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The T&T Plugin – Integrate T&T with Google Analytics

When Test&Target was being built back in the day and doing business as Offermatica, it was designed to be an open platform so that its data can be made available to any analytics platform.  While the integration with SiteCatalyst has since been productized, a very similar approach approach can be used to integrate your T&T test data with Google Analytics.  Let me explain how here.

The integration of SiteCatalyst leverages a feature of Test&Target called a “Plug-in”.  This plug-in concept allows you to specify code snippets that will be brought to the page upon certain conditions.  The SiteCatalyst integration is simply a push of a code snippet or plug-in to the page that tells SiteCatalyst key T&T info.

Having something like this can be incredibly helpful for all sorts of reasons such as integrating your optimization program with third party tools, or by allowing you to deliver code to the page via T&T which saves you from having IT make changes to the page code on the site.

To push your campaign or test data over to SiteCatalyst, you create a HTML offer in T&T that looks like this:

<script type=”text/javascript”>
if (typeof(s_tnt) == ‘undefined’) {
var s_tnt = ”;
}
s_tnt += ‘${campaign.id}:${campaign.recipe.id}:​${campaign.recipe.trafficType},’;
</script>

This code is simply taking the T&T profile values in red, which represent your test name and test experience names, and passes them to a variable called s_tnt for SiteCatalyst to pick up.  There is a back end classification process that takes place where these numerical values are translated into what you named them in T&T.  This is helpful to shorten the call being made to SiteCatalyst but not required unless the call to your SiteCatalyst has a relatively high character count.

After you save this HTML offer in your T&T account, you then have to create the “Plug-in”.  You can do so by accessing the configuration area as seen here:

T&T plugin, SiteCatalyst, Google Analytics

Then we simply configure the plug-in here:

T&T Plug-in Configurator

The area surrounded by a red box is where you select the previously created HTML offer with your plug-in code.  You also have the option to specify when the code gets fired.  Typically you want it to only fire when a visitor becomes a member of a test or when test content (T&T offers) are being displayed and to do so, simply select, Display mbox requests only.   If you wanted to, you can have your code fire on all mbox requests as that can be need sometimes.  Additionally, you can limit the code firings to a particular mbox or even by certain date periods.

Pretty straightforward.  To do this for Google Analytics you use the code right below to create a HTML offer and configure the plug-in in the exact same manner.  Note that we are not passing Campaign or Recipe (Experience) ID’s but rather profile tokens that represent the exact name of the Campaign name and Experience name specified in your test setup.

<script type=”text/javascript”>
_gaq.push(['_trackEvent', 'Test&Target','${campaign.name}','${campaign.recipe.name}']);
</script>

And that is it.  Once that is in place, your T&T test data is being pushed to your Google Analytics account.

Before I show you what it looks like in Google Analytics, it is important to understand a key concept in Google Analytics.

Test&Target is using the Custom Events capability of Google Analytics to populate the data.  Each Event has a Category, an Action, and a Label.  In this integration, the Google Analytics Event Category is simply Test&Target because that is our categorization of these Events.  The Google Analytics Action Event represents the Test&Target Test name.  And finally, the Event Label in Google Analytics represents the Test&Target Test Experience.  Here is a mapping to hopefully relate this easier:

Google Analytics Events

Now that we understand that, lets see what the integration gets you:

Google Analytics Test&Target


What we have here is a report of a specific Google Analytics Event Category, in this case the Test&Target Event.  Most of my clients have many Event Categories so it’s important to classify Test&Target as a separate Event and this plug-in code does that for you.

This is a very helpful report as we can get a macro view of the optimization efforts.  This report allows you to look at how ALL of your tests impact success events being tracked in Google Analytics at the SAME time.  Instead of looking at just a unique test as you might be used to when looking at test results in T&T, here we can see if Test A was more impactful then Test B – essentially comparing any and all tests against each other.  This is great if organizations have many groups running tests or if you want to see what particular test types impact a particular metric or combination of metrics.

Typically though, one likes to drill into a specific test and that is available by changing the Primary Dimension to Event Label which, as you know, represents the T&T Test Experience.  Here we are looking at Event Labels (Experiences) for a unique Event Action (Test):

Google Analytics Test Experiences

Here we can look at how a unique test and its experiences impacted given success events captured in Google Analytics. Typically, most organizations include their key success events for analysis in T&T but this integration is helpful if you want to look at success events not included in your T&T account or if you want to see how your test experiences impacted engagement metrics like time on site, page views, etc….

