Tag Archives: Analytical Culture

Is Your Digital Budget Big Enough?

At a high level, 2014 has been a year of questioning the productivity of digital marketing and related measurement of success.  For example, the most frequent C-level complaint about digital is not having a clear understanding of bottom-line digital impact. For background on this topic, see articles herehere, and here.

I’d guess this general view probably has not been helped by the trade reporting on widespread problems in digital ad delivery and accountability systems, where (depending on who you ask) up to 60% of delivered “impressions” were likely fraudulent in one way or another.  People have commented on this problem for years; why it took so long for the industry as a whole to fess up and start taking action on this is an interesting question!

If the trends above continue to play out, over the next 5 years or so we may expect increasing management focus on more accurately defining the contribution of digital – as long as management thinks digital is important to the future of the business.

If the people running companies are having a hard time determining the value of digital to their business, the next logical thought is marketers / analysts probably need to do a better job demonstrating these linkages, yes?  Along those lines, I think it would be helpful for both digital marketers and marketing analytics folks to spend some time this year thinking about and working through two of the primary issues driving this situation:

1.  Got Causation?  How success is measured

In the early days of digital, many people loved quoting the number of “hits” as a success measure.  It took a surprisingly long time to convince these same people the number of files downloaded during a page view did not predict business success ;)

Today, we’re pretty good at finding actions that correlate with specific business metrics like visits or sales, but as the old saying goes, correlation does not imply causation.

If we move to a more causal and demonstrable success measurement system, one of the first ideas you will encounter, particularly if there are some serious data scientists around, in the idea of incremental impact or lift.  This model is the gold standard for determining cause in much of the scientific community.  Personally, I don’t see why with all the data we have access to now, this type of testing is not more widely embraced in digital.

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Does Advertising Success = Business Success?

Digital Analytics / Business Alignment is Getting Better

I recently attended eMetrics Boston and was encouraged to hear a lot of presentations hitting on the idea of tying digital analytics reporting more directly to business outcomes, a topic we cover extensively in the Applying Digital Analytics class I taught after the show. This same kind of idea is also more popular lately in streams coming out of the eMetrics conferences in London and other conferences.  A good thing, given the most frequent C-Level complaint about digital analytics is not having a clear understanding of bottom-line digital impact (for background on this topic, see articles herehere, and here).

Yes, we’ve largely moved beyond counting Visits, Clicks, Likes and Followers to more meaningful outcome-oriented measures like Conversions, Events, Downloads, Installs and so forth.  No doubt the C-Level put some gentle pressure on Marketing to get more specific about value creation, and analysts were more than happy to oblige!

Is Marketing Math the Same as C-Level Math?

Here’s the next thing we need to think about: the context used to define “success”.

In my experience, achieving a Marketing goal does not necessarily deliver results that C-Level folks would term a success.  And here’s what you need to know: C-Level folks absolutely know the difference between these two types of success and in many cases can translate between the two in their heads using simple business math.

Here’s an example.  Let’s say Marketing presents this campaign as a success story:

Continue reading Does Advertising Success = Business Success?

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Digital Customer Analysis Going Mainstream?

Is it possible the mainstream digital marketing space is about to finally move on from a focus on front-end measurement (campaigns, etc. ) to creating knowledge around how enterprise value as a whole is created?  And actually enabling action in this area?

Judging by the material coming out of the recent Martech conference in Boston, one would think so.  And it looks to me like I’m not the only one thinking “it’s about time”.

A couple of years ago I lamented:

It’s been very popular among marketing types to talk about “the customer” but seek metrics for affirmation other than those based on or derived from the customer. Digital analysts have followed their lead, and provided Marketers plenty of awareness, engagement, and campaign metrics.  As I’ve said in the past, this is a huge disconnect. Does it make sense (analytically) to have discussions about customer centricity, customer experience, customer service, the social customer, etc. and measure these effects at impression or visit level?

If you’d like to review some commentary on the conference, see a list of 5 posts here.  I found the list of tweets here particularly indicative of Martech’s potential, for example:

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Marketing Funnel Not Dead, Using Funnel Model for Attribution Is

It’s become fashionable to declare the “Marketing Funnel Model” dead.

