immeria

Job: Product Manager at iPerceptions (Montreal)

2009-11-06T11:53:00.001-05:00

As you might know, I recently sold the WASP technology to iPerceptions, and I'm now a member of their Advisory Council. I'm happy to relay the information about a job opening that will certainly be very interesting: Product Manager. iPerceptions is in the business of "Voice of the Customer" with the famous free 4Q survey and their corporate-strength webValidator continuous listening solution, and now WASP. iPerceptions works with top brands such as Dell, Toshiba, Reebok, Intuit, BMW, Sony, Nissan, etc. and as offices in Montreal, New York and London.

Enough blabbing, here's the job!

Product Manager

The Product Manager is responsible for both product planning and product marketing. This includes managing the product throughout the product lifecycle, gathering and prioritizing product and customer requirements, defining the product vision, and working closely with engineering, to deliver winning products. It also includes working with sales, marketing and support to ensure revenue and customer satisfaction goals are met. The Product Manager's job also includes ensuring that the product and marketing efforts support the company's overall strategy and goals.

The Product Manager is expected to:

Define the product strategy and roadmap
Deliver Market Requirement Document and Product Requirement Document with prioritized features and corresponding justification
Work with external third parties to assess partnerships and licensing opportunities
Be an expert with respect to the competition
Develop the core positioning and messaging for the product
Perform product demos to customers
Set pricing to meet revenue and profitability goals
Deliver a monthly revenue forecast
Develop sales tools and collateral
Propose an overall budget to ensure success
Manage the Internet Sales channel (Web site, order process, payment process, sales inquiries, customer support, social networking)
Brief and train the sales force at quarterly sales meetings, if required
Brief press and analysts and go on press tours, if needed
Act as a leader within the company

Required experience and knowledge

Minimum of 2 years experience as a Product Manager or Product Marketing Manager
Knowledge of Web Analytics
Knowledge of Social Media (Facebook, Twitter and others)
Knowledge on how to manage a Web site (content management)
Demonstrated success defining and launching excellent products
Excellent written and verbal communication skills
Bachelor's degree
Technical background, with experience in using the Internet as a Sales Channel
Excellent teamwork skills
Proven ability to influence cross-functional teams without formal authority
Examples and at least one sample of an effective document delivered in the past

Interested? Contact info@iperceptions.com?subject=Product Manager Job

Review: AT Internet NX

2009-10-30T10:39:00.008-04:00

Last week at the eMetrics Marketing Optimization Summit in Washington D.C. there was a big buzz around the new Google Analytics features. But really, Google might win a prize for biggest industry shakedown (close to Adobe purchase of Omniture), but AT Internet would be a good contender for innovation in the field of web analytics. The France headquartered company has been pushing the web analytics envelope for a long time. Very strong in Europe, AT Internet was an early adopter of the freemium model with the Xiti solution launched in 1996!

Here comes NX!

The latest release, dubbed AT Internet Digital Workspace^NX, has nothing to envy to the leading players in the industry. Here's a summary of the new features:

Dashboard:

Multiple dashboards
Flexible dashboard layouts
Cool dashboard widget: monthly objectives

Advanced visualization:

Multi-metric and multi-time period diagrams
Multi-metric lines & bars graphs
Heatmaps (not merely click maps)
Radars graphs

Filtering:

Slice & dice from any element using a contextual menu available for each item in a table
Build custom filters using multiple metrics and operators
Merge several elements into one group
Easily compare metrics in pop up

Segmentation:

Create segments using a drag & drop interface, and a variety of operators
Create new segments derived from existing ones

Specific features:

Live alerts
ClickZone & Scrollview (not new but still unrivaled)
Custom data collection

Vision

AT Internet is, in my opinion, one of the most underestimated, yet most sophisticated web analytics platform out there. Their product offers a 360 degree view of online analytics:

Clickstream data, both tags (and log-based coming in the near future)
Server monitoring: if your site is poorly performing or simply down... guess what: your conversion will suffer! Yet, few vendors offer integrated server monitoring
Social media monitoring: now unavoidable
Both way API to integrate with custom data
Technological partnerships to extend the platform

Beyond all those nice features, AT Internet approach is very different from other vendors. Their services can go as far as handling your analytics by providing dedicated analysts. This is one way of going beyond the tool and empowering their clients despite limited budgets and resources availability.

Launch event

AT Internet is doing a Montréal launch event for the NX version, along with the book launch of Nicolas Malo and Jacques Warren.

When: Wednesday, November 4th, starting at 5:00pm
Location: Hotel InterContinental
>>> RSVP to Alexandre Metier: alexandre(dot)metier(at)atinternet.com <<<
(places are limited)

I want to take this opportunity to acknowledge AT Internet great corporate citizenship: they are a corporate member of the Web Analytics Association and they frequently sponsor or present at local networking activities. Would be great if more vendors and agencies would get involved locally, as they do wherever they have offices.

Full disclosure: AT Internet kindly offered a free account to test Digital Workspace^NX, has sponsored Web Analytics Wednesdays in Montreal and offered occasional dinner, no money or other types of retributions were involved in exchange for this post.

Book review: Web Analytics by Malo & Warren

2009-10-28T17:22:00.000-04:00

My friends Nicolas Malo, from France, and Jacques Warren from Montréal, have just published the first web analytics book originally authored in French. Entitled "Web Analytics : mesurer le succès et maximiser les profits de votre site Web", the book is clearly aimed at non-initiated marketing managers.

Organized around three main sections covering the basics of measuring online business success, outcome analysis and site optimization, the book offers a solution agnostic, easy to read and rich in examples overview of the underlying concepts of online analytics. They are not going into too much details, just the right balance, which is perfect for busy managers who just need enough understanding to "get it" :)

My only negative comment is the price... 50$ CDN seems a bit high for an introductory book by first time authors (compared to $30 for the latest Web Analytics 2.0: The Art of Online Accountability and Science of Customer Centricity by Avinash Kaushik).

There will be a special book launch in Montreal, November 4th, at the InterContinental hotel. This launch will be done jointly with AT Internet brand new NX offering (more to come on this). If you would like to attend, please RSVP to Alexandre Metier (Alexandre(dot)Metier(at)atinternet.com)

Smarter 404 with embeded Google Search Widget

2009-10-22T10:27:00.001-04:00

When I posted on the Yahoo! Web Analytics forum to announce the availability of the free Web Analytics Maturity Model paper, the post included this text: "the paper at http://immeria.net/wamm." (notice the dot). The link was broken because of the way Yahoo! parses text to automatically build links.

Step 1: Use custom 404 page

The first step to improve broken links handling (404 errors) is to modify your web server configuration to point to a custom page handler instead of the default, very technical and dull error. For example, doing this on an Apache-based web server is as simple as adding the line "ErrorDocument 404 /http404.htm" to a file named .htaccess in the root folder of the site.

The specifics of your server configuration isn't the goal of this post. Contact your IT department or search for "custom 404 page" and similar keywords for additional help.

Step 2: Make a smarter 404 page

The custom 404 page handler is just another HTML page, so it can include your site navigation, brand and useful content. Often, the 404 page will have a de-dramatizing tone and some people have gone to great extent to make funny 404 pages.

Beyond trying to be fun, you want your visitors to get to your content. Two things are invaluable in this context: the referrer and the landing page URL. The next step is to make your visitors life easier by providing a path to the right page, or at least try... To do so, you can add a smart Google Search Widget:

<script src="http://www.google.com/jsapi" type="text/javascript"></script>
<script type="text/javascript">
    google.load('search', '1', {"nooldnames": true});
    function OnLoad(){
        var searchControl = new google.search.SearchControl();
        var siteSearch = new google.search.WebSearch();
        siteSearch.setUserDefinedClassSuffix("siteSearch");
        siteSearch.setSiteRestriction("yoursite.com");
        searchControl.addSearcher(siteSearch);
        searchControl.draw(document.getElementById("searchcontrol"));
        searchControl.execute(location.pathname.replace(/\//g, ' '));
    }
    google.setOnLoadCallback(OnLoad, true);
</script>
<div id="searchcontrol"/>

The important elements are:

setSiteRestriction("yoursite.com"): forces the search to be contained within your site (change it to your own site domain)
location.pathname.replace(/\//g,' '): replace the landing URL slashes with spaces so you can have a more meaningful search keyphrase
You might want to add a stylesheet element to your page so the Google Search Widget is larger (something like ".gsc-control{width:480px !important}")

The rest of the code simply handles and render the Google Search widget. In most cases, the automated search will offer some meaningful links destinations. In the worse case, the visitor has a neat search box and the site navigation to find their way around.

Feel free to visit http://immeria.net/custom/404page to get an example. Do a "view source" to see how I made mine.