So there you have it.  A quick and easy way to integrate your T&T account with Google Analytics.  While this can be incredibly helpful and FREE, it is important to also understand that statistical confidence is not communicated here in Google Analytics or any analytics platform that I know of, including SiteCatalyst.  It is important to leverage your testing platform for these calculations or offline calculators of statistical confidence before making any key decisions based on test data.

While this was fun to walk you through how to leverage the T&T plug-in to push data into Google Analytics please know that you can use the plug-in for a wide array of things.  I’ve helped clients leverage the plug-in capability to integrate T&T with MixPanel, CoreMetrics, and Webtrends.  You can also use this plug-in capability to integrate with other toolsets other then analytics.  For example, I have helped clients integrate T&T data into SFDC, ExactTarget, Responsys, Causata, internal CRM databases, Eloqua/Aprimo/Unica , Demdex (now DBA Audience Manager), and display retargeting toolsets.  Any platform that can accept a javascript call or pick up a javascript variable can make use of this plug-in concept.

I’ve also helped customers over the years leverage the plug-in to publish tags to the site.  Years before the abundance of Tag Management Platforms became available, there were T&T customers using the plug-in to publish Atlas, DoubleClick, and Analytic tags to the site.  In fact, if Adobe wanted to, they could make this plug-in capability into a pretty nice Tag Management Platform and one that would work much more efficiently with T&T then the current Tag Management tool they have on the market today.

Published on October 22, 2012 under Analytics, Integrations

Optimization Test Techniques – Part II of II

In my previous post, I highlighted how it is important to understand what optimization techniques are available in the market today because by knowing the techniques, you are much better armed to apply additional strategy to your optimization efforts.

This post is a continuation of my previous blog post in that I walk through the remaining five optimization test techniques available in Test&Target. So far, I have covered 1:1 Campaign, 1:1 Display Campaign, A/B Campaign, and Flash Campaign. Here I will cover Landing Page Test, Landing Page Campaign, Monitoring Campaign, Multivariate Test, and finally the Optimizing Campaign.

test&target

Landing Page Test/Landing Page Campaign

I’ve combined both the Landing Page Test and the Landing Page Campaign types here because they provide the same core test functionality. These types of test techniques are very different compared to an A/B test in that visitors can switch branches or experiences of a test. This technique is highly effective when your test strategy requires that visitors be able to change branches of a test versus the A/B approach where visitors are forced to maintain membership in a particular test branch.

A great example of such a test is around SEM reinforcement. Lets say you have two different ad campaigns taking place on Google where one ad campaign is promoting a particular product and the other campaign is promoting discount messaging. If you have a test running that is basically quantifying the value of message reinforcement associated with source, then you would have an A, B, C Campaign. Experience A would be the default content or what is currently running on the landing page. Experience B would be targeted to the first Google SEM messaging on product messaging and Experience C would be targeted to the second Google SEM ad around discount messaging.

To effectively run this type of scenario you would want to leverage the Landing Page Campaign in the event visitors happen to click through on both of the SEM ads. Using an A/B campaign with this type of test would reinforce the messaging of the first ad clicked on the landing page even if the visitor clicked the second ad because with the A/B campaign, you are stuck with the first Experience assigned for the life of the campaign. The Landing Page campaign would recognize the ad clicked on and switch you to the corresponding campaign experience even if that means switching branches.

The SEM reinforcement example is just one way the Landing Page technique can help add additional strategy. I often find this technique to also be helpful when targeting campaigns to particular behaviors on the site or when offline data is incorporated into your online optimization efforts.

The key difference between the Landing Page Test and The Landing Page Campaign is that a Landing Page Test is used for Multivariate testing where the strategy involves having the visitors change experiences within a Multivariate test design.

Monitoring Campaign

The monitoring campaign is an incredibly helpful asset for any organization that leverages Test&Target.

The monitoring campaign is typically used to collect data or to run concurrently with other campaigns to track results. The monitoring campaign is not typically used to display content, although it can if needed.

