2011 Huddle Topics

Email is up 10%! Affilates are 20% over plan! SEM is growing 35%! Great! How come sales are DOWN 10% YoY? The culprit is Attibution … which Marketing program gets revenue credit for the sale. Like a herd of kids all chasing the same soccer ball each Marketing Channel is looking to claim credit which is compounded as visitors interact with ever more marketing touchpoints. How do you assess the true health of each Marketing Channel? Attribution is the answer however not one size fits all. In this huddle we will discuss the Attibution Hierarchy. Starting from siloed vendor reports, simple Last Click on site analytics, simple and complex scoring algorithms, all the way up to dedicated Attribution solutions and ROMI (Return on Marketing Investment). If you’ve ever wanted to better understand Attribution and what tool to use then this huddle is for you.
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Good news … you’re replatforming! You get to do a complete ‘redo’ of your onsite Analytics and finally clean up all those nagging bugs in your data that you can’t get prioritized with IT. Bad news … you’re replatforming! You have to do your day job to keep Legacy running while at the same time think through all of the implications of the new platform. Is there a better way to implement variables? If so then what about the comparison between Legacy and the new Platform? How do you stagger the releases? What about documentation and training? We’ll explore all of the benefits and “gotcha’s” of replatforming so that you don’t skip a beat.
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It's one of the most discussed topics amongst media companies of all sorts - from news organisations to broadcasters - should we charge for content online? Entire industries have been built around giving content away for free online, but recent market shifts have caused many in this area to re-evaluate and look for opportunities to make online business more profitable.

In this huddle, we'll talk about the science behind paywalls: are they right for your business and how would you know? How might you price or develop a charging model for your content? And how could you use analytics to build a business strategy?

For analysts, there is a major upside to paid models in the form of a better understanding of our customers - a persistent customer identity that allows you to analyse who they are, and what they read. This - combined with a direct link from content via customer to (subscription) revenue - provides a rich data set to empower your analysis. We'll discuss the benefit of persistent identity and what it means for your analysis, as well explore some ideas about exploiting this data to execute a paid strategy.
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Predictive analytics is a mature industry and there is a growing trend in combining this discipline with web analytics. This topic was popular at XChange last year, with many organisations starting to use statistical models to predict online user behaviour. There is significant mileage in the idea of building (even simple) statistical models to help identify which customers are most likely to buy something, to click, or which thing is most relevant to serve to a user to encourage them to engage further. Applications might include improving the targeting of email marketing and increase sales, or online behavioural targeting to improve usability and customer experience.

One of the biggest challenges in predictive analytics is that it typically requires a user identity to execute campaigns and online targeting - something often missing from web analytics data. The techniques are the same however you deploy them, requiring both an analysis phase and then identifying a way of influencing users to encourage them to improve on your objectives. In this huddle we will explore mechanisms for enabling predictive analytics using cookies alone. We will discuss both the analysis of anonymous users, and also the use of these insights to drive behavioural targeting or execute marketing activities without e-mail addresses or other persistent user identities.
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XChanger’s have been dreaming of geeky (but cool) analytics solutions for years. Finally there is a technology that can fulfill these dreams. Tag Management is revolutionizing the way we do analytics. It also offers the potential to fundamentally change the way that we do business. Don’t get left behind.
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There has been an explosion of companies that promise to take your data, secretly manipulate it and then provide you with untold riches. Before signing up with these companies you should answer some questions. Should we be outsourcing our insight generation? What impact does this have on our ability to create a Competitive Advantage? Is there a better way to do this?
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You know Web and Mobile Analtyics is a good business to be in when there seems to be a new company entering the space on a daily basis. The problem is how to keep up with them all and determine if you need to work with each new product. There are many slightly over-lapping categories of vendors – traditional analytics (Omniture’s Adobe, WebTrends, IBM, etc.), syndicated analytics (comScore, Nielsen, Quantcast, etc.), social media tools (Radian 6, Crimson Hexagon, Sysamos, this list goes on and on), and video vendors (Visible Measures, Conviva, Akamai) etc. This list could go on to include Multivariate testing vendors, vendors that specialize in Mobile Apps, and on and on.