Step 3: Analyze & Improve

Don't forget to put web analytics tags on that page so you can collect information about broken links. For Google Analytics, this is as simple as doing "_trackPageview('/404/'+location.pathname)" instead of the default "_trackPageView()" call. Create a custom segment to view all reports for broken links pages, look at the Content/Content Drilldown report, understand the source of traffic, what your visitors were looking for, and how you can further improve your site based this information:

If lots of traffic comes from a couple of sources, you might be able to ask them to fix their links
If those errors are the result of a site redesign, you might want to use redirections to map the old page URLs to their corresponding locations

Comments, additional ideas and any feedback is welcomed!

Google Analytics new features: my take

2009-10-20T13:30:00.006-04:00

It is now entrenched in tradition: Google Analytics makes announcements at the eMetrics Marketing Optimization Summit. So here's the latest, straight from the eMetrics floor where analytics evangelist Avinash Kaushik is addressing a jam packed room of enthusiastic web analysts!

Introducing Analytics Intelligence

The feature that excites me the most is something I discussed privately with Avinash a while back: once we spot a dip or spike in a metric, I shouldn't have to manually dig for the other metrics that are correlated with this significant change. The tool should be smart enough to point me to the other few metrics that have the highest correlation with this change.

Here's an example: conversion rate is significantly down. Ok... What does it really mean? Is there a spike in traffic? Or is there an issue in the process leading to conversion? In the former case, it means I'm bringing more unqualified traffic to the site. I can then review my Traffic Sources to easily pinpoint the issue. In the latter case, it means my conversion process as deteriorated or is failing at persuading people to convert.

Other features

There is also a host of new features (on top of the previously announced beta features):

Alerts! Once you have a good baseline, you want to be alerted of outliers: values significantly going beyond the historical trend. You can easily set up daily, weekly and monthly alerts.
Multiple custom metrics: adding "custom attributes" to visitors/visits is an essential feature of enterprise-level web analytics solutions (~~but I wish there was also custom metrics at the page level~~ Can have custom metrics at page, visit, visitor level - without limitations!)
Multiple-rule filtering: now you can more easily filter reports by building multi-criteria on-the-fly filtering rules.
Goals, more goals! (20) of them instead of four.
Segment unique visitors: something that should have been there from the beginning
Mobile analytics

More info at the Google Analytics official blog.

My take

Google keeps adding new features that challenges the traditional web analytics vendors. I have witnessed exactly the same phenomena in the high-end 3D animation/special effects software industry. When you are an industry leader enjoying high margin on product and services, you accordingly spend a lot of money on R&D. However, when you reach a certain feature set level, adding new innovations becomes exponentially expensive. At the same time, lower (and free!) tools can easily look at the top-line products and replicate and improve upon those features. Basically, the industry is leveling itself off, becoming a commodity: data collection & storage costs are being eliminated, intelligence and automations are being built in. This is obvious when a competitor you dismissed as being "irrelevant" can relatively easily replicate your unique value and offer a much cheaper (and free!) product. Even more if the true value of a product is being subsidized by other sources of revenues (ads in the case of Google).

The only alternative becomes to expand horizontally. Develop a suite of products. And this is exactly what Omniture has been doing over the past few years. Once it's done, or when you can't financially sustain the model, the way out is to move higher in the food chain... Adobe's acquisition of Omniture for example.

What does it mean for the web analytics industry?

As a member of the Web Analytics Association board of directors, any major shakedown in the industry raises some interesting questions. It is clear to me web analytics industry as we know it today won't exist in two or three years from now. Commodization of web analytics is not inherently a bad thing and is a demonstration of a maturing industry. To me, the path clearly points toward analytics, analysis: business analysis and process optimization, or what some call "business intelligence". On the way to the future, Google mammoth is likely to put several players to extinction...

Web Analytics Maturity Model: free paper available

2009-10-18T16:46:00.001-04:00

Today, while at the eMetrics Marketing Optimization Summit in Washington D.C., I was able to put the final touch on an important personal milestone: I’m really happy to make the Web Analytics Maturity Model paper available for general review and comments. On Wednesday, eMetrics chairman Jim Sterne will moderate the “Marketing Metrics Maturity” keynote panel (1:00pm) where Bill Gassman (Gartner Research), John Lovett (Forrester Research), Laura Patterson (VisionEdge Marketing) and myself (Stéphane Hamel) will debate the value and benefits of such maturity models and how they can be applied to your business.

To download the paper, all I'm asking for is to fill your email in the top-right box at http://immeria.net/wamm.

“So much has been written about why web analytics is valuable and how to make it work technically. The major stumbling block for most organizations is change management. Once convinced that they need to look at business from a different perspective, companies need a roadmap. The end game is so far off and the next steps are unclear” says Jim Sterne.

The paper provides an overview and a proposition for the Web Analytics Maturity Model (WAMM). Specifically, it defines the concepts necessary to understand the model and the motivation and purpose behind it. It describes the structural components, consisting of six key process areas (or pillars) within the six maturity levels of the model, and the principles that underline each of the maturity levels.

The primary benefit of such maturity model is to offer a framework to pause, think, plan and act based on an organization’s measurement and analysis skills. It offers a mean to assess the current and desired state, facilitate communication and change management. Bill Gassman highlights “the first benefit of a maturity model is the conversation it sparks. It puts the team in a mindframe to imagine what could be and to measure where they are”. Continuing on the objective of making web analytics easier, the overarching goal is to help organizations use analytics to make better decisions and extract maximum value from business processes.

The paper is a summary of an eighteen months eBusiness MBA project (Laval University, Québec, Canada). Adapted and derived from height models in fields such as business intelligence, process optimization, as well as those proposed by industry analysts and leaders, it is based on years of experience, countless hours of studying, reading and exchanging with fellow web analytics practitioners, managers, consultants and vendors.

Any feedback about the WAMM is welcomed and much appreciated. For further information, future research, including speaking, consulting and training, see http://immeria.net/wamm.

iPerceptions + WASP: my take

2009-10-14T09:10:00.002-04:00

I'm really proud and happy to announce iPerceptions has acquired the WASP product line and technology. You can read the official press release, but I also wanted to share some personal thoughts about what it means for me and for the 11,000 WASP users around the world.

Three years in the making

When I started working on WASP, around November of 2006, I was a part-time web analytics practitioner trying to solve, or at least simplify a real issue: how to check if our web analytics implementation was done correctly. I already had several years of experience implementating web analytics tools and knew how complex it was. What started as a proof of concept quickly became an interesting side project. One thing leading to another, a public beta was announced and in January 2009, a commercial product.

An unfulfilled need

Cookie deletion rate is a recurring topic; is it 3%, maybe 10%? It simply amazes me! The primary cause of poor analytics data isn't cookies, it's bad implementation... While you don't have much control over cookie deletion rate, you do have control over the site instrumentation (or you should!). In a study recently commissioned by Google (full PDF report), Forrester revealed the most important consideration factor for choosing a web analytics solution is "reliable data collection" (45%!). Yet, vendors generally do a very poor job at offering quality assurance tools.

Word of mouth kicked in, user base grew to over 11,000 worldwide, 150 tools detection and a market predicted by Forrester to grow 17% for the next several years. Feedback, feature requests and constructive comments helped gradually tweak the product. There is still a long list of ideas and things to do, and as the market evolve, so will WASP. Alternatives are either too complex, unpractical, or too expensive. Clearly, WASP is answering a need: I have never seen a perfect implementation!

Always be learning

WASP has been an amazing learning experience. As most of you know, I did everything on my own, from development to marketing, commercialization and support. However, I was at a crossroad: do I want to become a product vendor, hire a bunch of people and grow the business, or remain true to the core reason why I wanted to become a freelance. I've been a strong advocate of web analytics, I love teaching & speaking at conferences (hear me at Infopresse in Montreal this Thursday, and at eMetrics Washington D.C. next week!) and my interests are for research & education. WASP is why I won the WAALTER award, and certainly a strong factor behind my election to the Web Analytics Association Board of Directors. I have other projects I want pursue; the Web Analytics Maturity Model, the concept of Just In Time Tagging and other crazy ideas to make web analytics easier.

My future and the future of WASP at iPerceptions

"Why iPerceptions?" you might ask. There were other offers, but iPerceptions is best positioned to bring WASP to the next level while remaining true to its original spirit: free trial, single user entry-base product up to enterprise level capabilities; wide range of products detection; closely listening to the Voice of Customer. They can bring the expertise and manpower I couldn't.

The popularity of 4Q Online Survey also demonstrates their ability to bring innovative solutions to the market. As an independent thought leader and member of the iPerceptions Advisory Council, I will stay closely involved and help them with new and interesting applications that I'm sure will have profound implications for the analytics community.

