21 Top Metrics for Online Display Advertising

In this post I am listing the 21 metrics to measure the success of your display advertising.  Most of these are also applicable, with some variation, to other forms of advertising such as Paid Search, Social Media Ads, Print and email. I will cover these other channels and mediums in the future posts.

  1. Impressions – It is the number of times your ad is displayed. The number by itself does not hold much value but it is a metric used to calculate other metrics and KPIs. Keep in mind that an impression does not mean that someone actually saw the ad, it just that the ad was shown on a web page/app.
  2. Reach –This is the number of unique people (generally identified by cookies) that were reached by your ad. This number is always lower than the impressions because your ad is generally shown to same person (cookie) multiple times.
  3. Cost – The total cost of running the ad campaigns.  This is calculated differently by different tools and organizations. Some use actual media cost while other use a fully load number that includes the agency cost, creative cost etc. Whichever number you use, be consistent in your approach. If you are going to do comparisons with CPC models such as Paid Search then I suggest using the actual media cost. Most of the publicly available benchmarks are based on actual media cost and are expressed in CPM (explained later in this list).
  4. Engagement Rate or Interaction Rate– This applies to the Rich Media Ads, where a user can interact with the ad without leaving the Ad unit/widget.  Engagement Rate is the percentage of interactions per impression of the ad unit and is calculated as (Number of Interactions/Total Impressions)*100%.
  5. CPM – This is the cost for 1000 Impressions of the ad unit. Display advertising is generally sold on CPM basis. (For more information on CPM, see  Cost of Advertising: CPM, CPC and eCPM Demystified).
  6. Clicks – Number of clicks on an ad unit that lead to a person leaving the ad unit.  Keep in mind that a click does not mean that a person landed on the intended destination of the banner ad click. There are multiple factors that could lead to a click but not a visit to the destination (I won’t cover those here but am happy to discuss over email or a call).
  7. CTR (Click though rate) – It is the number of Clicks generated per impression of a banner ad. This number is expressed as a percentage. CTR = (click/impressions)*100%
  8. CPC – Cost per Clicks is the cost that you pay for each click.  Generally, display advertising is sold by CMP (see above), you can easily convert the cost in to Cost Per Click to compare it against other channels such as paid search. Cost per click is the effective amount you paid to get a click.  It is calculated by dividing the cost with number of clicks.  CPC = Cost/Clicks. Sometime this number is also referred as eCPC (effective Cost per Click).
  9. Visits – As stated above in the definition of clicks, not every click turns into a person landing on your destination (generally your website). Visits measures the clicks that did end up on your site.  (For more definition of visits, please see Page Views, Visitors, Visits and Hits Demystified)
  10. Visitors – Visitors metric goes one step ahead of the visits and calculates the number of people (as identified by cookies) who ended up on your site as a results of the clicks on the banner ads.
  11. Bounce Rate – Is the percentage of visits that left without taking any actions on your site. It is calculated as Number of Visits with one page view /Total number of visits resulting from the display ads. (Bounce Rate Demystified for further explanation).
  12. Engaged Visit Rate – Generally this is opposite of bounce rate (though you can have your own definitions of engagement).  It measure the quality of the visits arriving from your display advertising. You can calculate Engaged Visits as  (100 – Bounce Rate expressed as percentage).
  13. Cost/Engaged Visit – This is effective cost of each engaged visits. It is calculated as total Cost divided by number of engaged visits.
  14. Page Views/Visit – Page views the number of pages on your site viewed by each visit. With a lot interactions happening on one single page, this metrics is losing its value. However, for now, it is still a valuable metric for ad supported sites.
  15. Cost/Page View – As above, this is valuable metrics for ad supported site to figure out the cost of generating on extra page view.
  16. Conversions – Conversion is defined as the count of action that you want the visitors to take when they arrive from you display ads. Some examples of conversions are – purchase, signup for newsletter, download a whitepaper, sign up for an event, Lead from completions etc.
  17. Conversion Rate  – This is the percentage of visits that resulted in the desired conversion actions.  Conversion Rate = Total conversions/visits*100. If you have more than one conversion actions then you should do this calculation for each one of the action as well for all the actions combined.  In case of Leads, you can take it one step further and calculate not only the “Leads Generation Rate” (Online Conversion Rate) but also Lead Conversion Rate, which is, Leads that convert to a customer divided by total leads generated.
  18. Cost per Conversion – This is the Total Cost divided by the number of conversions achieved from visits coming via display ads.
  19. Revenue – This is total revenue that is directly attributed to the visits coming from display advertising. It is pretty straightforward to calculate in eCommerce but gets a little tricky when you have offline conversions.
  20. Revenue per Visit   – Shows the direct revenue achieved per visit originating from the display advertising. It is calculated as Revenue Generated from Display Ads divided by the total Visits.
  21. Revenue per Page – This is useful for ad supported business models. This is sometimes expressed as RPM (Revenue per thousand impressions of ads) = (Total Ad Revenue/Number of page views) * 1000

Note: In addition to Clicks, you can also looks at View Through and calculate your other related metrics by view through.  View Through is sum of all the cookies that visited a page that showed your ad on it, and then landed on your site. The assumption, in this calculation, is that you landed on the brands site because of that ad exposure.

 Where can you get these metrics from?

  • Impressions, Reach, Cost, Engagement Rate, Clicks, CTR and CPC data is available from your agency or ad server tool.
  • Visits, Visitors, Page Views, Bounce Rate, Engaged Visit Rate, Conversion, and Conversion Rate are available in your Web Analytics tool.
  • Revenue is available in either your Web Analytics tool or other offline sales database.
  • Cost/Conversion, Cost/Engaged Visits, Cost/Page view and Revenue/page are calculated using data from multiple tools.

Questions/Comments?

Originally Posted on http://anilbatra.com/analytics/2014/05/21-metrics-to-measure-online-display-advertising

Understanding Data – Context (Excerpt from Data Points: Visualization That Means Something)

Look up at the night sky, and the stars look like dots on a flat surface. The lack of visual depth makes the translation from sky to paper fairly straightforward, which makes it easier to imagine constellations. Just connect the dots. However, although you perceive stars to be the same distance away from you, they are actually varying light years away.

If you could fly out beyond the stars, what would the constellations look like? This is what Santiago Ortiz wondered as he visualized stars from a different perspective, as shown in Figure 1-25.

The initial view places the stars in a global layout, the way you see them. You look at Earth beyond the stars, but as if they were an equal distance away from the planet.

Zoom in, and you can see constellations how you would from the ground, bundled in a sleeping bag in the mountains, staring up at a clear sky.

The perceived view is fun to see, but flip the switch to show actual distance, and it gets interesting. Stars transition, and the easy-to-distinguish constellations are practically unrecognizable. The data looks different from this new angle.

This is what context can do. It can completely change your perspective on a dataset, and it can help you decide what the numbers represent and how to interpret them. After you do know what the data is about, your understanding helps you find the fascinating bits, which leads to worthwhile visualization.

Figure 1-25

Without context, data is useless, and any visualization you create with it will also be useless. Using data without knowing anything about it, other than the values themselves, is like hearing an abridged quote secondhand and then citing it as a main discussion point in an essay. It might be okay, but you risk finding out later that the speaker meant the opposite of what you thought.

You have to know the who, what, when, where, why, and how — the metadata, or the data about the data — before you can know what the numbers are actually about.

Who: A quote in a major newspaper carries more weight than one from a celebrity gossip site that has a reputation for stretching the truth. Similarly, data from a reputable source typically implies better accuracy than a random online poll.

For example, Gallup, which has measured public opinion since the 1930s, is more reliable than say, someone (for example, me) experimenting with a small, one-off Twitter sample late at night during a short period of time. Whereas the former works to create samples representative of a region, there are unknowns with the latter.

Speaking of which, in addition to who collected the data, who the data is about is also important. Going back to the gumballs, it’s often not financially feasible to collect data about everyone or everything in a population. Most people don’t have time to count and categorize a thousand gumballs, much less a million, so they sample. The key is to sample evenly across the population so that it is representative of the whole. Did the data collectors do that?

How: People often skip methodology because it tends to be complex and for a technical audience, but it’s worth getting to know the gist of how the data of interest was collected.

