics multiple domains
  • and so on and so on…

Each of those keywords above didn’t drive much traffic, but they make up that long tail which is vitally important! Why? Because SEO isn’t about optimizing for the keywords visitors already identify with your brand, SEO is about optimizing for keywords that visitors didn’t even know related to your site.

Now that we’ve all got why optimizing the long tail is important, let’s move on!

Percentage Change in the Number of Entry Pages

Similar to an increase in the number of organic search keywords, with an increase in the number of entry pages we’re looking at long tail success again.

How to find the number of entry pages from organic search in Google Analytics

Specifically with this metric we’re trying to determine, “How effective have we been at opening up our entire site to the world?” Assuming you’ve optimized your site correctly, you should be seeing a significant increase in the number of entry pages as search engines begin including more and more pages into their indexes.

Percentage Change in the Number of Brand Keywords

Similar to both of the above metrics, the objective of this one is to ensure that new keywords you associate with your brand (or just your introductory brand keywords if it’s a new business starting out) are being associated with your site.

When Nike launches a new men’s fitness shoe for example on their site I’m sure (or actually I hope) that they ensure to perform some optimization techniques in hopes that the name of the new shoe for example begins showing when visitors begin search for the product by name.

As Nima would say, you’re measuring “building brand through the long tail”. :)

Bringing it all together…

Finally bringing it all together, a very simple dashboard report might look something like the table below.

Before SEO (Jan 1 – 15, 2008) After SEO (Jan 16 – 31, 2008) % Change
Organic Search Visits 5,000 6,000 +16.7 %
Organic Search Keywords 1,234 1,658 +25.6 %
Number of Entry Pages 500 658 +24.0 %
Number of Brand Keywords 20 21 +4.8 %

The last note I’ll speak to here is that we’ve done a good job of picking a few metrics that allow us to measure our success in driving traffic to the site organically but what we’re not measuring is what that traffic does!

While Google may be able to drive traffic to your website, the traffic isn’t worth anything to you if they: bounce / never generate leads / never purchase a product / never tell a friend / never [ Insert your conversion event here ].

I’ve chosen to steer clear of mentioning this only because if you’re strictly evaluating SEO, you’re evaluating how your efforts have paid off in driving traffic to your site. After that, it’s the site’s job to give your visitors a reason to stick around which is really a separate topic altogether (optimization!).

In any case, I hope that helps at least some of you with understanding what to measure before heading into a costly SEO implementation. Happy optimizing!

Footnote! Recently read an additional article on KPIs of SEO that you should definitely have a peek at, a few new ones that you can choose to add to your SEO dashboard!

http://www.netconcepts.com/natural-search-kpis/

Posted in best practices, kpis, suggestions | 4 Comments

2008 Predictions: Web Analytics

Lilly pads!Yes yes, I’m taking a page from my colleague Avinash Kaushik, but I’m certain that he won’t mind too much :) .

  1. Video Analytics: as more media sites turn to this medium as a fundamental way to increase revenue by delivering higher CPM ad impressions via pre-rolls; companies will need to know which videos are working, which aren’t and how visitors are interacting. Keep a very close eye for Omniture, Coremetrics or WebTrends making an acquisition of Visible Measures – a company specializing in measuring internet video (and doing some very cool things in this area), even in its distributed form (i.e. embedding YouTube videos). Companies have made inroads here, but Visible Measures is really taking it to the next level.
    Check out a great demo put on by Matt Cutler (VP, Marketing) of their software: http://www.demo.com/demonstrators/demo2008/124778.html
  2. Web Analytics Job Market Explosion: the industry is mature enough and there are plenty of people getting their feet wet with analytics that more and more organizations will begin justifying full-time resources for analytics. I expect most organizations (as to be expected) will start small with one analyst (or analytics specialist) and once the model has been proven, blow out resources accordingly to the size of cross-functional departments (see Avinash’s book on centralized decentralization).
  3. Vendor Consolidation: Omniture certainly had quite the year for this in 2007 but I think we’ll see this continue with the other vendors. As free tools like Google Analytics and Microsoft Gatineau become more and more sophisticated the enterprise level vendors will have to have a diverse feature set available to sweeten the offering. In some ways Google Analytics actually has a more thought out feature set and interface. I’ll commend Google’s team till I’m blue in the face for having an interface that I truly believe to assist in making analysis easy and data actionable as well as the technical foresight I’ve seen with their event tracking model. If you haven’t read up on it yet I strongly suggest it!
    Innovations like these are precisely what keeps a warm burner under the bums of enterprise vendors to step up their game and differentiate their product offering.
  4. Quality Assurance: for awhile now I’ve always been amazed that companies don’t have analytics QA built into their processes and that analytics vendors don’t push this phase as part of their implementation process. At last year’s eMetrics summit in Washington D.C., a company called Maxamine made significant inroads by showcasing a tool that can be used to validate your entire analytics install. Watchfire also offers a similar service and I wouldn’t be surprised to see them making a trip out to eMetrics in Toronto! :)
  5. Bye bye Licenses Hello ASPs: As more and more organizations bang their head against the wall and come to the realization that the ownership of web analytics really doesn’t belong in IT, people will start whispering the words “ASP”. Clearly this is going to only really going to affect one of the “big three” vendors but it’s a way that more and more companies will go, why? Because businesses want intelligent insights, not reports. Screaming at your IT professionals to ensure that a top pages report is being produced everyday is not making the most of a web analytics investment.