And yet each category is becoming increasingly overlapping and competitive as each vendor tries to get into the others space. Omniture making a MRC approved syndicated data source and a Social Media tool, comScore producing a web analytics tool, etc. This session would be dedicated to discussing questions about this phenomenon:

• How does one select vendors to work with when so many are overlapping?
• Is it worth working with separate vendors for each of these, or can a company consolidate and focus on one? Or is it better to tag for various vendors and pull all of the data in house into an enormous internal data ware house?
• Is it even necessary to tag for a larger percentage of these companies?
• What criteria do companies use to determine who to tag for our use?
• Who is the best at each of these specialties and who is most likely to succeed in the long run? In other words, is anyone willing to guess who will win the Melee?
• For tag or beacon vendors, does it make sense for us as an industry to push for one tag that all vendors would use? This could reduce weight and page load times.
• Are we doomed to having to forever explain why the data from each of these vendors doesn’t match, or can we work towards standards across each of these tools?
• Does having more competition between tools create more confusion, or more opportunities for standardization?
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Learn how to find easy opportunities for predictive analytics. You don’t have to be deep reaching in order to take advantage of patterns in your historical data to identify risks and opportunities. While you certainly could spend lots of time uncovering hidden relationships in the data, that is - if you actually have the time to invest. But simpler and more readily available trending can be used. Come join your peers in sharing and exploring data and metrics already at your fingertips which can be evaluated for effective predictive analytics with a reduced time investment. What successful techniques have you used lately in order to deliver predictive insights from your data?
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How do you know when your organization needs more education and help understanding your data? How can you stay on top of information outflow from your analytics tool? Come explore how you can identify, using the questions being asked by whom, where your knowledge gaps are and what alarms should be raised. Learn management techniques and strategies such as Rolling Audits, Reporting Audits, Re-education programs and Stakeholder Training. Given all the daily demands faced, come join your peers in discussing what’s worth investing your time in to better manage your web analytics program and data.

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Many organizations are now crossing into “Big Data” territory and are having to learn with what this means. What should you be ready for in terms of hardware, applications, people, processes and political mindset? We hope to share stories of how small, medium, and large organizations are dealing with this question, and explore how this question changes with an organization’s maturity level. Are there best practices to share beyond just selecting your hardware? And how does this impact how your organization approaches analytics in general?
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Bounce rate…time on site…page depth…daily unique visitors...video views…file downloads...event registrations… demand generation...reach…user experience…. Whew! Measuring B2B website and marketing campaign effectiveness is a challenge. Join this huddle, moderated by Anne Commisso, Manager Web Marketing Metrics for Cisco.com, and share your thoughts, suggestions and best practices.
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Wouldn’t it be great to have a single metric which combined volume and success event measures into engagement scores you can compare across site areas or landing pages? And wouldn’t it be even better if an engagement score could be applied not only for site analysis, but also as a predictive indicator? Join this discussion, moderated by Anne Commisso, Manager Web Marketing Metrics for Cisco.com, to discuss the use of engagement scores.
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Which metrics are best in a crisis? Different data reveal different parts of the puzzle and it takes a seasoned analyst to piece it all together. Often a data holistic approach paints a much clearer and easy to manipulate picture. Web analytics may identify an area in need of improvement but the rest of the data tells us what exactly is broken and how to fix it. How has your organization brought the pieces of the puzzle together to diagnose and fix site problems or to create site enhancements? What pieces have you integrated (web analytics, usability, search log analytics, customer satisfaction surveys) and how? Is this a hands-on or automated job and how often do you perform this data holistic analysis? Come join your colleagues in discussing an integrated approach to evaluation data.
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Bringing data together is often essential to creating a realistic and accurate description of a problem. But how do you actually go about bringing data together? Analysts have to deal with three levels of integration: deep integration where data is tied together at the customer or detail level, integration of data at some higher level (such as campaign), and off-the-cuff integrations where the analyst simply uses two fundamentally different pieces of data to shed light on a specific problem. How do you know which level of integration to strive for around key data sources? How do you bring data points together to create those new perspectives or sudden insights? What are the most appropriate and powerful tools for real-world data integration (think anything for Excel to SQL Databases to Scorecards)? Join Susan Fariss in an exploration of the challenges in data integration - from deciding what to combine, to choosing the right level of integration, to thinking about the right tool for the job.
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Testing is a central ingredient in any good Web analytics and optimization program. It’s also a central concern for analytics teams. The design and creation of a cohesive testing plan is one of the fundamental concerns for an Online Measurement Team. Segmentation is the key to this enterprise. Matthew Fryer leads analytics and testing for Hotels.Com. In this Huddle, you’ll join him to explore the role of segmentation in designing a comprehensive approach to testing. You’ll discuss how to identify key segments, how to interpret their behavior to isolate key testing opportunities, how to use all of your data to target and design tests to be most impactful, and how to focus Web analytics on the creation and analysis of tests and their results.
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In this Huddle with Matthew Fryer of Hotels.Com, you’ll explore a data-driven approach to hypothesis generation. It’s a problem fundamental to the discipline of Web analytics: how do you know what problems to study and how do set the range of possible solutions. Undirected exploration of the data is highly unlikely to be successful. Purely subjective approaches seem to violate the commitment to data-driven decision-making that we are all committed to. Are there ways to use the data to set the agenda for analysis; to generate hypothesis about what is worth studying and to create the alternative solutions to a problem that are worth studying? Bring your best thinking about how to drive data-driven decision-making by using the data to tell its secrets for this unique session.
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Over the past decade, marketing organizations have enjoyed a buffet of internet delivered technology to help optimize the online channel. But many organizations need more. Limitations are felt when requirements call for advanced analytics, multi-channel integration and linking in metrics from social media analytics tools. In addition, business intelligence skills, such as data quality, data modeling and building semantic layers are often hard to find without engaging with the IT organization. Some market leaders have figured out how to combine the technical skills within IT with the business skills in marketing to outperform others. Other marketing organizations go it alone. This huddle will explore if there is value in working closer with the IT organization, the barriers in doing so and ways to break through the barriers.
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Social CRM is a business strategy which benefits communities and businesses by fostering engagements, while generating opportunities for sales, marketing, product development and customer service. Social media is a growing form of content and social applications are important channels to attract and interact with customers. This huddle will explore how this is being handled. Who’s in charge of the strategy? Which organizations are involved? What is the role of a social content management system? How is social data combined with marketing campaigns, sales applications, transaction records, customer master records and the customer service knowledgebase? What are the new challenges on the analytics team?
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Many organizations are considering tying details from a CRM database to a analytics system. As an analytics practitioner, what are the challenges to getting these systems up and running. How concerned are you about personally identifiable information. How much data do you want to be available in the cookie or exposed in the session? Do you track everything or limit the scope? Will you have data on enough of site visitors to make it worthwhile? Do you supplement with other data collection methods? What’s the payoff? The group will discuss first the benefits to the connection, what’s needed to make it a success from a business point of view and then what’s need from an technical/instrumentation point of view.

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At most organizations, analytics practitioners focus on one or two primary tools. However, many systems have specific databases of records for say transactions or activity within a site subset such as a vender add-on or mobile app. How do you reconcile issues between the overarching primary tool and the database of record for specific site actions or sections. When do you use the primary tool for reporting and analysis? When do you use the database of record to report on activity?

