Ideas for Effective Analytics Strategy

Many websites have Google Analytics setup, but the majority are not making the most use of these resources. Often, analytics is an afterthought or is dismissed as merely a way of tracking the number of visitors on a given day. But there is so much more actionable data to be had with a little time and forethought.

In this post, I am going to talk a bit about analytics strategy and then provide examples of actionable data that can be tracked and how it might be useful.



At a very high level, start by considering the goals of your site and how those map to your analytics tracking. Most eCommerce and Software as a Service (SaaS) businesses, for example, want to generate a purchase transaction. Services businesses such as consultancies may be looking to generate higher funnel leads that will eventually lead to contract for service offline, at a later time. Still others, such as news content sites, might define a goal as keeping a user on the site for a minimum amount of time or having them return a specified number of times within a month. Whatever your goals are, it is imperative to define those clearly – ideally before you even create your website, but certainly before setting up an analytics campaign.

Each of the above goals is possible to track using custom events, goals, events, and funnel tracking in Google Analytics. There’s even a way to setup custom widgets on the dashboard and have reports and alerts emailed to you on a schedule as well, making it easier than ever to access highly meaningful performance metrics. There really is no excuse to still be using a tool as powerful as Google Analytics to merely track your page views day-to-day.

Define Your Goals

What should we be tracking? Let’s take an eCommerce site as an example, since it has the most sophisticated and well-defined conversion funnel, and we’ll demonstrate the Key Performance Indicators (KPIs) at each major step of the funnel that we might consider tracking. This should give a good idea of what’s possible and get the creative juices flowing a bit. There are three major steps to the typical eCommerce funnel with an optional fourth step. Let’s walk through each one:

i. Acquisition

We start by looking at how traffic was acquired. How were users sent to your website and from where? Although you may never attain 100% visibility, you’d be surprised just how much visibility you can achieve. You probably already know this through the standard analytics reports: that you can see keywords that were searched and on which search engine. Google also makes it very easy to integrate AdWords data to see exactly which AdWords campaigns are generating traffic and which are converting. Google also owns Feedburner, which provides yet another trackable channel for which you can directly attribute traffic.

Tagging is possible for anything outside of the Google-sphere, making it possible to add (utm) tags to the querystring of any URL you embed into an email campaign, social campaign, or banner marketing campaign. For many people, that’s the point where the light really goes on, realizing that you can tag and thus achieve almost complete visibility of traffic sourcing, and factor all of this into your integrated analytics campaigns.

An example of using UTM tags to track external click events:×250-banner&utm_campaign=myproduct

With all of these tactical tracking opportunities in mind, imagine the possibilities. Here are just a few examples of valuable KPI data points you might consider tracking as part of acquisition:

  • Organic Search (SEO)
  • Paid Search Marketing (SEM)
  • Social Campaigns
  • Banner Campaigns
  • Links from External Sites
  • Links from Online Videos
  • Email Recipients
  • RSS Subscribers
ii. Engagement

Once you’ve got the attention of your users, are you effectively driving that traffic toward your funnel or toward micro-conversion events that help to keep them engaged? Even if the visitor does not purchase something today, it can still be extremely useful to capture an email address, get them to subscribe to an RSS feed, or any number of other activities that will keep the communication channels open and continue to educate and qualify them in preparation for a later purchase. This is particularly true of larger purchases or services, which require longer time for transactions to mature.

To begin thinking of KPI data points in the engagement segment of the funnel, consider what sort of user activities you could be implementing and the corresponding micro-conversion goals you could be setting. This may also help you realize that you could be doing more to engage your users. Here are a few examples of good engagement goals to track:

  • Account signup
  • Email signup
  • RSS subscription
  • Saving product to wishlists
  • Adding item(s) to cart
  • Contributing product ratings or reviews
  • Watching video
  • Content interactions (e.g. photo zoom, faceted search attributes, etc.)
iii. Conversion

You’ve made it from acquiring to engaging, and now you’re finally converting that prospect into a paying customer. This is the point at which you’re finally able to attribute cost and value to all of your efforts and begin making some decisions.

If you’re spending money on paid search campaigns, you can see the precise value of each ad campaign, if you’ve integrated conversion tracking. You’ll also be able to see percentage of conversions for other non-integrated channels such as SEO, social, and banner re-targeting. Plus, other details such as average order value and average time to complete a purchase, and you can segment those macro statics by channel to derive insights such as paid search converts with better velocity than social.

