About

I'm a partner in the advanced analytics group at Bain & Company, the global management consulting firm. My primary focus is on marketing analytics (bio). I've been writing here (views my own) about marketing, technology, e-business, and analytics since 2003 (blog name explained).

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29 posts categorized "Speaking & Writing"

September 11, 2015

@AMABoston #Marketing #Attribution 9/17 Panel Discussion Guide - Suggestions Welcome!

On September 17, I'm moderating a panel on marketing attribution analysis at a meeting of the American Marketing Association's Boston Chapter.

Here are some questions we've put together to guide the discussion.  What's on your mind?

  1. Let’s start with a plain English question: How do you decide where to spend your marketing dollars?

  2. What assumptions do you make about the relative effectiveness and efficiency of different options?

  3. What are these assumptions based on?

  4. So, for me, attribution is a fancy word for giving different marketing investment options -- channels, partners within those channels, creative alternatives -- proper, or at least more proper credit for their impact on a metric of interest, like a lead or a sale.  How would you define it, or improve on this?

  5. Earlier you told us about how you do it today, but I’m also interested in your attribution journey.  Where was the organization’s level of attribution sophistication when you got into your latest role?

  6. What attribution adjustments did you make first, and next?

  7. What was the logic for starting there? How much was it the potential value -- the magnitude of the spend, for example -- and how much was it about feasibility - you could reasonably expect to get the data?

  8. How much of the adjustment was based on “top down” statistical modeling of overall spend and impression data, and how much of it was bottom up based on user-level proxies like cookie data?

  9. How long did it take to get up and to an interesting insight you could put to work?

  10. What worked, and didn’t?

  11. What surprised you?

  12. How did you balance building the capability and getting results?

  13. What kind of results have you gotten so far?

  14. What’s next on your roadmap?

  15. How far do you think you can push attribution analysis before you hit diminishing or negative ROI?

  16. What’s the limiter? Is it data quality? Integration challenges like tracking a user across channels? Is it your ability to put insights to work?

  17. Let’s take each of those:

    1. We hear a lot about how cookies are dead, and then the death of the cookie has been greatly exaggerated -- how far can you trust cookie based data for attribution purposes?

    2. Now that the big platforms -- Facebook, Google -- can track us everywhere, and use that to do cross-channel advertising programs, do you try to beat them, or join them? If you try to beat them, how far can you take cross-channel tracking? When and how does privacy come into play -- what are your bright lines for this?

    3. What parts of your attribution insights are then integrated with your marketing automation platforms? What’s still manual?

  18. What does managing based on  more sophisticated attribution look like? Who does it? What kind of interfaces and reports does this person or team use?  How often do they review and act on the results?

  19. What kind of people and organizational challenges have more sophisticated attribution approaches created? How have you solved them?

  20. What advice would you offer to someone with a marketing budget of $1M? $10M? $100M? 

  21. What’s the practical technical frontier of what people are doing?

  22. How do you keep up?  What resources would you suggest for someone interested in learning more and staying up to date?

July 07, 2015

My Q&A With @chiefmartec's Scott Brinker

One Marketing Analytics Myth? The Perfect KPI... published July 6, 2015

February 20, 2015

My latest article in CMO.com: "Analytics Is Too Important To Be Left To Analysts"

"Analytics Is Too Important To Be Left To Analysts", published February 20, 2015

October 28, 2014

Driving Social Engagement With Sentiment Analysis: Text Analytics Summit West

McGraw Hill VP of R&D and Analytics Al Essa kindly invited me to join him in delivering this workshop in San Francisco on November 3.  Hope to see you there!

April 16, 2014

My New Book: #Marketing and #Sales #Analytics

I've written a second book.  It's called Marketing and Sales Analytics: Proven Techniques and Powerful Applications From Industry Leaders (so named for SEO purposes).  Pearson is publishing it (special thanks to Judah Phillips, author of Building A Digital Analytics Organization, for introducing me to Jeanne Glasser at Pearson).  The ebook version will be available on May 23, and the print version will come out June 23.

The book examines how to focus, build, and manage analytics capabilities related to sales and marketing.  It's aimed at C-level executives who are trying to take advantage of these capabilities, as well as other senior executives directly responsible for building and running these groups. It synthesizes interviews with 15 senior executives at a variety of firms across a number of industries, including Abbott, La-Z-Boy, HSN, Condé Nast, Harrah's, Aetna, The Hartford, Bed Bath & Beyond, Paramount Pictures, Wayfair, Harvard University, TIAA-CREF, Talbots, and Lenovo. My friend and former boss Bob Lord, author of Converge was kind enough to write the foreword.

I'm in the final editing stages. More to follow soon, including content, excerpts, nice things people have said about it, slideshows, articles, lunch talk...

January 17, 2014

Culturelytics

I'm working on a book. It will be titled Marketing and Sales Analytics: Powerful Lessons from Leading Practitioners. My first book, Pragmalytics, described some lessons I'd learned; this book extends those lessons with interviews with more than a dozen senior executives grappling with building and applying analytics capabilities in their companies. Pearson's agreed to publish it, and it will be out this spring. Right now I'm in the middle of the agony of writing it. Thank you Stephen Pressfield (and thanks to my wife Nan for introducing us).

A common denominator in the conversations I've been having is the importance of culture. Culture makes building an analytics capability possible. In some cases, pressure for culture change comes outside-in: external conditions become so dire that a firm must embrace data-driven objectivity. In others, the pressure comes top-down: senior leadership embodies it, leads by example, and is willing to re-staff the firm in its image. But what do you do when the wolf's not quite at the door, or when it makes more sense (hopefully, your situation) to try to build the capability largely within the team you have than to make wholesale changes?

There are a lot of models for understanding culture and how to change it. Here's a caveman version (informed by behavioral psychology principles, and small enough to remember). Culture is a collection of values -- beliefs -- about what works, and doesn't: what behaviors lead to good outcomes for customers, shareholders, and employees; and, what behaviors are either ignored or punished.

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Values, in turn, are developed through chances individuals have to try target behaviors, the consequences of those experiences, and how effectively those chances and their consequences are communicated to other people working in the organization.

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Chances are to  culture change as reps (repetitions) are to sports. If you want to drive change, to get better, you need more of them. Remember that not all reps come in games. Test programs can support culture change the same way practices work for teams. Also, courage is a muscle: to bench press 500 pounds once, start with one pushup, then ten, and so on. If you want your marketing team to get comfortable conceiving and executing bigger and bolder bets, start by carving out, frequently, many small test cells in your programs. Then, add weight: define and bound dimensions and ranges for experimentation within those cells that don't just have limits, but also minimums for departure from the norm. If you can't agree on exactly what part of your marketing mix needs the most attention, don't study it forever. A few pushups won't hurt, even if it's your belly that needs the attention. A habit is easier to re-focus than it is to start.

Consequences need to be both visible and meaningful. Visible means good feedback loops to understand the outcome of the chance taken. Meaningful can run to more pay and promotion of course, but also to opportunity and recognition. And don't forget: a sense of impact and accomplishment -- of making a difference -- can be the most powerful reinforcer of all. For this reason, a high density of chances with short, visible feedback loops becomes really important to your change strategy.

Communication magnifies and sustains the impact of chances taken and their consequences. If you speak up at a sales meeting, the client says Good Point, and I later praise you for that, the culture change impact is X. If I then relate that story to everyone at the next sales team meeting, the impact is X * 10 others there. If we write down that behavior in the firm's sales training program as a good model to follow, the impact is X * 100 others who will go through that program.

Summing up, here's a simple set of questions to ask for managing culture change:

  • What specific values does our culture consist of?
  • How strongly held are these values: how well-reinforced have they been by chances, consequences, and communication?
  • What values do I need to keep / change / drop / add?
  • In light of the pre-existing value topology -- fancy way of saying, the values already out there and their relative strength -- what specific chances, consequences, communication program will I need to effect the necessary keeps / changes / drops / adds to the value set?
  • How can my marketing and sales programs incorporate a greater number of formal and informal tests? How quickly and frequently can we execute them?
  • What dimensions (for example, pricing, visual design, messaging style and content, etc.) and "min-max" ranges on those dimensions should I set? 
  • How clearly and quickly can we see the results of these tests?
  • What pay, promotion, opportunity, and recognition implications can I associate with each test?
  • What mechanisms are available / should I use to communicate tests and results?

Ask these questions daily, tote up the score -- chances taken, consequences realized, communications executed -- weekly or monthly. Track the trend, slice the numbers by the behaviors and people you're trying to influence, and the consequences and communications that apply. Don't forget to keep culture change in context: frame it with the business results culture is supposed to serve. Re-focus, then wash, rinse, repeat.  Very soon you'll have a clear view of and strong grip on culture change in your organization.

September 01, 2013

#MITX Panel: Analytically Aligned Decision Making in the Multi-Agency Context

I moderated this panel at the Massachusetts Innovation and Technology Exchange's (mitx.org)"The Science of Marketing: Using Data & Analytics for Winning" summit on August 1, 2013.  Thanks to T. Rowe Price's Paul Musante, Visual IQ's Manu Mathew, iKnowtion's Don Ryan, and Google's Sonia Chung for participating!

 

May 20, 2013

"How to Engage Consumers in a Multi-Platform World?" See you May 22 @APPNATION bootcamp panel in NYC

Sponsorpay's Global Sales SVP Andy Bibby kindly asked me to join his NYC Internet Week APPNATION panel on Wednesday, May 22 2:15-3p at 82 Mercer.  Hope to see you there, watch this space for a recap of the conversation.

January 09, 2013

My New Book: Pragmalytics

I've written a short book.  It's called "Pragmalytics: Practical Approaches to Marketing Analytics in the Digital Age".  It's a collection and synthesis of some of the things I've learned over the last several years about how to take better advantage of data (Big and little) to make better marketing decisions, and to get better returns on your investments in this area.  

The main point of the book is the need for orchestration.  I see too much of the focus today on "If we build It (the Big Data Machine, with some data scientist high priests to look after it), good things will happen."  My experience has been that you need to get "ecosystemic conditions" in balance to get value.  You need to agree on where to focus.  You need to get access to the data.  You need to have the operational flexibility to act on any insights.  And, you need to cultivate an "analytic marketer" mindset in your broader marketing team that blends perspectives, rather than cultivating an elite but blinkered cadre of "marketing analysts".  Over the next few weeks, I'll further outline some of what's in the book in a few posts here on my blog.

I'm really grateful to the folks who were kind enough to help me with the book.  The list includes: Mike Bernstein, Tip Clifton, Susan Ellerin, Ann Hackett, Perry Hewitt, Jeff Hupe, Ben Kline, Janelle Leonard, Sam Mawn-Mahlau, Bob Neuhaus, Judah Phillips, Trish Gorman Clifford, Rob Schmults, Michelle Seaton, Tad Staley, and my business partner, Jamie Schein.  As I said in the book, if you like any of it, they get credit for salvaging it.  The rest -- including several bits that even on the thousandth reading still aren't as clear as they should be, plus a couple of typos I need to fix -- are entirely my responsibility.

I'm also grateful to the wonderful firms and colleagues and clients I've had the good fortune to work for and with.  I've named the ones I can, but in general have erred on the side of respecting their privacy and confidentiality where the work isn't otherwise in the public domain.  To all of them: Thank You!

This field is evolving quickly in some ways, but there are also some timeless principles that apply to it.  So, there are bits of the book that I'm sure won't age well (including some that are already obsolete), but others that I hope might.  While I'm not one of those coveted Data Scientists by training, I'm deep into this stuff on a regular basis at whatever level is necessary to get a positive return from the effort.  So if you're looking for a book on selecting an appropriate regression technique, or tuning Hadoop, you won't find that here, but if you're looking for a book about how to keep all the balls in the air (and in your brain), it might be useful to you.  It's purposefully short -- about half the length of a typical business book.  My mental model was to make it about as thick as "The Elements of Style", since that's something I use a lot (though you probably won't think so!).  Plus, it's organized so you can jump in anywhere and snack as you wish, since this stuff can be toxic in large doses.

In writing it amidst all the Big Data craziness, I was reminded of Gandhi's saying (paraphrased) "First they ignore you... then they fight you, then you win."  Having been in the world of marketing analytics now for a while, it seems appropriate to say that "First they ignore you, then they hype you, then you blend in."   We're now in the "hype" phase.  Not a day goes by without some big piece in the media about Big Data or Data Scientists (who now have hit the highly symbolic "$300k" salary benchmark -- and last time we saw it, in the middle part of the last decade in the online ad sales world, was a sell signal  BTW).  "Pragmalytics" is more about the "blend in" phase, when all this "cool" stuff is more a part of the furniture that needs to work in harmony with the rest of the operation to make a difference.

"Pragmalytics" is available via Amazon (among other places).  If you read it please do me a favor and rate and review it, or even better, please get in touch if you have questions or suggestions for improving it.  FWIW, any earnings from it will go to Nashoba Learning Group (a school for kids with autism and related disorders).

Where it makes sense, I'd be very pleased to come talk to you and your colleagues about the ideas in the book and how to apply them, and possibly to explore working together.  Also, in a triumph of Hope over Experience, my next book (starting now) will be a collection and synthesis of interviews with other senior marketing executives trying to put Big Data to work.  So if you would be interested in sharing some experiences, or know folks who would, I'd love to talk.

About the cover:  it's meant to convey the harmonious convergence of "Mars", "Venus", and "Earth" mindsets: that is, a blend of analytic acuity, creativity and communication ability, and practicality and results-orientation that we try to bring to our work. Fellow nerds will appreciate that it's a Cumulative Distribution Function where the exponent is, in a nod to an example in the book, 1.007.

 

 

February 02, 2012

Please Help Me Get Listed On The #Google #Currents Catalog. And Please ReTweet!

Hi folks, I need a favor.  I need 200 subscribers to this blog via Google Currents to get Octavianworld listed in the Currents catalog.  If you're reading this on an iPhone, iPad, or Android device, follow this link:

http://www.google.com/producer/editions/CAow75wQ/octavianworld

If you are looking at this on a PC, just snap this QR code with your iPhone or Android phone after getting the Currents app.

 

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Here's what I look like on Currents:

 

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What is Currents?  If you've used Flipboard or Zite, this is Google's entry. If you've used an RSS reader, but haven't used any of these yet, you're probably a nerdy holdout (it takes one to know one).  If you've used none of these, and have no idea what I'm talking about, apps like these help folks like me (and big media firms too) publish online magazines that make screen-scrollable content page-flippable and still-clickable.  Yet another distribution channel to help reach new audiences.  

Thank you!