If you’re the one who collected the data, then you’re good to go, but when you grab a dataset online, provided by someone you’ve never met, how will you know if it’s any good? Do you trust it right away, or do you investigate? You don’t have to know the exact statistical model behind every dataset, but look out for small samples, high margins of error, and unfit assumptions about the subjects, such as indices or rankings that incorporate spotty or unrelated information.

Sometimes people generate indices to measure the quality of life in countries, and a metric like literacy is used as a factor. However, a country might not have up-to-date information on literacy, so the data gatherer simply uses an estimate from a decade earlier. That’s going to cause problems because then the index works only under the assumption that the literacy rate one decade earlier is comparable to the present, which might not be (and probably isn’t) the case.

What: Ultimately, you want to know what your data is about, but before you can do that, you should know what surrounds the numbers. Talk to subject experts, read papers, and study accompanying documentation.

In introduction statistics courses, you typically learn about analysis methods, such as hypothesis testing, regression, and modeling, in a vacuum, because the goal is to learn the math and concepts. But when you get to real-world data, the goal shifts to information gathering. You shift from, “What is in the numbers?” to “What does the data represent in the world; does it make sense; and how does this relate to other data?”

A major mistake is to treat every dataset the same and use the same canned methods and tools. Don’t do that.

When: Most data is linked to time in some way in that it might be a time series, or it’s a snapshot from a specific period. In both cases, you have to know when the data was collected. An estimate made decades ago does not equate to one in the present. This seems obvious, but it’s a common mistake to take old data and pass it off as new because it’s what’s available. Things change, people change, and places change, and so naturally, data changes.

Where: Things can change across cities, states, and countries just as they do over time. For example, it’s best to avoid global generalizations when the data comes from only a few countries. The same logic applies to digital locations. Data from websites, such as Twitter or Facebook, encapsulates the behavior of its users and doesn’t necessarily translate to the physical world.

Although the gap between digital and physical continues to shrink, the space between is still evident. For example, an animated map that represented the “history of the world” based on geotagged Wikipedia, showed popping dots for each entry, in a geographic space. The end of the video is shown in Figure 1-26.

The result is impressive, and there is a correlation to the real-life timeline for sure, but it’s clear that because Wikipedia content is more prominent in English-speaking countries the map shows more in those areas than anywhere else.

Why: Finally, you must know the reason data was collected, mostly as a sanity check for bias. Sometimes data is collected, or even fabricated, to serve an agenda, and you should be wary of these cases. Government and elections might be the first thing that come to mind, but so-called information graphics around the web, filled with keywords and published by sites trying to grab Google juice, have also grown up to be a common culprit. (I fell for these a couple of times in my early days of blogging for FlowingData, but I learned my lesson.)

Learn all you can about your data before anything else, and your analysis and visualization will be better for it. You can then pass what you know on to readers.

Figure 1-26

However, just because you have data doesn’t mean you should make a graphic and share it with the world. Context can help you add a dimension — a layer of information — to your data graphics, but sometimes it means it’s better to hold back because it’s the right thing to do.

In 2010, Gawker Media, which runs large blogs like Lifehacker and Gizmodo, was hacked, and 1.3 million usernames and passwords were leaked. They were downloadable via BitTorrent. The passwords were encrypted, but the hackers cracked about 188,000 of them, which exposed more than 91,000 unique passwords. What would you do with that kind of data?

The mean thing to do would be to highlight usernames with common (read that poor) passwords, or you could go so far as to create an application that guessed passwords, given a username.

A different route might be to highlight just the common passwords, as shown in Figure 1-27. This offers some insight into the data without making it too easy to log in with someone else’s account. It might also serve as a warning to others to change their passwords to something less obvious. You know, something with at least two symbols, a digit, and a mix of lowercase and uppercase letters. Password rules are ridiculous these days. But I digress.

Figure 1-27

With data like the Gawker set, a deep analysis might be interesting, but it could also do more harm than good. In this case, data privacy is more important, so it’s better to limit what you show and look at.

Whether you should use data is not always clear-cut though. Sometimes, the split between what’s right and wrong can be gray, so it’s up to you to make the call. For example, on October 22, 2010, Wikileaks, an online organization that releases private documents and media from anonymous sources, released 391,832 United States Army field reports, now known as the Iraq War Logs. The reports recorded 66,081 civilian deaths out of 109,000 recorded deaths, between 2004 and 2009.

The leak exposed incidents of abuse and erroneous reporting, such as civilian deaths classified as “enemy killed in action.” On the other hand, it can seem unjustified to publish findings about classified data obtained through less than savory means.

Maybe there should be a golden rule for data: Treat others’ data the way you would want your data treated.

In the end, it comes back to what data represents. Data is an abstraction of real life, and real life can be complicated, but if you gather enough context, you can at least put forth a solid effort to make sense of it.

Excerpted with permission from the publisher, Wiley, from Data Points: Visualization That Means Something by Nathan Yau. Copyright © 2013

Author Bio
Nathan Yau
, author of Data Points: Visualization That Means Something, has a PhD in statistics and is a statistical consultant who helps clients make use of their data through visualization. He created the popular site FlowingData.com, and is the author of Visualize This: The FlowingData Guide to Design, Visualization, and Statistics, also published by Wiley.

For more information please visit http://flowingdata.com, and follow the author on Facebook and Twitter

 

Buy From Amazon: Data Points: Visualization That Means Something

Five Reasons Siegel's Book "Predictive Analytics" Matters to Experts

 
My new book — Predictive  Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die  — is a revealing, accessible primer positioned to appeal well outside our industry.
But, if you’re already an expert, here are five reasons to read it nonetheless:

  1. New detailed case studies
  2. Advanced topics (ensembles, uplift, etc.)
  3. An in-depth, startling treatise on privacy
  4. A compendium of 147 mini-case studies
  5. A means to share your field with your family, friends, or  supervisor

I took on a rewarding challenge: sharing with layreaders at  large a complete picture of predictive analytics, from the  way in which it serves actionable value to organizations, down to      the inner workings of predictive modeling. It’s high time the predictive power of data — and how to analytically tap it — be demystified to reveal its intuitive yet awe–inspiring nature. As you and I know, learning from data to predict human behavior is not arcane. Rather, it is a broadly applicable no–brainer. If we  spread the word with an appropriately friendly overview, we’ll readily earn broad buy in, much to the benefit of our blossoming  industry.

More than a string of anecdotes, this book delivers complete   conceptual coverage of the field and places predictive analytics into a worldview perspective, defining its societal and even      cultural context. Although packaged with catchy chapter titles and brand name stories, the conceptual outline is fundamental: 1) deployment, 2) civil liberties, 3) data, 4) core modeling, 5) ensembles, 6) IBM’s Watson, and 7) uplift modeling (aka net lift or persuasion modeling).

Although this pop science, mathless introduction is readable by everyone, you as an expert will also benefit from reading it. While some endorsers proclaim it is “The Freakonomics of big data”    that “reads like a thriller!”, others speak to the    practitioner:

“The definitive book of this industry has arrived. Dr.  Siegel has achieved what few have even attempted: an  accessible, captivating tome on predictive analytics that is a  ‘must read’ for all interested in its potential — and peril.” —Mark Berry, VP, People Insights, ConAgra Foods

“Written in a lively language, full of great quotes,  real-world examples, and case studies, it is a pleasure to  read. The more technical audience will enjoy chapters on The          Ensemble Effect and uplift modeling — both very hot trends. I highly recommend this book!” —Gregory Piatetsky-Shapiro, Editor, KDnuggets; Founder, KDD          Conferences

Here’s a bit more on the five reasons this book matters to you:

1. New case studies. Find detailed stories you have  never before heard from Hewlett-Packard, Chase, and the Obama Campaign. And did you know that John Elder once invested all his  own personal money into a blackbox stock market system of his own design? That’s the opening story of Chapter 1.

2. Advanced topics. Dive into ensemble models, crowdsourcing predictive analytics, uplift modeling (aka net lift or persuasion modeling), text analytics, and social media-based financial indicators. Plus, enjoy a fun yet fairly deep chapter on IBM’s Jeopardy!-playing Watson computer.