The KPIs to consider tracking at this funnel step are:

  • Return on ad spend (ROAS)
  • Return on investment (SEO, Social)
  • Revenue
  • Average order value
  • Average time to complete order
  • Average visits before conversion

* Consider segmenting all of these KPIs by ad channel

iv. Loyalty

All of the above analysis can be very valuable, but is a bit myopic if take in isolation, particularly if you have return visitors or a more sophisticated sales and marketing operation that involves multiple touches prior to conversion.

Consider the more complex scenario of a prospect who visits your site, then sees retargeted banners on other sites (reminding them of you), so they sign up for your newsletter and eventually convert into a customer. And what if they come back a second or third time thereafter and purchase again. How do you attribute the sales? Does it all get attributed back to the ‘first touch’ interaction with one of your ads?

The new version of Google Analytics (v5) introduces the idea of a multi-channel funnel, which helps to address this issue. With a series of new reports, you can finally see which touch triggered the transaction, but you can also see the path and which other touch points may have assisted with that transaction. This can go a long way toward helping to understand the less tangible value of the early-stage-funnel ‘assist’ campaigns. For example, the social channel has notoriously low direct conversion attribution… But with multi-channel attribution, you can finally begin to see its role in setting up other activities later down the funnel to trigger a transaction.


Putting it all together

Hopefully, you are seeing the sort of user behavior and ad campaign performance insights you can mine from Google Analytics, if you take the time to define a strategy and properly implement the tracking and reporting. And that really is the key take away: analytics is a powerful tool that will provide substantial actionable data and enable you to make much smarter marketing budget decisions; but it requires clarity for your goals and how you drive traffic and engage your users. Without that clarity, you do not have a road map to setup a meaningful analytics campaign. Clarity and discipline is where many businesses get stuck and why so few practice meaningful analytics, outside of the major enterprise. But if you have clarity around your traffic generation and engagement activities and goals, you can generate highly informative and actionable data to super charge your marketing efforts, and that is a real competitive advantage.

Article originally published at SEOMoz:
Actionable Ideas For an Effective Analytics Strategy


The Power of Visual Data

Data visualization means taking a set of data and representing it with visual modeling,in a way that makes it easier to understand and observe patterns.  In its simplest form, it can be a 2-dimensional chart or graph that represents a single dimension or a dataset. Or you can extrapolate complex representations as well. But what is the real value of modeling your data visually?


Socializing Data:
While attending a recent Digital Analytics Association symposium, there were a couple presentations on the importance of good visualization of data. They discussed how the data was better understood and more easily socialized within the organization, simply by making it more accessible. Then there are those infographics taking the Internet by storm, which provide a fun and easy way to demonstrate interesting statics and figures.

Clearly people love consuming charts and graphs more than reams of data.  But its more than simple enjoyment; by graphically modeling the data, you’ll often uncover important patterns that might have otherwise been missed.

Data VisualizationObserving Patterns:
A great example is the new flow visualization tool in Google Analytics (version 5).  It is now possible to observe how users and macro groups of users are flowing between pages. you can even apply flow visualization to a segments and compare how that one subset of users flows differently from others.

Imagine taking a segment and observing how they might flow through your site differently.  For example, try comparing the flow of visitors from Canada compared to the US.  Or more interestingly, consider segmenting around traffic you’ve tagged for different campaigns or marketing channels.  As you begin to observe the differences of flow between paid search (SEM), organic search (SEO),and social channels, you’ll really appreciate the power of this new resource.

Diagnosing Bottlenecks:
Another significant benefit of flow visualization is the ability to see non-symmetrical dropdown from one step to the next, along your flow, which may implicate a bottleneck that is negatively impacting conversions.

For example, imagine your you have 500 users enter your eCommerce catalog, 50 of them engage with the shopping cart, but only 1 of them continues on to the checkout form.  You might already know that industry standard would be for 2% of those 500 users (10 users) to complete a transaction and by contrast your number is very low.

By using flow visualization, you have relatively painlessly identified a bottleneck in your funnel that may have gone unrealized for years otherwise.  You’ll need to begin looking at usability and conversion optimization to correct the issue, but you’re well on your way to increasing return on ad spend and revenue generation by a considerable margin. If you’re able to increase your conversion rates and flow to industry standard, you may in fact increase your revenues by 10x!

Data visualization is a powerful tool for socializing and communicating data, observing patterns and diagnosing abnormalities.  Inforgraphics and executive dashboards are popular examples of how data can be better socialized through visualization and Google Analytics provides an excellent example of the power of visualization, to drive pattern recognition, diagnostics, and action.

