To Test or to Target? Where to Start for Best ROI?

The previous post had concrete recommendations for proving the ROI of behavioral targeting. Several smart reader comments brought together a pretty clear picture.

However, when I was meeting with a number of experienced online bankers in Europe recently, the question that I received was more difficult to answer than just proving the ROI of targeting.

Namely, the question was whether one can expect greater ROI from testing or targeting? Whichever promises greater ROI, shouldn’t that be where you may want to start?

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Behavioral Analysis for Driving Targeted Marketing

You might be squandering a huge opportunity if you aren’t using web analytics as a rich source of behavioral insights on individual prospects and customers.

Read the full article published on the brilliant new online-behavior site. There you’ll also see uses of Venn diagrams for behavioral analytics that are more serious than the recent fun with the nerd vs. geeks Venn diagram post.

Kudos to Daniel Waisberg for launching online-behavior.com!

The Nerd-Geek Venn Diagram Applied to Analytics

Ever since the brilliant Nerd-Geek-Dork Venn diagram below started zipping all over blogs in Sept 2009, I have been waiting for genius to strike me so that I might think of ways to apply this to the analytics topic.

Nerds vs. Greek vs. Dorks

Sadly, genius never struck.

But here are a few Venn diagrams anyway that kind-of, sort-of make sense and contain a few useful reminders.

The Analyst vs. Change Agent Venn Diagram

A good reminder how critical both business acumen and political skills are so that analysts can be the change agents that we so much desire to be.

Change Agent Venn diagram

The Bean Counter Venn Diagram

A web / marketing analyst also needs to balance an eye towards saving money with an entrepreneurial spirit towards identifying new sources of cash. Veer off too much into one or the other direction, you might be either a bean counter or something worse.

Bean counter venn diagram

The Segmentation to Recommendation Venn Diagram

A good reminder how critical segmentation is to analysis because static reports probably never tell a story that leads to action. Good reminder also that the true goal of analysis is to get to recommendations as Eric Peterson was pointing out in his keynote at the eMetrics Marketing Innovation Summit conference in San Jose in May.

Analysis venn diagram

The Business Optimization Venn Diagram

The purpose of the last one is to remind how web analytics by itself just doesn’t lead to web business optimization. It needs to be combined with customer analytics and put into context with the wider marketing history. The latter refers to preceding marketing touch points and each individuals’ responses (e.g. did or didn’t click-through on an email that they received).

Business optimization venn diagram

Another possibility that arises at the center of this Venn diagram is interactive marketing. My colleagues and I at Unica take interactive marketing verbally, i.e. the kind of targeted marketing communications that take into account each customer’s past and current actions. That makes the combination of web analytics, customer analytics, and marketing history indispensable.

Farewell to Coremetrics and Web Analytics as you knew it

Today is another exciting day in the history of web analytics.

Or was today another step forward on the inevitable path of web analytics (as we knew it) to becoming history?

For Unica’s read of today’s news, check my post on IBM’s acquisition of Coremetrics on Unica’s blog.

5 Multichannel Gems from eMetrics San Jose

Like most vendors at the eMetrics marketing optimization conference this year, I only had a chance to attend very few of the sessions. But each of the ones I did attend was awesome.

Even more awesome than I remember from past years.

Here are five track sessions that were real gems:

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Analytics for Tweets and Twitter API with Unica

Earlier this week, Unica announced the addition of innovative social media marketing capabilities for users of our online marketing solutions. Among these capabilities are Social Media Analytics for Unica’s web analytics solution, NetInsight. And one component of these capabilities is the integration of Twitter analytics into website stats.

More specifically, Unica’s Solutions Pack released today enables customers of Unica NetInsight, NetInsight OnDemand, and Interactive Marketing OnDemand to:

  1. Automatically download Tweets on selected subjects from the Twitter API
  2. Collect and store the data indefinitely for historical analysis (whereas Twitter discards older tweets eventually)
  3. Submit the data to NetInsight for extending web analytics reports with reporting elements for Twitter topics, Twitterer IDs, and complete texts of tweets

Tweets are included within a regular website profile in Unica NetInsight which makes it possible to view website visitation statistics within the same charts as the trend of Tweets obtained from the Twitter API.

Unica NetInsight report on trend of Tweets vs. site visits and conversions

Unica NetInsight report on trend of Tweets vs. site visits and conversions

Tweet trends for the keywords that you specified can also be broken out separately as seen in the above screenshot. For example, Unica is monitoring tweets on hash tags such as #measure, #SEM, #CRM, #emailmarketing, #interactive, etc.

As seen in the next screenshots, tweets can of course also be monitored intra-day. Alerts can be set up that send an email to responsible social media managers when the volume of tweets on a certain topics exceeds thresholds.

Unica NetInsight report on Tweets by hour by Tweet topic

Unica NetInsight report on Tweets by hour by Tweet topic

As mentioned earlier, Tweets can also be tied to individual Twitterers and reported that way to identify top influencers for your brand or targeted topical keywords.