A great use case for using a monitoring campaign would be to set a baseline for conversion rates or revenue metrics like total sales, revenue per visitor, or average order value. I often recommend to customers that if they have the mboxes on the site but the alternative content isn’t ready, to start a monitoring campaign to not only see some metrics but also to familiarize yourself with the Test&Target platform.

The Monitoring Campaign was not designed to replace an organization’s analytics but many organizations soon find themselves using the Monitoring Campaign to provide data on certain behaviors defined in T&T or to even augment analytics with pathing reports. Another interesting use of Monitoring campaigns that I have seen helpful to organizations is using it to deploy tags to the site independent of T&T. Before tag management solutions became so popular, the mbox was a nice and easy way to get code to the page without having to bother IT if an mbox was already in place. Nowadays, T&T has a plugin functionality that can handle that without having to setup a Monitoring Campaign.

Multivariate or MVT Campaigns

Multivariate testing is a somewhat political topic in the testing world. There are many schools of thought when it comes to multivariate testing and there is also much debate about whether it is as beneficial as A/B testing. I will leave those topics for future blog posts but simply outline how the T&T platform approaches MVT testing here.

The default or productized MVT approach in the Test&Target platform is the Taguchi approach. This approach is a partial factorial approach in that not all possible combinations of elements and alternatives will be incorporated into the test design – only a portion of all possible will be. The key benefit T&T advocates here is that less time is needed to get results because less experiences require less traffic to the test.

Here is an example of the Taguchi approach: lets say you have 3 elements and 2 alternatives for each element. The elements are the Call to Action, the Color, and the Text. If you had two different iterations of each of these elements that would represent a 3X2 MVT design. If you mixed and matched each element and each alternative, all possible combinations would come to 3ˆ2 = 8. By applying the Taguchi approach, only 4 out of the 8 possible combinations will be tested. The 4 experiences that are tested are not a random four but rather the 4 according to the Taguchi model. T&T helps you with this as you go about creating your test within the platform. Here is an example of a test design created by T&T with a 3X2 MVT:

The Taguchi approach becomes especially handy when you have more then 3 elements. In the above example, testing 8 experiences versus the 4 wouldn’t present as much of a challenge as testing 7 elements with 2 alternatives. A 7X2 MVT with all possible combinations would require testing 128 experiences (2ˆ7) versus the Taguchi approach where only 8 experiences would be needed.

The reporting that comes along with a T&T Multivariate test is very similar to what you can expect from any other type of test technique with one exception. For MVT tests, T&T provides what is called an Element Contribution Report. This report is helpful for a number of things.

First, when you test only a subset of all possible test combinations you are only getting data on those tested experiences. This report presents to you what the “Predicted Best Experience” is based on data collected thus far. With a 7X2 MVT Taguchi test design, you are only testing 8 out of 128 possible experiences – this report tells you which experience would have been the best given the odds of you having it in your test design would be only 8/128.

Secondly, this report is helpful to understand how each element impacts the given success event, hence the name of the report being Element Contribution Report. This data is incredibly helpful because you can use it for other tests designs. For example, I have seen many Taguchi MVT Element Contribution reports infer that a certain Message Approach as a test alternative was incredibly impactful with high statistical confidence. Those organizations can now take that Message concept and incorporate it into A/B tests or even in offline Marketing efforts. This report essentially helps identify themes that can be incorporated into other Marketing efforts.

Here is an example of an Element Contribution Reprot where you can see each element and which alternative of that element was more successful, making up what would be the best test experience even if it wasn’t part of the test design. Additionally, you can see that the most influential element was the Submit Button :

element-contribution-report

Just because T&T’s default approach to MVT is the Taguchi approach, that doesn’t mean that you are limited to running partial factorial multivariate tests with this platform. I have worked with many clients over the years including one right now that is using T&T for full factorial MVT tests. To do this, you simply have to create your test design offline and set it up as an A/B test within T&T. The post test data is then analyzed offline as well to quantify interaction effects.

Optimizing Campaign

This type of campaign technique is surprisingly unique to the Test&Target platform given that it can be very helpful to any Optimization team within an Organization.

[Correction: SiteSpect also offers this automated optimizing test functionality.]

The Optimizing Campaign is not your typical test type. It isn’t designed for the type of learnings that you might be used to with running other types of tests where you are comparing different experiences across different visitor sets. It is designed to allow the testing platform automatically deliver the right experience at the right time.