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It may be the single most challenging problem in Digital Analytics – how to create an accurate yet understandable view of the complex network of online marketing channels and how they are contributing to the organization. Scorecarding is an essential part of today’s enterprise management; but what’s the right recipe for success? Ian Gruber’s been leading Walmart.com’s Web Analytics efforts and you can join him in this exploration of the fine art of data reduction and data representation at the enterprise level. You’ll discuss a range of scorecarding issues (from finding the right framework for measuring success) to different strategies for integrating report data, to cool ideas participants bring for presenting their numbers.
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Getting your measurement infrastructure right once is a challenge. Keeping it right is doubly so. Ian Gruber has been managing the Omniture infrastructure at Walmart.com – one of the most demanding environments in the world. In this Huddle, he’ll guide an exploration of the processes that produce reliable and robust web measurement. With all the interest in Tag Management Systems, it’s easy to forget to that there is much more to good governance than technology. From measurement design to tool-specific KPIs to change management to administrative access, having the right processes in place is critical no matter what technology you use to drop the tag on a page. You’ll discuss which process steps are most important, how to get them right, and how to make sure they can scale in the large enterprise.
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Creator of the Online Analytics Maturity Model, Stéphane Hamel has been looking at the challenges, pitfalls and reasons why so many organizations are struggling to develop a data-driven culture. Is our task so special and unique that we can’t learn from other disciplines? Stop complaining web analytics is hard and do something about it! Chime in, learn what your peers went through and share your tips to bring the best of online digital measurement to your organization and clients.
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We went from logs to tags and now TMS - Tag Management Systems - are the latest weapon to get rid of IT - or are they? Tagging is the poisoned apple of analytics - nice and shiny on the outside, they are conceptually simple, yet, they can sicken and get even the toughest analysts crazy. What should you watch for, why? What is haunting your nights? What are the pitfalls to overcome? Are TMS the solution?
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The move to warehousing Web analytics data feels more like a tsunami than a wave in 2011. The integration of Digital data with Customer Data is probably the biggest single reason driving the trend. Steve Harris of Capital One will lead this exploration of the why’s and how’s of data warehousing and customer/offline data integration. From establishing the value of CDW/Digital integration, to choosing technologies, to finding the biggest opportunities and paybacks from integration, this Huddle will cover the key strategies and techniques for driving a data warehouse integration to a successful outcome.
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There’s no getting away from politics at the enterprise level. To be effective in a large organization, you need resources, access, and enough pull to make your voice heard. Web Analytics is a young field that’s still finding its way among a host of more mature marketing and research disciplines. Because of that, there’s no guaranteed place at the table for Web analytics, and it’s sometimes a fight to make sure your voice is heard. Join Steve Harris, Sr. Director of Web Analytics at Capital One, for an exploration of the ins-and-outs of promoting Web Analytics in the enterprise. If you’re a Web Analytics Manager at the enterprise-level, you know that this is, in many cases, job one. How to communicate the value of Web Analytics, how to create and maintain trust, and how to find and own the right place in a large organization are all critical pieces of the management challenge that you’ll discuss in this Huddle!
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Mobile isn’t just one platform any more. Between mobile apps, mobile sites, mobile video clips and a host of different mobile hardware systems, building mobile measurement infrastructure can be extremely challenging. Chris Johannessen of BarclayCard US has deep experience in mobile measurement including a US Patent pending for mobile uniques. His Huddle will focus on techniques for raw mining of the mobile stream, mobile visitor identification, and the guts of mobile implementations including measurement approach, QA, and governance. It’s a great opportunity to delve into the inner workings of Mobile measurement and share best practices and techniques for working with detailed mobile data across multiple platforms.