For example, here is a post worth reading on this topic by Rok Hrastnik.  There are some very good points in this post on why using a funnel to attribute media value is really a troubled idea.  I was flagged on this post because it has a quote from me that seems to support Rok’s thesis about the death of the funnel model and the related idea, “Direct Response Measurement is a Wet Dream”.   The quote is from a comment I made on a post by Avinash where we were discussing the value of sequential attribution models:

There are simply limits on what can be “proven” given various constraints, and that’s where experience and a certain amount of gut feel based on knowledge of customer kick in.  If you can’t measure it properly, just say so. So much damage has been done in this area by creating false confidence, especially around the value of sequential attribution models where people sit around and assign gut values to the steps.  Acting on faulty models is worse than having no information at all.

But none of this means the Funnel Model is dead, or that Direct Response Measurement overall is a Wet Dream.  What’s (hopefully) dead is  people using the funnel model inappropriately for tasks it was never designed for, in this case multi-step attribution of media value to goal achievement.  On the other hand, if this specific funnel use case is what Rok was coming after, I agree, because it didn’t make any sense to use a funnel model for this idea in the first place.

Let’s unpack these ideas

Funnel thinking is based on a relatively reliable model of human behavior, AIDA.  This model from human psychology does not specify tools, channels, or media.  It simply says that there is a path to purchase most humans follow.  That is:

A – Attention: (Awareness): attract the attention of the customer
I – Interest:  (Intent) promote advantages and benefits
D – Desire: convince customers the product will satisfy their needs
A – Action: lead customers towards taking action / purchace

Example:  I’m Aware of tons of products I would never buy.  There are lots of products I think are Interesting but I have no Desire for.  There’s a short list of products I Desire but have not Acted on.  The list of products in my head worthy of purchase consideration gets smaller and smaller at each stage of the AIDA model.  This is the funnel.

The AIDA funnel has not changed and it’s not dead.

It’s a model of human behavior, not media consumption.

Continue reading Marketing Funnel Not Dead, Using Funnel Model for Attribution Is

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Tortured Data – and Analysts

Fear and Loathing in WA

You may recall I wrote last year about the explicit or implicit pressure put on Analysts to “torture the data” into analysis with a favorable outcome.  In a piece called Analyze, Not Justify, I described how by my count, about 50% or so of the analysts in a large conference room admitted to receiving this kind of pressure at one time or another.

Since then, I have been on somewhat of a personal mission to try to unearth more about this situation.  And it seems like the problem is getting worse, not better.

I have a theory about why this situation might be worsening.

Companies that were early to adopt web analytics were likely to already have a proper analytical culture.  You can’t put pressure on an analyst to torture data  in a company with this kind of culture – the analyst simply will not sit still for it.  The incident will be reported to senior management, and the source of “pressure” fired.  That’s all there is to it.

However, what we could be seeing now is this: as #measure adoption expands, we find the tools in more companies lacking a proper analytical culture, so the incidents of pressure to torture begin to expand.  And not just pressure to torture, but pressure to conceal, as I heard from several web analysts recently.

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Customer Value in the Freemium Model

The following is from the November 2009 Drilling Down Newsletter.  Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, feel free to leave a comment and I’ll reply.

Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q: You kindly clarified a few issues when I was reading Drilling Down earlier this year – so I hope you don’t mind the direct email.

A: Yes, I remember!

I am working for www.XYZ.com, a social networking / virtual world site based abroad but visitors are 85% US.

Our growth up to now has been mainly viral and in the summer we hit 1.2M UVs operating on the Freemium model with only 5% of our registered users converting to paying customers and a significant portion of our revenue coming from ads.  On average our customers are active on the site for something like 4 months making their first purchase around day 28. 

But to take us to the next stage we are embarking on some marketing for the first time using AdWords and various revenue share campaigns, and of course to do this sensibly we need to arrive at a reasonable estimate of LTV.

A: Makes sense!

Q: To calculate an adjusted LTV I removed all customers with a lifetime of less than 4 months but this gives a low estimate as this calculation ignores the bumper summer months and the extra paid for features put in place earlier this year.  Calculating LTV using ARPU and monthly churn (not sure how to calculate this in our environment) gives another different estimate.  Is there any help or advice you could perhaps give us?  If not in the US then perhaps you could recommend somebody abroad – can’t find anything in the literature relevant for start-up like us.

