Multichannel Marketing Metrics
with Akin

Tune in to the recent Beyond Web Analytics podcast on the topic of the coming Standards for digital data collection via tags. Listen as the BWA hosts Adam Greco, Rudi Shumpert explore the topic and coming standards with IBM’s Eliot Towb (product management for digital analytics and tag management), and Sri (Viswanath Srikanth) from IBM Standards.

Visit the W3C’s related standards group page to see the list of current members in the effort including the who is who in digital.

Tags: Digital Analytics, Web Analytics // Add Comment »

Tags: Digital Analytics, Direct Marketing, multichannel marketing, Multichannel Marketing Measurement, Smarter Commerce, Web Analytics // Add Comment »

Having served in the digital analytics and marketing industry for the past 12 years, I remember waaaay back in maybe 2006 there were passionate voices in the industry advocating that the page tagging layer should be interchangeable, i.e. standardized, between web analytics solutions vendors.

Customers should have it easier to switch out web analytics solutions. Vendors should be competing on the merits of the insights that they help customers derive, not on the mechanics of data collection.

Back then, those proposals went nowhere since all of us back then at Unica, Coremetrics, Omniture, Webtrends, etc. were busy growing business like crazy and getting acquired.

Standardization is poised to become a reality now

I shouldn’t jinx it by speaking too optimistically but all signs are that we are on a very promising path to standardization of data acquisition via page tags now.

And this will be not just  for web analytics solutions, but more generally for all digital marketing applications.

The goal is to save marketers from needing to learn and program a whole new tag data collection language with every vendor’s solution that they want to try.  The value is that marketers can then be more agile with trying and using new applications since these could all feed off of a common data collection layer.

Who is in the standardization effort?

Today, the standardization effort is being lead by a few dozen member companies including the ‘who-is-who’ in digital.  They are working in the W3C Customer Experience Digital Data Community and making rapid progress towards proposing a standard for data acquisition.

The participants represent:

• Digital marketing and analytics vendors such as Adobe, Criteo, Localytics, Google, Marin Software, Reevoo, and of course IBM
• Tag management pure play vendors such as BrightTag, Ensighten, Tag Man, Tealium
• Web practitioners and managers from multiple businesses who will be among the prime consumers and beneficiaries of this specification
• The Digital Analytics Association is also a participating member

IBM’s “Sri”, Viswanath Srikanth, from the IBM Software Standards team is chairing the group effort.  Sri is planning to be in Nashville at the Smarter Commerce conference to share details from the community’s work.

How will this work?

Aside from the impressive list of participants, the other great news to me is that this is really straight forward from a technical and practical perspective.

You could compare it to the way standardized electrical power plugs and sockets make it possible to plug in any electrical device no matter where or which power company is serving the region. They all rely on there being a standard interface in between them, namely standardized power sockets and plugs.

In digital, data is the fuel that powers marketing and analytics applications. Yet all websites and digital marketing applications have developed their own data language, i.e. JavaScript key-value pairs for things such as page titles, categories, URLs, retail shopping cart details, visitor data, behavior events, etc. etc.

• So one application may expect page category in a variable named “pageCat = ABC” while the next app may expect it to be named “CategoryPage = ABC”.
• Similarly one website may place a shopping cart item into a variable such as cart[] while the next might place it in something like basket[].
• etc

Welcome the uniform JavaScript Object Data Layer

But … if there is a common translation layer in between sites and apps that everybody can rely on … that would solve the problem.

That translation layer will be a uniform JavaScript Object Data Layer, i.e. a set of key-value pairs under pre-agreed key names and definitions. Websites can populate these with their data. All digital marketing and analytics solutions that need access to this data can get it from the standard data layer regardless of the website’s details.

In other words, vendors and websites do not need to understand each other directly anymore, e.g. how a page is designed, or how shopping carts work – since the basic contract would be that the standard JavaScript Object gets populated and all solutions can get data from that layer.

How do you apply the uniform JavaScript Layer to Your site?

