About

I lead Force Five Partners, a marketing analytics consulting firm (bio). I've been writing here about marketing, technology, e-business, and analytics since 2003 (blog name explained).

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25 posts categorized "Speaking & Writing"

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!

July 16, 2010

#OMMA Metrics SF 7/21 "Modeling Attribution" Panel: Proposed Questions

Prepping for http://bit.ly/b7KIQz

Here are some discussion questions we're considering.  What's your "keep / change / drop / add" to this list? And, please take the poll at bottom!

1. How do you define "attribution analysis", and in particular, how do you distinguish it from media mix modeling?  Where are the boundaries with "CRM"? Is it just a question of the fineness of the degree to which you can relate media effects to each other? 

2. Everyone's got a poster child example or case study that illustrates the potential of multi-channel attribution analysis.  For each of you, what's your poster child?

3. What are the practical limits of the utility of this analysis, and what's behind those limits?  Put another way, at what point do you see diminishing returns to investments in attribution analysis, and why?

4. Let's talk techniques for a moment, since the session description promised we would.  What particular approaches to data integration or to statistical analysis do you find robust enough  for real-world use, and which ones are still too fragile to make work in most cases?

5. Some people approach attribution analysis as a capability-building exercise -- if we build it, they will come -- while others come at it from a tight, hypothesis-driven focus about where the value might lie, and in what sequence it might best make sense to explore connections.  What do you need to know about a client to suggest which way, or what mix of the two, might make sense for them?

6. What are some principles and tactics for the governance of attribution analysis -- things like reconciling metrics and comp with the global optimization it implies -- that make sense here?  Can you tell any stories about how these have been developed and applied?

7. What kind of experience, training, and topical education does it make sense for marketers to have, to fully take advantage of this?

8. How do you operationalize this analytic capability -- how do you make sure we move beyond insight and apply, either manually or even in automated ways, the directions the analysis suggests?  And, how does this prospective operationalization [warning: mouthful!] affect the analysis you consider doing, in turn?

9. Let's build the ideal RFP for attribution analysis efforts, to help our clients out.  What's in it?  What shouldn't be?

10. What's your recommended reading list for learning about and following this field?


June 14, 2010

OMMA Metrics & Measurement "Modeling Attribution" Panel SF 7/22: Hope To See You There

I'll be moderating a panel at the OMMA Metrics & Measurement Conference in San Francisco on July 22.  

The topic of the panel is, "Modeling Attribution: Practitioner Perspectives on the Media Mix".  Here's the conference agenda page.

The panel description:

How do you determine the channels that influence offline and online behavior and marketing performance?  

How should you allocate your budget across CRM emails, display ads, print advertising, television and radio commercials, direct mail, and other marketing sources? 

What models, techniques, and technologies should you use develop attribution and predictive models that can drive your business? 

Do you need SAS, SPSS, and a PhD in Statistics? 

Does first click, last click, direct, indirect, or appropriate attribution matter – which is best?

What about multiple logistic regression? 

What is the impact of survey and voice-of-the-customer data on attribution? 

Hear from experts who have to answer these questions and tackle these tough issues as they work hard in the field every day for their consultancies, agencies, and brands.

So far, Manu Mathew, CEO from VisualIQ, and Todd Cunningham, SVP Research at MTV Networks, will be participating on the panel as well.

Hope to see you there.  Meanwhile, please suggest questions you'd like to ask the panelists by commenting here.  Thanks!

April 28, 2010

MITX Panel: "Integrating Cross-Channel Customer Experiences" (April 29, 2010 8-10a) Part II

We've assembled a terrific panel for tomorrow's event:

  • SmartDestinations' Rob Schmults is also a Creative Good Council Leader;
  • Judah Phillips is a leader at the cutting edge of analytics in his role at Monster;
  • At Staples, Colin Hynes plays a leading role in figuring out store / digital integration, and is heavily focused on mobile's role in that;
  • VisualIQ's Manu Mathew sees a broad assortment of situations in facilitating his customers' efforts to develop a cross-channel perspective and optimize based on it.

Here are some of the questions we thought to cover:

  • What integrated experiences do you look to as best practice models?
  • What are you doing in your organizations (or your clients') to better integrate experiences?
  • Where do you believe the greatest opportunities for better integration still lie for you?
  • How are you addressing the organizational and technical challenges required for better integration?
  • How far down the path toward a more integrated, globally-optimized analytic perspective do you see yourself today?
  • What's your favorite integrated experience story, for good -- or not so good?
  • What resources have you found helpful for learning more / tracking what's going on in this area?
  • What advice would you have for folks trying to push further down this path?

Suggestions for questions welcome -- just email me via the link at left.

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Postscript:  a recap of the panel on the MITX blog

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By this point, many of you will be familiar with some of the more interesting and exotic examples of "integrated cross-channel product experiences", such as the Nike+ product/ service/ community.  But the approach has gone mainstream too.  Here's a recent example I experienced:

I went with my family to the "99" Restaurant in Centerville, on Cape Cod in Massachusetts (the one on Route 28).  Lying on the table was a pad of these forms:

99 Restaurant Loyalty Coupon Form0001

  I texted my information in, and 24 hours later this appeared in my inbox:

99 email

I clicked through:

99 coupon



Store to text to email to web to store, all nicely connected.  Cool!  Hope we're back before it expires.  Otherwise we'll have to sacrifice another family member's phone.  (Maybe do that anyway, and ask for separate checks... Hey, times are tough!) 

This program is run soup-to-nuts for the "99" by an external service called Fishbowl Marketing.  It's pretty good! I'm hoping to speak with them about experiences and results with it.

A few observations:

  • Instead of texting "99", they might have asked for "CapeCod", or "Cville" to track the geographic location of the signup, allowing them to compare signups to store traffic across regions. (Fishbowl might need an SMS address unique to the "99" client for this, and that's more expensive.)
  • I may not get back to the Cape soon.  When I clicked through from the email to the landing page from home, they could have recognized where the request was coming from and returned a link to a map of nearby locations under the coupon.  I'm betting most folks won't explicitly update their preferences, especially with the unremarkable landing page copy exhorting them to do so (good testing opportunity!).
  • I sometimes participate in other offers like this.  They could offer me an opportunity to personalize my offer based on crossing my cell number against other databases that also might have it, to see what other information might be there that might have helped them -- and me (analogous to caller ID).
  • Some sample of users could (may?) have been asked to participate in an exit survey about their experience, perhaps for additional benefits.
  • maybe implement a "Share this coupon with three friends and get another $5-off when they sign up" opportunity? (I did get follow up email messages on holidays inviting me back, and suggesting I invite friends; but when I clicked through to landing pages for inviting friends, the forms asked me to tell them who I was, again, even though I hadn't cleared cookies in the interim.)
  • Also, they might have added links to their social media presences like Twitter and Facebook (for feedback, or to offer other promotions), below the coupon. 
  • Finally, and I'm sure this is on Fishbowl Marketing's agenda, they might consider signing up with a mobile location-based service provider, like Foursquare or Gowalla, either as part of the vendor branded experience or via a "white label" application developed off those vendors' APIs.  That way the "99" could vary loyalty rewards granted according to number of check-ins, and take advantage of the viral marketing advantages of these services (your friends get notified when you check in at the "99", so maybe they stop by too).   Of course you say, are "99" customers leading-edge tech adopters with the latest 3G smartphones, with OC(I)D (Obsessive Check-In Disorder)?  Not yet, but what were we saying about Facebook a couple of years ago?

What's your favorite example?  Hope to see you tomorrow morning!

April 13, 2010

MITX Panel: "Integrating Cross-Channel Customer Experiences" (April 29, 2010)

On the morning of April 29 I'll be moderating a MITX panel discussion titled "Integrating Cross-Channel Customer Experiences", in Cambridge, MA (Kendall Square).  More here, more posts to follow.  Hope to see you there!

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