3. Privacy and other civil liberty concerns. This ethical realm is so intractable and inconstant, no one is a true expert, in a sense. My treatise on it, a chapter entitled “With Power Comes Responsibility,” addresses the questions: In what ways does predictive analytics fuel the contentious flames surrounding data privacy, raising its already-high stakes? What civil liberty concerns arise beyond privacy per se? What about predictive crime models that help decide who stays in prison?

4. A cross-industry compendium of 147 cases. This comprehensive collection of mini-case studies serves to illustrate just how wide the field’s reach extends. This color insert includes a table for each of the verticals: Personal Life, Marketing, Finance, Healthcare, Crime Fighting, Reliability Modeling, Government and Nonprofit, Human Language  and Thought, and Human Resources. One PhD-level technical book reviewer complimented me by saying, “The tables alone are worth the price of admission.”

5. Share your field of expertise. Would you like your colleagues and manager to better understand the value and potential of your work? Would you enjoy seeing your loved ones        not only learn what the heck it is you do and why it’s so  important, but enjoy it and get excited? Give this book to your  family, friends, and boss.

Author Bio        

Eric Siegel, Ph.D., founder of Predictive Analytics World  and Text Analytics World, and Executive Editor of the Predictive  Analytics Times, makes the how and why of predictive analytics      understandable and captivating. In addition to being the author of   Predictive Analytics: The Power to Predict Who Will Click, Buy,  Lie, or Die, Eric is a former Columbia University professor      who used to sing to his students, and a renowned speaker, educator  and leader in the field.

For more information please visit http://www.thepredictionbook.com

Data Analyst at Baystate Health, Springfield, Massachusetts

Data Analyst Departments of Strategic Planning and Digital Marketing Maximize your data analytical skills by supporting two departments utilizing various databases. We will provide challenging work and the ability to foster and sharpen your talents!As the Data Analyst, you will be part of a dynamic team responsible for strategic planning/business development and marketing analytics. Your work will support the business needs of the Strategic Planning & Business Development department (70%) and Department of Marketing & Digital Strategy (30%).

You will responsible for data collection, analysis and interpretation; best practice research; maintenance and quality control of multiple databases; and market/competitive intelligence for a wide range of business needs, constantly providing you challenging and rewarding work!

What do you need?
Bachelors Degree required.
Minimum of two years of experience analyzing, interpreting, reporting and communicating data.
Advanced skills in Excel and Access (0 preferred); strong understanding of HTML and web protocols; knowledge of Google Analytics or SEO is preferred.
Masters degree and previous experience analyzing healthcare market and service line data (DRG, ICD-9, CPT codes) is preferred.

In addition, you must have the following:
High energy, team focused and flexibility working between two departments
Strong sense of curiosity with demonstrated ability to proactively investigate data inconsistencies and anomalies,
Demonstrated capacity as a resourceful individual with proven ability to seamlessly balance multiple priorities,
Strong analytical skills (both qualitative and quantitative), ability to identify key points and trends, and develop succinct summaries of findings. Experience in statistical modeling/analysis highly is desirable.

What will you receive?

Opportunity to build a core set of skills and tools while contributing to the strategy of a world class healthcare system as well as growing your career;
Ability to work with a highly effective team that has a reputation for being innovative and influential;
Receive a competitive salary with great benefits including employer-paid retirement plan and leading work-life programs.

To apply, please visit www.baystatehealthjobs.com and search for position number 62554. For more information, please contact Jason Pacheco, Workforce Planning Consultant at Baystate Health at 413-794-2384.

Baystate Health is an equal opportunity employer committed to an inclusive and diverse workforce. EOE/AA

Apply at http://www.web-analytics-jobs.com/a/jbb/job-details/802691

Senior Web Analyst Sirius Xm Radio at District of Columbia

Lead Web Analytics for Siriusxm.com, leveraging Omniture and Google Analytics to provide insight into user behavior, business goals, and key performance indicators. Responsibilities include defining business requirements, implementation, data management, and analytics. Leverage data and analysis to optimize site performance for best user experience and conversion, partnering with finance and business units to develop and execute A/B and multivariate tests to maximize value of siriusxm.com.

Duties and Responsibilities:

Responsible for managing, organizing, and presenting Web analytics data; Establish key metrics and develop reporting and analysis using Omniture Site Catalyst, Test & Target and other tools.
Produce daily, weekly, monthly, and quarterly reports relating to outcomes based on the data analysis for various audiences, including management, marketing, product and editorial teams.
Create dashboards for senior management and various business units, synthesizing data from various sources.
Design, execute and evaluate A/B and multivariate tests that improve site experience and optimize contribution of siriusxm.com inventory. Partner with Finance to provide insights on value and opportunity cost of various site promotions.
Work with stakeholders (marketing, product, programming) to develop and execute landing page optimization testing.Work with marketing,product, and programming stakeholders to understand, define and prioritize tracking and reporting requirements. Work with IT and BI to identify gaps in data capture strategy.
Provide individual and group training sessions within the organization and ongoing support.
Create, manage and maintain data repositories and documentation and for exec-level analytics, training, internal processes and implementation details.
Provide insights, trends, and analysis of key performance indicators related to the category using competitive tools such as Hitwise.
Provide quick-turn-around responses to ad-hoc data queries.
Performs other duties as assigned.

Minimum Qualifications:

Bachelors degree or equivalent experience, MBA preferred
4 to 6 years of experience with Web Analytics Tools (Omniture, ClickTracks, WebTrends, HBX, CoreMetrics etc.)

Requirements and General Skills:

Expert in use of Omniture Site Catalyst and Test & Target; Functional proficiency with Google Analytics reporting required.
Proficiency in Excel is required, including charting and large data sets.
Experience driving the data strategy across multiple business areas and touchpoints including websites, surveys, testing, CRM systems, marketing databases, market research etc.
Ability to create useful dashboards based on the Web analysis.
Ability to lead the drive for data and to suggest, create and execute multivariate or a/b/c tests that drive fundamental improvements to the site experience.
A passion for numbers and the ability to use them to tell a story regarding site performance, consumer trends, and competitive analysis. Proactive in analyzing data and customer behavior. Willingness to take initiative and to follow through on projects.
Demonstrate ability to partner with technology teams to identify gaps in the data capture strategy and collaboratively implement enhancements. Should be able to partner with other business units and outside the company to ensure that best practices in metrics and decision making are being exposed to management and website decision makers.
Experience creating and managing Multivariate and A/B testing documents (from hypothesis creation to influencing creative to identifying success metrics) and post test analysis.
Manage Business requirements from multiple sources including product managers, development teams, and functional groups.
Create documentation relating to existing processes and suggestion / presentations for improving those processes.
Detail-oriented and organized with excellent verbal and written communication skills.
Ability to work independently as well as within a team structure.
Ability to work independently and remain flexible and motivated to work in a fast-paced environment.
Good public speaking and presentation skills; Ability to project a professional image over the phone and in person.Interpersonal skills and ability to interact and work with staff at all levels.
Commitment to internal client and customer service principles.
Strong organizational skills and attention to details.
Excellent time management skills, with the ability to prioritize and multi-task, and work under shifting deadlines in a fast paced environment.
Must have legal right to work in the U.S.

Technical Skills:

Basic knowledge of general internet technologies such as HTML, JavaScript and tracking/pixel structures is required.
Thorough knowledge MS Excel, and Access, ability to manage large data sets.
Strong analytic skills.
Experience with online ad serving, tracking, and reporting toolsExpertise in the SEM (Search Engine Marketing) / PPC (Pay Per Click) and SEO (Search Engine Optimization) strategies and a minimum one year experience measure success of SEM/PPC and SEO campaigns / efforts.

 

Apply at http://www.web-analytics-jobs.com/a/jbb/job-details/783614

Senior Web Analyst at Sirius XM Radio New York

Lead Web Analytics for Siriusxm.com, leveraging Omniture and Google Analytics to provide insight into user behavior, business goals, and key performance indicators. Responsibilities include defining business requirements, implementation, data management, and analytics. Leverage data and analysis to optimize site performance for best user experience and conversion, partnering with finance and business units to develop and execute A/B and multivariate tests to maximize value of siriusxm.com.