When the coming new standard is first established, the plan is for website managers to populate the uniform JavaScript Object Data Layer manually, just like you are used to adding any data collection tag to your site today.

But after doing this just once, all standards compliant third party solutions can plug and play.

When solutions require additional key-value pairs of data beyond those specified in the standard, no problem, those can be deployed through additional tagging.

In the future, once the standard is well on its way the plan is for content management and eCommerce systems to facilitate the uniform JavaScript Layer out of box as much as possible, cutting out even the initial manual effort where possible.

When can you expect to see the benefits of this?

The next milestones in the W3C Standards discussion group are for the data layer spec to be readied in May/June 2013 and finalized and published by July/August 2013.

From there, it is only a matter of time before the member organizations adopt the standard into their product road maps.

I have no doubt that the tag management solutions and major digital marketing suite vendors will be first to race and implement the standards. Once that has happened, point solutions will follow.

How can you contribute and influence?

Simply go to the W3C’s web page for the Customer Experience Digital Data Community Group and follow the links on information about how to join.

Why are vendors driving the standardization? Why now?

What is it you might wonder that is driving vendors such as IBM to invest in this standards effort now given that for so many years most vendors weren’t prioritizing standardization at all.

The first major change has been the advent of tag management solutions. With those available widely, no vendor can hope to lock in their customers by making it cumbersome to retag.

Secondly, many of the participating vendors offer a wide and ever growing portfolio of solutions. We need to make it easy for our customers to plug and play with our native solutions plus with point solutions of their choice.

This is a core strategy that customers should expect from their vendors. At least that is why IBM is in it.

After all,  … could you imagine undoing the standardization of electrical power plugs?

Learn more at the upcoming IBM customer conferences

To learn more, join IBM customers and prospective customers in Nashville (May 21-23) and Monaco (June 18-20). Sri and our IBM colleague Eliot Towb are presenting on the topic and available for discussion and your feedback.

Tags: Digital Analytics, Uncategorized, Web Analytics // 2 Comments »

The movie Moneyball isn’t really about baseball. It’s not even about statistics. It’s about the way data can be used to challenge conventional wisdom, and its something those of us in the field of marketing metrics have known for a long time. And yet, too many businesses are missing out—for example they know that there’s a lot of buzz around big data, but instead of seizing the opportunity they ignore it.

That is to say almost all use data for creating nice dashboards by now, i.e. small data.

But many aren’t yet using the underlying big data and analytics to make the transition from one-size-fits-all marketing to behavior-based, personalized marketing programs. That is despite the fact that both marketers and customers stand to gain when interactions are more relevant, helpful, and real-time.

Why is it that many marketers aren’t yet taking advantage of big data analytics, especially in digital channels that are a natural fit, such as the web, mobile and social media? An answer to this question (and many more) is to be found in the results of the 2013 Big Data for Marketing survey from Trip Kucera, at the Aberdeen Group. Here’s what they found:

1. There’s too much information in too many places: 35% of organizations say that integrating multiple data sources is a challenge.
2. They don’t understand the benefits: 30% are having a hard time understanding how marketing analytics could be used in their companies.
3. They lack the talent: 30% are having problems finding the right people with the right kind of knowledge of marketing analytics.

So what’s keeping your organization from leveraging big data in your marketing?  I’ll be taking part in a webcast featuring more results from the survey, along with Trip Kucera and Graeme Noseworthy, Big Data for Marketing, Media & Entertainment. Register for the webcast to join us and find out how the best in class in the survey incorporate data analytics into marketing programs—and how you can, too.

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What deployment model should marketers prefer for their digital analytics and other marketing software technology solutions that support their efforts? Should they pick:

• Cloud based solutions i.e. Software as a Service (SaaS)?
• Ground based solutions for on-premises deployment?
• or hybrid models that combine the two options?,

Of course, the answer is “it depends”.