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More and more businesses are finding that the traditional nuts-and-bolts approach to internet marketing may not be enough. The Web is as much an entertainment medium as an eCommerce channel – and that often makes for an uncomfortable blend as sites decide whether and how much they need to “entertain” visitors to keep them engaged. This Huddle, hosted by BarclayCard’s Chris Johannesen will focus on measuring analytics for non-media sites that have added content to drive commerce or engagement, from content consumption to purchase success. Explore this emerging area with Chris and help reach a consensus on the appropriate measurements to help your organization decide whether, where, when and how much “Merchtainment” is appropriate.
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Managers of search engine optimization dedicate considerable time to mining web analytics data without the expertise of analyst. We will discuss how to provide analysis that drives effective search engine optimization and how findings from SEO analysis provide insights across the business. In this type of analysis there is a tendency to focus on keyword rank, but we will cover broader topics including how organic search drives traffic/conversion, how to advise the business teams where to react and analytics to best inform strategy.
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Many retargeting programs are designed to be utilized by marketers without involvement of an analyst. While these programs can reduce resources required to execute it may exclude a data driven approach and the design of appropriate measurements before campaign execution. We will discuss what the analyst role should be in retargeting campaigns including how to best determine KPIs, advanced segment design, inclusion of A/B tests and how to best partner with the marketing teams to insure effective resource allocation.
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Two years ago we discussed the concept of a splintered web and today it is our every day reality. As the digital media world continues to fragment into multiple mediums (mobile phones, iPads, TV etc…) and companies embrace extending their presence on an ever increasing number of platforms (Facebook, Twitter, YouTube, iTunes etc…) all digital media businesses require access to more data than ever. The ability to pull this data quickly and efficiently is key for companies to separate themselves from competitors and remain profitable. In this huddle we will discuss current issues and solutions for managing disparate data sources and still providing actionable insights.
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In 2010 companies committed vast resources on “Social” projects. In 2011 we are trying to understand what the return on these investments is. While everyone in our companies continue to experiment with Facebook’s open graph and other social widgets it’s our job to understand what works. Whether your company is using facebook connect, integrating the “+1” button or building fan pages you will most likely continue to integrate your online business. This huddle will discuss strategies for measuring social behavior whether it occurs on your site or on a social media site.
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Many more advanced organizations are looking for ways to do more with their Web analytics data. Dylan Lewis has been leading the industry by driving advanced measurement at Intuit’s TurboTax division. In this Huddle, you’ll explore ways to use raw clickstream data – not the aggregated data cubes common in traditional Web analytics. With raw clickstream data, you have new opportunities and new problems to deal with. How can you manage the vast amounts of data raw clickstream can generate? What are the right ways to use traditional tools for more advanced analysis? How hard is it (and what are the best ways) to aggregate clickstream data into a useful data model? And, of course, what exactly can you use clickstream data for that you can’t get from traditional analytics? Bring your own experiences, questions, and thinking about the tools and techniques for profitably bringing raw clickstream data to traditional BI.
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In this Huddle, you’ll join Intuit’s Dylan Lewis to kill off the curse of the ad hoc question! Every organization struggles with the problem of how to control the flood of questions data can generate. Many measurement departments find that the vast majority of their time is absorbed building ad hoc reports and answering basic questions for users throughout the organization. All that interest in the data is great, but at the end of the year you may find yourself wondering whether you’ve really answered any of the important questions. Try to deflect those questions, and you may indeed find yourself in that uncomfortable position of “One Against the Mob.” In this Huddle, you’ll explore ways to handle and prioritize your ad hoc requests and keep your organization focused on the questions that matter. Should you democratize data access? Can you build better reports? Is having a plan enough? What are the politics behind prioritization? Help answer these questions and make sure you know how to keep the mob at bay!
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Your business has shifted to software-as-a-service. But your A/B testing is still stuck on acquisition landing pages. Discuss how to build the experimentation mindset into your online app, game, or subscription offering.
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The Finance function is increasingly looking to Analytics to weigh in on budgeting and forecasting models. This huddle is based the assumption that it is reasonable to look to historical customer web (and eventually mobile) activity as a predictor of future revenue. That being said, Finance teams are not typically used to dealing with the ambiguity so common with Analytics data. Training the financial spotlight on Analytics requires an understanding of caveats and specialized techniques for modeling unique visitors, engagement, conversion and monetization . This huddle will draw upon the collective experience of its participants to identify best practices in the following areas:

- Arriving at internal and external growth rate assumptions
- Ideal sources for unique visitor data and the limitations of those sources
- Monetization pitfalls
- Conservatism and knowing when is a model too precise
- And more!

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Cloud computing has the potential to revolutionize Web Analytics. Tired of the time and expense required to set up server infrastructure internally, analytics practitioners are turning to Amazon, Rackspace, Oracle and other cloud providers for help. What they are finding is nothing short of amazing! Burst processing capacity, easy set-up and low costs – it all seems too good to be true. In this huddle we will discuss the benefits of the cloud and share architecture ideas. We will identify how to get started with data exported from clickstream providers as well as more advanced integration and processing of multiple data sets. We will touch on ways to get Executives and Legal on board. Perhaps most importantly, we will highlight specific examples of value created by leveraging the cloud.