Duties and Responsibilities:

Responsible for managing, organizing, and presenting Web analytics data; Establish key metrics and develop reporting and analysis using Omniture Site Catalyst, Test & Target and other tools.
Produce daily, weekly, monthly, and quarterly reports relating to outcomes based on the data analysis for various audiences, including management, marketing, product and editorial teams.
Create dashboards for senior management and various business units, synthesizing data from various sources.
Design, execute and evaluate A/B and multivariate tests that improve site experience and optimize contribution of siriusxm.com inventory. Partner with Finance to provide insights on value and opportunity cost of various site promotions.
Work with stakeholders (marketing, product, programming) to develop and execute landing page optimization testing.Work with marketing,product, and programming stakeholders to understand, define and prioritize tracking and reporting requirements. Work with IT and BI to identify gaps in data capture strategy.
Provide individual and group training sessions within the organization and ongoing support.
Create, manage and maintain data repositories and documentation and for exec-level analytics, training, internal processes and implementation details.
Provide insights, trends, and analysis of key performance indicators related to the category using competitive tools such as Hitwise.
Provide quick-turn-around responses to ad-hoc data queries.
Performs other duties as assigned.

Minimum Qualifications:

Bachelors degree or equivalent experience, MBA preferred
4 to 6 years of experience with Web Analytics Tools (Omniture, ClickTracks, WebTrends, HBX, CoreMetrics etc.)

Requirements and General Skills:

Expert in use of Omniture Site Catalyst and Test & Target; Functional proficiency with Google Analytics reporting required.
Proficiency in Excel is required, including charting and large data sets.
Experience driving the data strategy across multiple business areas and touchpoints including websites, surveys, testing, CRM systems, marketing databases, market research etc.
Ability to create useful dashboards based on the Web analysis.
Ability to lead the drive for data and to suggest, create and execute multivariate or a/b/c tests that drive fundamental improvements to the site experience.
A passion for numbers and the ability to use them to tell a story regarding site performance, consumer trends, and competitive analysis. Proactive in analyzing data and customer behavior. Willingness to take initiative and to follow through on projects.
Demonstrate ability to partner with technology teams to identify gaps in the data capture strategy and collaboratively implement enhancements. Should be able to partner with other business units and outside the company to ensure that best practices in metrics and decision making are being exposed to management and website decision makers.
Experience creating and managing Multivariate and A/B testing documents (from hypothesis creation to influencing creative to identifying success metrics) and post test analysis.
Manage Business requirements from multiple sources including product managers, development teams, and functional groups.
Create documentation relating to existing processes and suggestion / presentations for improving those processes.
Detail-oriented and organized with excellent verbal and written communication skills.
Ability to work independently as well as within a team structure.
Ability to work independently and remain flexible and motivated to work in a fast-paced environment.
Good public speaking and presentation skills; Ability to project a professional image over the phone and in person.Interpersonal skills and ability to interact and work with staff at all levels.
Commitment to internal client and customer service principles.
Strong organizational skills and attention to details.
Excellent time management skills, with the ability to prioritize and multi-task, and work under shifting deadlines in a fast paced environment.
Must have legal right to work in the U.S.

Technical Skills:

Basic knowledge of general internet technologies such as HTML, JavaScript and tracking/pixel structures is required.
Thorough knowledge MS Excel, and Access, ability to manage large data sets.
Strong analytic skills.
Experience with online ad serving, tracking, and reporting tools Expertise in the SEM (Search Engine Marketing) / PPC (Pay Per Click) and SEO (Search Engine Optimization) strategies and a minimum one year experience measure success of SEM/PPC and SEO campaigns / efforts.

 

Apply at http://www.web-analytics-jobs.com/a/jbb/job-details/783616

Web Conversion Specialist Destination at Maternity Corporation, Philadelphia, Pennsylvania

Destination Maternity Corporation is the world’s largest designer and retailer of maternity apparel. In the United States and Canada, as of September 30, 2012, Destination Maternity operates 2,008 retail locations, including 625 stores, predominantly under the tradenames Motherhood Maternity, A Pea in the Pod, and Destination Maternity, and 1,383 leased department locations, and sells on the web through its DestinationMaternity.com and brand-specific websites. Destination Maternity also distributes its Oh Baby by Motherhood collection through a licensed arrangement at over 1,100 Kohl’s stores throughout the United States and on Kohls.com. In addition, Destination Maternity is expanding internationally and has exclusive store franchise and product supply relationships in India, the Middle East and South Korea. As of September 30, 2012, Destination Maternity has 119 international franchised locations, including 103 shop-in-shop locations and 16 Destination Maternity branded stores.

The Web Conversion Specialist, reporting to the Internet Metrics Manager, is primarily responsible for optimizing website conversion. The Web Conversion Specialist is responsible for the day to day management of website testing and conversion efforts to various traffic channels, while creating the best user experience possible.

Job Responsibilities:
– Manage Monetate Testing
– Site Search and Landing Optimization
– Maintain reporting of key metrics

Requirements:
– Minimum of a Bachelors degree in math, science or related field, along with 2-4 years of relevant experience
– Power user of Omniture, Google Analytics, or Core Metrics Applications (Familiar with the technology used to build, tag and track web sites)
– Proficient in a standard database queries and manipulation, using statistical tools like SASS
– Power Excel/ Access user capabilities
– Understanding of web marketing and use of cookies for tracking and behavioral targeting.
– Must be user and customer experience driven

 