Imagine if you will, five different pieces of content for testing. This content can be home page hero content, navigational elements, calls to action, email content….anything really that you wish to have tested as part of a test design. Typically you would approach this with either an A/B test technique or a Multivariate test so as to see which version versus the other led to increases in given success events. The Optimizing campaign test technique is designed to not maintain an equal distribution of test content to give you this data but rather it will automatically shift traffic to the better performing experience of all the possible experiences. If Experience C was consistently outperforming the other Experiences, the Optimizing Campaign will automatically shift more and more of that that visitor traffic to that test experience.

T&T takes the Optimizing Campaign to another level with how it leverages segments in this automation. If you include segments in this campaign setup, the Optimizing Campaign will provide its automation to those segments by automatically providing the most effective experience for that segment. Additionally, the reporting associated with this campaign type provides a report called “Insights” that shows what segments impacted what test offers and whether that impact was positive or negative. This is incredibly powerful because the tool is doing the discovery for you and you are then enabled to create a new campaign right from this report targeted to that discovered segment.

Here is a screen shot of an Insights report from T&T:

test&target optimizing campaign

I find that the Optimizing Campaign test technique is most effective for tests that are being run in email campaigns. Lets say you have an email blast that is going out to 200,000 email subscribers and you were running an A/B/C test of content within that email. The Optimizing Campaign has the potential to learn what experience within that test design was the most successful from the first sets of visitors that opened that email. If, for example, the first 2,000 visitors reacted much more favorably to Experience B, the Optimizing Campaign would shift more and more visitors to get Experience B if they haven’t opened the email yet. This approach allows organizations to immediately capitalize on test learnings for short marketing cycles like those in email campaigns.

Published on August 25, 2012 under Optimization Mechanics

Optimization Test Techniques – Part I of II

As I talk to more and more companies that are using testing solutions, I find many of them are unaware of the test techniques that are available in their testing platform.  Testing solutions available today offer more then just A/B and multivariate testing capabilities.  There are different techniques around multivariate tests but there are also other test techniques available that offer additional strategy for your tests.  Familiarizing yourself with the different techniques available will allow you to get much more value out of your testing solution and your optimization program.

Here I will share what test techniques or types that are currently available in Adobe’s Test&Target (T&T) platform.

In T&T, tests types are referred to as campaigns and campaign types.  All the campaign types use the same core components such as the mbox and the offer.  The mbox, which is short for marketing box, does many things but for this topic, it is best to think of it as the area of real estate on the website that you wish to assign content as part of a test.  That content that you assign as part of the test is your offer. Campaigns are where you assign business rules to your mboxes and offers.

test&target


1:1 Campaign

The 1:1 campaign is a campaign type that is only available to those customers that have a Test&Target1:1 license.  Test&Target1:1 is the former Touch Clarity product acquired by Omniture and has since been incorporated into the Test&Target platform as a test type allowing users to leverage a shared profile and a single platform for their optimization efforts.

The 1:1 campaign is designed to leverage models to determine the right content to present to the individual vs. a segment of visitors.  These models are focussing on a single success event that you specify in the campaign setup.  These events can be anything that can happen in a session such as:  click through, form complete, purchase, revenue per visitor, etc…

There will be two branches of this type of test, similar to an A/B test.  The first branch serves as a control and is presented to 10% of traffic.  These visitors will randomly see any one of the offers you are using in the test.  The engine learns from this 10% of traffic by understanding how visitors react to the content and then correlating that reaction to the profile attributes of those visitors.

The other 90% of traffic benefits from this by receiving targeted content based off of the real time scoring the 1:1 engine provides.

I have seen this campaign type offer a ton of value to customers in highly trafficked pages such as the home page or main landing pages.  The big benefit here is the automation.  You set it up and let it do its thing with minor tweaking here and there.

This is what the summary report looks like in the 1:1 campaign type where you can see the two branches of the test:

test&target1:1

The other key value that this test type provides is what is called an “Insights” report.  Yep, Adobe has an Insight product for analytics and also a report in 1:1 called Insights.  This Insights report in 1:1 provides data on what profile attributes of visitors are offer a positive and negative propensity against a given offer.  In other words, this report discovers segments or profile attributes that are impactful.    Here you can learn things like people on their 3rd session and are from California respond positively to a particular offer – hence discovering this segment for you and providing a marketing insight that can be used in other tests or in offline marketing!