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eBay has been one of the leaders of the movement toward mammoth integration – the combination of nearly everything in a comprehensive enterprise data store and Bob Page has been a leader at eBay with that vision. Not every organization has the same vision or the same resources and even in a comprehensive data store fundamental integration questions can remain. What types of information can be joined and what makes the join useful? This conversation will focus explicitly on the integration opportunities within the world of Big Data. You’ll explore the ways to bring large systems together, share experiences on which integrations yield significant benefits and which only yield significant costs. Some of the most advanced Big Data practitioners in the world come to X Change, and this is their (and your) chance to share in the collective discussion.

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Still struggling with mobile measurement and analytics? You’re not alone. Mobile has proved a challenging measurement environment and a difficult channel to grasp and manage. In this conversation, you’ll join Bob Page of eBay in thinking through the levels of mobile measurement maturity – from a focus on the operational to an understanding of consumer usage to an analysis of the cross-channel implications of mobile. Few organizations aren’t doing mobile at some level, but most still view mobile measurement as more promise than reality. This is a chance to think about how best to handle each type of mobile measurement and how to get your organization to be effective at each level.

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The digital analytics industry is full of experts, gurus, consultants, and companies that focus on tagging and various technicalities related to web data collection and the configuration and deployment of technology and tools. All of this technical work is critical and necessary, but is not sufficient for doing what your teams were hired to do: analyze the data to generate profitable revenue - whether incremental or new. This session is for people who have grown tired to some degree of hearing about wt.this, utm_that, s_blahs, dimensions, measures, e_whatevers, and so on. In this huddle, we are going to have a collaborative, active, and participatory discussion about how you can rise above the technical layer and make sure your analysis, insights, and recommendations have the opportunity to be heard at the highest possible level so your company can make more money or be more efficient (and thus reduce cost).
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Digital analytics has been called a lot of different things over many years: easy, hard, complex, necessary, important, and inaccurate. Depending not so much on notions of "maturity," digital measurement may be one or all of those concepts simultaneously and likely many more adjectives specific to the nuances of your role, responsibility, team, supporting functions, and company politics and culture. To be successful at digital analytics it may or may not take a village, but it will take cross-functional teamwork by teams and people that you may or may not control with shared accountability who may or may not want to even help you and your team. In this session, we are going to have a deep discussion where you will contribute to identifying what has worked and what hasn't worked for delivering measurement, reporting, analysis, insights, and outcomes, which have enabled you to execute measurement across the road map, releases, and projects in a managed, sustained, and hopefully optimized way.
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For the past few years, we've had plenty of discussion about the impending convergence of BI tools and Web analytics. In 2011, it happened at a surprising number of places. Katie Reagan has been pushing Marriott's aggressive strategy of BI reporting and analysis with Digital data. If you're well along on road to BI and Digital nirvana, trapped somewhere in BI and Digital purgatory, or worried your efforts are heading somewhere worse, this is your chance to compare notes and discuss some of the biggest challenges around BI and digital data. Bring your solutions, ideas, or problems around staff training (digital to BI or vice-versa), tool selection, data models, reporting & scorecarding, and performance to this deep-dive into the rapidly maturing world of digital data with traditional BI tools.
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Measuring campaigns is the digital equivalent of blocking-and-tackling in the NFL. It's a fundamental skill without which you simply can't be successful. Yet it's surprising how many organizations struggle to create a robust framework for campaign measurement. Katie Reagan of Marriott has been deeply engaged in the creation of an end-to-end measurement system for digital campaigns. Chances are pretty good, you have similar efforts underway. In this conversation, you'll discuss the core elements of campaign measurement and governance: mechanisms for campaign tracking, governance around the creation and use of campaign codes and campaign meta-data, channel-specific issues, reconciliation, reporting, and even attribution. Just because we all do it doesn't mean we all do it well - bring your best practices and your game-face!
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Have you ever worked on a project that failed? More often than not, failure has more to do with a lack of upfront agreement about what defines success, that it does any one individuals performance. But getting a diverse group of stakeholders to agree on a common set of success metrics is difficult. It also happens to be the most critical (and most neglected) competency among analysts. What strategies do you use to move stakeholders towards common goals? How do you establish KPIs that provide a clear and common vision of what success looks like?
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Analysts are naturally drawn to improving things like revenue per order or leads per campaign, but what about customer satisfaction? This critical metric is proven to have the most potent impact on a firm's economic value over the long-term, but it also the KPI that the analytics community knows the least about (that is, if a count of blog posts on the topic is any indicator). What are the drivers of customer satisfaction on your site? What techniques do you use to improve it? How do you get the rest of your organization to care about it?
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Behavioral targeting is an important component of the site optimization toolkit. Onsite BT’s appeal is obvious: individual level targeting based on real time predictive analytics to deliver personalized, relevant, and profitable customer experiences. But behind the automation and analytical power BT also requires care and feeding: marketers must plan and produce content and promotional variations, and analysts must coordinate data, segments, and guide the “training” of new models. This session will delve into the underlying details of how BT works in the real world to identify how organizations can best implement a new BT program or maximize the impact of current programs. Key discussion items will include:

