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 CustomerThink.com (no registration required)

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

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

• Digital channels
  • Edward Boyd
  • Eric Enge
  • Alan See
  • Kim Dushinski
  • Jim Sterne
• Digital marketing techniques
  • Ardath Albee
  • Robert Lesser
  • Chris Ryan
  • Steve Woods
  • Naras Eechambadi
• Digital marketing optimization
  • Jim Lenskold
  • Laura Patterson
  • Tom Manning
  • David Raab
• and myself for the digital strategy framework

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

The following is cross-posted from the original at the IBM Unica blog.

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Exciting news for our IBM Unica NetInsight OnDemand customers and really all marketers: IBM today announced the new IBM Digital Marketing Optimization Suite which accomplishes three great “coming-togethers”. Namely, the following:

1. Combines the Best of IBM Coremetrics and IBM Unica NetInsight OnDemand

Since IBM’s acquisition of Coremetrics and Unica our web analytics teams have been merged together like a deck of cards to make the best use of the combined development and best practices expertise. Our combined team now takes care of both IBM’s on demand and on-premises offerings and customers for web analytics.

And as previous competitors, it was much to my surprise that we had been very like minded in the decade leading up to this merger. Both Unica and Coremetrics had been working in parallel to make sure web analytics delivered not just reports for optimization but also provided individual customer insights for refining relevancy of marketing messages.

2. Fuses together: Customer Profiles, Analytics, and Digital Marketing Execution

The next great coming together I see for our customers in the IBM Coremetrics Digital Marketing Optimization Suite is the tight integration between LIVE Profiles, Web Analytics, and the IBM Coremetrics Digital Marketing Applications such as IBM Coremetrics LIVEmail and IBM Coremetrics Intelligent Offer. This tight integration is the secret sauce that enables our users to execute more relevant digital marketing campaigns driven by analytics. The IBM Coremetrics suite inherits this product design from the Coremetrics side where this combo had been available for years while other vendors were merely talking about it in Powerpoint presentations.

3. Adds a More Flexible and Open Data Architecture for Multichannel Analytics

Now, like D’Artagnan teaming up with the three musketeers, the new IBM Coremetrics Suite adds increased flexibility and openness to the trio of LIVE Profiles, analytics, and digital marketing applications. This is being achieved thanks to experience and technology assets coming from Unica NetInsight OnDemand. And it is a true 1+1 = 3 situation. Not only can marketers extend their analytical lens by combining online and offline insights (using the new IBM Coremetrics Multichannel Analytics add-on), but now they can also target digital marketing execution programs, e.g. through IBM Coremetrics LIVEmail, using the cross-channel picture of an individual’s interests.

The Result: Two Great Growth Paths for our Customers

All marketers have web metrics available to them. Competing on analytics requires us to be cleverer with our use of analytics than the next marketer.

Technology needs to be our “power arm” that helps get things done quickly that would be very tedious, expensive, and time consuming otherwise. The new IBM Coremetrics Digital Marketing Optimization Suite provides IBM customers with a “power arm” that helps them go beyond commodity web metrics and move towards digital analytics where discovering new opportunities with segments or individual prospects and customers means more strategic opportunities.

Our customers also have another growth path to go from analytics to digital marketing execution, and from there to integrations with their enterprise (e.g. to their Netezza data warehouse or their IBM Unica Enterprise Marketing Management system), and with the rest of their digital marketing eco-system, e.g. through the eco-systems of IBM Coremetrics LIVEmail (i.e. Email service providers), and IBM Coremetrics AdTarget (i.e. display ad networks).

Now the ball is in your court. How are you going to put all these multichannel analytics and digital marketing opportunities into the race for beating out your competition?

For Our Customers …

Existing NetInsight OnDemand and Coremetrics customers, please keep your eyes peeled for further information by email. Please register for the upcoming customer-only launch webinars. There is no requirement to move to the combined solution immediately. IBM plans on continuing support of the existing Unica NetInsight OnDemand and Coremetrics versions into the future, accompanied by the same industry leading service and support you have come to expect. IBM believes there are compelling components in the combined release that are meaningful and important to your business. In the launch webinars, you will learn about all the great business benefits that our Unica NetInsight OnDemand customers that upgrade will have available. For example, all customers can use their current and new release in parallel during their upgrade process.