Apply: http://www.web-analytics-jobs.com/a/jbb/job-details/776116

200+ Analytics Blog Posts that you might have missed

Post Title Blogger
Mark Your Calendars For These Upcoming Analytics Events Google Analytics
A Deep Dive Into Facebook Advertising Hiten Shah
What Data Brokers Know vs. What They Tell You All Analytics
Illinois Lawmakers Tell Employers Seeking Social Media Account Info to Take a Hike All Analytics
Garbage in, Garbage out: What It Means for Big-Data Quality All Analytics
Our First Week at DABC:All Highs, No Lows! Nabler
Choosing The Right Metrics [cartoon] Daniel Waisberg
How Your Customers Hold The Key That Unlocks Your Amazing Product Hiten Shah
The Marketing/IT Tug-of-War Bryan Eisenberg
How to Align the Stars in Your Big-Data Universe All Analytics
Pinning Social Media Hopes on Pinterest Analytics All Analytics
A Strategic Mistake With Big Data IIA
The Evolution of the 2-3 Year Analyst Corry Prohens
CSS Inline Styles: Enhance the Aesthetic Appeal of Your Link Bait Robbin Steif
3 Useful Optimization Tools Daniel Waisberg
An In-Depth Look at the Science of Twitter Timing Hiten Shah
Storing user agent strings in Google Analytics Matt Clarke
Privilege & Responsibility: Reflections on a Career All Analytics
Behind the Big-Data Hype All Analytics
Transform Your Business Through a Reliable Deployment Architecture All Analytics
Quantifiable Design Data Drives Ford Quality Efforts All Analytics
Employees are People Too IIA
Forecasting Account Performance and Why to Exclude IP Addresses – LunaTV Ep. 13 – PPC Robbin Steif
Webinar this Thursday: Multi-Channel Funnels Google Analytics
How to Increase Your Facebook Fans and Twitter Followers Hiten Shah
How To Use Index Status in Google Webmaster Tools to Diagnose SEO Problems Glenn Gabe
Have to Laugh – Klout vs. Social IQ Marshall Sponder
Testing Firm Scores Big With Analytics All Analytics
IT, Analytics & the Speed of Knowledge All Analytics
Relationship Analytics: An Emerging Branch of Big-Data All Analytics
TOOL: Facebook Post Optimizer Robbin Steif
Simple Optimization Ideas – Real Impact Daniel Waisberg
The Ultimate Guide to Startup Marketing Hiten Shah
Xcel’s SmartGridCity: More Analytics, Less Acrimony – Please! All Analytics
Using the Google Analytics Tax field for Transaction Type Peter ONeill
Google Analytics Goal Flow: How Visitors Really Move Through Your Funnel Robbin Steif
The Web Analyst’s Toolkit Gary Angel
Social Media Monitoring Tools and Services Report – July 2012 – from @Ideya Marshall Sponder
Solving The Wrong Problem [cartoon] Daniel Waisberg
Rethinking Retargeting All Analytics
E-Chat Thursday: Tom Davenport on How Big-Data Is Different All Analytics
How to Make the Most of Your Forecast All Analytics
The Analytics CoE: Don’t Lose Sight of Its Importance All Analytics
The Analytics CoE: Don’t Get Smashed on the Rocks All Analytics
Settling the Big-Data Whirlwind All Analytics
Understanding the Hows & Whys of Analytical Pursuits All Analytics
Down the Rocky Road to Do Not Track Agreement All Analytics
Shh! Data Scientists Are Really Plumbers! All Analytics
My Customer Experience Experience All Analytics
Tweets per Day Analysis Gunjan
Potencializando o Track Social do Google Analytics com ações do Facebook Leonardo Naressi
IIA’s Analytics Executive Symposium Highlights – Emergence of CAO Summit IIA
IIA August 2012 Newsletter IIA
A Prerequisite for On-time Analytics Projects IIA
Review: ‘What a makes a great web analyst?’ Dan Croxen-John
Better Adwords Remarketing through Google Analytics Robbin Steif
10 Quick Adwords Optimizations Tips for All PPC-ers Robbin Steif
When Should I Post To My Social Networks? – LunaTV Ep. 12 – Social Media Robbin Steif
Introducing the Multi-Channel Funnels Reporting API Google Analytics
Data Information & Context Daniel Waisberg
Measure Campaign Profits – NOT Return On Ad Spend Daniel Waisberg
Smarter Analytics – Smarter Commerce Daniel Waisberg
New features: Annotations and Benchmarks Localytics
50 Ways To Seduce Your Web Visitors With Persuasive Landing Pages Hiten Shah
10 Helpful Twitter Lists for Social Media Marketers Hiten Shah
What Are The 3 Most Important Things Businesses Need To Know About Social Media? Hiten Shah
Turn Copy Into Customers – 7 Lessons From The Legendary Joseph Sugarman Hiten Shah
Webinar #7 – How to Find the BIG Wins that Your A/B Tests Are Missing by KISSmetrics and Optimizely Hiten Shah
Comparing Presidential Candidates Facebook and Twitter Presences – Web Journal – July 27th, August 1st 2012 Marshall Sponder
Big Data Does Not Mean Big Amounts of People Bryan Eisenberg
Web analytics, business intelligence and big data Stephane Hamel
Google Analytics Training in Montreal – Sept 19-21, 2012 Stephane Hamel
X Change – Content is King Gary Angel
NBC London 2012 FAIL! David Iwanow
Remarketing com o Google Analytics – o que já era bom ficou ainda melhor Leonardo Naressi
IQ Blast – Vol. 6 Issue 11 Corry Prohens
Looking at SocialBakers Analytics Pro and Really Liking it – Web Journal – Friday, July 27th, 2012 Marshall Sponder
Slideshow: Catch the Olympic Spirit! All Analytics
Analytics Is No Gamble for Foxwoods Resort Casino All Analytics
Analytics, Big-Data & the I/O Path All Analytics
Bits & Bytes of Random Data All Analytics
Yogi Frost and Analytics. Take the Fork in the Road! IIA
Quick Look at Analytics Job Trends Corry Prohens
Rethinking Blog Metrics Justin Cutroni
Analytics Advocate Justin Cutroni Answers Your Burning Questions (Part 2) Google Analytics
A simpler way to re-connect with your website visitors Google Analytics
This Inexpensive Marketing Plan Can Lead to More Traffic, More Leads and Higher Customer Retention Hiten Shah
Twitter Branding Decisions Reviewed David Iwanow
How to Catch Up to and Compete With Amazon.com [Video] Bryan Eisenberg
Dismay or Delight? Customer Analytics in Online Retailing for Hospitality & Travel All Analytics
Listen Up & Forget Your Fans All Analytics
Analytics That Work for Your Business (Not the Other Way Around) All Analytics
Aurora: A Call for Analytics All Analytics
Fear & Reassurances About Big-Data All Analytics
Twitter Words Association Analysis Gunjan
As possibilidades de atuação dentro do Pinterest Leonardo Naressi
Let your customers tell you how to make your site better Tim Leighton-Boyce
Customize Your Ad Placement with Facebook’s Power Editor Robbin Steif
Critical Thinking In Web Analytics Daniel Waisberg
Smartphones New Weapon in Battle for Swing States Localytics
How To Catapult Your Email Campaign Optimization To The Next Level Hiten Shah
Turning Regulatory Challenges Into Opportunities All Analytics
Tracking Adjusted Bounce Rate In Google Analytics Google Analytics
Bing Price Predictor: An Illustration of Reactive Predictive Modeling All Analytics
Analytics & Big-Data: Press ‘Pause’ on the Stairmaster All Analytics
Upstart Movenbank Moves Forward With Big-Data All Analytics
Understanding And Using Page Value Google Analytics
An In-Depth Look at The Science of Facebook Timing Hiten Shah
Radian6 Big Data Marshall Sponder
Disruptive Customer Experiences Bryan Eisenberg
Social123: the conclusion Stephane Hamel
The WAO/FACTOR Newsletter LinkedIn Group Jacques Warren
The Curious Link Between Big-Data & Cannibalism All Analytics
Keep Calm & Use Analytics in Your College Search All Analytics
Social Media Listening & Learning: E-Chat at 2:00 PM ET Today All Analytics
Week 15 of the IQ Workforce #Measure Fantasy Baseball League Corry Prohens
Facebook Ad Units Round-up – A Complete Guide Robbin Steif
Making Google Analytics Content Experiments Even Better Google Analytics
How to Get Google to Index Your New Website & Blog Quickly Hiten Shah
Web Journal and the Problems of Curating – July 13th – 22nd 2012 Marshall Sponder
Academics (& Then Some) by the Algorithms All Analytics
Social123: When your social life becomes the target of creepy tactics Stephane Hamel
In the Eye of the Hurricane Models All Analytics
We’re Too Small to Embrace Big-Data, Critics Claim All Analytics
To find frequency of the words using RapidMiner Gunjan
What to Test When Testing PPC Ad Copy Robbin Steif
News Through Data by Jer Thorp Daniel Waisberg
Web Analytics Consulting: A Simple Framework For Smarter Decisions Avinash Kaushik
What Matters Most in Enterprise Analytics – X Change as a Mirror on our Community Gary Angel
Social Sharing Report for Google Analytics Justin Cutroni
Webinar #6 – How to Get Better Insights in Less Time With Google Analytics Hiten Shah
Congress by the Not-So-Impressive Numbers All Analytics
The Myth of De-Identification All Analytics
Don’t Let Fear Get in Way of De-Identified Data’s Use All Analytics
Aprenda a anunciar através de Product Listing Ads e ganhe destaque no Google Leonardo Naressi
8 Habits Of Conversion-Focused Copywriters Hiten Shah
A Healthy Regimen: MPP, MapReduce & In-Database Analytics All Analytics
Near Real-Time Analytics Promote Better Health All Analytics
Dirt Track Date – Ecosystems & the Networked Economy All Analytics
3 Reasons Big-Data Has Relevance All Analytics
Keep Your Hands Off My Data All Analytics
The Difference between Data Scientists and Rocket Scientists IIA
Analytics Questions & Answers: Volume 2 Justin Cutroni
Why Do I See My Own Domain in the Referrers List of Google Analytics? Robbin Steif
What to Test When Testing PPC Ad Copy Robbin Steif
Let Us Know How To Make Social More Useful For You Google Analytics
Analyzing On-Site Search Logs: From Mess to Meaning Daniel Waisberg
What Startups Can Learn From Quora Hiten Shah
Getting started with data mining in R using Rattle Matt Clarke
Analytics in a ‘City That Works’ All Analytics
1 Big Love Fest for Big-Data Here All Analytics
Analyze Thyself All Analytics
Protecting Data From the BYOD Deluge All Analytics
Five Observations About Recruiting Big Data Professionals Corry Prohens
SEO Resources for Beginners and Advanced Users – LunaTV Ep. 11 – Search Engine Optimization Robbin Steif
Moving Google Analytics Forward – Retiring The Old Version Google Analytics
20 Bonehead Marketing Mistakes You Must Avoid Hiten Shah
How To Use Social Reports in Google Analytics To Analyze Specific Blog Posts or Content [Tutorial] Glenn Gabe
Big Data, Advanced Digital Segmentation, and Powerful Data Exploration Gary Angel