So the guest blog post on  the Smarter Commerce blog has my two most important pieces of advice on how to explore SaaS vs. On Premises when you choose between them for your company. This was posted on the occasion of the recent IBM Marketing Center product release. That one is a cloud based product which prompted this question on deployment models.

Link to the post

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IBM today announced the new IBM Marketing Center — an all-in-one solution that combines digital analytics data with real-time marketing execution. Marketing Center provides A/B testing, website personalization, email marketing, and more.

For more information and to download the data sheet see the product’s web page at ibm.com/marketing-solutions.

What I find most exciting here is that digital analytics and marketing are glued together in a single application: i.e. there is no room for a chasm between analytics and action anymore!

Tags: Customer Centricity, Digital Analytics, Direct Marketing, Multichannel marketing metrics, Smarter Commerce, targeting, Web Analytics // Comments Off

This video is about – what I think is – the most interesting idea in IBM’s Smarter Commerce vision. Namely, synergies that companies can reap from sharing customer-centric insights between their Supply Chain, Marketing, Selling, and Services teams.

Compared to the previous post, I raised it up a notch to be more specific about the tried & true vs. more novel tactics that are used in each corner of the business. Unlike the previous video though no muppets are to be found in this one.

Tags: Smarter Commerce // Comments Off

They say, if you can’t explain something in a simple and clear way, maybe you don’t understand what you are talking about. So … I was asking myself … could I explain IBM’s Smarter Commerce portfolio of solutions (which include Unica, Coremetrics, Tealeaf, DemandTec, Sterling, iLog, Websphere, etc. products) in such simple terms that even my five year old would understand.

I think I can, and here it is:

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Continuing the question what digital analytics are vs. web analytics, here are 10 things that hopefully don’t describe you or your company.

1. You think improving business success with mobile and social channels is not part of the digital/web analyst’s job
2. You think visitors are trying to accomplish the same thing with your site regardless of whether they are visiting by using their PC, their tablet, or their Smartphone
3. You operate without benchmarks and competitive intelligence that would tell you where you are vs. your peers so you know where you could be
4. You operate without voice of customer surveys that would show why customers did what they did
5. You think your job is just to measure, test, and improve content and ad spend using data … when you could also be thinking about decisions and actions that digital data can drive (e.g. by identifying changes in demand, willingness to pay, or individual customer intent)
6. You think the value with analytics is just in KPIs, reports and tables … not in the underlying data warehouse of customer insight
7. You think you are just one silo’d channel that your company is running … when digital is increasingly intertwined with every next move customers are thinking about taking with your company’s offerings
8. You think visitors’ behavior in one session says much of anything … when today the number of sessions between transactions are becoming more frequent (6.8x on average) and shorter and more surgical. The real beef is in identifying what experiences increase customers’ future looking lifetime value
9. You think of your website as your only digital home and see the rest of the Internet as incoming channels of traffic. Yet, digital marketers increasingly orchestrate off-site interactions as continuations of previous on-site experiences, e.g. via targeted advertising and email that is not only targeted but dynamic (e.g. displays coupons or recommendations that are current at time of opening)
10. You think customers’ interactions with your digital channels are unrelated to the customer context, i.e. where they are (e.g. using their Smartphone in your store), who they are (e.g. at risk of leaving), and your past history  of interactions (e.g. an email or call center interaction during which customer was pitched a particular cross-sell product)

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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 Macys.com 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:

• Kevin Hillstrom’s forensics method for forecasting the long term contribution of any channel or product or “thing”
• Jim Novo’s method for forecasting the level of engagement of an individual in order to optimize e.g. who receives a retargeting incentive vs. who doesn’t
• Gary Angel’s data mining based customer segmentation method to identify different groups of customers that pose different opportunities
• Predictive analytics skills for marketers to score, value, rank, profile interests / risks

Yay, lots to do and learn.

Analytics is fun again!

Tags: Business Metrics, Customer Centricity, Digital Analytics, Multichannel marketing metrics, Web Analytics // 4 Comments »