For More Information …

Please keep an eye on Unica.com and Coremetrics.com as we will progressively publish more details in the next 10 days of about the new capabilities that our customers can expect. For now, see:

• The press release
• Summary of the IBM Coremetrics Digital Marketing Optimization Suite

Earlier on this blog I referenced an article by Steve Woods  from Eloqua on RPM, Revenue Performance Management. RPM is a relatively new term in the area of demand marketing optimization. Will it stick? As I was writing earlier, there seem to be so many terms already that describe B2B marketing automation. Why another one?

Lauren Carlson wrote a post on that topic is a good read.

So will it stick?

I like of course the idea of scientific, analytics driven, revenue optimization.

But I fear that the term is at risk because it is so broad.

Not marketing optimization

not customer optimization

but total revenue optimization.

So everybody is responsible for RPM, and if everybody is responsible the danger is that nobody takes responsibility.

When talking about retailers’ savings / discount cards, the first thing the analytics industry used to point out was the benefit for customer identification. The card helped tie transactions to known customers or households and facilitated the range of well known customer analytics such as: Market basket analysis across transactions Shopping preferences segmented by any demographic information that was supplied when signing up for the card Loyalty analysis in terms of RFM and latency Response analysis to preceding marketing contacts Marketing targeting analysis based on past purchases

And so Wikipedia still says: “The store — one might expect — uses aggregate data internally (and sometimes externally) as part of its marketing research. These cards can be used to determine, for example, a given customer’s favorite brand of beer, or whether she is a vegetarian.”

So we should add a point #6 to the list above, i.e. turn the customer data into a revenue generating product that the store can sell to others.

But why a savings card when credit cards help identify you anyway?

Do you recall the last time you paid cash for the weekly basket at the supermarket? Or for any clothing item or really any item above $20 at a retailer?

So, given that the use of credit cards is pervasive and the card reveals name and credit card ID of shoppers, what is the point of needing a loyalty card anymore? (Never mind whether it is an actual plastic card or a virtual card on your Smartphone that is scanned into the register).

Doesn’t the credit card identify you sufficiently anyway?

Granted, there is a law against reverse credit card append, i.e. matching your credit card number against a database with addresses and contact information. But using just the name from your card + your zip code (that you sometimes get asked at the cash register) retailers can match your data against 3d party databases to satisfactory degrees without violating the reverse append rules (see e.g.  Address Capture).

The point needs to be marketing (while analytics are only a supporting act)

The difference that remains to credit cards is that savings cards can establish permission to market. This may include:

1. Permission to contact you, if you opt-in
2. Permission to sell your data, if you opt-in

So the point is about being able to establish marketers’ ability to contact the individual with marketing messages. Then the analytics and the additional demographic data come in with the aim of making those marketing message more relevant.

Retailers can use the data directly or sell it to other markters that have essentially the same goals.

While frequent buyer cards (e.g. airline miles) enlist the customer in a rewards scheme and attitude, savings cards are just a key to getting the advertised discount in a store. So that is another reason why the burden is on marketers to use the savings card “relationship” for something useful.

How well is it working?

If the point is better marketing then how well is it being done today by marketers?

Do you feel you are getting relevant information in your inbox or mail box by the merchants where you are using savings cards?

The previous post had concrete recommendations for proving the ROI of behavioral targeting. Several smart reader comments brought together a pretty clear picture.

However, when I was meeting with a number of experienced online bankers in Europe recently, the question that I received was more difficult to answer than just proving the ROI of targeting.

Namely, the question was whether one can expect greater ROI from testing or targeting? Whichever promises greater ROI, shouldn’t that be where you may want to start?

Thinking about it in terms of anecdotal results

Testing tends to be much more black and white in outcomes when you first begin to optimize a website. After all, no perfect website falls from the sky. At first you can get a big impact from making changes to messaging, calls-to-acton, layout, etc.

There are case studies, e.g. from Unica web analytics customers, where website conversions were improved by as much as 1900% over time with the help of continuous testing, measurement, and improvement.

Now, I have seen many great case studies of behavioral targeting online. But I haven’t seen one where a better targeted message (via email or website or ad network) drove a 1900% increase in conversions.

Should you count on a 1900% improvement from your testing efforts?

Most web marketers when they hear these great testing case studies can be very disappointed when their own testing efforts only yield a percentage point or two in improvment. That happens a lot too.

And depending on the size of your web business, a 1 percent improvement from testing can still be a highly profitable outcome.

But, it goes to show that a mere comparison of anecdotal results that other people achieved from testing vs. targeting is not going to be enough to help you decide whether you should start with one or the other.