Does This Look Good on Me? All Analytics
Patient-Centered Data-Driven Care: Carolina Advanced Health All Analytics
Vanguard Explains How It Keeps Customers Happy All Analytics
Staving Off Downtime & Other Benefits From Industrial Analytics All Analytics
SEO for Images Robbin Steif
An In-Depth Look at The Science of Blog Timing Hiten Shah
Conversion Conference 2012 David Iwanow
Business Analytics Software ‘Crosses the Chasm’ Into Mass Market, IDC Says All Analytics
The Correlation Matrix: Simple Tool, Powerful Insights & Clear Priorities All Analytics
It Pays to Listen to Your Customers All Analytics
Estimate Keyword Search Volume Using Bing Webmaster Tools & Excel Robbin Steif
Making a Career in Big Data Daniel Waisberg
New Platforms and Some Thoughts about NetBase – Web Journal, July 8th-15th, 2012 Marshall Sponder
The Process of Enterprise Reporting Gary Angel
Stroking the Data for Better Healthcare All Analytics
Mid Year 2012 Trend Report Corry Prohens
Mobile Will Require Advertisers To Redefine How They Measure Success Google Analytics
Plato’s Cave & Analytics All Analytics
E-Chat Today: Preparing for the Analytical Talent War All Analytics
The Secret Sauce For Developing Written Content IIA
How WBC Used Advanced Segments To Boost E-commerce Conversion Rate By More Than 12% Google Analytics
Accurate Measurement [cartoon] Daniel Waisberg
54 Quotes from Startup Leaders on How to Improve Conversions Hiten Shah
Cloud Advocate Puts First BI Project Out There All Analytics
Predictive Modeling Gives New VC Firm an Edge All Analytics
The Data Challenge All Analytics
Nabbing the Bad Guys & Keeping Gas Costs Down All Analytics
Different Shades of Data… & Social Media All Analytics
LunaTV Ep.10 – Google Analytics – Is Google Analytics Suitable for a really large site? Robbin Steif
Analytics Goal Workshop, Part 3: Engage with Events Robbin Steif
Data Analysis & The Trouble With Taste Daniel Waisberg
5 Reasons Email Marketing Crushes Social Media Marketing for B2B Hiten Shah
Mid Year 2013 Trend Report Corry Prohens
Mobile Websites vs Responsive Design: What’s the right solution for your business? Google Analytics
Slideshow: 10 Tips for Predictive Analytics Success All Analytics
Records Management Protects Employees & Companies All Analytics
Quote of the day Juan Damia
Unique Visitors In a Multi-Device World Robbin Steif
Analyzing Personas Using Advanced Segments Daniel Waisberg
Google Analytics Custom Tagging – Part 1 Gabriele Endress
How One Health Plan Achieves Its DataTa-Da! All Analytics
A Study in Psychology: Using Stats to Detect Research Fraud All Analytics
Public Transportation Moves With Analytics All Analytics
Cloud Expo NYC… and, of Course, Big-Data All Analytics
Four Simple Truths About Analytics All Analytics
Analytics Admittance: Adults Unaccompanied by Minors All Analytics
5 Advantages of Using a Social Media Management Company Robbin Steif
Marketers: 5 Ways to Kick Your Guesswork Marketing to the Curb with Analytics Hiten Shah
How to View the Visitor Flow of Specific Pages in Google Analytics Google Analytics Premium
Driving Analytics Discussions on Oil & Gas All Analytics
For Doomsday Virus, the End Is Already Here All Analytics
How Webtrends Measures Their Own Site Daniel Waisberg
Interesting Stuff & Web Journal – July 1-7th 2012 Marshall Sponder
How to Read, Write data and Transform Cases in RAPIDMINER Gunjan
Paypal Redesign Homepage David Iwanow
Think First, Collect Second All Analytics
Building a measurement plan, from the strategy to the tactic Juan Damia
Webinar #5 – How to Run A/B Tests that Get REAL Results Hiten Shah
Aurora & Others Collaborate on Information-Sharing Healthcare Network All Analytics
Big-Data Improves Speed, Accuracy for Lenders All Analytics
AP Reports This: Old Content Requires NoSQL All Analytics
Job Applicants: It’s Not You, It’s the Software All Analytics
The 5 Surprising Factors Behind the Most Shared Tweets (and How to Use Them) Hiten Shah
Turning Numbers Into Narratives as Easy as 1, 2, 3 All Analytics
Shoppers Love Sony, Wal-Mart & Toilet Paper All Analytics
3 Lessons the Internet Teaches About Writing a Blog for SEO Robbin Steif
Taking Analytics to the Next Level Daniel Waisberg
Undocumented features in the Google Analytics tracking code Matt Clarke
Local Remarketing – 6 Remarketing Strategies for Local Businesses Glenn Gabe
Why Will Analytics Be the Next Competitive Edge? All Analytics
Our Holiday Treat for Data Geeks All Analytics
Como criar e medir o desempenho de sitelinks do Adwords Leonardo Naressi
[Video] What really matters in Digital Analytics today? #3 – Gary Angel Nicolas Malo
How to Apply Buzz Marketing Principles for Effective Internet Marketing Hiten Shah
You say Analytics Maturity Quotient? I say wtf! Stephane Hamel
Creepy or Incredible? Your Data & Google Maps to Come All Analytics
A Strategy Management Tour de Force All Analytics
Slideshow: Data Scientists Revisited All Analytics
CORE Security Digs Through Data to Find Threats All Analytics
4 Ways to Use Bing Webmaster Tools for SEO Robbin Steif
Recent Changes in Google Analytics Rundown Robbin Steif
World Wide Web: A Planet Of Its Own [cartoon] Daniel Waisberg
[Video] What really matters in Digital Analytics today? #2 – Isabelle Mouli-Castillo Nicolas Malo
The Ultimate Guide to Creating a Positive Brand Image for Online Reputation Management Hiten Shah
Counterpoint: Plan Carefully for Next-Generation Data Analytics All Analytics
Point: Let’s Hit the Reset Button on Traditional Data Analytics All Analytics
eMetrics Chicago 2012 Juan Damia
There’s No Holiday From Security Threats All Analytics
5 Questions about Big Data Daniel Waisberg
[Video] What really matters in Digital Analytics today? #1 – Tom Betts Nicolas Malo
The Role of Segmentation in Reporting Gary Angel
6 ways to improve your digital dashboard Dan Croxen-John
Facebook down David Iwanow
Mounting Amazon EC2 instances on OS X with SSHFS Matt Clarke
Connecting to MySQL on Amazon EC2 over a SSH tunnel Matt Clarke
Politics and PeekAnalytics.com – Web Journal and the Demcratization of Data Marshall Sponder
Courting Better Health: Time to Focus on Health Analytics All Analytics
NEW! Google Analytics Android App: Reporting on the Go Justin Cutroni
NEW! Google Analytics Mobile App Tracking: Data & Reports Justin Cutroni
Data At Your Fingertips: Announcing The Google Analytics App For Android Google Analytics
6 Ways You’re Undermining Your Email Campaigns Before You Even Write Them Hiten Shah
The Must Have Big Data Tools Bryan Eisenberg
Bigger Fish to Fry Than Big-Data All Analytics
Measuring a Mobile World: Introducing Mobile App Analytics Google Analytics
Beyond the Words: A Case for Handwriting Analysis in the Hiring Process All Analytics
What Is Operationalizing Analytics? All Analytics
Slideshow: Looking at the Big Picture All Analytics
Trends in Risk Management All Analytics
Focus on The Right Questions [cartoon] Daniel Waisberg
Testing connection Peter Sanborn
Social Media & The Arts, Social Media Measurement and the move to Transmedia Story Telling Marshall Sponder
Analytics in a Philosophical Context: Why We Do What We Do All Analytics
Secrets of Profitable Marketing From Chico’s & Staples All Analytics
Oil, Gas, & EIA Predictions Don’t Mix All Analytics
Live E-Chat Today! MIT’s Lead IT Researcher on Getting the Most From Big-Data All Analytics
Are your Outbound Links stealing your Visits? Nabler
Manage Local Citation Sources Using GetListed.org Robbin Steif
Predictive Intelligence In Digital Marketing Daniel Waisberg
Sideværdi, profil kopiering, nye metrics og andre undergrundsnyheder Jacob Kildebogaard
A Business Mandate: Take Charge of the Information Explosion All Analytics
Reflecting on the First Half of the Year All Analytics
Tell a Story All Analytics
Facebook Strikes Again All Analytics
Quality Data Trumps Intuition All Analytics
LunaTV Ep. 9 – Social Media – Should I Have One or Multiple Facebook Pages? Robbin Steif
Workflows Simplified – Introducing Flow Viz PDF Export and Alerts Widget Google Analytics
App Retention Increasing; iPhone Crushes Android Localytics
Google Knowledge Graph Review Brian Ussery
5 Psychological Studies on Pricing That You Absolutely MUST Read Hiten Shah
Forces of nature: donate to the Red Cross Stephane Hamel
Having a Strategy vs. Being Strategic All Analytics
Big-Data Demands Gut-Busting Analytics All Analytics
A Lesson in Customer Service From Chick-fil-A President Dan Cathy All Analytics
Board of Directors’ Dashboards: Navigation or Naivete? All Analytics
Truth or Error: The State of US Joblessness All Analytics
Turning Chicago Into the City of Big-Data All Analytics
Analytics Goal Workshop, Part 2: Pages Playbook Robbin Steif
Big Data – What It Means For The Digital Analyst Daniel Waisberg
Intelligence events – en overset perle i Google Analytics Jacob Kildebogaard
The 7 Growth Hacks That Led Groupon to a $12.7 Billion IPO Hiten Shah
New York Times Small Business Summit – 6-25-12 + Semphonic Webinar on Big Data on 6-26-12 Marshall Sponder
Building Teams for Digital Big Data, Buy vs. Build in Tag Management, and Social Media Measurement and CRM Gary Angel
What to Do When Data Is Behaving Badly All Analytics
AllAnalytics.com Kicks Off Year 2 With a Bang All Analytics
Save Us From Blind-Copy Fails All Analytics
Wilhelm and Henriette: A Conversion Rate Optimization Folk Tale Robbin Steif
Using Analytics To Improve Education Daniel Waisberg
EU Cookie / Privacy Laws: Implications On Data Collection And Analysis Avinash Kaushik
Google.com.au Algo Change? David Iwanow
How to Identify and Control Blog Comment Spam Hiten Shah
NYU ITP CAMP Presentation and Web Journal – Week of June 18th, 2012 Marshall Sponder
Upcoming Event: How to Approach Big-Data With SAS VP of Big-Data, Paul Kent All Analytics
Making Complaints Part of the Analytics Process All Analytics
Slideshow: Treasures From Digital Landfills All Analytics
Predictive Analytics – Powerful & Dangerous [cartoons] Daniel Waisberg
Webinar: How to Build the Funnel that Will Grow Your Subscription Business the Fastest Hiten Shah
Econsultancy purchased by Centaur David Iwanow
Premier Bankcard Credits Predictive Analytics With Success All Analytics
Cleaning Up Data Quality in Dirty Environments All Analytics