Consider what else might be possible with data visualization of your data.  How might you be able to instigate action within an organization, uncover important patterns, or drive more sales, simply by presenting the data differently?

Landing Page Optimization #3 (Testing & Analysis)

This is now the third in a series of three blog posts, providing a comprehensive overview of landing page optimization.  The first post discussed laid out the 5 tenants for effective online selling.  The second applied those concepts to design, marketing and implementation best practices. We are now ready to discuss how testing analysis form the basis of a on-going optimization methodology.

Even though there are known landing page optimization best-practices, and heuristic models for usability that guide us, testing is still at the heart of any effective optimization campaign.  It’s a process.  And the truth is that all of rules of thumb are just like any other advice in life – half true at best. At best you could argue that these rules are true some or most of the time.  No matter how great of an expert one is at site optimization, even the best minds in this space often find themselves surprised at what’s working, as evidenced by the success of sites like, industry experts come to socialize and guess which landing page will win.

Thus what truly separates an expert from a novice is the systematic methods by which they arrive at an optimized page, more than anything else.  Think in terms of what a build > Measure > Learn feedback loop in which you build a landing page using best-practices to begin, then test it against a few other variants, and analyze the results to uncover what’s working. 

Based upon this effort, you not only determined which of your variants was stronger, hopefully you’ve revised your knowledge of what works for your target demographic, so that you can build upon it for the next batch of variants that you will test.  This process repeats until you’re convinced that you’ve optimized sufficiently, or that the law of diminishing returns catches up with you.

To setup your own testing process, you need to properly instrument your site with Analytics tools, and site optimization tools.  Let’s discuss each on of these:

The first step is to properly instrument your site with Analytics, so that you can perform behavioral analysis after a test has run.  There are number of tools such as Google Analytics and Adobe Site Catalyst (aka Omniture) that will suffice and allow you to see who came to your page, what keywords they may have been searching how long they stayed, and where they went from there. You can pass tags also to identify campaigns and thus attribute conversions accordingly.  Goals can be defined as well that you can track against your attributed campaigns to uncover the cost of customer acquisition and return on ad spend (ROAS).

There are still other complimentary analytics tools that may make sense at times. For simple landing page optimization, you might also consider looking at, as it provides a simple heat map to indicate where the mouse went on your page, thus indicating areas of focus.  If you’re looking at site wide and conversion optimization, a lifecycle analytics tool such as ClickTale  allows you to track (anonymously) the entire session on your sit, in detail.  Careful study can help you to uncover bottlenecks in your sales funnel that can be corrected for significant gains in profit and ROAS.

Always Be Testing
Separate from analytics tools, there is another class of tools that specifically manage systematic testing of content variations. Tools such as Google’s Website Optimizer (GWO),  Adobe’s Experience Management, Unbounce and others, enable you to  systematically test variations of a page and graduate the winner of a test to primary status.

A/B Testing provides a simple approach to compare different versions of a page whereas Multivariate Testing (MVT) testing variants of specific tagged elements within a page, such as swapping out a headline, image, or button.  Internet marketing companies that are really great at this stuff, make variant testing a regular part of their process and it is not uncommon to be running a dozen or more variants at any given time in these organizations. Internet marketing companies who excel at this stuff, are regularly testing as a matter of process, and it is not uncommon to be running a dozen or more variants at any given time.


So there you have it.  After three lengthy blog posts, you now have a fairly complete overview of landing page optimization.  At a very high level, the goals are to provide a simple and consistent user experience and to remove barriers from achieving our goal, such as opportunities for distraction and trust issues.  To execute on these goals, do research to better understand your demographic and the nuances of exactly what they’re looking for.  You can then respond with more effective marketing copy and improved design that takes advantage of layout for focus, and images to invoke emotion.

Be aware of implementation issues that could handicap your success such as load time, relevance, and SEO accessibility, particularly if dealing with Google AdWords.  And above all else, instrument your site with analytics to gain visibility into what “is* on your site, and make testing and incremental refinement a matter of process, to discover what *could be*.   If you can follow these steps and make a commitment to testing as a matter of process, then congratulations – you’re already well on your way to seeing double, possibly even triple digit gains in returns on ad spend.

Part 3 of a 3-part series on Landing Page Optimization

Web Analytics Symposium Reivew

This week I had the opportunity to attend the Web Analytics Association (WAA) Symposium in Santa Monica.  Overall it was a well put together event, and while there weren’t a lot of actionable tactics to take away, there was an abundant amount of strategy level discussion.   Here’s some of what I took away:


Attribution – the hottest topic on everyone’s lips was attribution.  I met several vendors working on products to help solve the multi-touch attribution issue.  In other words, if you made contact with a customer through multiple advertising channels, which spending account do you attribute the sale to?