Parting thoughts

Thanks to my "angel advisers" (you know who you are!) for your insights & recommendations. Your willingness to help is always deeply appreciated and I'm trying to "pay it forward" whenever I can. Thanks to you: web analysts, vendors, fellow bloggers and users of WASP!

I will keep an eye on WASP and help iPerceptions the best I can. In the meantime, and as always, I'm happy to hear your feedback!

iPerceptions Acquires WASP Product Line to Empower Site Owners to Optimize Web Analytics Performance

2009-10-14T09:05:00.000-04:00

Introduction of new easy-to-use tool into the iPerceptions solution set allows users to audit web analytics tags to ensure that quality data is provided to site owners

NEW YORK, NY – October 14, 2009 –– iPerceptions Inc. (TSX.V:IPE), a leading provider of Voice of Customer web analytics, announced today that it has acquired the groundbreaking Web Analytics Solution Profiler (WASP) product line to continue to empower site owners with powerful tools to improve web analytics implementation. The WASP tools complement iPerceptions 4Q and WebValidator solutions by providing site owners and web analytics professionals with an easy and low-cost way to do quality assurance, understand how their web analytics solution is implemented, and make fixes that improve data quality. iPerceptions will continue to make the existing product line, including a free “test drive” version, available through http://webanalyticssolutionprofiler.com/ as part of its solution suite.

“We are seeing a pronounced shift towards tactical insights in the world of web analytics,” said iPerceptions President and CEO Claude Guay. “To achieve tactical results, organizations must begin to put muscle behind proper analytics tool implementation, and that’s where WASP’s value is really showcased. We are very pleased to now offer WASP through iPerceptions to extend our customers’ experience and benefits.”

“WASP is a required cornerstone to ensure data quality, leading to better decision making. Today, more than 10,000 analysts use WASP for diagnosis of over 150 different web analytics tools,” said Stephane Hamel. Hamel is the founder of Immeria and a leading Web analytics innovator who developed WASP. “iPerceptions is extraordinarily prescient in its voice of the customer analytics vision, and the company understands the power of the core technology developed by Immeria. Going forward, I am please to also work hand-in-hand with iPerceptions on some new interesting applications with profound implications for the analytics community.”

WASP recently received the Web Analytics Association Leadership and Technical Excellent Recognition (WAALTER) for leadership and innovation in the field of web analytics. The solution provides a powerful crawler for tag edits and features an intuitive interface and compatibility between all major web analytics providers. The new solution, created specifically for web analytics professionals, also features:

Page-by-page, technical details for tags (beacons)
Crawl whole sites or sections of a site for easier quality assurance and tag audits
Convenient sidebar with as-you-browse information for testing complex scenarios
Enhanced tag views and more for approximately 150 top web analytic solutions
Frequent updates and enhancements

About iPerceptions

iPerceptions is one of North America's leading web-focused Voice of Customer analytics providers. Its webValidator Continuous Listening solution, free website survey solution 4Q, Web Analytics Solution Profiler (WASP) and proprietary iPerceptions Satisfaction Index (iPSI) turn thousands of data points into easy-to-understand strategic and tactical decision support for website marketers. iPerceptions' clients include such well-known brands as InterContinental Hotels, General Motors, Dell, Hyundai, LG Electronics, Choice Hotels International, BMW and Monster Worldwide. iPerceptions has offices in New York, Atlanta, Toronto, Montreal and London.

The TSX Venture Exchange does not accept responsibility for the adequacy or accuracy of this press release.

Media information: Emily Brady
Brady Public Relations
Tel: 415-606-9350
emily@bradypr.com

Investor information: Claude Guay
President & Chief Executive Officer
iPerceptions Inc.
Tel: 514-488-3600
Fax: 514-484-2600

Free Web Analytics seminar: Oct. 26th, Montreal sponsored by Unilytics

2009-10-13T14:31:00.001-04:00

Going beneath web analytics data into real information

Unilytics, is sponsoring a free, half-day seminar in which they will explore the current state of web analytics and the potential it holds. The first half of the seminar will be high-level and present industry trends and general best practices. It will be of particular interest to upper management. The second half will be more technical and focused on those who make analytics part of their day to day job. You can opt for the full seminar or only the executive portion.

The challenge many companies have with analytics is that there is just too much information to really consume, understand, and action it all. These huge volumes of data are inappropriate for proper decision making. Quantity of information far exceeds quality.

The metrics needed to make truly informed decisions are often hidden by an array of reports and the complexity of their presentation. Key Performance Indicators (KPIs) hold the promise of tracking a few select values which elucidate how your web site is performing. These KPIs are even more invaluable when measured against business goals and objectives. In this seminar we'll discuss best practices for determining, measuring, and tracking these KPIs.

Mature analytics adoption often renders simple reports showing most popular web site pages and numbers of visitors as a passing curiosity only. These mundane metrics have given way to integration with cross-channel data as well as other customer data across the organization. We will also investigate the potential of social media, 1:1 marketing, and KPI analysis and governance. Finally, we will demonstrate Webtrends 9 Insight, the latest version of the award winning web analytics software.

Location:
Loews Hotel Vogue (Map)
1425 rue de la Montagne
When: October 26, 2009
Agenda:
8 - 9 am Registration & Breakfast
9:00 - 10:15 WA overview & Executive briefing
10:30 - 11:45 Technical discussion & Webtrends v9
11:45 - 12:00 Q&A
Registration: unilytics.com/seminar2009.shtml

About Unilytics

Unilytics offers market leading web analytics products and services to address the needs of eMarketers in all vertical industries. As the world’s largest Webtrends partner, we offer unparalleled product expertise and consulting services for both Webtrends and Google Analytics.

PostRank Analytics

2009-09-24T12:12:00.000-04:00

Couple of days ago I was solicited to take a look at a new offering by PostRank called... PostRank Analytics!

The service is pretty clever and offers insight into your blog performance by merging social media measurement and quantitative data. The graph bellow shows an overview with timeline, indicators when you posted on your blog, and overall stats. Clicking on one of the post indicator leads to a more detailed report.

Learning how your content is performing with your audiences, improving your blogging, and developing relationships with your readers should be as important to you as to larger media outlets. But web analytics itself, such as Google Analytics, isn't adressing very well the social media aspect of your blog performance.

This detailed report shows individual posts with indication about the relative PostRank Engagement index, page views, time on page, and number of mentions in several social media outlets such as Twitter, Digg, Delicious, Reddit, etc. For individual posts, you also get all Twitter mentions.

Basically, PostRank Analytics allow you to better identify when, where, and how your audiences are engaging with your content, not only in the last week or month, but also today. It will help you find readers on all the important social hubs where they consume, organize and share content. You can not only see overviews of your audience engagement activity, you also see it as it happens, enabling better connection for timely conversation.

My take

A very interesting service worth giving a try. With so many data sources and different ways to look into social media and general web analytics data, PostRank Analytics provide an easy to use and pretty complete picture. Even if only $9/month, my worry is the number of clients willing to pay for a service that gathers data readily available for free from different sources, and particularly when so many bloggers are relying on a collection of free tools. Still, the insight and visualization is pretty useful, and serious bloggers should at least give it a try for a month (for free!).

Getting started in web analytics: career advice

2009-09-21T10:47:00.002-04:00

I often get asked about tips & tricks to get started in the web analytics field. This post is a summary of various resources to get started.

Education or training?

Education is about gaining knowledge and competencies, such as mastering the concepts of statistics, marketing and technology in order to truly understand what web analytics is all about. Training, on the other end, is more about acquiring specific skills, such as hands on learning of how to use Google Analytics. Generally, employers will look for trained people, while employees will seek education as a way to advance their career. The balance between the two is important to increase and sustain your value in the market.

Getting started

There is no magic trick here. Do your homework! Read, learn, try. Network, get involved, share. Nowadays you can get started very easily and quickly. Google Analytics as certainly democratized the web analytics industry, but don't be a fool and think this is enough. Web analytics is not about the tool you use, it's about a whole lot more! Check out the Web Analytics Maturity Model for more insight on all aspects of web analytics. Expertise and experience can only be gained through time and expanding your horizons.

Getting out of the catch 22

A frequent issue for those starting is the field is finding a way to gain hands on experience while not being employed. Without access to a playground to put your newly acquired knowledge and skills at work, it's pretty hard to move on. Not enough experience to find a job, no job to gain experience. How do you get out of this catch 22?

Your own site. Create a blog or a small site about something of interest to you. This is relatively easy and can be free. On the positive side, you have total control and you can touch on the three main dimensions of web analytics: marketing & business strategy, technology and analytics. The challenge here is to have enough traffic to make it interesting!
Get involved with a non-profit or a local site. There are plenty of them, and they will generally accept some help. With local sites, the challenge might be the limited traffic and relative simplicity of the site, but it's a start.
Crowdsourced analytics. the Web Analytics Association is working on a project that would allow WAA members and UBC students to volunteer work on a large-scale non-profit organization. More to come...

Ressources to get started in web analytics

Education

Web Analytics Association Base Camp:half or full day introductory courses
University of British-Columbia Award of Achievement in Web Analytics:four four-weeks long online courses
University of California Irvine Certificate in Web Intelligence:full-semester online education
University of San Francisco Internet Marketing Training Online

Training

Google Analytics training: several GAACs (Google Analytics Authorized Consultant) are offering training
Vendor training: visit your vendor's website for information about product-specific training

Social & networking events

Web Analytics Wednesday: the de facto social event for web analytics. A great opportunity to network, learn & share.

Conferences

eMetrics Marketing Optimization Summit: the official Summit of the Web Analytics Association, several cities world-wide
X Change: put together by Web Analytics Demystified and Semphonic, two consulting agencies. Early Fall in San Francisco.
Internet Marketing Conference: in several cities including San Francisco, Vancouver, Stockholm, Barcelona
Check for your specific vendor conference, such as the Omniture Summit, WebTrends Engage

Books

Web Analytics an Hour a Day, Avinash Kaushik
Advanced Web Metrics with Google Analytics by Brian Clifton
Always Be Testing by Bryan Eisenberg
Check my full bookshelf for additional readings

Forums & others

Web Analytics forum on Yahoo! Groups: please, before asking a question, check if it has been answered before!
Twitter hash tag #measure
Create a LinkedIn profile and join web analytics related groups

If you have other good starting resources to suggest, let me know!

Web Analytics Maturity Model: Case Study of European Car Manufacturer

2009-09-18T01:21:00.004-04:00

In this case, the WAMM was used to assess the current “state of the union” and as an effective communication and change management tool at an European car manufacturer.

The ecosystem consists of nearly 50 different versions of its web sites, each one characterized by specific marketing activities, car models, cultural aspects and local legislations. The group also manage other sites such as media, B2B, social presence and a typical corporate presence. With a multitude of visitor personas, business objectives, success events and supporting metrics and KPIs, web analytics plays a crucial role in providing insight to more than a dozen stakeholders. In the competitive automotive market, and especially during hard economic times, web analytics is used as a competitive asset.

“We are using the WAMM as support for developing a Web Analytics roadmap and strategy. It is a long road to implement culture change in a large organization - especially when you are on the IT side. It already triggered interest; that is a good start!”
Web Project Manager & Web Analytics Specialist.

Think globally, act locally

While local agencies handle the localized aspect of online/offline marketing and advertising activities, the head office group serves as an internal agency responsible for the hosting, content management and web analytics services. The group also provides the design, site templates, global content and assets as well as online tools such as the Car Configurator and the Dealer Locator.

From a marketing measurement perspective, the group provides two important services:

Measure the marketing performance against business objectives defined at the global level – improve and optimize the content and tools provided by the group.
Provide the NSMCs with personalized metrics so they can optimize their own activities at the local level.

WAMM Assessment

This organizational structure is common in the automotive industry and other global organizations. Objectives and Scope are high, while Management commitment and general adoption of analytics still have to be demonstrated. The team strive to handle multiple jobs at the same time and because of that, although the web analytics tool is good and quite sophisticated, it can’t be fully leveraged.

Web Analytics is mostly perceived as an IT project servicing online marketing needs, particularly Search Engine Optimization and online campaigns.

As mentioned previously, the TME team is using the WAMM to define and communicate goals, create a sense of urgency, demonstrate the complexity and requirements that will lead to the best outcomes.

To move from the actual “analytically initiated” state to the desired “analytically operational” maturity state, this organization will need to:

First, identify a senior executive who will act as a champion, someone with strong political skills, a stakeholder with some versed interest to make things happen for web analytics.
Secondly, the team will need to be extended, either by hiring skilled personnel to fill the knowledge and expertise gap on the business, technological or analytical dimensions, or better still, bring current employees who have demonstrated interest for analytics.
Lastly, the analytical process will be defined and owned by the newly formed team, with approval and support from the manager, and communicated to stakeholders.

From this point on, proper definition of objectives & scope will lead to an appropriate use of the technology and not only facilitate the continuous improvement of online processes, but also a growth in analytics maturity.

About this organization

This car manufacturer oversees the wholesale sales and marketing of two brands, parts and accessories, and manufacturing and engineering operations. Operations in Europe are supported by a network of several localized marketing and sales companies across most European countries, several thousand sales outlets, and manufacturing plants.

For further information regarding the WAMM and its future evolution, including speaking, consulting and training, visit the Web Analytics Maturity Model area on immeria.net.

Coming up next: other case studies!

Adobe + Omniture + WPP = game changer

2009-09-16T09:23:00.001-04:00

Twitter was on fire!

A short post to share my thoughts. I won't go into a long rambling about it.

Some deep thinking and speculation from all horizons. For the most part, people didn't see it coming... why did Adobe purchase Omniture? To make Flash tagging easier?

That’s not the point.

This picture clearly says what it's all about:

Adobe + Omniture means they will be looking at the whole value-chain process of developing website content and applications. This is far beyond making it easy to tag Flash!

Also, don't forget the huge strategic agreement with WPP. Add up Adobe + OMTR + WPP and you’ve got a major player who can change and steer the industry.

Web Analytics Case Study: Quebecor Media - Canoe

2009-09-10T23:20:00.000-04:00

This is the first case study of using the Web Analytics Maturity Model in the field and a couple of others will be published in the coming days.

In this case study, the WAMM is used to highlight the amazing accomplishment Quebecor Media realized over the past three years.

When Simon Rivard joined Quebecor Media as Vice-President of Marketing in November of 2006, he didn’t only bring over fifteen years of marketing experience, he also brought a strong belief for online marketing analytics. Quebecor now had a web analytics champion on board, the first and most critical success factor for a successful web analytics program.

Rivard is responsible for the marketing strategy of over 200 websites ranging from news portal to music & bookstore to auto and home classifieds, dating, as well as newspapers and TV stations. Deploying a web analytics solution, let alone educating everyone to the importance of data driven decision making, was a daunting task:

“Evolving the web analytics practice within such a large organization requires time and a good understanding of the critical success factors, otherwise risks of failure are significant. At Canoe, we intentionally planned the work over a three years timeframe to allow enough time for each required ingredient (knowledge, technologies, process, etc.) to be defined, understood and owned. Trying to skip some steps revealed to be a mistake and we had to step back. After all, implementing web analytics is a classic example of change management involving a business culture shift.”
Simon Rivard
Marketing Vice President
Quebecor Media

While some managers welcomed the move with enthusiasm, there was also some skepticism and passive resistance, questioning and challenging the strategy. Communication and education, as well as sensibility for political issues were key. But sometimes putting the foot down to impose a decision was also required. For example, vendor selection and the deployment strategy were sensible topics. At this scale, free vs paid played an important role, but there were also other factors such as the ability for the solution to grow from “initiated” to “integrated” and eventually, “competitive”. Several deployment strategies were considered, but the decision to start with a globally standardized minimal implementation proved to be the right tactic.

WAMM Assessment

Simply put, three years ago the organization was just getting initiated to analytics, trying “stuff” here and there without coordination or specific plans. As is often the case in large organizations, there was already an untapped pool of talented and skilled personnel. They lacked coordination and a favorable environment to create a critical mass and move beyond local, specific tactical initiatives.

Moving from “analytically initiated” to “analytically integrated” required lots of efforts, but the accrued knowledge is now influencing decisions at the CXO level. The work isn’t over yet. Two multidisciplinary teams, one in Toronto and the other in Montreal, are handling the configuration, service and analysis for hundreds of websites and stakeholders. Gradually, as each internal client becomes more educated and aware of the benefits of web analytics, responsibilities are delegated and the multi-disciplinary teams keep evolving into ever more complex and sophisticated analytics.

About Quebecor Media Inc.

Quebecor Media Inc. is a communications company with operations in North America, Europe and Asia. Quebecor Media owns operating companies in numerous media-related businesses, including: cable, newspapers, television network, a number of specialty channels, a network of English- and French-language Internet properties, magazines and book publishing, production, distribution and retailing of cultural products, DVD and console game rental and retail chain.

Web Analytics Maturity Model

2009-09-04T10:15:00.003-04:00

Now that I have offered a definition of Web Analytics, explained what is a Maturity Model and we have reviewed six existing models, it's time to look at the Web Analytics Maturity Model itself!

