X Change 2012 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.

At the enterprise level, data warehousing initiatives are big, scary, expensive and time-consuming. Of course, it doesn’t have to be this way. There are a range of fast, agile technology systems that can form the basis of a small, inexpensive customer analytics test-bed: a platform that you can use to experiment on your data, bring it close to your analysts, and give yourself the flexibility to play with the data. Even if you have a full-on data warehouse, there is often significant benefit to a smaller, less controlled platform. Many of the best and most interesting uses of data emerge in this type of environment. We’ll explore how to source your data, how to think about sampling, panels and short data windows, ETL and ELT alternatives, technologies and partners to make your life easier, and even some ways to justify your initiative. Along the way, we’ll talk about technologies like the Amazon Cloud and Azure, data management systems like Hadoop, columnar databases like Infobright, cloud-based data integration and analytics services like Quantivo, advanced analysis shops like Coldlight, and traditional database integrators with a focus on digital like iJento.

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 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.

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.

• Linking Power Point to Excel (file management, linked graphs, linked cells, using conditional formatting).
• Excel Data Visualizations (Month over Month comparisons, trending with mixed granulaties, custom data labels)
• Other Data Visualizations, (Word Clouds and Word Could customizations, Power Point charts and visualizations)
• Macro-less Refreshing (from Excel plugins, from external data sources, rolling date ranges)

If you've ever needed to combine data across multiple sources to quickly extract insights, this class is for you. Learn how to take CPC data and combine it with keyword and bounce rate to see which campaigns are working for you. Learn how to use Tableau's built in map feature to get more power from geolocation and zip data. You don't need to have a degree in business intelligence to integrate data using Tableau desktop. Also covered are best practices for data visualization and presentation.

Imagine a world where you can make a change to your analytics implementation with a few clicks a couple key strokes. A world where you don't have to talk with IT to make a change made. A world where you can put Google Analytics on your site in under 5 minutes. That is a world that tag managements solution providers envision and claim they can provide, but what is the reality of it? Life is rarely that simple but they are powerful cutting-edge tools that will make any large site look twice. They are not going away anytime soon and can drastically cut down implementation and maintenance time/resources. This class will cover why you would want to use one, how they work, implementation strategies, real world examples and more. Emphasis and examples will given using SiteCatalyst/Ensighten, however many of the concepts can be applied to other solutions.

An exploding apps market is taking mobile marketing to dizzying new heights. Traditional web centric measurement strategies are simply not enough to evaluate and quantify mobile app performance - and downloads are a meaningless metric if not taken in context with other metrics. Recency, Frequency, Intensity, Duration, and Monetization metrics provide a solid framework for mobile app measurement and this class will offer an in depth review of the mobile application measurement landscape focusing on the metrics and measurement techniques you need to be successful with mobile application measurement and optimization.

Facebook, Twitter, YouTube and social media mentions tracking doesn't belong in silos. Pulling together these independent channels might pose challenges, but it's an essential step for companies dedicated to fully understanding their full social presence. This class will walk through the end to end process of building an automated, multi source social report that shows competitive comparisons and how your brands overall social footprint is trending. We will evaluate the tools that can facilitate this level of automation and identify the right tool mix for any set of needs and budget. A portion of the class will be dedicated to developing a rich set of social media specific KPIs that go beyond what is immediately available within the social tools and will connect social behaviors back to your business. Finally, visual representations will be generated around many of the KPIs to showcase them in a way that make them impactful and easy to interpret at all levels of the organization.

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.

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.

In the past, I’ve taught classes on Use Case-Analysis, Functional Analysis, and Survey Analytics. I wanted to combine those three into a single “integrated” analytics class that focuses on how best to understand your customer’s online behavior and the drivers of consumer decision-making. This class will do just that. We’ll start with a look at developing use-cases and understanding their performance with Functional techniques. Then we’ll focus on how to re-engineer your online survey program to analyze the drivers of choice within each use-case. Finally, we’ll walk through the use of the analysis in structuring a testing program and driving site change. It’s designed to be a complete survey the analytic techniques necessary to drive ongoing site improvement.

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.

It's a web analytics show down! Does the marketing live up to the hype? What are the closely guarded Achilles heels' of each tool? We will consider both GA Standard and GA Premium in this class as we compare the capabilities to the vast improvements of SC 15. We'll cover modifications, costs, and compare real site examples.