X Change 2011 Think Tank Information

One of the most ignored and poorly performed tasks in web analytics is making sure that your implementation is right. When end users do not trust the data or analysts are not clear on what is being measured, web analytics loses credibility in your organization. Whether your testing a new implementation or auditing an existing one, it’s essential to understand what to look for and how to make sure what’s there is right. This class will cover the use of HTTP Debuggers including Firebug and Charles to test individual pages and functions, tools like WASP & ObservePoint to scan sites, templates for building testing checklists, scanning sites for likely measurement trouble spots, and the many joys of web analytics administrative configuration. A must for anyone doing or faced with serious implementation or auditing work.

Excel is the single most important business intelligence and reporting tool. It is by far the most common source of web analytics data in most organizations. But building and distributing Excel reports can be a nightmare for a central organization. In this class, we'll cover how to build user-driven and analytic capabilities into your Excel templates so that far fewer reports can deliver more flexibility and more information to users. A focus will be placed on features that keep automated reports fresh, relevant and actionable months after they are rolled out. Techniques covered will include many advanced Excel techniques for optimizing user selection, laying out analytics data, creating robust navigation, building automated annotation, and doing all this while keeping the size of your Excel reports manageable.

Moving Digital Analytics data into the warehouse is the hottest trend in enterprise measurement. Taking the jump from SaaS solutions to warehouse solutions isn’t easy, however. Not only are the systems more expensive and the resource requirements much higher, the data itself presents many challenges. Moving server call level data into a warehouse is far from optimal. Server call data is too large and too hard to use effectively; not matter what your technology, having a more robust data model for online data is essential to get the most from your digital data. In this class, we’ll work through the essentials of building a really robust digital data model for the warehouse. You’ll learn key techniques for aggregating data in a warehouse and for creating a powerful digital analysis and database marketing platform.

With new technologies putting the Internet in everyone's pocket and an exploding apps market taking the possibilities to dizzying new heights, mobile devices have assumed a central role in the Internet equation. But going mobile is the easy part. The trick is to make sure your investment pays off, and for that, new metrics strategies are needed. This class will offer an in depth review of the mobile measurement landscape from a SMART perspective focusing on the Strategy, Measurement, Analysis, Reporting, and Tactics you need to ensure mobile success. We will cover mobile metrics and tactics for measurement enablement across mobile web sites and mobile applications. This class will help you answer questions such as "Why does mobile matter and where does it fit within my organization?", "What mobile metrics can I collect and how do I capture them?", and "What are the current capabilities and limitations of mobile measurement tools?"

Why does analytics take hold in some organizations and not others? Why does a strategy that's worked in one company, not work in another company with similar characteristics? In this session, we'll analyze scenarios and case histories in a range of organizations through the lens of management practice, business process and communication strategy. We'll review why some analytics programs never seem to get beyond basic measurement while others quickly achieve credibility and value. You'll learn how to develop solutions to bottlenecks and obstacles with diplomacy, leadership and creativity so that you can move your program ahead… whether you lead an analytics department of one or 100.

If you've ever wondered about the relationship between what you want to measure and what goes into a tag, this is the class for you. A class for implementers AND managers, the goal of this class is to show how specific business requirements drive down to a tagging specification and then an implementation. Along the way, you'll see some different approaches for mapping requirements that we've used and find out what worked (and didn't work!) with each. If you're a developer, this class will help you really understand why a tag is or should be the way it is. If you're a manager, this class will help you understand how what you want has to get embedded in the tag and what's involved in getting it there.

If you’d like to take your web analytics beyond counting page views, visits, and unique visitors, then this tutorial is for you.

In this session, Phil Kemelor will lead you through a step by step process on how to develop executive dashboards, as well as the web metrics and reports for your online marketing and content teams. This is a tool neutral class that will focus on both the business and technical aspects of metrics development and report building. The goal: Your understanding of the complete process required to get to the next level of web analytics.

To do this, we will start with a set of requirements based on class participant use cases. We’ll use this baseline to develop metrics for the dashboards and reports. We’ll also evaluate the pros and cons of creating scheduled management reports vs. ad hoc reporting vs. deep dive analysis of a finite data set. We’ll then consider the technical implications of creating the metrics, such as potential data collection issues, integration with offline data and calculation of customized metrics, as well as when it makes sense to use Excel instead of the analytics’ solution interface. Finally, we’ll discuss visual formatting options for presenting your reports and analyses.

To be clear, this is not a “silver bullet” class, where you’ll get a plug and play solution to your challenges. This is a “teaching to fish” tutorial where you’ll learn what you need to create metrics, reports and analyses that can drive decisions and actions.

Many of today’s most sophisticated enterprises are realizing that some of their most important data assets are trapped in siloed systems as text or voice based data that is almost entirely unused by the organization. Marketing’s ever-growing emphasis on understanding customer attitudes, needs, and decision-making is driving key trends in both behavioral and VoC analytics.

On the behavioral side, it’s driving toward the integration of database marketing techniques. On the VoC side, it’s driving toward the creation of universal text-based Customer Intelligence Systems. In this class, we’ll focus on the key data sources that drive a Customer Intelligence System – from VoC to Social Media to Call Center. We’ll show how each can be integrated and mined to create a comprehensive view of consumer attitudes and priorities.

Everyone agrees that they want to measure engagement, but what exactly is it that they are measuring and how should they go about doing so? This class will first describe different approaches to understanding what engagement is, including definitions around visitor satisfaction, eCommerce, success, frequency, recency, depth, reach, focus, or reliability.

New factors, such as viral proclivity or mobile participation, will also be discussed. Second, the class examines different techniques for measuring and reporting on these kinds of engagement: the advantages and disadvantages of scoring and indexing, ongoing segmentation, longevity, and up-sell. When more detailed and nuanced understanding of segmentation is required, analytical techniques such as factor, regression, or time-series analysis might be necessary, which will also be illustrated through case-study examples.

Finally, the class will discuss ways to disseminate engagement definitions within the organization, so that everyone agrees on what is meant by “visitor engagement” and can respond to these metrics actively. When visitor engagement might be the only KPI relevant for a given website, all these considerations and techniques become especially important.

Why in the date rich world of social media tracking do so many dashboards go no further than showing brand mentions and your Facebook fan trend? In this class we'll push social media scorecarding well beyond the standard (and boring) KPIs and discuss how to add insight and intellect to our reporting. To get started, we'll stroll through the end to end process of scorecarding social media from of vendor selection (as it pertains to report output), to building social media keyword profiles to generating scorecards. Our focus will be on creating the richest set of KPIs possible through segmentation and competitive comparisons. Visual representations will be generated around many of the KPIs to showcase them in a way that make them impactful but easy to digest for all levels of the organization. Participants will walk away with the skills to increase the value of social media data and broaden the organizational appeal of social media scorecards.

Everything old is new again! In this class, we'll drill-down into behavioral use-case analysis and examine a set of techniques and methods that we've been having great success with at Semphonic. Use-Cases have always been a fundamental design technique in the online world and they've been studied before. But we've found that by taking a systematic approach to use-case identification and study we can often find the unexpected use-cases that capture new and important site behaviors. In this class, we'll look at some actual examples of use-case analysis, explain some of the techniques for measuring use-case efficiency and identifying new use-cases, and consider how best to present a use-case analysis. We believe that along with Functionalism, Use-Case Analysis is one of the most powerful and generalizable methods of real-world analysis. If you're interested in techniques for "breaking the analysis barrier," this class is a perfect fit.

Many Web Teams struggle to communicate their need for resources to improve the operational infrastructure for the Web. Executives will make investment in a new re-design or better technology, particularly if there is a visible result. But, what about enhancements to infrastructure that are less visible but just as crucial like removing redundant or outdated content, or hiring a content strategist or editor to bring coherence and consistency to content? Often teams are at odds to make a business case for these less visible by highly impactful infrastructure roles that can help raise quality and improve Web site performance

In this class, Lisa Welchman will discuss strategies to translate basic Web analytics data into meaningful information for executives—with an aim towards helping executives understand the importance of maturing the organizational approach to digital development.

More and more often us web analysts are being pulled from the comfort and security of web analytics based dashboards and are thrust onto building all encompassing digital dashboards. Instead of cracking under the pressure of seemingly limitless data sources, we'll discuss how to seamlessly integrate web analytics, competitive insights, social media, survey and others. We'll start with tips for pulling and organizing multiple data sources that lack a common integration point. Then, moving from the backend data pulls to the forward facing dashboard visuals, the class will walk through displaying the variety of sources in a way that creates a single, logical, high impact report. While the primary reporting tool used for this discussion will be Excel, we'll also discuss the application alternatives like Tableau.

Few metrics and concepts in web analytics are more confusing to the eager stakeholder than the attribution of success events to marketing, merchandizing, or content elements. Often the culprit in common web analytics frustrations (“Why don’t these numbers add up?” “Why are PPC codes showing up in my Email segment?”), attribution in traditional marketing is different from attribution in web analytics, with different approaches and alternate vocabulary.

Most of the time, the lifespan and attribution model used in a tool was chosen either through guess-work, or by simply using the tool’s defaults. This class explores first what attribution means, using examples from different industry verticals, so that participants all understand the implications of first, most recent, linear, or participation models. Second, we will discuss what factors should go into choosing one model over another – how to determine life-span, for example. Finally, more advanced options will be discussed, exploring the feasibility and usefulness of mixed and dynamic models.

Enterprise deployments of Google Analytics are now estimated to be 60% according to Forrester. Often this starts as a simple need for campaign tracking and expands to something more. This raises the question of how should you be using Google Analytics in conjunction with your existing analytics platform? In this class we will cover common deployment gotchas, data reconciliation issues, what Google Analytics is and is not good for and how to put it all together.