Brace Yourselves for ‘Killer Apps’ All Analytics
Ad Copy Testing for the Google Adwords Beginner Robbin Steif
Tracking E-Commerce on Google Analytics Daniel Waisberg
9 User Experience Pitfalls That Repel Website Visitors Hiten Shah
Where the Hell is Matt is Back! David Iwanow
Yahoo Analytics Closes David Iwanow
Microsoft Surface Tablet David Iwanow
How to ditch your email preference centre with RFM Matt Clarke
Predictive Modeling Keeps Chicago Beachgoers in Safe Waters All Analytics
Break Out of the Hoarder Mentality All Analytics
A Lot to ‘Like’ About Social CRM All Analytics
Twitter Tool for Increased Engagement Robbin Steif
LunaTV Ep. 8 – PPC – How Does The Google AdWords Campaign Quality Score Work? Robbin Steif
The Ultimate Guide to the New Google Analytics Social Reports Hiten Shah
It’s Official: Google Wonder Wheel is Back, and It’s Called the Contextual Targeting Tool [Tutorial] Glenn Gabe
All Analytics Welcomes a New Community Editor All Analytics
How to Create a Filter to Tidy up Email Referrals Google Analytics Premium
A Perspective on Using Metrics Appropriately All Analytics
Analytics Is Like Dentistry – All on the Inside All Analytics
Plugging Into Better Decision Making All Analytics
IQ Workforce at eMetrics Chicago June 25th & 26th Corry Prohens
INFOGRAPHIC: The Complete Social Media Sizing Cheat Sheet Robbin Steif
Mobile Search Traffic On The Rise – Things to Consider Daniel Waisberg
The Secret to Getting Great Feedback from Your Users Hiten Shah
‘Big Brother in Arkansas’ Is Watching (& Profiling) Us All Analytics
If Correlation Doesn’t Equal Causality, What Else Might it Equal? All Analytics
Como o buzz pode auxiliar na estratégia de atuação em mídias sociais Leonardo Naressi
The Power Of Data & What It Can Tell Us Daniel Waisberg
If only Google Analytics were connected to Google Merchant Center… Matt Clarke
Think Different – Be Creative [cartoon] Daniel Waisberg
Web Journal – Mid June 2012 Marshall Sponder
Managing Reporting Fatigue : The Great Challenge of Digital Reporting Gary Angel
Revenue Management & Pricing Executives: This Is Your Call to Action! All Analytics
4 Unmarketing Insights From Scott Stratten All Analytics
How Strategies from Caesars Casinos Can Increase Conversions Hiten Shah
How Dow Chemical Uses Analytics to Understand Costs in a Tight-Margin Business All Analytics
Use That Data! All Analytics
Live E-Chat Monday: Exploring Data Quality for Analytics All Analytics
What’s The Definition Big Data? Who Cares? IIA
GA Advocate Justin Cutroni Answers Your Analytics Questions Google Analytics
Managing Marketing Metrics at Intuit Daniel Waisberg
The Digital (Analytics) Divide … Gabriele Endress
Average News App Outperforms Twitter on Mobile Localytics
Study Social Media Measurement at University of California Extension Irvine Marshall Sponder
Claiming Your Unfair Advantage Bryan Eisenberg
Why You Need to Evolve Your Thinking About Managing Data All Analytics
CatchFree Acquires KISSinsights Hiten Shah
Remember: Your Analytics Work Has a Shelf Life All Analytics
Google AdWords Even Ad Rotation Update Robbin Steif
The 7 Ways Dropbox Hacked Growth to Become a $4 Billion Company Hiten Shah
Understanding Analytics Professionals All Analytics
How Analytics Can Help You Find That Dream Job All Analytics
Using an Analytics Approach to Find Analytics Talent IIA
Women in Digital Analytics Corry Prohens
LunaTV Ep. 07 – SEO – Split Duplicate & Unique Content on 1 Page, Effects of Google+ Local on Places Robbin Steif
Calling all Non-Profits, the Semphonic Non-Profit Analytics Challenge begins again! Google Analytics
Do You Have a Long-Term Social Media Marketing Plan? Hiten Shah
Senior Analytics and Optimization Manager – ZAAZ Seattle, Washington Optimization Today
Kraft Eats Up Social Media Commentary All Analytics
Unlocking Big-Data & Reaping Data Equity All Analytics
Three Lessons Learned From One Dismal BI Failure All Analytics
Intelligent People but Stupid Choices – Try Using Analytics! All Analytics
Week 10 of the IQ Workforce #Measure Fantasy Baseball League Corry Prohens
5 Things You Should Be Doing in Google Analytics, but Probably Aren’t Robbin Steif
Learn How Google Analytics Helped BuildDirect Increase Sales By 50% Google Analytics
Building A Bulletproof Analytics Implementation Daniel Waisberg
Customer Analytics: How Analyzing Real People Will Improve Your Business Hiten Shah
Persona-Based Segmentation Gary Angel
Domain Knowledge Makes a Difference All Analytics
IQ Blast – Issue 6 Vol 8 Corry Prohens
Bing’s 3 Recent Reminders that Bing Matters Robbin Steif
Trends in Business Analytics Daniel Waisberg
Google Plus enables Search as You Type David Iwanow
Google Wallet is smarter at eCommerce David Iwanow
Getting Informed at Netroots Nation 2012 – Summary #NN12 Marshall Sponder
Netroots Nation 12 and Radian6 Tracking Marshall Sponder
Arriving at Practical Insights Takes Patience – Sometimes Lots of It All Analytics
Webinar: How to Start Using Analytics Without Feeling Overwhelmed Hiten Shah
Counterpoint: Insourcing Is the Answer for Big-Data Analytics All Analytics
Point: If You’re Contending with ‘Big-Data,’ Outsource Please All Analytics
Thoughts from XChange EMEA 2012 Peter ONeill
Operationalizing Greatness Corry Prohens
Two Questions You Absolutely Need To Ask Before Improving Your Customer Lifetime Value Hiten Shah
Polling Data and NetRoots Nation Day 1, Providence, RI Marshall Sponder
Call It Material or Data, You Still Need the Whole Picture All Analytics
Blogging Problems! Robbin Steif
Three Ways to Prepare Your Business for Google Plus Local Robbin Steif
Web Analytics TV #25 – The Silver Anniversary Show! Google Analytics
Why the Operating System Report is not showing iPhone and iPad visits? Google Analytics Premium
The Red Queen Economy: Running in Place Faster All Analytics
Is an Option-Pricing Approach in the Future for Revenue Management Analytics? All Analytics
Nonprofits Seek Better Donor Data All Analytics
Queen Elizabeth II’s Diamond Jubilee – What if Companies had a King and Queen? IIA
Building Blocks of Digital Attribution: How to get started with Google’s attribution tools Google Analytics
Be A Part Of ClickZ / Google Analytics Mobile Research Google Analytics
Getting Started with Google Analytics Daniel Waisberg
8 Surefire Ways To Increase Engagement Facebook Hiten Shah
Website Privacy Standards Inforgraphic from Ensighten Optimization Today
Analytics and Insights Director at Healthline Networks New York Optimization Today
E-Chat Thursday: How to Build an Insight Advantage All Analytics
Google Analytics eksperimenter, social og andre nyheder Jacob Kildebogaard
Get Agile With Your BI & Data Integration, Too All Analytics
Assessing Social Media Analytics & the Race for the US Presidency All Analytics
LunaTV Ep. 6 – Google Analytics – Seeing Pages Before Conversion, Tracking User w/ Many Devices Robbin Steif
Always Be Truthful To Statistics Daniel Waisberg
Google Penguin, Panda, Unnatural Links, Matt Cutts & More – SMX Notes Brian Ussery
Rethinking Email Marketing Hiten Shah
+1 Reports in Google Webmaster Tools – How To Analyze the Search Impact of +1 Annotations Glenn Gabe
The Second Age Marshall Sponder
Google Ratings for Places just too Confusing! David Iwanow
Mark Your Calendar: On-Demand Analytics Webinar Set for June 27 All Analytics
How to Pick the Right Tool for Your Analytics Project All Analytics
Horse Racing’s Triple Crown – Just Like Business Analysts All Analytics
Analytics Goal Workshop, Part 1: Plan Ahead Robbin Steif
[New Feature]: Conduct Browser-Size Analysis Within Google Analytics Google Analytics
Using Google Analytics to Lift Sales in E-Commerce Sites Daniel Waisberg
25 Awesome Free Google Tools for Marketers Hiten Shah
Affiliate Summit East 2012 David Iwanow
Reporting is about triggering efficient decisions Juan Damia
Why 100 Can Make for a Messy Metric All Analytics
SPSS Text Analytics for Surveys – Tips and Tricks 5 Gunjan
Google Website Optimizer is Dead. Long live Google Analytics Content Experiments Robbin Steif
How it Works: Analytics Explained In 5 Minutes Daniel Waisberg
Google Analytics Content Experiments – A Guide To Creating A/B Tests Daniel Waisberg
Google Analytics Custom Reports: Paid Search Campaigns Analysis Avinash Kaushik
Der Himmel über Berlin – Account of X Change Europe 1st Edition Jacques Warren
Meet Outfox, analytics and conversion optimization experts Lars Johansson
50 Excellent Google Analytics Tips and How To’s Optimization Today
NYU ITP Camp, BlogWorld NYC & NetRoots Nation Marshall Sponder
Reflections on the X Change Berlin Gary Angel
Google Website Optimizer Moves to Google Analytics – Experiments section under Content Section Google Analytics Premium
Yahoo Genome Advances Analytics Services for Advertising All Analytics
Lançamento Google Analytics Content Experiments Leonardo Naressi
Why Small and Medium Businesses (SMBs) Are a Big Opportunity for Business Analytics IIA
Helping to Create Better Websites: Introducing Content Experiments Google Analytics
What Startups Can Learn From Instagram Hiten Shah
Novation Gets User Ovation for Visual Dashboards All Analytics
Oil/Gas & Utilities: Finding the Value of Analytics All Analytics
IQ Blast – Vol. 6 Issue 7 Corry Prohens
Analytics Questions & Answers: Volume 1 Justin Cutroni
Why Knowledge Graph Just Made Google+ A Little More Relevant Robbin Steif
Future of Advertising Event – DoubleClick Insights Google Analytics
Find Your Valuable Business Treasure Faster with This Google Analytics Map Hiten Shah
Someone You Should Know: Stats Prof Jennifer Lewis Priestley All Analytics
Analytics Education: Take Our Quick Poll, Join Friday’s E-chat All Analytics
What to Make of Facebook’s ‘Big-Data’ Meltdown All Analytics
5 tips on mobile website usability testing Dan Croxen-John
LunaTV Ep. 05 – Social Media – Coordinate Social, Do I Need Google Plus, Social Analytics Prices Robbin Steif
Answers To Your Burning Google Analytics Questions Google Analytics
Upgrade now to the new Core Reporting API Google Analytics
Marketing Optimization Analytics Maturity Curve Daniel Waisberg
Day 1 @ XChange Europe 2012 in Berlin Nicolas Malo
Day 2 @ XChange Europe 2012 in Berlin Nicolas Malo
A Beginner’s Guide to Facebook Insights Hiten Shah
New Job at Brightcove 2012 Meng Goh

