Seattle Marketing Analytics MeetUp WrapUp!

Daniel Kissin presenting
Seattle Marketing Analytics MeetUp

Last night, eSage Group sponsored its 4th Seattle Marketing Analytics Group MeetUp. This month’s presenter was Daniel Kissin, Sr. Analytics Manager at Expedia. The topic was:

How to scientifically measure impact of TV advertisements on other channels, like websites, SEM and Online ads (or so-called ‘halo’ effect).

Definitely a HOT topic for marketing these days!!

It was a great turn out with lots of good dialog around marketing analytics. Also, it was a fun learning environment with good food and beer!

Next month, November 19th, Tableau Software is going to be presenting on data visualization. Make sure to join the MeetUp to register and get updates. It is free!!!

Also, we are starting a Marketing Analytics MeetUp in LA! It is on November 5th. Check it out if you live down there!!

Beer and Food almost make marketing analytics fun!!
Beer and Food almost make marketing analytics fun!!

Repost: Breaking Down the Silos

Analytics 2.0I am reposting this because I have heard during several discussion over the past few days, how organizational silos are difficult to break down – harder than integrating the data.  Thoughts?

Harvard Business Review recently published the article “Advertising Analytics 2.0” in which it discusses the unprecedented amount of data available to help marketers manage their marketing mix in today’s multi-channel environment including both on and off-line. While there is vast opportunity, so is the challenge to sift through various data sources to tune down the “noise” and find actionable insights. Those that can effectively capture these insights have shown improvements in marketing performance of at least 10% to 30%.

The article states that companies must implement new analytic strategies to harness the power of the deluge of data. They point to 3 necessary activities – Attribution, Optimization, and Allocation. Attribution is the process of qualifying the contribution of each marketing activity. Optimization is the use of predictive analytics to run various scenarios. Allocation is then the redistribution of marketing resources in real-time.

Let’s first look at Attribution. The key to this step is to collect data from a wide variety of sources across your organization including sales, customer service, distribution, and finance; publicly available data like weather, traffic, unemployment rates and consumer confidence; and of course, the data from the various marketing tactics. By layering this information on top of each other in non-structured data stores, such as Hadoop, analysis can be done to look for correlations and causal effect. Getting your data out of the silos for analysis will allow you derive more robust insights.

Look for our next post on Thursday discussing Optimization and Allocation. In the meantime, check out our advice  on getting started with your analytics data integration project.

For the full Harvard Business Review article text, click here.

REGISTER NOW! September 12th Cross-Channel Engagement Panel in LA

Register

Use the Promo Code ESAGEVIP to save 35%!

Today as marketers, we are faced with the challenge of allocating marketing spend across more channels than ever before – social, web, TV, print, mobile, digital advertising, email, etc.
  • How do we effectively evaluate the relevancy of a channel to our target customer?
  • How do we measure what channels will give us the biggest bang for our buck?
  • How can you influence the customer journey both on and off-line?
  • How do you attribute sales?
On September 12th, enjoy an evening of learning and lively discussion with industry experts including:

Doug BaraschUniversal Music Group
Sr. Director of Digital Marketing and Strategy

Joshua ColeUniversal Studios
VP of Marketing and e-Commerce

Sarah JohnsonNestle USA
Manager of Multi-Brand Scale Marketing

Moderator will be Duane BedardeSage Group
Founder & President

             
Date: September 12, 2013
Time: 6:30pm-9:30pm
Where: CAP Theatre map
13752 Ventura Blvd
Sherman Oaks, CA 91423
Cost: $35 for Members
$45 for Non-Members
$50 at Door
Cost includes entrance to event, light appetizers,
and beverages
Register now
Use the Promo Code ESAGEVIP to save 35%!
       

Cross Channel Customer Engagement Panel – Sept 12th

CCCE Banner

ama los angeles &
esage group

presents

Cross Channel Customer Engagement

On September 12, 2013, AMA Los Angeles and eSage Group presents the first in a series of panels on Cross Channel Customer Engagement. Enjoy an evening of learning and lively discussion from industry experts including:

Today as marketers, we are faced with the challenge of allocating marketing spend across more channels than ever before – social, web, TV, print, mobile, digital advertising, email, etc.

  • How do we effectively evaluate the relevancy of a channel to our target customer?
  • How do we measure what channels will give us the biggest bang for our buck?
  • How can you influence the customer journey both on and off-line?
  • How do you attribute sales?
Register Now!
Transform Your Thinking
Date: September 12, 2013
Time: 6:30pm-9:30pm
Where: CAP Theatre 13752 Ventura Blvd Sherman Oaks, CA 91423
Cost: $35 for Members
$45 for Non-Members
$50 at Door
Cost includes entrance to event, light appetizers, and beverages

Register Now

Insights into Big Data and Marketing

Recently, I came across an article by Michael Brenner, VP of Marketing and Content Strategy for SAquestionP and Forbes contributing author. He highlights that to derive value from Big Data, make sure that you start with a set up well thought out questions. He also refers to some tips that eSage Group’s own Dean Bedard wrote in a prior Information Management article about the same subject.

Check out Michael’s article here: http://bit.ly/13Iapji

Got Data? Big Data Panel in LA a success!

I can’t believe it has been two weeks since the AMA Los Angeles and eSage Group sponsored Big Data panel in LA. It was a full house at BlankSpaces in Downtown LA. The 3 panelists where Raj Babu from Universal Music Group, Christopher Bridges from ValueClick, and Brian Kao from AEG. eSage Group’s Duane Bedard moderated. There was lots on great insights from the panelists. I will be posting more edited clips, but for now, here are a few pictures and a video clip!

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Definitions for “Big Data” – A Starting Point

Big Data

Written by Rob Lawrence, eSage Group’s Strategic Relationship Manager

Will someone please tell us all, once and for all, just what in tarnation is Big Data? What is it? Where is it? Who’s doing what with it? And why are they doing that? In one blog article I can maybe just scratch the surface of those questions. I might even provide some level of understanding for those curious marketers, bewildered and attempting to make heads or tails of the concept of Big Data. I could certainly dive deeper than even that because I’ve spent some time with this, and done homework, and lived Big Data. But this is a blog article, not a dissertation, so I’ll keep it at a 10,000 foot view of the ever elusive, yet intriguing, Big Data!

If you are one of the rare data scientists that have graduated recently from one of few schools offering Big Data degrees, which makes you an expert in this field, please feel free to stop reading here, or continue on to better understand what the rest of us are, well, trying to grasp when it comes to Big Data. For the rest of us, here is my take on the whole Big Data craze:

Big Data is simply all the data available. That means, in realistic terms, all of the data one can gather about a subject from all the places data resides: data sitting in some long forgotten enterprise software program in the basement of a large corporation, data from social media websites, website traffic data (click-through’s and pathing and such), text from blogs, even data from a sensor on a rocket ship or bridge in Brooklyn (not sure if they’re using sensor data on the Brooklyn Bridge, but they could be). Sources of data are vast, and growing. It’s cheaper to store data than ever before, and we now have the computing capability to sift through it, so now there is lots more data being collected, “Big” amounts of Data are being stored and analyzed. There is a lot you can do with all this Big Data, but this is where it gets dicey. You can collect all kinds of data with one subject, question or problem in mind, but end up realizing (through analysis) more important information about a totally different subject, question or problem. That’s why Big Data is so confusing to lots of folks just getting their hands dirty with it, and apparently also why it is so valuable to Marketers, Engineers, CEO’s, The FBI, Data Geeks, and anyone else interested in edging out the competition. Let’s explore some basics:

Wikipedia says: “Big data usually includes data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process the data within a tolerable elapsed time. Big data sizes are a constantly moving target, as of 2012 ranging from a few dozen terabytes to many petabytes of data in a single data set. With this difficulty, new platforms of “big data” tools are being developed to handle various aspects of large quantities of data.”

The Big Data Institute says: “Big Data is a term applied to voluminous data objects that are variety in nature – structured, unstructured or a semi-structured, including sources internal or external to an organization, and generated at a high degree of velocity with an uncertainty pattern, that does not fit neatly into traditional, structured, relational data stores and requires strong sophisticated information ecosystem with high performance computing platform and analytical capabilities to capture, process, transform, discover and derive business insights and value within a reasonable elapsed time.”

So, we’ve only scratched the surface of truly understanding what Big Data is here in this blog, and really the multitude of possibilities Big Data represents has only begun to unfold to those of us using it to better understand whatever it is we’re collecting data about. I hope at a minimum by reading this you have gained a better understanding of what “Big Data” is, but moreover, a curiosity to learn more and perhaps even apply it to something you are working on. These are exciting times whether you are using data for marketing or designing a new rocket ship to explore Mars. Big things are coming, and it’s all due to Big Data!

Here are some great articles I’ve recently enjoyed regarding Big Data: