We are proud to announce that the ink has dried on a definitive agreement to acquire Widemile, which adds world-class multivariate testing and site optimization to our arsenal of customer intelligence technologies and services. The combination produces an unmatched analytics and optimization platform giving our customers an even greater advantage in the marketplace. For us, this deal reinforces our company’s momentum under the helm of our CEO Alex Yoder and further solidifies our position as the leading enterprise customer intelligence company.

“Webtrends now offers the most open, elegant and powerful analytics and optimization platform available anywhere.  Our customers want to further leverage the rich data set available with Webtrends Analytics, and Widemile’s capabilities provide a natural path to help our customers achieve better performance and improved ROI,” said Alex Yoder, Webtrends CEO.

Designed by optimization experts, Widemile’s platform provides the capabilities marketers need most, including intuitive wizards, real–time reporting and analysis, advanced visitor segmentation, full service and best practices services and training. Widemile’s third–generation, on–demand multivariate testing and site optimization platform is best known for its industry leading ease of use, algorithms and architecture, and reporting capabilities.

According to Forrester Research, “All too often, multivariate and A/B tests are performed as a means to identify problems and address issues, rather than a method to create better pages from the start.”  Marketers have been hesitant to use and deploy multivariate testing and targeting solutions, which have been traditionally difficult to use, time consuming, and resource intensive.  In response to the needs of the market, Widemile has built a platform that is both comprehensive in it capability and easy to setup and use in its operation.  Adding this functionality to the existing Webtrends platform further extends the core objective that customer behavior must be tested, interpreted, optimized, and measured to provide customer intelligence professionals with the ability make their businesses more successful.

“The Widemile and Webtrends offerings fit naturally to address the macro challenges and opportunities facing our customers in the coming years,” said Robert Bergquist, Widemile CEO and President.  “The combination is a best-in class integrated web analytics and optimization platform allowing users to plan online marketing programs with the assurance that built-in testing, targeting, and optimization solutions will maximize conversion rates.”

We’re on a mission to provide best-in-class enterprise customer intelligence applications capable of testing, monitoring and measuring all aspects of your online visitor’s interactions with your brand. 15 years ago we created the web analytics market and forever changed the marketing world by giving the online space its ultimate trump card: measurement. Fast forward to present day and the customer data landscape has grown significantly, especially over the past decade. We’ve made some big moves under the leadership of our CEO to prepare for the customer data driven future. Forrester recognized our efforts in their latest Wave Report saying,

Webtrends has undergone the biggest transformation of all vendors evaluated in the past year, with the restructuring of its entire management team and refocused efforts on Web analytics and its concept of openness. The result is a company united in delivering leading enterprise-class capabilities, which it does with exemplary metrics, dimensions, and correlations. The company scored high marks because of its ability to create unlimited custom and calculated metrics, as well as the capacity to perform unlimited correlations. Reference clients expressed high levels of satisfaction overall, with extreme satisfaction in responsiveness/support, application reliability, and value. Webtrends continues to develop its extensibility through expansion of data exchange, accessibility options, and a strong partner program.

Social media is changing the way businesses connect with markets. Conversations take place where the participants choose and are often spread across multiple sources. Pulling the conversation together in order to make informed, engagement decisions is at the heart of marketing’s challenge in this new media landscape. To demonstrate how Webtrends Social Measurement helps with a social media campaign, we advertised on the outside of Portland’s light rail, MAX, to monitor Twitter for responses to our ad. The idea is to publish the results on another MAX ad in October. We forecasted it would take 3 months to get a volume of results that would tell a compelling story, but a compelling story emerged in less than a week and spanned Twitter, blogs, and mainstream news. This is an update on that campaign.

Campaign results

The following are results from our measure of conversation on social media driven by our marketing campaign.

If a source had two or more posts, we combined the results. KATU had the most comments. BikePortland had the most commenters. Also worth noting, after we filtered for duplicates we discovered that the number of comments that KATU reports on their site are nearly double the actual amount. Unique commenters are considered unique usernames.