Previous posts in the WAMM series:

"Experience is what you get when you did not get what you wanted."
Randy Paush, known for "The Last Lecture" (must see video) and professor at Carnegie Mellon University

From "impaired" to "competitive"

Remember "maturity levels" defines an evolutionary plateau toward achieving a mature process. In the studied models, the number of levels ranges from four (DM3) to six (TDWI) and uses qualitative terms such as “Initial”, “Chaotic”, “Ad hoc”, “Pre-natal” and “Aware” up to “Optimizing”, “Sage” or “Pervasive”.

For the proposed model, each Key Process Area can be graded on a scale from “1 – Analytically impaired” through “5 – Analytical competitor”, as summarized below:

Analytically impaired: Characterized by the use of out of the box tools & reports, limited resources lacking formal training (hands on skills) and education (knowledge). Web Analytics is used on an ad-hoc basis and is of limited value and scope. Some tactical objectives are defined but results are not well communicated and there are multiple versions of the truth (side note: just think of the challenge so many analysts face when they have to define what is a "visitor", and why clicks-through metrics provided by their ad network don't match their Google Analytics campaign metrics) .
Analytically initiated: Working with metrics to optimize specific areas of the business (such as marketing). Resources are still limited but the process is getting streamlined. Results are communicated to various business stakeholders (often director level). However, web analytic might be supporting obsolete business processes and thus, be limited in its ability to push for optimization beyond the online channel. Success is mostly anecdotal.
Analytically operational: Key Performance Indicators and dashboards are defined and aligned with strategic business objectives. A multidisciplinary team is in place and use various sources of information such as competitive data, voice of customer, and data from social media or mobile analytics. Metrics are exploited and explored through segmentation and multivariate testing. The Internet channel is being optimized, personas are being defined. Results start to appear and be considered at the executive level. Results are centrally driven, but broadly distributed.
Analytically integrated: Analysts can now correlate online and offline data from various sources to provide a near 360° view of the whole value chain (see “Limits of web analytics” note). Optimization encompasses complete processes, including back-end and front-end. Online activities are defined from the user perspective and persuasion scenarios are defined. A continuous improvement process and problem solving methodologies are prevalent. Insight and recommendations reach the CXO level.
Analytical competitor: This level is characterised by several attributes of companies with a strong analytics culture:
1. One or more senior executives strongly advocate fact based decision making and analytics
2. Widespread use of not just descriptive statistics, but predictive modeling and complex optimization techniques
3. Substantial use of analytics across multiple business functions or processes
4. Movement toward an enterprise level approach to managing analytical tools, data, and organizational skills and capabilities.

The last two levels are gradually leaving the realm of “web analytics” to enter that of “business analytics”, as defined by Davenport in "Competing on Analytics".

Limits of web analytics

There is a distinction to make between “web analytics” and other disciplines such as “analytics” and Customer Relationship Management (CRM). Too often, management and practitioners expect web analytics to work like CRM or other core business systems. For example, online sales as provided by web analytics solutions should not be used as a valid representation of financial figures for the purpose of accounting. They do not aim and do not account for cancellations, errors and returns.

The table below contrasts some elements of web analytics and customer relationship management:

	Web Analytics	Customer Relationship Management
Realm	Online	Multichannel
Individuals accuracy	Based on cookies and other techniques, sometimes authenticated	1:1 – Authenticated most of the time
System type	Analytical	Operational and analytical
Accuracy	Sampling and margin of error	Close to 100% accurate

Can you think of other contrasting elements between web analytics and other disciplines such as BI or CRM?

Key Process Areas

Key Process Areas are similar to “critical success factors” (CSF), a term initially used in the world of data and business analysis. It identifies the elements that are vital for a strategy to be successful. Most organizations have perceived Web Analytics as a technological tool for solve problems in individual areas such as online marketing. But those initiatives are largely characterized by a lack of coordination and structured methodology. Unsurprisingly, Web Analytics Critical Success Factors are not that different from those of any other strategy involving strong commitment and cultural business changes, be it Customer Relationship (CRM), Business Intelligence (BI) or Process Optimization (ex. SixSigma) programs: human factor, processes and technology needs be addressed.

Changing the corporate culture, employee behaviour and business processes, is certainly the most difficult and risky part of any major organizational change. By its nature, developing an analytical culture is an iterative and continuous learning process. While data analysis can contribute to business improvement by answering pending questions and validating hypothesis, they also lead to further questioning and new hypothesis to explore.

Because web analytics touches on aspects of marketing, BI and process optimization, among others, it is easy to recoup some commonly identified CSFs and reveal the following items:

Management, Governance and Adoption
Objectives Definition
Scoping
The Analytics Team and Expertise
The Continuous Improvement Process and Analysis Methodology
Tools, Technology and Data Integration

The first element is unambiguously and unanimously the most critical factor in most of the reviewed models. Case studies (to be posted later) offers several examples of the importance of Management, Governance and Adoption. To be successful, executives must recognize web analytics is more than a reporting system and represents an effective way to identify weak points and improvement opportunities. They must perceive analytics (not just web analytics) as a mission critical and competitive resource that can empower each department. Sophisticated use of analytics can contribute to three key elements of a successful organization:

Efficient and effective execution.
Smart decision making.
Optimized business processes.

However, we must stress that web analytics, as commonly thought of, is nothing more than a tool providing indicators and metrics. Making sense of them requires knowledge and expertise, as highlighted in the next section.

Common Features

Common features are attributes that indicate whether the implementation and institutionalization of Key Process Areas is effective, repeatable and lasting. The following common features are identified:

Commitment: Is the level of commitment from the organization appropriate and defined by organizational policies, structure and management sponsorship?
Resources: Are resources to accomplish the task readily available: tools, training & education, organizational structure and people?
Process: Are the roles and procedures to perform each activity defined, tracked and adapted if necessary? Are recommendations implemented and reviewed to contribute to the overall learning process?
Reporting and Analysis: Are out-of-the-box reports used or complex multiple-data-source regression analysis conducted to provide customized Key Performance Indicators and dashboards?
Tools: What are the tools, their features and capabilities, is their use optimal and effective?
Quality: Are mechanisms in place to insure the data being collected is adequate and of good quality? Are reports, insights and recommendations audited to insure their quality over time?

Key Practices

Each Key Process Area is described in terms of key practices that contribute to satisfying the goals. The key practices describe the means and activities that contribute most to the effective implementation and institutionalization of the key process area. They describe “what” is to be done.

Key process areas of the Web Analytics Maturity Model include:

Data collection methodologies (log files, tags, network probes, etc.) and data modelization
Reporting & Analysis
Problem resolution techniques
Defining Key Performance Indicators and Dashboards
Communication
Exploration and visualization tools methods
A/B and Multivariate testing
Personalization and behavioral targeting
Predictive analytics
Process analysis and modeling

Review of Maturity Models

2009-09-01T21:57:00.003-04:00

This is a long post part of the Web Analytics Maturity Model (WAMM) series. This time, I'm looking into six maturity models from various domains:

WebTrends Digital Marketing Matutiry Model (DM3) (Web analytics vendor)
Gartner’s Maturity Model for Web Analytics (Market analyst/Information technology)
Capability Maturity Model Integration (CMMI) from the Software Engineering Institute at Carnegie-Mellon University (Academic/Software engineering)
The Data Warehousing Institute Business Intelligence Maturity Model (Association/Business intelligence)
Stratigent Marketing Analytics Model (Web analytics consulting)
Competing on Analytics maturity by stage, by Thomas Davenport in "Competing on Analytics: the new science of winning" (Academic)

Those models will serve as inspiration to develop the Web Analytics Maturity Model.

Previous posts in the WAMM series:

For more information visit the Web Analytics Maturity Model area on immeria.net.

WebTrends Digital Marketing Maturity Model (DM3)

The DM3 model, announced in the spring of 2009, claims to offer a "framework and objective criteria to determine the sophistication of an organization’s measurement and analysis skills, staffing and best practices across multiple digital marketing disciplines, from web sites to social media". The proposed model defines six core areas, each one graded on a four level scale.

In their model, WebTrends consider the first "pillar" to be the most important one, and most pillars are further sub-divided.

Measurement strategy: A measurement strategy is in place and aligned with business objectives.
Analytics resources and domain expertise: The number of employees dedicated to measurement and analysis, resources allocation and problem resolution skills.
Data integration and visualization: Establish correlations between multiple data sources and communication of insight through the organization, presentation and delivery of data.
Data analysis and insight: Skills to turn web-based data into insight.
Adoption and governance: Role-based training, change management, security, data consistency and quality and process-driven governance.
Ongoing optimization: A continuous improvement process to identify opportunities and test various optimization scenarios is in place.