A better way to think about it

Testing is a key competency for targeting. As the previous post suggested, you would probably have a hard time proving the value of targeting if your organization didn’t know how to do (hold-out) testing.

Likewise, reporting is a key competency for testing. If you didn’t know how to measure and report on key metrics, how could you prove which test candidate truly drove better results?

Growth path

That is why it does make sense to follow a maturity model where the organization grows from reporting to site optimization (with testing) and then targeting similar to the diagram below from one of Unica’s whitepapers.

Just don’t get stuck in the stage of reporting and testing but make sure you continue to climb up the maturity curve when the business value that you are generating in Stage 2 begins to level off.

Behavioral analysis and targeting (for interactive marketing) has helped companies who do it well push up business value beyond the plateau that they reached from testing alone (see previous post).

It is often said that building (or proving) the business case for (site-side) behavioral targeting has been a lot harder than justifying an investment in more straightforward site optimization techniques such as A/B testing.

As a result, you can read independent industry analyst reports observing that some applications that can do testing and targeting (hint, hint) are a lot more frequently used for just testing rather than targeting today.

You can even hear from some of the best known and experienced consultants in the online optimization industry that they don’t feel convinced by the business case for (site-side) behavioral targeting because they feel it is less clear cut vs. testing.

This doesn’t need to stay this way.

The problem is that we have been asking the wrong question.

The question should not be “proving the business case for behavioral targeting”. But we need to make the question specific to the use case for targeting that the marketer wishes to pursue / prioritize.

That is to say, we need to seek the business case for using behavioral targeting technology to do one or multiple of the following things:

1. Improve conversion rates for acquiring new clients
2. Improve on-boarding of customers
3. Improve cross- / up-sell
4. Improve customer service case resolution times
5. Improve customer retention
6. Improve win-back of former customers
7. Improve satisfaction with the site’s usability, i.e. ease of finding what visitors are looking for.

When restated in this fashion the business case becomes much clearer. For example, if behavioral targeting allows you to improve customer retention by 1%, then you can calculate what that is worth to your business.

How do you prove it then?

How do you prove that behavioral targeting has been able to help you improve XYZ by some percentage though?

Simple

You do it through hold-out testing. You simply compare what happens to the hold-out group vs. the test group who are exposed to behaviorally targeted recommendations for the use case.

If you think that hold-out testing is complicated … then you have no business even thinking about behavioral targeting. Your organization needs to first learn how to do A/B testing.

Why has this been so hard for online marketing optimizers then?

My personal guess is because:

1. Despite the wonderful, 2001 emetrics paper by Jim Sterne and Matt Cutler, web analysts are – still – not thinking about the customer life cycle enough (i.e. acquire, convert, on-board, grow lifetime value, retain, etc.). Instead, analysts may be too busy optimizing ads and pages. We aren’t measuring customers but ads, pages, transactions. And frankly, web analytics tools were originally created for the latter and most do a horrible job when it comes to measuring customers.
2. We seem to have a blind spot for hold-out groups somehow. As a symptom, Jim Novo and Kevin Hillstrom have been frequently reminding their readers of this neglect. Strange though. After all, hold-out testing is just another name for A/B testing, which we supposedly master so well online.

Go figure

You might be squandering a huge opportunity if you aren’t using web analytics as a rich source of behavioral insights on individual prospects and customers.

Read the full article published on the brilliant new online-behavior site. There you’ll also see uses of Venn diagrams for behavioral analytics that are more serious than the recent fun with the nerd vs. geeks Venn diagram post.

Kudos to Daniel Waisberg for launching online-behavior.com!

The team at Online Marketing with RSS Ray kindly invited me to present on BrightTALK yesterday on five ways to increase returns from SEM.

This was a welcome opportunity for me to detail my recommendations for how to optimize search engine marketing from end-to-end rather than focusing only on search bid management and SEO.

If you are new to online or search marketing, you will hopefully find this a useful intro to help you plan your optimization efforts. If you are already experienced in online marketing, especially SEM, then the only useful piece for you in this presentation will be a reminder that SEM optimization requires you to take a complete view.

Otherwise, the weakest link in the chain will break your ROI.

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.

In part 1 of this series I summarized the crossroads at which digital marketing has arrived in 2010. Then part 2 explored the surprising advances that turned database marketing into a digital marketing discipline.

Now it is time to look at online marketers.

Back in 2006, my colleagues and I at Unica were still joking about our web analytics competitors’ understanding of multichannel marketing. Back then it seemed much like a scene in the movie Blues Brothers where they would go into a bar to be told by the bar owner that he was interested in all kinds of music:

 ”Country and Western”

Similarly web marketing back then was multichannel only in a sense similar to:

“Google and Yahoo”.