Thoughts and opinions are always welcome!

What do you think will be the top things to expect in web analytics in 2008?

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Put A Little Web Analytics Into Your Projects!

If you’re one of the many organizations moving toward a more project-based approach to operations perhaps even with a Project Management Office (PMO) then this post is for you!

It’s often difficult to fully integrate a web analytics methodology into projects and some companies even have to abandon trying.

It isn’t that anyone has a secret hate-on for measurement it’s because of Eric T. Peterson’s now famous catch phrase: “Web analytics is hard!”

Let’s assume that you have a “typical” project process that looks something like the one below:

Sample Project Process

Initiation

Initiation (also known as kick off)During this time period the PM group is engaged by a business unit looking to get some kind of initiative in the pipeline. Often at this time, a business unit may not know exactly what what the final project will look like, but the basic ideas are there for what they’d like to accomplish.

It’s at this point however when analytics can play a very large part! The designated analytics person on your team (assuming of course you have one) can play a consulting role here.

Depending on the site type (content-based, e-commerce, lead generation / marketing), any initiative should be tied towards improving the key performance indicators of the site. If, for example, we’re dealing with a content-based site and the strategy is Growth, Loyalty and Engagement then it’s the job of an analytics resource to do a quick check that the current initiative maps to what the data is showing.

If for the past few months, engagement metrics have been in serious decline and the initiative proposed is largely targeted to bringing in new visitors (growth), then perhaps there should be some discussion at this level of the project before serious time and money goes into it any further.

Plan

Plan, plan, plan!After the initiation phase, it’s assumed that everyone has signed up for the project (no turning back now!). Your analytics specialist (which may be the current reader) has given things a look and decided that the initiative makes sense in light of current trends exhibited by key performance indicators.

As per usual in this type or project process, Business Analysts normally get involved to start documenting requirements usually in the form of a Business Requirements Document (BRD). The BRD is largely meant as a communications tool where by all stakeholders on the project can clearly understand what’s required of the final outcome including a broad list of the feature set planned by the new initative. Some examples of what typical outcomes may be:

  • Redesign tool/site with an easy-to-use and engaging interface
  • Findability – Improve findability of pages from Web search engines
  • Improve browsing experience of the site
  • Increase revenue

None of the above goals are bad per say, but how will we know that we’ve had any success towards them when the project is done? For example, is there currently any way to measure that “Findability” has improved by 10% for example?

Champagne - It’s Party Time!!And what is the goal threshold anyway – when will the project team know to head out for champagne and celebrations? Is it a 5%, 10%, 15% increase in “Findability”?

Clearly what we’re lacking here are clearly defined project success metrics as well as goals for those metrics. Here are a few reasons for why success metrics and goals are a good idea:

  • Defined metrics and goals that are signed off on by stakeholders mitigate the risk of those questions at the end of a project when people begin mentioning those pesky words, “Return on Investment”
  • Defining goals for success metrics forces stakeholders to have realistic expectations for what the project will and won’t do from a results side, not a feature side
  • Provide an easy way to communicate the success of your project to stakeholders

So let’s take two of the goals listed above and try to make them measurable!

Redesign tool/site with an easy-to-use and engaging interface

Notice that this goal already mentions two “fuzzy goals” being a tool / site that is “easy-to-use” and “engaging”. It’s the job of your web analytics resource to:

  1. Translate “easy-to-use” and “engaging” into metrics and
  2. Help clients set goals for these metrics

So let’s get to it.

Survey Dude!“Easy-to-use” is a difficult goal to evaluate using the traditional web analytics metrics so instead, let’s employ the use of a qualitative survey here. Before making any changes to the tool, I would employ the use of any of the online survey providers and place a survey either throughout the entire site or tool being redesigned. Although surveys of this sort can be farily complex, let’s assume its a few simple questions (*Note: I am not a professional survey designer, I’m sure there’s tons of bias in the questions below!):

Q1: “How would you rate this website in terms of ease-of-use?” 0 – not easy to use, 1 – somewhat easy to use, 2 – easy to use, 3 – very easy to use

Q2: “Were you able to complete your task on this site / tool easily?” Yes / No

Q3: “Would you recommend this site / tool to others?” Yes / No

This simple qualitative survey now provides metrics that I can directly apply to understand the success of the project in terms of improving ease-of-use:

  • Average point score from Q1
  • Percentage of Yes responses Q2
  • Percentage of Yes responses Q3

That covers “ease-of-use” now onto engagement. Although many people will define engagement very differently, I feel a good number of generic metrics to group together in order to get a general sense of engagement are:

  • Average pageviews per visit
  • Bounce rate
  • Average time on site

Note: In addition, I would actually recommend adding in certain conversion events you may already have tracked in your tool. For example, signing up for an e-mail newsletter or sending a page to a friend are, in my opinion, also key examples of engagement metrics.

Another Note: If you’re only evaluating a tool it can be tough to grab something like “average pageviews per visit” for just the tool itself. What I recommend in this case, is work with your analytics vendor (or a consultant in the case of Google Analytics – I strongly recommend the guys at EpikOne) to create a segment based on all visits that used the tool in the course of their visit and then pull your regular engagement metrics for these visitors.

Segmentation in general is a key way to evaluate one area of the site in terms of its influence on other areas. Once a segment of those visitors is created, you can compare your key performance indicators of that segment versus the entire site and see if the area is worthwhile.

Setting goals for the above metrics is an exercise that requires involvement of your client group. A great idea at this point however is to think about the monetary implications (if any) of the goals you’re setting. For a site with paid advertisers, expectations around average pageviews per visit will seriously affect ad inventory levels and revenue for the site. Just something to keep in mind!

Findability

Magnifying GlassYou’ve got to love that word don’t you? How do we measure “findability” in the context of: “Improve findability of pages from Web search engines”?

Most analytics tools out there should have the ability to segment your visitors (or visits) by traffic source and the fancier ones can do groupings like “organic search”.

If you’re in the lucky group that has a tool that will group your search results in this way, then the simple success measure is “Percentage Growth in Organic Search Visits / Visitors (depending on your tools capabilities)” defined as (Total Organic Search Visits After Project – Total Organic Search Visits Before Project) / Total Organic Search Visits Before Project.

The timeframes for “Before” and “After” project are arbitrary but they have to be the same length and I wouldn’t recommend anything less than a month in order to allow search engines to properly reindex all your content.

Hopefully those above examples gave you a bit of an idea of how to translate a fuzzy goal into a definable metric. There’s no exact science to it so I just recommend relying on experience to improve on it!

Design

In the design portion of a project a Functional Requirements Document (FRD) is produced and teams fully plan and develop how the solution will look with illustrations documents such as wireframes.

Detailed WireframesIt’s important at this stage that the analytics resource works with technical personnel (either your vendor or internal resources or both) to identify any gaps between data you’re collecting now and the data you need to collect for your success metrics.

In some cases, you may be required to make changes to the site before the site launches in order to have a benchmark to compare metrics before and after launch. This is an important reason for web analytics personnel to be involved as early as possible in projects. It’d would be a pain to delay a project due to measurement restrictions.

I’d also recommend incorporating any technical instructions related to measurement in the technical document for the project. Creating separate documentation just adds one more thing for your developers to have to refer to when coding so why not make their lives a bit easier?

Develop

Development is a low key time period for an analytics resource. The main job here is to develop the test cases required to ensure that any technical changes recommended in the Design phase are working. Outside of that, there’s a little break here. :)

Deploy and Test

Another hopefully low-effort time for an analytics resource. Ideally the solution proposed in the Design phase worked without any problems and passed quality assurance (QA) test cases created in the Development phase. If not however, revisions will need to be done to documentation and coding iteratively until the solution works and key metrics are able to be captured.

Close and Maintain

Finish LineThe close and maintain portion of the project represents the end of things for most resources, but not for an analytics person!

During maintain and close the analytics resource is finally able to have a look at the changes in key success metrics and perform the most valuable contribution to the entire project cycle.

Reporting on the success of the project is relatively easy as the key measures of success have already been determined, but where the true value comes in of having an analytics resource on the team is in the analysis and optimization.

During this phase, I strongly recommend the creation of a Key Insights Analysis Document. This document reports on the “Before and After” of all the key success metrics previously determined but also includes an analysis section of the results observed as well as suggestions for further optimization.

It is the Key Insights Analysis Document which should communicate if the project overall was a success or not and what lessons were learned. Did an assumption about a tool’s effect on a metric like Average Pageviews per Visit prove to be false? Is this information properly communicated to both the project team and the organization as a whole? A well written Key Insights Analysis Document should be able to spell these things out in order for anyone to be able to pick it up and quickly understand what worked and what didn’t.

In addition to the Key Insights Analysis Document, the analytics resource should produce a Web Analytics Operations Document. This document should act as a living guide for operations teams to be aware of any technical changes made to the site that need to be maintained for further updates.

Occasionally collecting specific data requires some pretty nifty hacks and once their on the site, there’s no guarantee that they’ll be maintained so that site owners can monitor these metrics after the project is over. The operations document should red flag what was performed, how it needs to be maintained and who to contact if anyone isn’t sure.

Wrapping up…

Incorporating web analytics into web projects isn’t always easy, but if you can’t prove the value of a very expensive and time consuming project, then what is the point in doing it in the first place?

In addition, being far more organized on projects like this allow you to quickly communicate successes and failures so that an organization as a whole doesn’t end up making the same mistakes twice.

First thing’s first though…you’ll need a dedicated or semi-dedicated web analytics resource so go out there and hire one!

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The Impact of Cookie Deletion

Cookie!I’ve come across a comScore study released in June of 2007 which attempts to measure the impact of cookie deletion on what they’re calling “site-server” and “ad-server” metrics. I’ll let everyone download / read the whitepaper at their own leisure but I’ll summarize their conclusions and implications:

Conclusions

  • 31% of US users delete their first-party cookies in a month
  • First-party and third-party cookie deletion rates are generally similar
  • Computers with active security programs (i.e. Mcafee or Norton) experience somewhat higher cookie deletion rates, but nothing incredibly significant
  • “Serial cookie deleters” (users who often delete cookies after every browsing session) have a profound impact on inflating analytics tools that use first / third-party cookies for tracking (account for 7% of computers, but represent 35% of observed cookies)
  • Analytics tools using cookie-based tracking measures can overstate true number of unique visitors by a factor of up to 2.5

Implications

Cookie deletion leads to following inaccuracies in site-centric measurement:

  • Overstatement of unique visitor counts
  • Understatement of repeat visitor counts
  • Understatement of conversion rates

Mike’s Take…

Alright, we’re all aware (or should be by now) that cookie deletion represents a problem for the Google Analytics’, Gatineau’s, Coremetrics, Omniture’s and WebTrends SDCs of the world, but studies like comScore’s don’t mean we all should start running for the hills just yet.

The number one problem with studies such as these is it truly takes people’s eyes of the ball of what they really need to be paying attention to trends! What the comScore study notes (which is important) is that there’s a level of inaccuracy about measurement tools that use cookie-based tracking. But I would argue that web analytics isn’t about accuracy, it’s about reliability! Say I know for a fact that 31% of my audience on average possibly deletes their cookies per month every month. Then what I have is a predictable margin of error. If I know this is the behaviour my audience exhibits then I can just note that in an analytics report and be on my way. Thus, web analytics is still reliable.

And folks here’s the plain and simple truth: when it comes to the Internet, there really isn’t one best way of tracking your visitors.

comScore uses a panel to capture its measurements. You sign up to be a part of the panel, often because of an incentive like a contest or in exchange for antivirus software. In exchange for whatever the incentive is, comScore is allowed to place What are the big problems already that we see here?

  1. By definition, with comScore you are only sampling an audience. Samples are great and there are plenty of statisticians who’ll argue to tell you how valid they can be using some pretty advanced mathematics. But as they would also tell you, sites require statistically significant audience sizes in order for a random sample of the audience to accurately represent the whole – this unfortunately is not the case for many small guys. It’s been said that in Canada, don’t even bother with comScore unless your audience size is above 100,000 monthly uniques (I personally think you’d need around 500,000).
  2. Getting people to do anything with narrow incentives automatically creates a bias in a sample. There’s a certain type of person who goes for these incentive based activities, I personally would never be one of them and I’m sure I’m not alone. Therefore, you’re only getting a certain segment of your online audience when they visit – that’s no good!
  3. Downloading anything onto a computer is traditionally a personal computer thing only – not something you do at work. Therefore if you’re a site that relies on a business audience (Toronto Stock Exchange for example) then you might be stuck. Yet another bias!

And yet, many people rely on comScore (especially advertisers!) and I can’t say that I blame them, after all, what else is there (in Canada) for competitive analysis?

The point is, comScore itself has some very large troubles too but I won’t bash those guys either. When it comes down to it I always tell people one thing, in what other marketing channel could you ever get the depth of information that you are able to get when using a web analytics tool? It just doesn’t exist…that’s partially why so many marketers are looking to spend more online, you can finally directly prove the worth of marketing efforts with these tools.

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