1:1 Campaign Display

This campaign type is the exact same at the 1:1 except that it is used in display ads versus a website.

A/B..N Campaign

This is by far the most popular of the campaign types and, as you can imagine, it is the test type that allows you to compare two different experiences.  You can have just two experiences competing against each other but you can also incorporate as many different experiences as your traffic and creative permits.  Here is what the architecture of a standard A/B test looks like with two different offers being assigned to two different mboxes:


campaign setup

An important thing to note regarding the A/B test is that whatever experience or branch of the test the visitor falls into, they are stuck with the experience for the life of the campaign.  That is, if they continue to visit the area that is being tested, they will continue to see that test content until they convert which is defined as the primary success event in T&T.

Flash Campaign

This campaign type is used when you wish to test content within flash files.  This is a great technique to use if you wish to apply optimization to your display ads.  Onsite profiles collected by T&T can be used for quick and easy targeting with this type of campaign.

Adobe’s CS5 of Flash has productized the integration with T&T in that within CS5 of Flash, you can leverage a Flash Extension to quickly “mbox” components of the flash asset to be used as part of a test in T&T.  In T&T then you select the Flash campaign and during the campaign setup, you either upload the “mboxed” flash file or point to where it lives in the network.  T&T then identified the “mboxed” components where you can assign alternative content to it as part of the test.

The flash campaign follows the same technique as an A/B test in that visitors are stuck with whatever experience they were originally provided.

In the follow up post, I will highlight the Monitoring Campaign, Multivariate Campaigns and the Optimizing Campaign.

Published on April 10, 2012 under Optimization Mechanics

The Unknown and the Known

In the Demand Generation world it is all about the “Known” and “Unknown”.  Before visitors fill out a form they are considered to be “Unknown”.  After supplying their information on a form, they are considered “Known”.  Increasing the percentage of visitors that fill out these forms adds a significant amount of value to organizations.

If you are unfamiliar with Demand Generation tools, they are often used to capture information from prospects, score leads, and send targeted emails to prospects, among other things.

Focusing on optimization techniques will allow you to increase the progress of “Unknowns” to “Knowns”, and progress to true personalization; where you know exactly what to show to each person on your site. To start, using the traffic source, environmental variables, online behaviors and geographic variables to target content will help discover what is the most effective content to present to visitors.  These types of visitor profile attributes should serve as the foundation of your visitors’ marketing profiles.  Then, add to them with offline data and contextual data to determine content to present to visitors as part of an optimization.

Let me walk you through two examples that have allowed companies to extend the value of their Demand Generation Platform by integrating it with their Optimization Platform.

The architected solution that is shown here leverages Adobe’s Test&Target and can applied to Demand Generation tools such as Aprimo, Eloqua, and Unica.  This model can be adapted to other platforms and technologies; these are simply the ones that I have helped customers execute and see value with in the past.

This first example highlights ways to increase the percentage of visitors that complete these forms.  Here we are optimizing to the Unknowns.

Optimizing the Unknowns

Unknown Visitors Test&Target Demand Generation

1.  An Unknown contact comes to the website and we want to increase the likelihood of them filling out the form.  The areas on the website and in the email in light red represent mboxes, which is short for marketing box and is the Test&Target code that is placed on the page.  This mbox does two key things in this exercise:  it allows for injection of content to target this visitor and it sets a unique visitor ID.

In order to increase the likelihood of visitors filling out the form and becoming Known, we have to be relevant.  We can target different product promotions, messaging, or content that is relative to the referral messaging to find out what is the most relevant content that leads to increased form completes.  Optimization allows us to not only understand what is the most effective content for form completion for the general population as a whole but also across segments.  For example, we may learn that SEM traffic should be presented with promotional messaging and visitors who are on their third visit should be presented with branded messaging as that increases their likelihood to fill out the form and convert.

2.  In this step a visitor has completed completed the form.  They supplied information such as title, organizational department, company size, industry and personal information such as email, name and address.  All if this information is helpful for the Demand Generation tool to manage this particular lead.  There are two additional data points that should be communicated to the Demand Generation tool as well that only the Optimization Platform can provide.

The first is the information on what targeted content was presented to this individual.  Consider how helpful it would be for the Account Manager or the Sales Person if they knew if a visitor was presented with promotional content versus branded content.  In cases where the company is presenting differentiating products, having that data tied to this lead is even more valuable.

