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

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 CustomerThink.com, the community dedicated to customer-centric business. Recently CustomerThink.com has had many offshoots such as DigitalMarketingOne.com and SocialBusinessOne.com

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“.

Happy Halloween!

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

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.

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.

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. 

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.

Summary

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

• Dave Chaffey: Digital Marketing Strategy Planning Tool
• 64clicks: Omnipresent marketing
• Stephane Hamel: Web analytics maturity model
• Gartner (Bill Gassman): Web analytics maturity model
• Many more …

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

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?

Marketing Mix Management (MMM)

Today’s discussion is at the level of point solutions such as search bid management tools (for PPC) and demand side platforms (for display advertising). In coming years, will we see all these combined into a single solution for MMM?

MMM would not only allocate advertising budgets towards marketing mix optimization. It would also automate the execution of these ad strategies, their testing, and the data collection into marketing performance management.

Marketing Performance Management (MPM)

Today’s discussion is at the level of web analytics, benchmarking, landing page and site optimization, social media monitoring, predictive analytics, BI, analytical CRM, social CRM, etc.

In coming years, will we see all these combined into a single MPM environment?

MPM would have to combine the aforementioned point solutions for analytics into one interoperable data environment. Users would want drag & drop flexibility to analyze across silos. Think Minority Report.

The data that flows into MPM would include in-house data marts with sensitive information. That means that we may see the pendulum swinging back to in-house software for things such as web analytics.

Interactive Marketing (IM)

IM is the successor to behavioral targeting and direct marketing. It is based on the accepted notion that marketing is more successful when it is timely and relevant. Therefore, interactions via websites, IVR, email, and any other addressable channel should take into account each user’s past and current behavior to personalize content and marketing offers.

Marketing – Fulfillment Synchronization (MFS)

The dream of automating marketing mix execution requires good synchronization with fulfillment. After all, you wouldn’t want to advertise on product XYZ if it is out of stock. And your ability to set a max PPC bid price for product ABC depends on its true margin, i.e. includes product costs and not just ROAS (ROAS=revenue/ad costs).

Companies such as Amazon have been working on creating ads programmatically for years based on inventory. MFS would take this capability to the enterprise software market.

Marketing Operations Management (MOM)

Already used by the largest marketing operations today, MOM is the successor to spreadsheets, notes on napkins, and the like. It is used e.g. at one famous furniture retailer to orchestrate the development of their catalogues. If any of the other ideas above are to become true, hordes of marketers in the organizations need to work together like a machine. Digital assets need to be created in support of personalized messaging. MOM provides project and workflow management on steroids to facilitate all that.

 …

One level down we may see practical applications that include software and services in support of specific steps in the customer lifecycle. These more confined solutions may help companies start small, prove value, and grow from there.

On-Boarding Concierge

Successful on-boarding is key for turning newly acquired customers into clients with a high lifetime value expectation (e.g. in banking). The automated concierge would connect to marketing performance management and interactive marketing in order to monitor and orchestrate what needs to be done.

Re-Marketing Optimizer

Re-marketing may be the oldest trick in the book. But it is still tricky to predict who needs just a reminder vs. who needs an incentive to come back. The re-marketing optimizer would provide that intelligence based on marketing performance management insights and connect to interactive marketing to get the message out.

Multichannel, Multi-touch Marketing Attribution

Point solutions for marketing attribution online vs. response attribution in direct marketing need to merge into one multichannel platform. Marketers should ask software vendors for more than just attribution reports. They should also ask for advice on which touch points deserve how much of the credit. Ideally, the marketing mix modeling function would also be covered by providing advertisers with a prediction as to what they can expect from placing their next ad dollar in each channel.

…

And the list could go on and on.

…

None of the above can replace good old fashioned, customer service with a smile.

But for companies that are already doing a good job at taking care of their customers and building products that delight, the next step can be to compete on Marketing.

Exciting times should be ahead for that.

For those about to rock & roll with marketing, I salute you.

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 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.

“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

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.

Magic???

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.)

(This post is part of a series on the state of multichannel metrics today, one year after the book came out.)

The previous post paid homage to the original innovators behind the online-to-offline conversion improvement idea, namely the automobile industry. Now, let’s look at a modern adaptation from the B2B, high tech, sector at National Instruments.

National Instrument’s Michelle Rutan and I presented this case together at the eMetrics Marketing Optimization Summit in San Jose this May. By popular demand, the session will be repeated live, online, namely in the WAA”s upcoming webcast on July 21st.

The challenge

Take these stats in:

• The company’s web site has 1 million unique URLs.
• Visitors reach the site through one of 500,000 monthly keywords.

Add to that the fact that there are more than 6,000 part numbers of National Instruments (NI) products. So what we have at hand is a great challenge for managing a long, long tail of web pages, keywords, and products.

In this complex situation, how can the sales and marketing team get insight into what prospects are interested in? Imagine being a sales person and asking your account whether they’d be interested in one of 6,000 products today?

Hey, how about a 200 MhZ Wave form generator for you today? Would you like Fast, Flexible 6.6 GHz RF Instrumentation with that?

Or imagine being a marketing person crafting an email that will be perceived as relevant.

Hey, we got to Wave form generators for the price of one today?

Boy, that seems hard.

The general idea

Much like car buyers, many of NI’s buyers use the web site to do their own product research. So NI said to themselves, why should we ignore the click signals that buyers are sending us through their keyword searches and content views?

As a side note, there is one great advantage for this in B2B that some companies leverage. Namely, buyers need not even be registered for their clicks to be attributed to a specific prospect. Often it suffices to translate the IP address into the company’s domain name to know that somebody from company X has been visiting the site.

“What happens on the web site, stays on the web site”, no more.

You could say that in web marketing 1.0 the web site was a silo by itself. Prospects might do their research but marketers and sales teams would pretty much ignore them until they email or call in.

At NI, the marketing team has been pondering for a long time already how they might turn the data on visitors’ behavior into better customer service.

• Surely, a recent and frequent visitor to the product (not support) section of the site is more likely to be an active prospect.
• Surely, a visitor who is deeply engaged with product pages (again, not tech support pages) is likely to be an active prospect.

But identifying active prospects is only part pf the equation. With a long tail of products the question for sales and marketing remains what these prospects are interested in.

Getting to the essence of a prospect’s interests

Profiling visitors’ interests based on their web behavior turned out to be much easier said than done.

NI experimented with several methods of mapping keywords and web content to the products that the pages relate to. Turns out this isn’t so easy at all. Several methods were tried and eliminated.

• Do each of 1 million URLs really contain the necessary information for mapping them to their content?
• Can you conceive of a way to map that many URLs to their essential contents manually — and keep the mapping up to date?

Not so easy.

Then Michelle Rutan had another totally cool idea of how content and keywords could be mapped out. Applying this new mapping to her web analytics data, she generated a test segment of prospective buyers for a particular product and geo area.

The Results

The test campaign was launched as an email and achieved a whopping 44% open rate and 25% click-through rate!

This is great testament to the fact that recipients perceived the content as relevant.

The data is still so fresh that resulting sales information was not available (not that it would be publicly available anyway).

The million dollar question:How did Michelle map web behavior to prospects’ essential interests?

Since this is entirely Michelle’s idea, it isn’t for me to reveal her innovative approach. But if you are curious, you can hear from her directly by tuning into the upcoming webcast.

Michelle will present from the business perspective. Then I will run through a lab case of how this idea can be turned into reality by integrating web analytics into the data warehouse, BI, or CRM system.

I know, Michelle and I look forward to your questions.