Still in beta, this model certainly needs further refinement. The sub-division and ratings are based on strong experience but lack empirical approach and supportive evidence. The desire to push for an industry standard is certainly good but the actual approach centers heavily around this vendor consulting services. As others have criticized, the spider-chart is "making an assumption that certain groups of activities come together" and "gives the impression that adjacent pillars are somehow correlated because the area that is formed by joining their scores depends on both scores and doesn’t give each one visual independence of the other".

More info: WebTends Digital Marketing Maturity (DM3)
Image credit: WebTrends

Gartner Maturity Model for Web Analytics

This model was first published in 2008 and is aimed at "CIOs and other IT and business leaders responsible for the strategic success of their organization's Web optimization strategy". In this model, Gartner analyst Bill Gassman reiterates the fact "the problem tends to be a lack of skills and processes rather than issues with the tools themselves".

This model focuses on the responsibility to pick the right solution (or set of solutions) for the stated business goals. It is acknowledged that organizations can demonstrate a level of maturity for some tasks while not necessarily mastering everything at a specific level. These levels are merely guidelines to set goals and analyze the gap between current and desired state. Although being very pragmatic and straightforward, it addresses only one dimension of a successful analytical organization: the web analytics solution technologies and their usage sophistication.

In its DM3 model, reviewed later, WebTrends criticize the Gartner model as failing to "address social media, SEM and other digital marketing measurement channels". However, looking beyond the specifics of each level, managers should understand the concepts and level of sophistication demonstrated at each level, and therefore, easily acknowledge social media, SEM, mobile and such are covered at "Level 4 - Collaborative" of the Gartner model.

More info: Gartner Maturity Model for Web Analytics
Image credit: Gartner

Capability Maturity Model Integration (CMMI)

CMMI was originally developed in 1989 as a tool for objectively assessing the ability of contractors’ processes to perform a contracted software project.

The main point of CMMI is the objective evaluation of the “ability to perform” and as been applied to many areas beyond technology and engineering, notably risk management and business process optimization.

Ad hoc (chaotic): Typically undocumented and in a state of dynamic change, tending to be driven in an ad hoc, uncontrolled and reactive manner by users or events.
Repeatable: Some processes are repeatable, possibly with consistent results. Process discipline is unlikely to be rigorous, but where it exists it may help to ensure that existing processes are maintained during times of stress.
Defined: Sets of defined and documented standard processes established and subject to some degree of improvement over time. These (as-is) standard processes are in place and used to establish consistency of process performance.
Managed: Using process metrics, management can effectively control the actual process. In particular, management can identify ways to adjust and adapt the process to particular projects without measurable losses of quality or deviations from specifications.
Optimizing: Focus is on continually improving process performance through both incremental and innovative technological changes/improvements.

CMMI has been criticized as being "overly bureaucratic and promoting process over substance" and being a "classical engineering approach that does not take under consideration numerous human cognitive, organizational, and cultural factors essential for the success of every project". Those criticisms should serve as a reminder in defining a simple, realistic and readily applicable model for web analytics.

More info: Capability Maturity Model Integration (CMMI)

TDWI Business Intelligence Maturity Model

Wayne Eckerson is the creator of The DataWarehouse Institute (TDWI) BI Maturity assessment tool, Director of Research and author of "Performance Dashboards: Measuring, Monitoring and Managing Your Business". The TDWI model main purpose is to "gauge where your datawarehousing initiative is now and where it should go next". Each of the six stages are defined by a number of characteristics: scope, analytic structure, executive perceptions, types of analytics, stewardship, funding, technology platform, as well as change management and administration.

The TWDI model addresses the business intelligence maturity, a term coined by Gartner analyst Dresner in 1989 as the "set of concepts and methods to improve business decision making by using fact-based support systems".

Prenatal – Management Reporting: Standard set of generic reports distributed without discrimination for actual needs. Inflexible and hard to modify, users tend to bypass the established solution.
Infant – Spreadmarts: Individual, disconnected spreadsheets and desktop solutions with their own set of data, metrics and rules that are not aligned with the organization. Although they offer a low cost and locally controlled solution, they prevent management from getting a clear and consistent picture of the organization.
Child – Data Marts: All knowledge workers are empowered with timely information and insight. Data is shared and standardized at the department level, offering a standard set of application, business data and metrics.
Teenager – Data Warehouse: Definitions, rules and dimensions are standardized across the organization and deeper analysis is available through interactive reporting and analysis. Queries crosses functional boundaries and the datawarehouse becomes a tactical tool to improve process efficiency across the whole value chain, contributing to a fact-based decision making culture.
Adult – Enterprise Data Warehouse: There is now a single version of the truth, data becomes an asset as important as people, equipment and cash. Scorecards and dashboards contribute to align every worker with the corporate strategy. ROI becomes positive and new, unexpected ways of using this knowledge emerge as a competitive asset.
Sage – BI Services: Data is open to customers and suppliers, extending the value chain beyond the corporate boundaries. Knowledge workers don’t have to switch context to analyze data since the data, information and insight is embedded into operational applications and contribute to decision engines (think of fraud detection, behavioural targeting, and automated applications). Business Intelligence becomes ubiquitous and value increase exponentially.

According to Thomas Davenport, analytics represent a subset of business intelligence. While BI can answer questions such as "what happened; how many, how often, where; where exactly is the problem; what actions are needed", analytics can answer "why is this happening; what if these trends continue; what will happen next; what is the best that can happen". From this perspective, we can asses a Web Analytics Maturity Model could borrow from the TDWI model.

More info: The Data Warehousing Institute Business Intelligence Maturity Model
Image credit: The Datawarehouse Institute

Stratigent Marketing Analytics Model

The Stratigent model outlines the four phases through which companies typically progress on the path to becoming data-driven organizations. A study conducted in 2007 revealed that:

A clear evolution of web analytics practices exists, and the progress of an organization can be ranked into one of several categories.
Internal education and adoption of analytic techniques are leading indicators of how quickly companies build competitive advantages in analytics.
Large budgets and big teams do not always correlate to success.

Foundation Building: Focus on implementing web analytics. Limited executive support and no significant ROI. The availability of data spurs interest and builds momentum across the organization.
Customization: The technology is customized to meet business-specific requirements. More relevant data spur adoption, drive ROI and secure funding for future investments.
Optimization: Multivariate testing is introduced to gain additional insight about customer preferences and improve marketing program performance. Online data integration and the emergence of a continuous improvement process provide additional insight and set the stage for the next phase.
Predictive Modeling & Targeting: Online and offline data are integrated to offer a complete view of the customer, allowing to deliver a highly targeted message for customers

The model is very interesting and highlights several aspects relevant to the definition of the Web Analytics Maturity Model:

A model can provide the vision, framework, and tactics necessary to put in place a web analytics program and develop a competitive advantage
Shows how web analytics can benefit marketing departments and contribute to a culture of analysis and insight
Provides a framework to demonstrate how the technology contributes to the organization’s capability to compete with analytics.

More info: Stratigent Marketing Analytics Model
Image credit: Stratigent

Davenport’s Maturity of Analytical Capability by Stage

Davenport, in "Competing on Analytics", proposes a maturity model encompassing three vital areas of a successful analytical company: organization, human and technology capabilities (what others refer as "people, process and technology") defined in 5 stages:

Analytically impaired
Localized analytics
Analytical aspirations
Analytical companies
Analytical competitor

From a business perspective, "Competing on analytics" is without a doubt one of the best primer on the topic of analytics and its concepts can readily be applied to web analytics. Furthermore, some of the mentioned analytic competitors are well known for their online activities: Amazon, Google, Netflix, and Yahoo!, among others. For those reasons, the proposed model appears to be very close to the desired specification of the Web Analytics Maturity Model.

More info: "Competing on Analytics: The New Science of Winning"

Components of the Web Analytics Maturity Model

2009-08-31T22:27:00.003-04:00

This post if part of the series on the Web Analytics Maturity Model, a research project for my MBA. See the first two posts on this topic: "Overview of the Web Analytics Maturity Model" and "Definition of Web Analytics".

What is a Maturity Model?

A capability maturity model (CMM) contains the essential elements of effective processes for one or more disciplines. It also describes an evolutionary improvement path from ad hoc, immature processes to disciplined, mature processes with improved quality and effectiveness.

All reviewed models share some similarities in their attempt to define a "framework and objective criteria to determine the sophistication of an organization’s measurement and analysis skills".

In the next couple of posts I will propose a review of some existing models (listed in the 1st post) and how they apply to the objective of defining a web analytics maturity model.

Defining a Maturity Model

Anyone can make the simple complicated. Creativity is making the complicated simple.
Charles Mingus, American jazzman

Some prominent voices in the web analytics industry claim that "web analytics is hard". Rather than spreading fear, uncertainty and doubt, I’d rather be of the school of thought that web analytics can be easier if approached in the right way and given enough time.

Complex projects can only be achieved pending goals and expectations are realistic, resources are allocated and execution is sound. Web analytics, albeit its own challenges, isn’t so different or any harder than other challenges faced by organizations competing in today’s environment.

Attributes of a Maturity Model

Maturity models are not strict paradigms and they often prompt criticism whenever a specific item doesn’t match one’s own view of the world. While it is acknowledged maturity levels and their features contains gray areas and are subject to interpretation, the important elements are not so much the specifics of each level but the structure of the maturity model.

The Web Analytics Maturity Model is looking into the following attributes:

Maturity levels: A defined evolutionary plateau toward achieving a mature process.
Process capability: The range of expected results that can be achieved by following a process. The process capability provides one means of predicting the most likely outcomes.
Key process areas: Cluster of related activities that, when performed collectively, achieve a set of goals considered to be important.
Goals: The goals define the scope, boundaries, and intent of each key process area.
Common features: Common features are attributes that indicate whether the implementation and institutionalization of a key process area is effective, repeatable, and lasting.
Key practices: Key practices describe the infrastructure and activities that contribute most to the effective implementation and institutionalization of the key process area.

Pitfalls of Maturity Models

In an essay published in a 1994 issue of American Programmer magazine, James Bach pointed out several problems with CMMI that could readily be applied to the various maturity models reviewed:

Lack of formal theoretical basis: Models are based on the experience of "very knowledgeable people".
Vague empirical support: Without a comparison of alternative process models under controlled conditions, the empirical case can never be closed and most accounts remains anecdotal.
Revere process but ignore people: Process can never make up for mediocrity, and thus, any maturity model should be viewed as an element of a larger whole encompassing employee skills and aptitudes as well as the corporate cultural environment.
Reveres institutionalization of processes for its own sake: Too much focus on the “ability to commit” can easily blur the “ability to execute”.
Encourages displacement of goals from the true mission of improving process to the artificial mission of achieving a higher maturity level: This has been a frequent criticism of other similar concepts such as ISO and SixSigma, where the “culture of x” becomes the mission.
Little information about process dynamics: Why each element is defined at the level they are is quite suggestive, as mentioned in the first item.

Despite those concerns, a maturity model brings value where there are no better or reasonable alternatives, and as a mean to assess the current and desired state, as well as a communication and change management tool. At the same time, those caveats are strong indications of opportunities for further research. As Bill Gassman commented on the first post in the series "The first benefit of a maturity model is the conversation it sparks. It puts the team in a mindframe to imagine what could be and to measure where they are."

Want more?

Previous posts in the series:

Coming up:

Critics of 6 current models, the WAMM model itself and several case studies: Toyota Motor Europe (with the help of Michael Notté), Quebecor Media - Canoe (Simon Rivard), SaveTheChildren.org (thanks to Adam Laughlin) and a failed project (name retained for obvious reasons!).

View all posts on Maturity Model topic.

For further information regarding the WAMM and its future evolution, including speaking, consulting and training, visit the Web Analytics Maturity Model area on immeria.net.

Definition of Web Analytics

2009-08-28T13:51:00.006-04:00

In the previous post I gave a quick background on the Web Analytics Maturity Model. This time, I'm giving a jab at the definition of "web analytics". Now that we know what is a maturity model, we need to agree on what is "web analytics".

Although some elements of performance measurement were technically available at the inception of the World Wide Web in the early '90s, interest for measuring web business performance has been on the rise over the past couple of years. If anything, three disruptive circumstances might explain this level of attention for web analytics:

Google democratization of web analytics with the launch of its free Google Analytics service in 2005
Marketing uncovered clear benefits of Web performance data to optimize online marketing activities
The economical downturn of 2008-2009 forces ebusiness initiatives to be measured and accountable for success.

A Marketing centric definition of web analytics

The Web Analytics Association defines web analytics as "the measurement, collection, analysis and reporting of Internet data for the purposes of understanding and optimizing Web usage". This definition centers on Internet data and website optimization from an online marketing point of view, whilst the broader scope of analytics, process and business optimization isn’t specifically addressed.

Definition of "analytics"

Davenport and Harris, in "Competing on Analytics: The New Science of Winning" are among the few providing a conceptual background to analytics and business optimization. In their book, the authors define analytics as being "the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions". This definition, much broader than that of "web analytics", is considered to be a subset of business intelligence: "a set of technologies and processes that use data to understand and analyze business performance".

Proposed definition of "web analytics"

I'm defining web analytics as:

The extensive use of qualitative and quantitative data (primarily, but not limited to online data), statistical analysis, exploratory (multivariate testing) and predictive models (behavioral targeting), business process analysis and fact-based management to drive a continuous improvement of online activities and improved ROI.

As we will see in the Web Analytics Maturity Model, the earlier stages naturally focus around online marketing, and the higher level match the lower realm of Davenport definition of "competing on analytics".

Want more?

This post is part of a series extracted from my MBA thesis paper. Comments and critiques welcomed!

Previous:

Overview of the Web Analytics Maturity Model

Coming up:

What are the components of a maturity model? Critics of 6 current models, the WAMM model itself and several case studies.

View all posts on Maturity Model topic.

For further information regarding the WAMM and its future evolution, including speaking, consulting and training, visit the Web Analytics Maturity Model area on immeria.net.

Overview of the Web Analytics Maturity Model

2009-08-26T14:30:00.002-04:00

I've been talking about a Web Analytics Maturity Model for a while now, both on this blog and at previous eMetrics conferences. I'm pursuing my research as part of my MBA thesis and in the coming days and weeks I will share some elements of an upcoming paper (or book?) on this topic. Of course, I'd love to hear from you! Any feedback is welcomed, good or bad :)

Overview

Jim Sterne, dubbed as the “godfather of web analytics”, was pushing for online marketing as early as 1994. In his “E-Metrics: Business metrics for the new economy” paper published in 2000 he mentioned that “while all e-business managers clearly recognize the tremendous value of e-customer analytics, most lack the staff, technical resources, and expertise to harness and put to effective use the flood of raw data produced by their Web systems“. A decade later, we can only admit this statement remains true.

The Web Analytics Maturity Model (WAMM) is adapted and derived from proven models in fields such as business intelligence and process optimization, or inspired from models proposed by industry analysts and leaders. Based on the critical success factors contributing to the “use of analytics to make better decisions and extract maximum value from business processes”, those are applied to a five level multi-dimensional capability maturity model.

The proposed model presents five maturity states:

Analytically impaired
Analytically initiated
Analytically operational
Analytically integrated
Analytical competitor

The six key process areas, or success factor dimensions, are:

Management, Governance and Adoption
Objectives definition
Scoping
The Analytics Team and Expertise
The Continuous Improvement Process and Analysis Methodology
Technology and Data Integration

Those maturity levels and key process areas defines common features and attributes as well as key practices that will significantly increase the likelihood of success and positive return of a web analytics program.

What is a Maturity Model anyway?

A capability maturity model (CMM) contains the essential elements of effective processes for one or more disciplines. It also describes an evolutionary improvement path from ad hoc, immature processes to disciplined, mature processes with improved quality and effectiveness.

All proposed models share some similarities in their attempt to define a “framework and objective criteria to determine the sophistication of an organization’s measurement and analysis skills”.

I have reviewed a number of existing models and how they apply to the objective of defining a web analytics maturity model. The following models were evaluated:

Capability Maturity Model Integration (CMMI) from the Software Engineering Institute at Carnegie-Mellon University
The Data Warehousing Institute Business Intelligence Maturity Model
Gartner’s Maturity Model for Web Analytics
WebTrends Digital Marketing Matutiry Model (DM3)
Competing on Analytics maturity by stage, by Thomas Davenport in "Competing on Analytics: The New Science of Winning"

Coming up

In the next post: my take on a definition of web analytics and later on, a critique of other maturity models. Also, I'm putting the model to the test with some organizations and those cases promise to be very interesting! View all posts on Maturity Model topic.

For further information regarding the WAMM and its future evolution, including speaking, consulting and training, visit the Web Analytics Maturity Model area on immeria.net.

WASP v1.26 released

2009-08-21T15:37:00.000-04:00

WASP v1.26 is now approved at addons.mozilla.org and had been available from WebAnalyticsSolutionProfiler.com for a couple of days.

Another round of bug fixes and minor enhancements while I work on WASP v1.50 (or what could turn out to be WASP v2.0).

What's new

WASP for Analyst:
- Breakdown of tags now shows an "(uncategorized)" branch for tools where help is available but specific tag usage is unknown (applies to Google Analytics, Omniture SiteCatalyst, WebTrends and AT Internet Xiti)
- Fixed detection failing when some JavaScript variables were defined with a null value
New/updated tools:

Please take 2 minutes to submit a review at addons.mozilla.org and visit the UserVoice page to suggest improvements and cast your vote.