Unica NetInsight report on top Twitterers by Twitter hash tag

Unica NetInsight report on top Twitterers by Twitter hash tag

You can also drill to individual Tweets and read their content to understand context. Unica NetInsight’s limitless flexibiliy is showcased nicely by the fact that a simple click on any individual Twitter’s comment will hyperlink the analyst directly to that individual’s Twitter page to see all their updates or to respond to them directly.

Unica NetInsight drill down to individual Tweets

Unica NetInsight drill down to individual Tweets

With the full text available, it is possible to set up metrics in NetInsight such as “Re-tweets”. Now, you can measure for example how viral your own tweets are, i.e. how often you get re-tweeted.

How does it work? You simply set up a metric that starts with “RT” and contains the text pattern from your original update.

The latter also works for Twitter’s newly announced Promoted Tweets. This way you can identify engagement with your promoted Tweets even if they did not click-through to your site.

Going from Twitter Analytics to Action

As always with Unica, the story doesn’t stop with reporting but extends into action. For Twitterers where CRM records contains both the Twitter ID and customer registration, or website cookie information, Unica Interactive Marketing can turn analysis into action.

For example, provided that permission to market exists

  • Social media influencers and opinion leaders can be identified and targeted with campaigns designed to motivate and encourage them to promote the company’s brand.
  • A company’s most loyal clients whose engagement with the brand is waning can be prioritized for retention campaigns.
  • Users that click through on a tweet relating to a particular topic can be profiled accordingly so that future communications are made relevant to their topics of interest.

The latter bullet point also applies to click-throughs from Promoted Tweets. In your promoted tweets, just as with any other tweets, simply make sure that hyperlinks back to your site include tracking codes. That way your web analytics can attribute the source of the click-through for the session.

For more information

For more information about the Solutions Pack for Social Media Analytcis, Unica customers can contact their account managers.

As a final note, Unica absolutely also recommends that customers use social media monitoring solutions such as Radian6, Scoutlabs, and Viral Heat for more complete monitoring. Some of these solutions also provide APIs. It is the plan to provide similar integrations for these APIs.

Analytics for Facebook Applications with Unica

Unica announced the addition of innovative social media marketing capabilities this week. Among these capabilities are Social Media Analytics for Unica’s web analytics solution, NetInsight. Specifically, one of the components of the Solutions Pack released today encompasses analytics for Facebook applications. This enables marketers to gain insights on application usage and users including details from the Facebook API.

More specifically as a customer of Unica NetInsight, NetInsight OnDemand, and Interactive Marketing OnDemand you can:

  • Instrument all aspects of your Facebook application for granular behavior analysis and optimization
  • Rely on the highest degree of accuracy in their analytics by basing your sessionization and unique user insights on the Facebook ID and employing cache busting mechanisms to avoid the loss of click data due to caching (e.g. in the browser cache).
Report in Unica NetInsight on Facebook application usage trends by visit duration

Report in Unica NetInsight on Facebook application usage trends by visit duration

You can also include any desired detail from the Facebook API along with the click-stream analysis as long as you comply with Facebook’s platform policies. The API data will help you understand usage trends, success, and user preferences based on available insights about users’

  • Social graph, e.g. how do key influencers use the application vs. the average user?
  • Demographics, e.g. how do people at various age ranges use the application?
  • Geographic location, e.g. how to users from different parts of the country or world prefer to use the application?
  • Relationships or affiliations, e.g. how to married folks vs. bachelors differ in their preferences for using the application?
Unica NetInsight on current locations of today's Facebook application users (based on API data on users)

Unica NetInsight on current locations of today's Facebook application users (based on API data on users)

Privacy and Facebook’s Platform Policies (Note: I updated this section on April 27th)

Key to including any insights from the Facebook API in analytics is not only marketers’ good stewardship of this data. This is also expressed in the Facebook platform’s developer principles and policies.

The policies previously used to limit the kind of API data that can be stored, including by web analytics solutions, for longer than 24 hours. However, with the launch of the Facebook open social graph on April 21st 2010 the policies were revised to remove that limit. Instead there is

  1. A greater emphasis on the principles of using data towards a good experience for users which expressly excludes spam.
  2. A greater emphasis on gaining user consent for access to API data beyond the basic elements which are user ID, name, email, gender, birthday, current city, profile picture URL, and the user IDs of the user’s friends who have also connected with your application
  3. A greater emphasis on gaining user consent for using that data beyond the Facebook application.

I think that is a great move by Facebook but clearly means that marketers must act responsibly. It may only take a few violations to create a backlash by Facebook users. All marketers would suffer a set back as a result.

    Unica NetInsight report on today's Facebook application users by gender and age range

    Unica NetInsight report on today's Facebook application users by gender and age range

    Going Beyond Analytics to Interactive Marketing

    As always with Unica NetInsight, the built in data warehouse stores the granular and complete interaction history of each individual Facebook application user keyed in their Facebook ID.

    Unica NetInsight, granular data drill down to individual Facebook app users

    Unica NetInsight, granular data drill down to individual Facebook app users

    Not only can the Facebook application remember its user’s preferences. But by going from analysis to action, Unica customers can also use the profiles of Facebook application users to personalize future emails or website sessions. This assumes, of course, that the Facebook user is identified with their email address or website cookie and that permission to market has been earned.

    What data is available from the Facebook API?

    As Facebook application developers can glean from the documentation of the Facebook API, rich access to details about app users is available through API functions such as Users.GetInfo.

    It is however key to point out that not all data fields from API functions such as the one above are available for all users. Rather, only the fields for which the user’s privacy settings permit access are available to applications. Additionally, some particularly sensitive fields require explicit user permissions.

    • For example the email address (even the proxy’d version) requires extended user permissions.
    • For example, the gender info is only available if the user clicked the checkbox on their profile to include gender as part of their profile page

    For more information

    Unica customers can contact their account mangers for more details on the Solutions Pack for Social Media Analytics.

    Analytics for Facebook Fan Pages and Tabs with Unica

    One of the most exciting developments in web marketing over the past twelve months has been that the website is now considered only one of multiple components of a company’s web presence. Among the many other web presences that companies have these days is often a Facebook Fan page such as the one from Unica seen in the image below.

    Fan pages can include custom HTML content on custom tabs such as the tabs “MIS2010” for Unica’s upcoming customer conference and “Save Ned” for an innovative social media campaign of ours.

    These things take effort to create. So, naturally you want to measure usage and behavior to help you improve usability and ROI.

    Facebook page 8 - Unica MIS2010 custom tab

    To that effect, Unica announced the addition of innovative social media marketing capabilities for users of our online marketing solutions this week.

    And among these additions is the Solutions pack for Social Media Analytics for Unica’s web analytics solution, NetInsight. Part of the solutions pack addresses tagging of Facebook fan pages and custom tabs for tracking with Unica NetInsight.

    More specifically, Unica NetInsight, NetInsight OnDemand, and Interactive Marketing OnDemand customers can:

    • Report on usage trends for their Facebook Fan Page’s Wall tab
    • Analyze usage of any custom HTML / FBML tab that they create
    • Understand interaction within custom tabs, e.g. the clicking of FBJS driven interactive buttons or links

    Facebook page 10 - Facebook fan page trends

    (click to enlarge)

    Users can also create engagement funnel reports such as the following example. This shows visitors interacting with the Fan Page Wall vs. those who proceed to interact with various tabs vs. those who interact with dynamic content within tabs. An example of a custom tab with dynamic content is for instance the Save Ned tab on Unica’s Facebook Fan Page.

    Facebook page 9 - Unica Save Ned custom tab

    Below is an example of such a funnel. (not actual Unica data from Save Ned)

    Facebook page 11 - Facebook fan page funnel

    (click to enlarge)

    For more information about the Solutions Pack for Social Media Analytcis, Unica customers can contact their account managers.

    Q&A with Eric Siegel on Predictive Analysis using Web Analytics Data

    Last Wednesday (March 31st) Eric Siegel presented on 5 Ways of leveraging predictive analysis using web analytics data.

    Registrations and attendance were very strong which isn’t surprising because the WAA”s yearly survey had recently shown that predictive analysis is a top question on which web analysts seek to get more education.

    You can access the recording of the webcast here.

    Meanwhile, Eric was nice and speedy enough to answer all the questions that came in during the webcast. You can access the Q&A on the new Unica blog.

    Check this Q&A blog post out even if you don’t have enough time to watch the webcast.

    By the way, did you know Unica had a blog? It was recently restarted and is on fire with lots of contributors blogging across the company now.

    Thanks much to Eric Siegel for a super insightful webcast and Q&A. If you had any doubts on whether predictive analysis makes sense on web analytics data, then be sure to watch this webcast to open your eyes.

    Is Web Analytics 2.0 Right to Discourage Predictive Analysis on Web Data? I don't think so.

    The great Eric Siegel is going to speak in a webinar on March 31st on the topic of predictive analytics for online applications using web analytics and other data as input.

    In web analytics we always think that predictive analysis is the natural next step and will do great things for us. But most of us, when asked, have a very hard time explaining what exactly predictive can do. Avinash Kaushik in his (otherwise groundbreaking and highly recommendable) book Web Analytics 2.0 (and earlier on his blog) almost downright discourages predictive analysis on web data.

    But, this is one area where I think Avinash’s opinion is not as balanced as it should be.

    Predictive analysis folks such as Neil Mason and Eric Siegel and myself have made various recommendations in articles and posts in the past to showcase opportunities from predictive analysis. Of course, Eric Peterson too has aimed to describe the possibililties in his paper “The coming revolution…” 

     

    But come and see the webinar with Eric Siegel so you can make up your own mind.

    … 

    P.S.: I highly enjoyed Avinash’s web analytics 2.0 book though and will hope to post a critique  in coming weeks.