Senior Analytics and Optimization Manager – ZAAZ Seattle, Washington

Are you a thought leader? Put your MBA and web strategy experience to use in a dynamic environment with opportunities to influence the evolution of web analytics as it relates to global campaigns for our clients. ZAAZ is a pioneer in the use of analytics to develop strategic site optimization plans that become an integral part of our clients overall business model. Our analysts work closely with our creative, development and client relationship teams to deliver exceptional, results-driven work that is based on insightful analytics data. Were looking for passionate, number-crunching aficionado to join our team. Are you the one?

Responsibilities:
Helping clients define web channel goals and key drivers.
Determine appropriate metrics to measure goals.
Create and deliver custom Scorecards based on site goals to measure website performance.
Analyze web analytics data as well as other on- and offline data to evaluate site performance.
Discover underperforming areas of sites, identify opportunities to improve site performance.
Collaborate with usability experts, IA specialists, designers and developers to recommend solutions to the problems identified.
Define A/B/MVT test scenarios and success metrics.
Perform monthly analysis of clients site performance, delivering recommendations to improve performance.

Required Skills:
MBA or equivalent business experience.
Web Strategy Background (5+ years).
Excellent communication & presentation skills.
Experience working with senior managers and executives.
Data skills and experience are a must. Strong familiarity with behavioral and attitudinal data sets.
Some travel, including Helsinki.

Ideal Candidate has:
Direct response marketing or CRM.
Experience managing a team.
Web Analytics: Omniture, HBX, WebTrends, Google Analytics and/or other web analytics tools.
Ad serving tools: DoubleClick, Atlas.
Social monitoring tools: Visible Technologies, Nielsen BuzzMetrics, Radian6, TNS Cymphony and other tools.
Agency background.
Strong, working familiarity with statistics and statistical concepts.
Benchmarking – industry, competitive and/or vertical views.
A/B/MVT Testing.
Multilingual/multi-cultural experience. French, Finnish and other languages a plus.
Experience in the telecommunication services and device markets are also a plus.

Apply with 1-Click: SimplyApply

Source: http://www.web-analytics-jobs.com/a/jbb/job-details/704745