A:  It sounds to me like you’re trying to make this too complicated, at least for the place you are at this time.  Monthly churn and the “28 day” threshold are nice to know on a tactical level, but LTV is more of a Strategic idea that does not necessarily benefit from analysis at that level.  And you may not really want LTV, but a derivative that might be more helpful.

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The Other 3 P’s

It’s interesting most folks that consider themselves Marketers, especially of the online variety, seem to only discuss and have ideas about Advertising.  But of the 4 P’s that make up Marketing – Product (which includes People), Price, Place (channel), and Promotion – Promotion (Advertising) is the weakest element of the four.

I say weakest because Advertising cannot fix a poorly thought out Product, Pricing Strategy, or Distribution system.  It just can’t.  Yet huge amounts of money are wasted trying to do exactly that.

Perhaps this why someone feels they need to publish a book that tells people Product is important in Marketing.  To me, that’s the most circular or redundant idea for a Marketing book I’ve ever heard.

Marketing starts with Product, which should include all the audience or market segmentation studies (People) that drive the creation of the Product – defining the need.  If you do this first and develop a Product which truly fills the need, AND you get the Pricing and Distribution right, the Product will literally sell itself to the core audience.

If you can make it that far, THEN the Product can perhaps be sold to the next segment out from the core through Advertising.  All “Marketers” should know this.

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Marketing Jump Ball

Marketing Accountability.

Brand is what you do, not what you say

Marketing Alignment.

Here are 3 free webinars you might want to take advantage of.  You might not agree with these opinions, but hey, it’s a good idea to get out of the echo chamber once and awhile, don’t you think?  Try these online sessions for a little brain stretching:

———

Moving Marketing From “The Money Spenders” to The Money MAKERS
April 15, 2009  noon ET    Jonathan Salem Baskin, Jim Sterne, Jim Novo

With 10% of marketing executives being perceived as strategic and influential by the C-suite there’s clearly a crisis of confidence.  I’ve mentioned Jonathan’s blog and book before and here’s a chance to hear a bit of the inside story.  You’ll learn how to exceed expectations of both C-suite executives and customers, neutralize political feuds by organizing cross-departmentally, and how to stop thinking like a reporter and start acting like an advisor

———

Everything They’ve Told You About Marketing Is Wrong
April 21, 2009   1pm ET  Ron Shevlin

Are you sick and tired of reading the same old blah, blah, blah, from the so- called marketing experts who just tell you stuff you already know? Then you need to attend this session as the grumpy old man cuts through the morass of bad advice and introduces you to the must-dos in the new world of marketing.  I know Ron personally (as in offline) and even if you disagree, you will be entertained.

——— 

What Online Marketers Can Teach Offline Colleagues (and vice versa)
May 19, 2009  noon ET     Kevin Hillstrom, Akin Arikan, and Jim Novo

A WAA event, open to both members and non-members.  Web analysts are not the first to grapple with multiple channels.  Traditional marketers have always had to illuminate customer behavior across stores, call center, direct mail, etc.  So, rather than reinventing the wheel in each camp, what proven methods can you teach each other?  Three different but aligned approaches on solving the multichannel puzzle, should be something for everyone here.

———

Take your brain out for some exercise, will ya?

 

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Analytical Culture – 3 Books

The web analytics conference season is upon us and I find myself sitting on several panels dealing with analytical culture issues.

“The Culture” is a tremendously important issue and am pleased to see the progress since developing the Creating and Managing the Analytical Business Culture course for the WAA.

At eMetrics Toronto, I will be moderating a Round Table discussion group called “Getting Buy-in and creating an Online Analytics Culture” and on a panel moderated by Jim Sterne called “From Web Analytics to Online Intelligence“.  At Webtrends Engage, I’ll be on a panel called “Socialization of Data” moderated by Barry Parshall.

With all this activity surrounding the Analytical Culture, I can’t help but suggest 3 books for those of you who are interested in / struggling with these analytical culture issues.  The first book you probably know about, but for the sake of providing a complete toolkit, I include it – best book for “CEO buy in” I can think of. 

The 2nd two books are probably off your radar screen because they deal with organizational issues, but trust me, these are the concepts the senior people need to understand to get any action going.  I find the biggest impediment to creating a proper analytical culture is the “roadmap” problem, and these two books together pretty much spell it out for you, including lots of tools to get you moving.

Here’s the list:

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