• Key skills and resources required for behavioral targeting
• Potential data streams that feed behavioral targeting such as behavior, source, environmental, and customer data
• The applications of behavioral targeting and the best locations to employ this technique
• The behavioral targeting lifecycle from planning, development, deployment, and ongoing maintenance
• Where behavioral targeting fits in with other site optimization techniques such as Multivariate Testing
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Mobile is exploding and is poised to become a major source of traffic and revenue. But it’s not all about mobile websites and search; as smart phones gain traction mobile applications have become an important component of the mobile ecosystem. To stay ahead of the curve and make the most of this emerging channel, measurement is critical, and tracking app store downloads isn’t enough. This session will explore the impact of mobile applications and how organizations are using analytics to build great customer experiences and a profitable mobile presence. This huddle will discuss the following topics and more:

• When it makes sense to build a mobile application
• Technology solutions for measuring mobile applications
• Which metrics and KPIs drive mobile conversions and great customer experiences
• How mobile application experiences differ from traditional and mobile websites
• Navigating the increasingly complex device ecosystem, spanning mobile and internet connected devices, tablets, and multiple mainstream operating systems
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Many marketers know "last click" is a poor approximation for assigning credit. So how should you decide how to spend that next marketing dollar? Putting this into practice is easier said than done. In this huddle you can learn from your peers about what works and what to avoid.
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What’s the biggest challenge to doing real analysis? The constant drumbeat of ad-hoc reporting. What’s the biggest reason for that drumbeat? The stream of new content and tools hitting sites. There are host of reasons why establishing a strong measurement cycle around new content and tools is critical. Failure to deploy measurement on new tools is disastrous. Relying on ad hoc reporting is painful. Establishing success criteria after the fact is dishonest. Reinventing a measurement framework for every new process is laborious and wasteful. What’s the solution? Join Alice Watson of The Men's Wearhouse in an exploration of the right way to create a virtuous measurement cycle around new content. From a strong measurement foundation, a stable IT team, a pre-existing framework for creating measurement design, a commitment to specific success metrics, to a standard post-implementation analysis, what are the techniques you use (or would like to use) to get the job done?
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One of the biggest barriers to effective personalization at many organization’s isn’t technical or analytic – it’s the very understandable desire to avoid the potential creepiness (and risk) of too much of the wrong sort of personalization. In this Huddle, you’ll join Alice Watson of The Men's Wearhouse in an exploration of the ways to make sure personalization is productive not transgressive; ways to help soften the edges of personalization both for the customer and the organizations. Whether you’re far down or just embarking on the journey to personalize your customer communications – whether via email, retargeting or Web testing, you’ll want to share your experiences, fears, best-practices, and scary stories to arrive at the best methods for keeping personalization productive not scary.
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