Get WASP v1.26 now!

Speaking about Web Analytics Maturity at Internet Marketing Conference

2009-08-09T13:56:00.001-04:00

The Internet Marketing Conference

I've been invited to speak at the Internet Marketing Conference in Vancouver, September 16-18.

I spoke several times at the eMetrics Marketing Optimization Summit and local events in Montreal, but IMC will be my first time speaking at a conference not specifically targeted to a web analytics crowd. Other speakers includes my friends Avinash Kaushik and John Hossack, chair of IMC and a host of other speakers from Canada and abroad.

Presenting the Web Analytics Maturity Model

The theme for IMC Vancouver 2009 is "Quality Traffic". Traffic not only needs to be "relevant" to your business, it also needs to be proven successful. This fits very well with the topic I will be presenting: the Web Analytics Maturity Model (WAMM). As I did at eMetrics Toronto and San Jose in the spring, this highly interactive session will guide you through a SWOT analysis of your web analytics maturity. Review the six Critical Success Factors of successful web analytics programs and see where you stand, what you should do next. Don't let people simply tell you "web analytics is hard" and make you feel, at the end of the session, you will be armed with clear arguments and indications on what to do next in order to bring you, and your organization, to the next level.

This presentation received a score of 94% at eMetrics San Jose, 4th best speaker of the conference! I have pursued my research I will present an even better version of the WAMM.

Panel: Measuring Online Marketing in a Real-Time World

I will also participate in a panel with Kevin Hillstrom, Manoj Jasra, Braden Hoeppner, Amanda Rose and Eric Hansen, moderated by Ean Jackson, where we will jump in to answer the crowd questions and share our views and opinions about online marketing measurement.

Other opportunities to hear about the WAMM

InfoPresse, Montréal, October 15th: "Web et optimisation de sites"
eMetrics Marketing Optimization Summit, Washington, October 19-23: "Marketing Metrics Maturity Panel" with Bill Gassman (Gartner Research), John Lovett (JupiterResearch), Laura Patterson (VisionEdge Marketing)

"Unique Visitors" doesn't have much to do with people

2009-08-04T11:17:00.000-04:00

I was taking my morning coffee, reading Brian Clifton post about "Should you focus on website visitors as individuals?", his views of a recent e-Consultancy interview of Coremetrics Chief Strategy Officer, John Squire. I commented on Brian's blog, but as is often the case, my thoughts turned into something too long for a comment. I strive to participate in conversations I know won't end up with the now classic "let's agree to disagree".

Tracking individual customers, really?

Coremetrics is differentiating its technology by focusing on individual customer data in a multichannel environment. They look at “complete historical online behavior and brand interactions on websites, across multiple ad networks and via email, video, affiliate sites, social media, and more”.

(emphasis mine) I salute Coremetrics (and others) objectives to track "unique people" instead of "unique cookies" in the hope to get more precise and detailed information. But this is a lost cause... the inherent technologies of the web don't allow that, unless you can authenticate every single visitor coming through all channels... As soon as there is "multichannel" and "web analytics" in the same phrase I get suspicious... "multichannel" when everything is online is something, but how is data from call center, back-end core systems and other touch points integrated to give a "single view of the customer"? We're heading in the realm of business intelligence (BI) and customer relationship management (CRM), and despite the marketing fluff, I don't see any of the current web analytics vendor really playing in this space. In the above statement, all of the mentioned "channels" are "online", which, I agree, gives you a very good view to start with, but a view where your sight is concentrated and everything else in the periphery is blurred.

I like Brian argument that aggregating & sampling is the way to go. After all, web analytics is closer to statistics: with a population, segments, sampling/aggregating... and a margin of error, confidence and significance... then it is to core systems where each piece of data should be 100% accurate and traceable.

Trust me, I'm accurate (and honest)

One of the thing playing against Google Analytics is the fact that experienced analysts (those who have a statistical background, come from the offline world or have lots of experience in a real multichannel, multi-system environment) want to audit, validate and diagnose the data they are relying on. The inability to audit the data and have a peak at the methodologies employed by Google to provide the data is a big showstopper to some organizations. It's basically asking for a blind trust where your provider (AdWords) is also giving you your results (analytics conversions)... or your employer is also managing your bank account... For that mater, your also have to trust other vendors because you can't have access to the algorithms they use for aggregating or sampling data, but they do not play a dominant role in your online marketing (PPC) spends.

From time to time, access to the raw data, or the lowest level possible, is justifiable and necessary. The latest Forrester Wave: Web Analytics Q3 2009 reveals that 49% of surveyed web analytics clients said "accuracy of information" is one of their three most important factors when selecting a vendor. This comes ahead of reporting options, and far ahead of TCO! Yet, despite vendors secret formula to calculate accurate visits & visitors, research I conducted using WASP shows the number one source of distrust and inaccurate data comes from inappropriate and incorrect instrumentation.

My take

Detailed or aggregate? Really multichannel or "online channels"? I'll put my old record again: it depends on your Web Analytics Maturity Level. For most organizations, even if they have access to detailed data, they simply won't be able to make good use of it. If you wonder, it's probably because you don't need detailed data and Google Analytics will be just fine. If you do your homework, you'll look at offerings from various vendors and put aside frivolous and inflated claims boasted with buzz words such as "real time", "multichannel" (when they really mean online channel), "single view", "complete" and the worst of all: "leading".

Playing with Google Analytics Pivot Tables

2009-07-24T17:09:00.001-04:00

Google Analytics is introducing Pivot Tables. Since not everyone is a lucky winner, here's a snapshot of Referring Domains broken down by Source of Traffic & Visitor Type, showing Visits and Bounce Rate for today's traffic on immeria.net.

Look for the Pivot Table button in most detailed reports:

If you combine the recently introduced slicing (advanced segmentation) with this dicing, we're in business!

What's next? My personal wishes:

Visit and page level custom attributes: we need more than the current single visitor attribute. People have found creative ways to stuff more than a single value in the setVar(). What makes a web analytics platform powerful is the ability to extend it's data.
Import API: once the above is solved, why not provide an import API? You will then see a number of "addons" to extend GA capabilities
Addons: speaking of addons... why not provide a repository of approved and under development addons? A bit like the Mozilla Firefox addons concept. From the GA setup interface you could pick & chose various addons to be included in your tags. For example, I'm providing some code to automatically track outbound links and downloads. This would make for a nice addition to make tagging and data collection easier.

Kampyle + Google Analytics, VOC + WA, qualitative + quantitative

2009-07-23T22:42:00.042-04:00

I've been a long time user of Kampyle, a solution to collect, analyze and manage your website visitors' feedback. I've talked about it several times in the past. So you might ask, what do I have to say this time?

A few weeks ago Kampyle announced the integration of Google Analytics data and my friend Eran Savir, co-founder and VP of development, kindly offered the update. I waited some time to see what kind of insight I could gain from the combined results.

I'm running Kampyle on the WASP site, which doesn't receive a huge level of traffic but sufficient enough to make Kampyle or worthwhile addition.

Now I can see the number of feedback by visitors, which is a nice way to see how engaged are my users. But I can also see Feedback by User Loyalty as well as Feedback by Top Landing or Top Exit Pages.

According to my WASP market data, the number of sites using Kampyle keeps increasing and there are other interesting features on the way: Feedback by adWords campaigns as well as behavioral targetting. Most times innovation doesn't come from ground breaking ideas, but from interesting combination of existing technologies. That's what Kampyle is doing, and doing very well!

WAA Championship - have you got what it takes?

2009-07-11T11:38:00.001-04:00

Again this year, the Web Analytics Association is putting up the Championship challenge for its members: put your web analyst skills at work and analyze the WAA website!

This is a unique opportunity! I often get contacted by students of the UBC Award of Achievement in Web Analytics and others who want to start in the web analytics field. One of the challenge is to get your hands on the tools and play with a site that has sufficient level of data to make it interesting. So now is your chance!

Three simple steps:

Have a peak at Google Analytics, WebTrends and Yahoo! Analytics as implemented on the WAA website
Do your analysis and provide insight & recommendations
Win prizes! But beyond all, you get to learn & experiment a real web analytics environment on a real website and get involved in the association. And be assured we will take your insight and recommendations with interest as we are looking at some revamps & enhancements for the WAA website.

FYI, I'm one of the judges, along with my friends "Wandering" Dave Rhee and Judah Phillips, under the supervision and great help from Daniel Waisberg. Which brings a nice international participation, unless I'm mistaken, Judah is in Boston, Dave is in Germany, Daniel is in Telaviv and I'm in Québec City!