Sentiment – While it seems like behavioral analysis is well understood and powerful tools already well know, there was a lot of interest on how to quantify the fuzzier topic of social sentiment.  It was noted that Radian6 (recently acquired by seems to be the leader in looking at this question.

Iterative Optimization – It was interesting to see the analytics community seems to feel a lot of ownership over the topics of A/B and MVT testing.  I suppose it makes sense, since the optimization of an application is ultimately accomplished with analytics tools. I didn’t expect to see this however.

Setup v Analysis – One speaker gave a talk on what he called “setupland versus action land”.  He described how after years of work as an analytics consultant, he watched the majority of his clients get stuck on implementing analytics packages (tagging, etc), and very little time actually analyzing the data.  It seemed many in the community related to this challenge.

Tag Management – There were three different vendors at the conference offering what they called a tag management system. If you embed a single javascript tag into your page, you can use their system to “walk the DOM” of each page, and bind analytics events to various interface interaction points.  Its a great solution because a company can spend a lot of time and money tagging their application and becoming higher dependent on a single vendor. By using a TMS, swapping out vendors is much easier.  it also makes it easier for the marketing dept to easily embed javascript tags without needing to burden the IT department, a common challenge in large organizations.

Goal-Driven Strategy – This seems almost obvious but seems to be a consistent problem as many people touched upon the issue.  The goals and KPIs of a project must be clearly defined up-front, in order to direct or measure the success of the initiative. As annoying as it can be, Stakeholders need to be challenged to provide well defined objectives and priorities before implementation begins.

Profile of Attendees – The vast majority of those I met at the Symposium, were in-house analysts at large companies. There were certain companies that seemed to have a larger presence that others, such as Kelley Blue Book and Experian.  I met a few consultants, people from local universities and even local marketing companies.  Interestingly, the vast majority of the attendees use some form or another of Omniture/Adobe tools. I heard of very few people (if any) using Google Analytics at the Enterprise level.  I also didn’t hear much mention of WebTrends or CoreMetrics this time.

Maturing Discipline – Finally, it was interesting to observe that what is still a quickly evolving area, is already beginning to look mature.  It was apparent in many ways. Large companies have acquired smaller ones and have entered niche markets.  For example, Adobe purchased Omniture, and now offers even a Tag Management System, competing with the niche guys.  I also heard rumors that IBM is working on collecting and building a massive play in the analytics space.  I heard also that in many organizations, analytics is now understood as a KPI for the business and thus more analytics heads are reporting directly in to the CFO, not the CTO.

All in all, it was a great meeting and good to see what some of the leading West Coast analytics minds are thinking about and working on.  I think there are a number of lessons that can be applied to smaller organizations and application development cycles as well.

Digging Deeper With Analytics

Google Analytics suffers from a perception problem.  It is the most commonly used website analytics package most likely because it is free and easy to use .  But few are compelled to truly discover what is possible with Analytics.  Whatever the reason, there is a lot of power under the surface that I think many could benefit from.  So without further ado, here are the “power features” of Google Analytics:


i. Profiles & Filters – In Analytics, a filter (or combination of filters) can be created to show only a certain subset of data, and this can be mapped to a profile.  Each user account can have up to 50 profiles, so this provides a sort of “view” of the larger application that you can use if you find yourself often needing to looking at certain subsets of data.  For example, what if you wanted to only look at your Canada traffic, separate from US, or Mobile compared to desktop? You could easily track these in separate profiles and make it possible to easily drill down into the reports to only reflect those subsets of users.

Below is a diagram illustrating the structure of an Analytics account:Analytics Structure

ii. Goals & Funnels – One of the real power features is the ability to specify goals and track visual conversion funnels based upon the progression from a landing page to the specified goal.  When you create a goal, you enable Analytics to determine the efficacy of any ad or form on your site.  Combine that with proper campaign tagging and you’ll be able to track through which campaigns are converting better than others.  Or even better, combine it with the pass-through of cost data from AdWords, and now you can see your exact customer acquisition costs and ROI.  Goals don’t necessarily need to be purchase or signup oriented either, though this is obvious the main use for them.  You could however also setup goals to track how long someone spends on your site, or how many pages they read.  This is the beginning of real accountability in your analytics data, as you begin to think about all of the goals you could set and test for.Converison Funnel

iii. Site Search - When you setup a profile for a website, you also have the opportunity to setup search tracking.  You just need to specify the search query parameter during setup, and Analytics will begin tracking for you, what everyone has searched for.  This can be tremendously valuable information as you try to determine what products you should be carrying, or what aspects of the site perhaps are difficult to locate.  To have that facility built in to Analytics is fantastic.