Sentiment is a hot aspect of social media. We recently wrote a post challenging the use of algorithms to determine sentiment, and this campaign is a great example of how NLP falls short. Sentiment is a complex tapestry of human emotions, not just positive, negative, or neutral. In this case our criteria was:

• Yes answers: People that only said yes.
• No answers: People that only said no.
• Same answers: People that said the amount paid now is fine.
• More answers: People that said pay more; including answers about licensing and registration.
• Less answers: People that said pay less; including answers about rebates or tax credits.
• Other answers: Comments that didn’t explicit state a position; including answers that were sarcastic or answered with a question as we can’t be sure of their inference.

As our results are human scored and could be interpreted differently by other people, we are providing our data so that it can be reinterpreted by anyone who is interested. We showed the top four sources broken out to show what impact sources had on the overall sentiment. Overall, the sentiment was that people favored either the same or less taxes than cyclists currently contribute. The strongest opposition came from Twitter, our original target source for monitoring conversation for this campaign.

Tag cloud for all conversation

Tag cloud for KATU

Tag cloud for BikePortland

Tag cloud for OregonLive

Tag cloud for all Twitter

Reflecting the salient points

In today’s media landscape, it’s challenging to track many viewpoints from many stakeholders. Making sense of a high volume of conversation from disparate sources isn’t easy for anyone. After tracking this conversation with our tools, here are some of the main points we learned:

1.) There is a lot of confusion on the facts about who pays for what currently

The most quoted source was the Federal Highway Administration (FWHA), which reported that 92% of the funds for local roads come from property, income, and sales taxes. It was the lack of general awareness of this fact that we believe causes a lack of empathy with cyclists as it pertains to taxation/registration. We did notice that the mainstream news sites that had the most “yes” answers to our question, many of which were accompanied by messages that indicated people didn’t think cyclists paid taxes currently. Others pointed out that cars, boats, motorcycles, airplanes and more have additional taxes including licensing, registration, and fuel taxes. Respondents pointed out that many cyclists are also motorists and therefore not only pay the unique motor vehicle taxes, but that it would be double taxation. To which people replied that the additional taxes are paid for per vehicle regardless of use, which therefore doesn’t constitute double taxation.

What is clear to us is that more conversation around this point could help clarify for everyone where contribution currently comes from, which is key to having a discussion about where obligations should be moving forward. While the information is out there, it doesn’t appear to be widely distributed, nor agreed upon. We see this as the greatest opportunity for constituents involved in public policy development around transportation.

2.) More taxes on cycling could be bad for everyone

There were two reasons for arguing this point. First is that people pointed out that less traffic, less damage to the environment, and more benefits were good for everyone. Participants reasoned that anything that discouraged cycling, such as taxes, prevents the community from reaping those rewards. As bikes do not use fuel, the only additional per vehicle costs that could apply would be licensing and registration. The only argument we saw against this point was the feeling of it being unfair that road faring cyclists didn’t have to pay these costs as well. Contenders pointed to the fact that state governments and municipalities who have adopted bike registration programs have later abandoned them due to the loss of the revenue to overhead.

3.) Some cyclists want more taxes, but under specific conditions

When people said they’d be willing to pay more taxes, they were only willing to pay more if the money went to bike specific infrastructure (we’ll include numbers in our final report). Nearly every answer for more taxes included the word “if”, often in all caps, and ended with extra exclamation points–indicating that people felt strongly that paying more was critically tied to the conditions that the money went to bike specific infrastructure. People expressed interest in better maintenance of existing bike lanes, more and better bike lanes, new bike-only paths, theft recovery, and more.

Other themes that came up were: Motorists are rude and sometimes dangerous about sharing the road; Road laws are not enforced equally on cyclists; Cyclists aren’t required to have liability insurance; Some people consider “cyclist” a loaded word.

Transparency

As part of our campaign, we are being transparent. That means we share openly about all details of the campaign. It also means our employees are free to discuss their thoughts publicly, even if they are critical. So, let’s talk about how we make money with this campaign. As I mentioned earlier, this campaign is part of a larger campaign called The Open Campaign. The Open Campaign will have it’s own microsite that will openly display the methods and results from various campaigns we’ve run using our tools. The concept is to provide a reference to businesses for what running campaigns with our tools looks like. It is that site that we’ll use to build leads for our sales team. While we do have a landing page for the MAX ad with a form on it, that form is to enter to win a free TriMet pass. Information from that form is *not* given to our sales team. It is strictly a promotional offer to encourage participation.

Want to see the results and make your own reports? Download our data »

Next Steps

Our question surfaced a diversity of viewpoints in much less time than we expected. As a result, we have an opportunity to progress the conversation by asking another question. If you have a suggestion for a follow up question, please share it as us a comment below.

Hi folks.  My name is Jason Widup and I recently rejoined WebTrends with a colleague of mine (Brandon Ralls) to start a Digital Marketing Optimization practice within the WebTrends Client Services organization.  Some of you may remember both of us – I used to manage the Strategic Business Consulting practice at WebTrends from mid-2005 through mid-2006 and Brandon worked on my team during that time.  My first post is more like an article than a blog post.  I promise not all of my posts will be this long, but this topic is something that is near and dear to my heart.

Throughout my career in web analytics I have had the opportunity to work on web projects for some of the largest and most well-known websites in the world, and I’ve been able to do this from many different perspectives, including client-side, vendor-side, and advertising agency-side.  While I expected many of the websites to be slow in adopting some of the more advanced web analytics topics such as behavioral targeting, multivariate testing, and tagging, I didn’t expect for most of them to have the challenges with ongoing performance reporting and representation of data that they did.

These companies all struggled with most of the aspects related to putting together a dynamic and effective monthly report: extracting accurate data from their measurement tools, data organization and visualization, report formatting (including delivery vehicle), and analysis/insights/recommendations.  Most of them were decent with analysis; however, because everything else took so much longer than it should they didn’t have the proper amount of time to spend on analysis, so even that suffered.  Fortunately, the solution to this is relatively simple in explanation and not much more complex in execution: data quality, automation, and a consistent, accessible report format – what we call an Integrated Digital Marketing Scorecard.

At this point you’re probably making a decision as to whether or not you should read the rest of this article – so I’d like to give you a few reasons to continue reading.  While this topic has been written about and discussed quite a bit, I feel that it still has yet to sink in because I’m not seeing it take hold in the work that I do.  And while I don’t profess to be a true EXPERT at anything, I am an intelligent, logical, and creative thinker and like to think that I just get it (and I been practicing Web Analytics for 6 years).  And as previously noted, I’ve had the opportunity to do this type of work for lots of different websites from a multitude of perspectives – the most helpful being my time at a very large and well-known digital advertising agency.  Many of the lessons I learned I did while managing Measurement Operations at that agency.

To formally define the problem, analysts are spending a much larger % of their available time extracting and formatting report data and not enough time on the analysis, insights, and recommendations – where the true utility of the data comes into play as it is converted to decision-making information.  In my rough estimation analysts are spending about 75-80% of their time on the tactical reporting work and only about 25% of their time on the real analysis work.  In a perfect world this would be reversed – spending just 25% of their time on tactical work and 75% on analysis.

As mentioned, the solution that we have come up with to address these problems is what we call an Integrated Digital Marketing Scorecard (or IDMS).  “Integrated” because it is a single report that includes data from multiple data sources, “Digital Marketing” because it contains data from all online marketing and website measurement systems, and “Scorecard” because it is a visual display of key performance indicators on a single screen, providing user-driven comparison and progress metrics and used to make management decisions.

Let’s look at each of the problems individually, as well as how they are addressed with the IDMS…

Extracting accurate data from their measurement tools

At one point not too long ago in my Web Analytics career I was managing the monthly reporting for nearly 15 separate websites, all of which wanted their report as close to the beginning of the month as possible.  Each of the sites had their own set of complexities and issues: tagging problems, custom report issues, communication breakdowns with clients, etc.  There always seemed to be some issue with some data point each month that meant I could not fully automate my data extracts because I had to scrub the data in some way.  This is where Data Quality comes in.  At the core of any good, automated reporting solution is high quality data.  It can sometimes take a good amount of money and/or resources and certainly process changes to achieve the quality of data needed to support this style of reporting, but from experience I can say that it will pay for itself in time saving and decision making support.

In this role I was so incredibly busy during the first few weeks of the month that I chose to only partially automate my data extractions and pull the remainder of the data manually.  I justified this by telling myself that it would actually take longer to automate the query for a data point than to pull it manually.  I also failed to consistently document how I would manually derive a certain data point and would need to reconstruct it and compare it to the previous month’s number to make sure I did it correctly.  This was incredibly time consuming.  This speaks to the second component of the solution, automation.  The bottom line is that if the calculation of a data point can be done fully automated, always do it.  It will save time and reduce the occurrences of errors compared to pulling the data manually.  When we build an IDMS for a client our goal is for there to be as few steps as possible each month to update the data and populate all charts and graphs.  In many cases we’re able to get this down to 4 steps: select a new month, click button to run queries, validate new data, click button to update tables/charts/graphs.

Data organization and visualization

Analysts struggle to find the best way to organize, visualize, and present the information in their reports.  It is very rare that I’m impressed when an analyst shows me a report they authored that they feel is one of their best pieces of work (by the way, don’t bring an example report to an interview unless it looks like something you would see on TV – you know who you are).  It amazes me the lack of attention to detail that is pervasive across the industry.  Presentation of the report can, in some cases, determine its success or failure.  If you have bad data to report, at least make sure it is presented professionally.

There are a few guidelines we follow when organizing and visualizing the data in an IDMS:

• Organize the data in a tabular or navigational format so that the user can page through different sets of data while remaining on the same screen.
• Group similar data points together into the different tabs and have them follow some type of logical progression (i.e. Acquire-Convert-Retain)
• Show a minimal amount of data on a screen, but allow the viewer to interact with the report to show historical data and compare it against more recent data.
• Only show one or two data points on a graph that are related – don’t overcomplicate it with 3 dimensions and multiple metrics, etc.

Report formatting (including delivery vehicle)

It can take a very long time to manually update all of the charts and graphs and screenshots necessary for a given report, we get around this by extending the automation to include updating the charts and graphs in the IDMS, not just run the queries.  Most people don’t fully understand the formatting capabilities of Excel but there are a lot of fancy things that can be done with formatting and interactivity – especially in Excel 2007.  Have you ever heard of the camera function?  If not, Google it and I’m sure you’ll find a great use for it.

Speaking of Excel 2007, that is our preferred vehicle for delivering monthly reports.  It supports the tabular navigation previously discussed, all historical data can be included within the file in hidden sheets, the Scorecard can be made to look like a polished web application, and most importantly, it’s in Excel – something that everyone has access to. Alternatively, tools like Excelcius can be used to build this same type of functionality but publish it as an interactive Flash object embedded within a PDF file.  I also love the idea of delivering these via the web, but that would require some web development because as of yet there is still not an available tool that I know of that can WYSIWYG a Scorecard.

There are quite a few other report formatting topics that I could discuss, but to keep this relatively readable I’ll add just one more that truly sets the IDMS apart from other solutions – specific real estate is set aside in the Scorecard for the analysts’ insights, observations, and recommendations.  This section updates when the viewer pages through the different tabs in the Scorecard so that it corresponds with the data they are viewing.  This is where data is turned into information that can drive decisions – without this analysis a report is not incredibly useful for obvious reasons.

The best way to approach writing the commentary is to first understand the business questions that need to be answered every month.  The questions shouldn’t simply be worded versions of KPIs like “How many visitors came to the site this month compared to next month?” – they should be business questions like “Which media tactics drove the highest engagement with product content?”  These are the questions that will be answered in the analysis section every month, supported by the KPIs and data in the Scorecard.

If you made it through this article, THANKS FOR READING.  I sincerely hope that it was worth the time you spent reading it.  If you’d like to chat further about this topic or see some screenshots of our Integrated Digital Marketing Scorecard, please feel free to reach out to me via email at Jason.Widup@WebTrends.com.  Happy Analyzing!

*originally posted on IQ Workforce