The old web marketing

In the growth years of Internet usage, web marketers’ focus was centered on their own website and biased towards acquiring visits to the website through advertising.

Rocket science algorithms would optimize advertising spend automatically, e.g. with automated search bid management. Rocket science testing solutions would generate and evaluate thousands of multivariate versions of the same web page to test which one is best at persuading visitors.

But any thought of focusing on the customer was deprioritized.

For example, I recently called my iPhone carrier to say that I was thinking about cancelling the service since reception at my home was unusable. Yet, when I logged into my online account afterwards the website made no attempt to retain me or win me back.

Instead, it was still busy cross-selling me stuff.

Web marketing in 2010: Focus on individual level data for targeting and accurate ROI calculations

It wasn’t due to learning from more tenured marketing colleagues that web marketers changed. After all, in 2010 the web vs. other marketing teams still remain frustratingly silo’d.

But the addition of new online channels has thrust greatness on the online marketer:

Mobile

Mobile is an inherently personal device. So, web marketers aren’t just treating it as a second website but looking into opportunities for more personalized dialog.

For example, San Francisco based GoodGuide’s iPhone application allows users to scan barcodes in the store to get information on a product’s environmental and social acceptability, as well as healthiness. But users can also set lists of favored and “avoid these” products in their GoodGuide account on the fixed Internet website. When you login to your account from the iPhone your favoreds and avoids become available to you.

It is hard to think of a more crunchy-granola (i.e. socially responsible) business than GoodGuide’s. And yet they have integrated individual level data across channels!

Not as an evil scheme, but as a service to their customers! And with opt-in, of course.

That is very promising!

Behavioral Advertising and Email

While ads and email were mass marketing channels, they are now increasingly becoming an extension of a company’s website.

• The ads that you see when visiting e.g. a newspaper’s site can be targeted to you based on your prior behavior on the advertiser’s website. Many ad networks exist that, for example, help re-market to individuals based on products they abandoned or segments for which they were profiled.
• The emails that you receive can show personalized content and promotional offers (e.g. coupons) that were dynamically selected for you based on your click behavior on the website. For example, one Unica client in Europe is sending more than 1 million unique email variations per month.

Advertisers

It is most unexpected, but another push to go from the aggregate to the individual level comes from advertisers.

Why?

As more marketing funds are shifting online, accountability is king. Media buyers want to take credit for influencing individuals that were exposed to ads even if they didn’t click on them. That requires integrating web and ad serving analytics at the level of individual ad viewers and website visitors.

Several analytics vendors, including Unica, make that possible now.

Social Media

Finally, social media pushed web marketers over the edge in their appreciation for multichannel integration with an eye towards individual level interactions.

• Marketers are keen to learn which customers have interacted with their Facebook application even if there wasn’t a direct click-through to the website.
• The Facebook API provides information on an individual’s social graph, i.e. their connection to other Facebook users.
• Websites equipped with Facebook Connect can draw on Facebook authentication outside the Facebook.com domain. That means they can also draw on other Facebook API information in the visiting individual and include that in their analytics and behavioral targeting.
• Advertising networks have become available that target ads to individuals based on their social graph, i.e. assuming that you are more likely to care about XYZ if your direct friend connections purchased XYZ.
• Social CRM has become a buzzword and refers to various online interactions with individual customers. For example web marketers are keen to see that disgruntled Twitterers receive a direct response to turn them around. Meanwhile fans should get encouraged to keep spreading the word.

There is still a missing link for integrating CRM with Social CRM in terms of mapping individuals’ identities. However, vendors are already working on closing that gap.

• Social media monitoring tools such as Radian6 list together each individual’s blog vs. Twitter vs. Facebook identities if they can detect them.
• Vendors such as RapLeaf have begun offering social data append services for CRM databases.

Summary

1. Bottom-line, the web marketing world is in the midst of an onsite-offsite integration era.
2. That has required web marketers to move beyond aggregate level data and think about data at the level of individuals.
3. With that, they now share with direct marketers an appetite for individual level click data for the purposes of analyzing and behavioral targeting.
4. This happened at a time when technology has become increasingly integrated between analytics, email marketing, and behavioral targeting.
5. Online-offline integration is not main-stream yet. But never before have web and direct marketers been so parallel in their multichannel goals and thinking.

I am excited for 2010.