iv. Tagging – If you currently run advertising campaigns and want to track the results from the campaigns, Google Analytics provides a set of tags that you can add as query string parameters when specifying the destination URL of your campaign.  By adding these tags, Analytics will be able to track and properly attribute use trends and conversions, for the proper campaigns.  Again similar to Site search – these are things that can be accomplished outside of Analytics, but it sure is convenient that its already built in right there!   And what if you’re using Google AdWords for some of your advertising campaigns?  Provided you have integrated Google AdWords and Analytics products together, you simply need to toggle on the auto tagging option in AdWords, and the system will take care of munging URLs with proper tags behind the scenes.  And don’t worry if you’re not a techie and aren’t comfortable tagging your own URLs – Google has provided a tool to do this for you, if needed.

Analytics Tagging Parameters

v. eCommerce  – The eCommerce tracking is really pretty powerful.  On each checkout page, you just need to add a little javascript to create a transaction object and add each item that was purchased to the object.  Later, you’ll then be able to breakdown items sold compared to transactions and overlay this data with your goals and funnels.
eCommerce Report

vi. Event Tracking - This is the part where I get really excited!  Imagine you have a sophisticated AJAX or Flash application that constitutes numerous “virtual page views” that you’d like to track, even though the page does not refresh.  Doable.  Using a couple simple Javascript API calls, you can record a virtual page or an event and can run reports on the data just like other page data.  You could probably even do the same with your video, by pushing an event every few seconds to track just how deep into the play people are going.  Or, track the download of a static file such as a PDF, or outbound click to another site, using a JavaScript onClick event to report the event to Analytics.  This really opens the doors to possibilities for better client-side interface tracking.

Analytics Event Tracking

vii. Custom Reports – There is a drag and drop tool for building custom reports that can later be accessed just like the predefined reports.  Imagine you are reporting custom fields or have some specified view that you want to create in a single report rather than needing to refer to several others.  It is all possible here.  And when you’re done, schedule the report to be sent to you via email each week while you’re at it.
Analytics Custom Reports

There really is so much more here once you start to dig into the minutia, particularly as you start to look at how to combine and factor these features in very custom patterns.  So many details are customizable as well, either through account settings or via the API.  So if you haven’t gotten to know Google Analytics at a deeper level yet, perhaps it is time.  Try digging just a little below the surface and see what you find!

AARRR Customer Lifecycle Model

Dave McCLure  gave a speech at Seattle Ignite where he introduced what he called his “AARRR” customer lifecycle model. The goal with this model is to illustrate the various segments of the funnel that a business must acknowledge and master.  The 5 stages are as follows:

1. Acquisition – Think about how you’re obtaining those initial customer introductions. Typical methods would include SEO, PPC, Press Releases,  etc. This is an area that can be improved upon with marketing optimization techniques such as SEO keyword targeting, etc.

2. Activation – Once you have people at your site, what could you do to better improve their experience and ensure they actually signup for your free trial?  A/B testing and landing page optimization can be helpful here.

3. Retention – Once the user is signed up, what are you doing to incubate those relationships?  Many email marketing houses now provide fairly sophisticated auto-responder options.  Marketing automation programs can take it to the next level. Inbound marketing such as blog content and Facebook fan pages can further the cause.

4. Referral – What are you doing to assist your existing users to spread the word about your business? Contests, badges and widgets they can put on their website all help incentivize them to spread the word, which reduces acquisition costs.

5. Revenue – Finally at some point, there must be a monetizable transaction that justifies all of the effort.  Think about what it is and what could flow naturally given the above statements. A typical example would be a SaaS product that provided a free trial in the activation segment of the funnel, and when the 30 day trial is up, or when the user needs additional functionality, they choose to signup.

At the end of his presentation,  he suggests your business needs to be instrumented with the proper analytics and intelligence by which to make decisions.  Suggests you need a tool for each of the following purposes:

  • Quantitative – Traffic analysis & user engagement
  • Qualitative – Usability Testing & Session monitoring
  • Comparative – A/B & Multivariate Testing
  • Competitive – Monitoring & Tracking competitors

Here is the slideshow for anyone interested in further detail: