So, what is Digital Analytics then?

The WAA renamed itself to DAA (which was announced at eMetrics in San Francisco last Monday) to reflect the reality of how the profession/industry has grown since its website centric origins. That brings up the question what Digital Analytics should stand for?

No doubt,  every vendor (including me) and consultant will bellow now that digital analytics are exactly what he/she said all along that companies should be doing with analytics. And it is of course exactly what his/her/my company happens to be offering. 😎

We’ll also see the more mundane proposition that Digital Analytics is the combination of web, mobile, and social analytics and also includes VOC, benchmarking, email analytics, search analytics, performance, replay, etc.

Nothing wrong with the above.

It’s just that I think Digital Analytics has greater potential than all that.

Namely, as the digital and physical worlds are increasingly intertwined, digital analytics are becoming a key intelligence for business decisions and CRM, not just channel optimization or making page content/layout better.

For example, already in 2009 Macy’s CEO went on record saying that every dollar spent on led to $5.77 influenced in stores within the next 10 days. This reflects the well known “research shopper” phenomenon. Since then, Smartphone ownership in the US has crossed 30% of cell phone users and 4 out of 10 have said in surveys they used their phone to get more information on items while in a store.

Likewise, 33% of retailers said in a survey that equipping their store staff with mobile POS capabilities is a key investment coming now. So both buyers and sellers are going to be even more digitally intertwined than they have been in past years.

As a result we should see that an increasing portion of data used in data warehouses, business intelligence, and CRM is digital data.

To be more specific, we are talking about behavioral data and customer , not just transactional data because the latter has been integrated some time ago already.

New cycle of continuous improvement

To bring this to the point, until here the profession of web analytics has often been identified with a continuous cycle of improvement as seen below. We set goals, measure where we stand, test/experiment with alternative content, pick the best design, rinse and repeat.

As all interactions with a business are becoming increasingly intertwined with digital, it is time to embrace the more strategic potential of digital analytics by moving to the cycle below. Here the insights are used either for business decisions or to identify the next most relevant content or product/service/promo offer for each customer based on their current interests.

For example, at emetrics Steve Petitpas from Microsoft shared their analysis that led to the decision to discontinue the Cash incentives program for Bing. Or in Eric Peterson’s whitepaper Dashboards are not a Strategy, the work of The North Face’s Mike Mayfield is described where Mike identified demand for certain products via digital behavioral data and worked with their merchandise buyers to match supply to that demand. Or Freshdirect is using analytics to identify customers’ willingness to pay for different kinds of their 4-minute meals so that they can provide the right price for the market.

Additional analytics skills

More analytical skills are needed than page and ad and conversion optimizers will have employed in our daily work. Good examples would be:

Yay, lots to do and learn.

Analytics is fun again!


Strategic Roadmap for Digital Marketing in 2011: eBook for Marketing Execs

15 authors, 15 articles. Free, yet with priceless insights.

Learn from marketing thought leaders how to engage with customers and create value for stakeholders in a complex digital world. Covers digital channels, marketing techniques, accountability and technology. Truly a must-read resource for every CMO!

One-click Download from (no registration required)

With many thanks to our producer, publisher, and my co-editor, Bob Thompson at and

And, of course, all my gratitude to our 15 authors, bloggers, consultants whose insights into digital marketing strategy make up this ebook.

Together, we set out to puzzle together the silo’d niches of digital marketing into one coherent strategic roadmap. The resulting strategy advice could maybe be summarized as follows (and I hope I am doing justice to all my co-authors):

  1. Derive digital strategy from your overall marketing mission and the role that you want digital to play in it
  2. Pay attention to the special nuances of each digital channel but also fuse the channels together into a cross-channel approach
  3. Do the opportunity with digital marketing justice by making appropriate use of its biggest strength: intelligent interactivity
  4. Consider the additional contribution that digital channels and analytics can have on your online-offline customer sales and marketing programs
  5. Get more of what you want (e.g. revenue, budget, etc.) by investing in marketing accountability and ROI optimization
  6. Derive technology strategy from your overall digital strategy



Scoring the customer experience: By Bob Thompson, CustomerThink

Following the recent series on articles for ROI measurement and optimization, I was struck by Bob Thompson’s advice on measuring the customer experience.

To quote from Bob’s writing:

With the classic “funnel” thinking, only a small fraction of those entering the top of the funnel are likely to become customers. But ALL prospects will form an impression! Why not take the opportunity to turn everyone into an advocate for your business, even if they are not the right fit at this point in time?

Strictly speaking, this isn’t counter to traditional ROI measurement and optimization. After all,ROI does in theory include all future long term effects that an initiative should be credited with.

But in practice, probably few ROI analysis projects ever get as far as to correctly assess the value of non-buyers who however influence future buyers.

So, therefore I find Bob’s recommendation thought provoking to take the perspective of the prospect for a change and score and optimize their experience.


By the way, Bob Thompson, is CEO of CustomerThink, a research and publishing firm focused on customer-centric business management. He is also Founder/Editor-in-Chief of, the community dedicated to customer-centric business. Recently has had many offshoots such as and

Spiders vs. Bars for Maturity Models

Sharp, as always, Jacques Warren commented on my previous post why maturity model people always gravitate to Spider graphs?

Wouldn’t it be easier to read bar charts?

Worth a try!

So, belowe are the three examples from the digital marketing maturity model as bar charts instead of spider diagrams.

Which to prefer, Spider or Bars?

Comparing to the spider charts from the previous post, I’d say Jacques is right on. The Spider charts look more sophisticated and interesting. But the bar charts are much easier to read.

Graph masters

Dress your charts to impress. That may sometimes mean making them look fancy, but usually probably means making them meaningful and easy to interpret.

There is nothing that “sells” analytics like good visuals.

To that point, some people are just so genius that I feel hopelessly behind to their masterminds. Case in point, see for example the following Halloween costume chart by “MB“.

Halloween costume guide

Happy Halloween!

Maturity Model for Digital Marketing Strategy

It makes sense to have a maturity model as a companion to the new digital-marketing strategy framework . (See the thumbnail of the framework below.)


What’s a maturity model?

Maturity models are well established today. Their purpose is to be a roadmap to marketers. You find your personal “You are Here” point on the map. Then you see what next steps you may wish to consider for further growth.

How does this model (below) relate to the framework (above)?

The framework proposed five major components for digital-marketing strategy:

  1. Setting Digital’s mission
  2. Deriving the digital strategy
  3. Deriving the interaction strategy
  4. ROI measurement and improvement
  5. Technology strategy

The job of the maturity model below is to score different levels of maturity with each of these 5 different areas.

Here is the Maturity Model

Click to expand

Maturity model for digital marketing strategy

How can we use this model?

Below are three examples of typical companies that you will find in the market place today.

1: Digital laggards

Typical laggards may look like the following spider chart when scored against the digital strategy maturity model. Usually there is no defined mission, or only a vague or basic definition for the contribution of the digital channel.

And everything goes downhill from there.

Sadly, many CPG, pharma, manufacturing, or book publishing companies find themselves in this boat. The reason is not ignorance at all. It is that these business models make it hardest to prove the contribution that their digital channel has on the business. They typically don’t sell directly, neither online nor offline.

Digital-marketing maturity model example - digital laggards

These companies will need very creative business and ROI measurement strategies to unlock their digital potential.

2: Digital leaders that lack cross-channel integration

Digital marketers can get very sophisticated within their silo without yet taking a look beyond their plates. So many web teams have grown up in isolation from the rest of marketing (or sit outside marketing alltogther) so that they slide into this one-way street.

Digital-marketing maturity model example - digital leader

Part of the reason for the online-only silos has also been that marketers have tried to avoid their IT departments at all cost. That locked them into SaaS only technologies and clicks & cookies only views of their customers.

Again, it wasn’t for ignorance. For many reasons, IT at most companies has been ill equipped to support digital marketing. So marketers that experienced this voted IT off the island and crossed to using SaaS technologies in the past 5-8 years.

3: Digital leaders including a true cross-channel view

While still the tip of the pyramid, you now increasingly enocunter digital marketers that have moved beyond the digital silo. They are typically building data warehouses that bring together customers’ online click behavior with the same customers’ offline transactions and other marketing data.

They prioritized these (not cheap) projects because they realized a true (i.e. cross-channel) view of ROI of digital strategies was necessary in order for company leadership to take the digital channel seriously. They also use this central data mart as the basis for cross-channel marketing integration, e.g. re-marketing, cross-sales, or retention marketing. 

Digital-marketing maturity model example - cross-channel leaders

Even these leaders don’t necessarily apply long term analytics yet. I am thinking of analytical methods such as Kevin Hillstrom’s Multichannel Forensics. He aims to predict longer term migrations of customers across channels or products to help companies decide where they should invest now based on that forecast.


There are many frameworks and maturity models. They each have their merrits, and their blind spots. See a few good ones below:

Take a look around and pick the models that best speak to your own business needs.

Soup to Nuts Marketing Optimization – In the Coming Big League

Exciting times! The consolidation in the marketing technology industry is producing a big league of solutions providers.

Dreaming ahead into the future, what can companies hope to achieve with this new breed of marketing software and services providers?

The end-to-end conversion optimization vision that still seemed far reaching to me back in February, looks much more limited now given the new outlook today.

Disclaimer: The following perspective reflects only my personal dreams and shouldn’t be taken to represent the positions, strategies or opinions of my employer.

Digital Enterprise Marketing++

It isn’t possible to do the coming future justice by calling it next generation analytics, campaign management, or marketing automation. The step up in caliber requires also a step up in language.

Might the following become every day terms in enterprise marketing technology in 2011 and beyond?

Soup to Nuts Marketing Optimization

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Q&A with Eric Siegel on Predictive Analysis using Web Analytics Data

Last Wednesday (March 31st) Eric Siegel presented on 5 Ways of leveraging predictive analysis using web analytics data.

Registrations and attendance were very strong which isn’t surprising because the WAA”s yearly survey had recently shown that predictive analysis is a top question on which web analysts seek to get more education.

You can access the recording of the webcast here.

Meanwhile, Eric was nice and speedy enough to answer all the questions that came in during the webcast. You can access the Q&A on the new Unica blog.

Check this Q&A blog post out even if you don’t have enough time to watch the webcast.

By the way, did you know Unica had a blog? It was recently restarted and is on fire with lots of contributors blogging across the company now.

Thanks much to Eric Siegel for a super insightful webcast and Q&A. If you had any doubts on whether predictive analysis makes sense on web analytics data, then be sure to watch this webcast to open your eyes.

Multichannel Marketing – 2 years later: Digital is at a crossroads now (part 1/3)

In the two years since publishing the Multichannel Metrics book, the face of marketing has changed drastically.

We are entering a critical crossroads in 2010.

By 2013, will we look back and find that this was the year when marketers from online and other marketing teams first realized how similar their goals have become and took steps towards integration across camps?

Or will we look back and find that the camps remained ignorant of each other and instead set in stone silo’d technologies making integration more difficult than ever? 


What do you mean, web and direct marketers’ goals are aligned now?

Marketers have had no choice.

Greatness has been thrust upon them!

Direct marketers

  1. Have seen marketing dollars beginning to shift from offline to online
  2. Finally see clearly that a large portion of interactions with their customers has moved online. For example, according to anecdotal feedback from several older European banks, 25% to 50% of their clients use online banking now. Some financial institutes acquire the majority, if not all, customers online.

Online marketers

  1. Have had to abandon their silo’d, website-centric thinking because their websites are now only one component of their total web presence. Other presences include social media, mobile sites, behaviorally targeted ads and personalized emails.
  2. They may continue to treat the offline as a step child for another couple years. Yet, they are already adopting multi-online-channel marketing practices for the purpose of integrating all these web presences.
  3. The latter has required them to move from their traditional focus on aggregate level metrics and dashboards to looking at data about individuals across website, mobile, social, and advertising. This experience with individual level data will also make it easier for them to integrate their customers’ offline interactions down the road.

As a result, both online and direct marketers are now pursuing multi-channel data integration at the level of individual prospects and customers. Both camps do this for the purposes of

  1. behavioral targeting,
  2. better understanding of marketing ROI.


The technology gap is closing

While all vendors talked the talk for 360 degree views, the reality was different. Web analytics data was far removed from a direct marketers’ access.

  • After all, the data are owned by the web team who couldn’t care less about individual level data at that time.
  • The data are also hosted remotely at SaaS based web analytics vendors that prioritized reporting and good looking charts over granular data. As a result, data feeds (while available) would come with no SLAs. A feed might or might not arrive at the agreed time of night. That made it too unreliable for driving interactive (let alone real time) marketing programs.

Meanwhile, web marketers could integrate analytics based targeting into email marketing only by bridging the gap between several vendors and paying for integration services.

These technology gaps are now increasingly closing.

  • Omniture is positioning its online marketing suite along with integrations with ESP partners through its Genesis program.
  • Unica is positioning both
    • Its eMessage and Interact products for email and web personalization integrated with Unica’s web analytics and campaign management products for enterprise clients
    • Its recently launched Interactive Marketing OnDemand product where SaaS based customers use web analytics, email, and web personalization within a single application and UI.


The crossroads

This alignment of methods, goals, and technology represents our arrival at a crossroads.

(note added on March 12th): Maybe the word alignment is too much said.  But methods, goals, and technology are now more parallel and similar than ever.

But will we leave these crossroads into an integrated future or will we set in stone two silo’d multichannel worlds between online and direct marketing teams?

That is the big question.

In part 2 we will look at direct marketers vs. digital. Then in part 3 we will review where multichannel web marketing stands in 2010.