The second data point to be passed to the Demand Generation tool is the Test&Target unique visitor ID.  This ID, when coupled with Demand Generation unique ID, allows for augmentation of the visitor profile attributes with offline data – something I address in the second example.

This communication of optimization Attributes happens programmatically behind the scenes as part of the integration.

3.  At this point, the visitor has made the progression from an Unknown to a Known.  The Optimization Platform provided the ability to determine what content was relevant and would lead to a higher percentage of form completes.  The Demand Generation tool has an increased amount of leads to manage that also have the rich test information provided by the Optimization Platform.

Optimizing the Knowns

Test&Target target on offline profiles

1.  While optimizations are running targeting content to different segments of Unknown visitors, we can also simultaneously run optimizations to different segments of Known visitors.  Clients see incredible value doing this because they are continually being relevant by personalizing the site and email communication even after they have gotten the lead.

In step two in the first example, I pointed out that the optimization platform should communicate to the demand generation the Test&Target ID.  This ID is then coupled with the ID the Demand Generation tool manages.  As activity takes place offline such as phone calls or email communication, the profile of that lead gets richer.  Test&Target allows users to augment the online ID it creates with offline information such as sales cycle stage.  This is something that is accomplished programmatically when lead data is exported from the Demand Generation tool and then feed into Test&Target’s offline profile API.

2.  With all this rich information made available to the online profile, we now have the ability to target content in the same mboxes that were being used in the first example.  Using the Web Analytics Demystified’s website as an example, if this Known visitor came back to the site after filling out our form and then attending one of our ACCELERATE conferences, we may want to use the real estate in the mbox to promote our next ACCELERATE conference.  Anything that is known about this visitor can be used.  Another great example of the personalization capabilities here would be around targeting content based off of interest expressed offline.  Lets say a visitor came to the Demystified website and submitted their information for us to contact them.  During a phone call that we had with them, we found out that they were interested in the SiteCatalyst audits that Adam Greco provides.  We notate their interest in our Demand Generation tool.  That then gets pushed into their T&T profiles and upon subsequent visits to the site we can target content associated with Adam’s offerings that clients love.  This personalization or relevance can help progress this visitor into further engaging with Adam for his services.

3.  In this step, Test&Target is augmenting the Demand Generation tool’s profile by again communicating additional optimization data points as well as any recent website behavior.  This is very similar to Step two in the first example but in this case the visitor is already Known and may have visited other pages of the site or was presented with specific targeted content that is worth noting for the Sales Person or Account Executive.

So there you have it.  If you are using a Demand Generation tool and you are also using an optimization platform that supports the augmentation of the online ID with offline data, I highly recommend integrating the two.  There is incredible value in optimizing form completes and by continuing to be relevant to visitors even after they completed a form.  Because we are using an optimization tool to accomplish this, all the effort here is easily quantifiable to show the value and ROI.



Published on March 12, 2012 under Integrations

Brian Hawkins, Demystified

I am extremely excited to be joining Adam, Eric, and John here at Web Analytics Demystified.  While at Offermatica, Omniture and then Adobe I witnessed first hand the value this firm brings to clients and I am incredibly proud to be working with them.

A bit about me

I’m originally from Chicago but moved to San Francisco not long after finishing Graduate School in 2004.  Soon after arriving I met the fine folks at Offermatica and started my optimization career servicing clients large and small and across every industry.  It was during these years I found out how to best help organizations scale their optimization programs and, more importantly, how to get the most value out of their optimization platform.

In the years that followed at Omniture and then at Adobe, I spent most of my time continuing to help clients build best of breed optimization teams and practices.

These practices included auditing implementation, training, campaign road mapping, and the ever important process of analysis and communicating results to other parts of the organization.

During those years I also architected solutions for clients that allowed them to get more value out of their personalization and optimization platforms by integrating those platforms with their Analytics, Demand Generation tools, tag management systems, Email service providers and with other tools that share data internally and externally.  I am a strong believer that optimization and personalization should span across all marketing efforts and not just on the website; and integrating internal and external tools enables this.

Going forward

At Web Analytics Demystified, my hope is to continue helping clients in this manner as I see the incredible value it brings them.  I want to show them how to get the most out of their optimization and personalization tools.  While my background has been heavily focused around the Adobe technologies such Test&Target, Test&Target1:1, and Recommendations, I am already branching out and applying my skill set to other vendor tools.

I really look forward to sharing my insights here on this blog and I hope to hear from all of you here as well.  If I can be of any help to your business or you would like to chat, do not hesitate to let me know.   I can be reached via this page or by email at brian.hawkins@webanalyticsdemystified.com.

Published on February 23, 2012 under About this blog

 


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SiteCatalyst Unannounced Features
Adam Greco, Senior Partner

Lately, Adobe has been sneaking in some cool new features into the SiteCatalyst product and doing it without much fanfare. While I am sure these are buried somewhere in release notes, I thought I’d call out two of them that I really like, so you know that they are there.

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Hello. I’m a Radical Analytics Pragmatist
Tim Wilson, Partner

I was reading a post last week by one of the Big Names in web analytics…and it royally pissed me off. I started to comment and then thought, “Why pick a fight?” We’ve had more than enough of those for our little industry over the past few years. So I let it go.

Except I didn’t let it go.

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Competitor Pricing Analysis
Adam Greco, Senior Partner

One of my newest clients is in a highly competitive business in which they sell similar products as other retailers. These days, many online retailers have a hunch that they are being “Amazon-ed,” which they define as visitors finding products on their website and then going to see if they can get it cheaper/faster on Amazon.com. This client was attempting to use time spent on page as a way to tell if/when visitors were leaving their site to go price shopping.

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How to Deliver Better Recommendations: Forecast the Impact!
Michele Kiss, Partner

One of the most valuable ways to be sure your recommendations are heard is to forecast the impact of your proposal. Consider what is more likely to be heard: "I think we should do X ..." vs "I think we should do X, and with a 2% increase in conversion, that would drive a $1MM increase in revenue ..."

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ACCELERATE 2014 “Advanced Analytics Education” Classes Posted
Eric T. Peterson, Senior Partner

I am delighted to share the news that our 2014 “Advanced Analytics Education” classes have been posted and are available for registration. We expanded our offering this year and will be offering four concurrent analytics and optimization training sessions from all of the Web Analytics Demystified Partners and Senior Partners on September 16th and 17th at the Cobb Galaria in Atlanta, Georgia.

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Product Cart Addition Sequence
Adam Greco, Senior Partner

In working with a client recently, an interesting question arose around cart additions. This client wanted to know the order in which visitors were adding products to the shopping cart. Which products tended to be added first, second third, etc.? They also wanted to know which products were added after a specific product was added to the cart (i.e. if a visitor adds product A, what is the next product they tend to add?). Finally, they wondered which cart add product combinations most often lead to orders.

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7 Tips For Delivering Better Analytics Recommendations
Michele Kiss, Partner

As an analyst, your value is not just in the data you deliver, but in the insight and recommendations you can provide. But what is an analyst to do when those recommendations seem to fall on deaf ears?

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Overcoming The Analyst Curse: DON’T Show Your Math!
Michele Kiss, Partner

If I could give one piece of advice to an aspiring analyst, it would be this: Stop showing your "math". A tendency towards "TMI deliverables" is common, especially in newer analysts. However, while analysts typically do this in an attempt to demonstrate credibility ("See? I used all the right data and methods!") they do so at the expense of actually being heard.

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Making Tables of Numbers Comprehensible
Tim Wilson, Partner

I'm always amazed (read: dismayed) when I see the results of an analysis presented with a key set of the results delivered as a raw table of numbers. It is impossible to instantly comprehend a data table that has more than 3 or 4 rows and 3 or 4 columns. And, "instant comprehension" should be the goal of any presentation of information — it's the hook that gets your audience's brain wrapped around the material and ready to ponder it more deeply.

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Automating the Cleanup of Facebook Insights Exports
Tim Wilson, Partner

This post (the download, really — it’s not much of a post) is about dealing with exports from Facebook Insights. If that's not something you do, skip it. Go back to Facebook and watch some cat videos. If you are in a situation where you get data about your Facebook page by exporting .csv or .xls files from the Facebook Insights web interface, then you probably sometimes think you need a 52" monitor to manage the horizontal scrolling.