What's a web analytics STRATEGY vs. TACTIC?

“Hey, in 2010 let’s be strategic with our web analytics. Let’s not get lost in the tactical weeds”

OK, so what’s a web analytics strategy vs. tactic then?

  • The web analytics solution that you use is a tactic. The strategy is in the reports that you run.
  • The reports that you run are a tactic. The strategy is to start with your key performance indicators (KPIs)
  • The KPIs are a tactic. The strategy is to equip, free up, and incentivize your web analytics team so that they will focus on value generating analytics vs. lolligagging or answering to never ending reporting requests
  • The web analytics team and incentives are a tactic. The strategy is to compete on analytics
  • Competing on analytics is a tactic. The strategy is to treat your customers well
  • Treating your customers well is a tactic. The strategy is to increase their lifetime value to your company
  • Your company is a tactic. The strategy is to have a happy, healthy, peaceful 2010

Some people wield the words “strategy vs. tactic” as if they were swinging a sword and being profound. Yet they mean not much more than “left vs. right”.

No matter where you stand, there is always something to your left and always something to your right.

So, … maybe the strategy is to hug both of them, the strategy and the tactics.

Happy holidays

Privacy, Schmivacy!

Other than “How about cookie deletion?” the second biggest question that I have received in the past year when discussing the topic of online-offline integration is the question about privacy.

  • Will it be OK with privacy regulations if I integrate click data from web analytics with customer data in order to improve the relevance of my marketing communications?
  • More importantly, will it be OK with web site visitors’ expectations?

The regulations side is usually a short answer for me. Mind you, the regulations seem rather cumbersome to read. But the bottom-line boils down to:

  • Have a clear privacy policy on the site
  • Make it as easy to opt-out as possible, ideally a single click
  • Extra credit, if in addition to opt-out you allow the individual to set their own preferences of how they’d like to be contacted and on what topics
  • In countries where it is required, work with opt-in

To me, the bigger question seems about site visitors’ expectations.

It may seem we are wearier of being tracked than ever. There is always a big outcry when Facebook et al announce a move towards ad targeting.

But in reality, we are much more public with our lives than ever. especially in our social networks. See this article for instance.

So what is it about this privacy thing that we really want?

The following examples help me.

Privacy in a store

We hate walking into a small store if the sales person is too much in our face and doesn’t let us browse the items on our own. Maybe we fear getting pressured into buying something before we are ready. Heck, we may well be browsing for entertainment and not thinking of buying anything at the moment. And the shop keeper that is in our face makes us feel bad about ourselves.

But we also hate being in a big box retail store and not being able to find someone to answer our questions when we are ready to ask them.

Really, we want the person to be right there — magically — just when we need their help but not before. And we love it if they understand us so well that they can recommend just what we will benefit from buying.

Privacy in a restaurant

We hate when the waiter is too much in our face, especially after we are done with the meal. Maybe we fear pressured in vacating the table for the next guests.

Just as much we hate it when the waiter is nowhere to be found when we need the check or want to order something (else).

The waiter should just — magically — refill the glasses as soon as they are empty. They need to be right there with the desert menu and our check just when we want it.


How does it work in those stores and restaurants that do this well? Is it magic?

No magic.

The perfect shop keeper and waiter are super observant. They put a web analytics tool to shame when it comes to tracking our behavior.

But they aren’t in our face about it.

And they don’t pressure us into buying something or ordering an appetizer along with the expensive main course.

They are at our service.

And yet they still do bring us the best cross-sales offer at the best time.

Marketing so relevant that it feels like a service

I still cringe when I hear that marketing should be so relevant that it feels like a service. At first glance it seems a cheesy thing to say. It seems a utopian dream of techies like me.

But wait.

How about all those educational webinars on the web that I love to attend and learn from?

Guess what! The people doing them (e.g. me, myself) aren’t altruistic at all. Their purpose is purely marketing. They cost a ton of money, by the way. Yet, it is a service and doesn’t feel like marketing at all unless the speaker is too salesy.

There are other examples too:

  • How about book recommendations on Amazon
  • Movie recommendations on Netflix?

They tend to be quite relevant and not at all in your face. Ignore them easily if you want.

In fact, haven’t you come to expect and demand that any product page on a retailer’s web site will contain information on accessories that go with the item?

So, it can be done

These examples prove that marketing, in the ideal cases, can:

  1. feel like a service
  2. be not in your face and not pushy

My take away is that the combination of click and customer data, if used the right way, can absolutely enable service oriented marketing. But if you abuse it for span, you will cause all of us marketers to look bad and to lose out.
(This post is part of a series on the state of multichannel metrics today, one year after the book came out.)