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The Recent Forrester Wave on Web Analytics ... is Wrong
Eric T. Peterson, Senior Partner

Having worked as an industry analyst back in the day I still find myself interested in what the analyst community has to say about web analytics, especially when it comes to vendor evaluation. The evaluations are interesting because of the sheer amount of work that goes into them in an attempt to distill entire companies down into simple infographics, tables, and single paragraph summaries.

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Funnel Visualizations That Make Sense
Tim Wilson, Partner

Funnels, as a concept, make some sense (although someone once made a good argument that they make no sense, since, when the concept is applied by marketers, the funnel is really more a "very, very leaky funnel," which would be a worthless funnel — real-world funnels get all of a liquid from a wide opening through a smaller spout; but, let’s not quibble).

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Reenergizing Your Web Analytics Program & Implementation
Adam Greco, Senior Partner

Those of you who have read my blog posts (and book) over the years, know that I have lots of opinions when it comes to web analytics, web analytics implementations and especially those using Adobe Analytics. Whenever possible, I try to impart lessons I have learned during my web analytics career so you can improve things at your organization.

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Registration for ACCELERATE 2014 is now open
Eric T. Peterson, Senior Partner

I am excited to announce that registration for ACCELERATE 2014 on September 18th in Atlanta, Georgia is now open. You can learn more about the event and our unique "Ten Tips in Twenty Minutes" format on our ACCELERATE mini-site, and we plan to have registration open for our Advanced Analytics Education pre-ACCELERATE training sessions in the coming weeks.

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Current Order Value
Adam Greco, Senior Partner

I recently had a client pose an interesting question related to their shopping cart. They wanted to know the distribution of money its visitors were bringing with them to each step of the shopping cart funnel.

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A Guide to Segment Sharing in Adobe Analytics
Tim Wilson, Partner

Over the past year, I've run into situations multiple times where I wanted an Adobe Analytics segment to be available in multiple Adobe Analytics platforms. It turns out…that's not as easy as it sounds. I actually went multiple rounds with Client Care once trying to get it figured out. And, I’ve found "the answer" on more than one occasion, only to later realize that that answer was a bit misguided.

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Currencies & Exchange Rates
Adam Greco, Senior Partner

If your web analytics work covers websites or apps that span different countries, there are some important aspects of Adobe SiteCatalyst (Analytics) that you must know. In this post, I will share some of the things I have learned over the years related to currencies and exchange rates in SiteCatalyst.

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Linking Authenticated Visitors Across Devices
Adam Greco, Senior Partner

In the last few years, people have become accustomed to using multiple digital devices simultaneously. While watching the recent winter Olympics, consumers might be on the Olympics website, while also using native mobile or tablet apps. As a result, some of my clients have asked me whether it is possible to link visits and paths across these devices so they can see cross-device paths and other behaviors.

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The 80/20 Rule for Analytics Teams
Eric T. Peterson, Senior Partner

I had the pleasure last week of visiting with one of Web Analytics Demystified’s longest-standing and, at least from a digital analytical perspective, most successful clients. The team has grown tremendously over the years in terms of size and, more importantly, stature within the broader multi-channel business and has become one of the most productive and mature digital analytics groups that I personally am aware of across the industry.

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Ten Things You Should ALWAYS Do (or Not Do) in Excel
Tim Wilson, Partner

Last week I was surprised by the Twitter conversation a fairly innocuous vent-via-Twitter tweet started, with several people noting that they had no idea you could simple turn off the gridlines.

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Omni Man (and Team Demystified) Needs You!
Adam Greco, Senior Partner

As someone in the web analytics field, you probably hear how lucky you are due to the fact that there are always web analytics jobs available. When the rest of the country is looking for work and you get daily calls from recruiters, it isn’t a bad position to be in! At Web Analytics Demystified, we have more than doubled in the past year and still cannot keep up with the demand, so I am reaching out to you ...

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A Useful Framework for Social Media "Engagements"
Tim Wilson, Partner

Whether you have a single toe dipped in the waters of social media analytics or are fully submerged and drowning, you’ve almost certainly grappled with "engagement." This post isn’t going to answer the question "Is engagement ROI?" ...

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It’s not about "Big Data", it’s about the "RIGHT data"
Michele Kiss, Partner

Unless you’ve been living under a rock, you have heard (and perhaps grown tired) of the buzzword "big data." But in attempts to chase the "next shiny thing", companies may focus too much on "big data" rather than the "right data."

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