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 the 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:

2 obstacles to marketing change in organizations: accountability and complacency. @paulroetzer #MarTech

Marketing CMOs now own the whole customer experience in the most progressive companies, from product to retention. @lauramclellan #MarTech

The best marketers can think on a strategic level, then execute on a tactical level & get hands dirty. @paulroetzer #MarTech

On average, marketers depend on data for only 11% of customer-focused decisions. @ceb_news #MarTech

What makes a marketing technologist? Curiosity. Leadership. Creativity. Risk-taker. Can start as tech or marketer. @lauramclellan #MarTech

Marketing: right brain. Technology: left brain. #MarTech needs people strong in BOTH brains. Our greatest challenge is very rare talent. @cspenn

While the technology stack for achieving customer-focused value measurement has certainly improved over the past several years, the cultural support for a  movement like this is may be still lacking.  There are of course exceptions, but in general I find most corporate structures in digital have a hard time finding and dealing with the knowledge created from introspection at the customer level.  That thing  called “customer” typically touches a lot of different parts of the business, so the determination of value would also.

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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.

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Marketing to Focus on Customer. Analytics?

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.  Web 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 the impression or visit level?

Is someone who visits or purchases or comments one time really a customer, for the purposes of analyzing “centricity” ideas and concepts?  I think not.  Visit metrics simply don’t work for understanding these customer concepts, because by definition they unfold over time, not as single events.   Add in the fact most web activity is 1x in nature – even buyers – and you begin to realize that analyzing “traffic” yields very little in the way of “customer” insight.

From a Marketing perspective, hey, happy to have the 1x revenue, but these are interactions I’m not really excited about increasing spend on, knowing they will be a one-night stands.  This is especially true when you also know re-allocating some of the funds spent on the 90% 1x-ers to the other 10% could double company profits!

If you have followed my writings over the past 12 years, none of the above perspective is new.  What might be changing is this: more people in the online world are beginning to think the same way.

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“Missing” Social Media Value

I have no doubt there is some value in social beyond what can be measured, as this has been the case for all marketing since it began ;)  The problem is this value is often situational, not too mention not properly measured using an incremental basis (as you point out).
For example,  to small local businesses who do no other form of advertising, there is a huge amount of relative value to using social media, versus no advertising at all.  Some advertising is much better than none, and since it’s free, the incremental value created by (properly) using social is huge.
On the other hand, I wonder why social analysis seems to forget that people have to be aware of you to “Like” you in the first place.  Further, it seems unlikely a person would “Like” a brand or product if they have not already experienced it, and are already a fan.  If this is not true, if people “Like” a company even thought they do not (paid to Like?), then the problems with social go way beyond analysis…
But if true, , the number of “Likes” doesn’t have as much to do with awareness as it does with size of customer base, and is much more aligned with tracking customer issues (retention, loyalty) than anything to do with awareness / acquisition.
Add the fact many companies are running lots of advertising designed to create awareness, and the incremental value of social as a “media” may be close to zero, or at least less than the cost to analyze the true value of it.
And this last, really, is the core of the issue.  It’s simply not possible to measure “all” the value created by any kind of marketing, and there are hugely diminishing returns as you try to capture the last bits.  I think it’s quite possible the optimism for “value beyond what can be measured” is less than the cost of measuring it *if* people keep looking in the awareness / acquisition field.
Folks who want to find this “missing” social value should start doing customer analysis, and look in the “retention / loyalty” area, where the whole idea of social is a natural, rather than a forced, fit.

Has to be There

I find it really interesting that whenever there is a discussion of measuring the value of social media, there’s such a bias towards believing there is value in social beyond what can be properly measured.  See the comments following this post by Avinash for a good example.  Speculation is fine, but the confidence being expressed that a new tool or method will uncover a treasure trove of social media value seems un-scientific (as in scientific method) at best.

I don’t doubt there is some value in social media beyond what can be measured, as this has been the case for all marketing since marketing measurement began.  These measurement problems are not new to social either:  Marketing value created is often situational, it depends on the business model and environment.  What works in one situation may not work in another.

For example:

To small local businesses who do no other form of advertising, there is a huge amount of relative value to using social media, versus no advertising at all.  Social advertising is much better than none, and since it’s free, the incremental value created by (properly) using social is huge.  It’s also really easy to measure the impact and true value, since the baseline control is “no advertising”.  Lift, or actual net marketing performance, can be pretty obvious in his case.

On the other hand, many companies are running lots of advertising designed to create awareness, and the incremental value of social as a “media” may be close to zero for these companies, or at least less than the cost to analyze the true value of it.  Possible explanation:  Social events such as “Likes” or comments are simply representations or affirmations of awareness already created by other media, so by themselves, create little value.  In other words, events such as Likes might track the value of other media spending, but may not create much additional marketing value.

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Defining Behavioral Segments

The following is from the April 2011 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: I purchased your book and have a few questions you can hopefully help me out with.

A: Thanks for that, and sure!

Q: We have 4 product lines and 2 of them are seasonal. i.e we have customers that year in year out purchase these items consistently but seasonally, for example, every spring and summer.  Then they are dormant for Fall and Winter.  Should I include these customers along with everyone else when doing an RFM segmentation?

A: Well, it kind of depends what you will using the RF(M) model for, what kinds of marketing programs will be activated by using the scores. If you know you have seasonal customers and their habit is to buy each year, AND you wish to aim retention or reactivation programs at them, I would be tempted to divide the customer base so that seasonal customers are their own segment.  Then run two RF(M)  models – one for the seasonals, and one for everyone else.

Q: If I include seasonal customers, and I run RFM say on a monthly basis, these seasonal customers will climb / fall drastically with time depending on the season, so it seems like it may complicate the scoring process.

A: Sure, and you could segment as I said above.  Or, you could run across a longer time frame, say across 2 – 3 years worth of data. This would “normalize” the two segments into one and take account of the seasonality in the scoring – perhaps be more representative of the business model.  However, the scores would become less sensitive due to the long time frame so the actions of customers less accurately predicted by the model.

Q: Can you provide me with some examples as to how segmentation is carried out?  Let’s say I being with RFM and all my customers are rated 5-5, 5-4, 4-5 etc.  What are the next steps, do we overlay with other characteristics like age, gender, etc?  Or are the 5-3 etc. our actual segments?

A: This goes back to what you want to use the RF(M) model for.  In the standard usage, each score will have roughly the same number of customers in it, those with higher scores will be more likely to respond to marketing and purchase, lower scores less likely.

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Increase Profit Using Customer State

The following is from the March 2011 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: We’ve been playing around with Recency / Frequency scoring in our customer email campaigns as described in your book.  To start, we’re targeting best customers who have stopped interacting with us.  I have just completed a piece of analysis that shows after one of these targeted emails:

1. Purchasers increased 22.9%
2. Transactions increased 69%
3. Revenue increased 71%

A: There you go!

Q: My concern is that what I am seeing is merely a seasonal effect – our revenue peaks in July and August.  So what I should have done is use a control group as you described in the book – which is what I am doing for the October Email.

A: Yep, that’s exactly what control groups are for – to strain out the noise of seasonality, other promotions, etc.  But don’t beat yourself up over it, nothing wrong with poking around and trying to figure out where the levers are first.

Q: Two questions:

1.  What statistical test do I use to demonstrate that the observed changes are not down to chance

2.  How big should my control group be – typically our cohort is 500-800 individuals

A: Good questions…

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All Talk, No #Measure

Hypocrisy in Web Analytics?

Before every eMetrics (I’ll be in San Fran teaching Basecamp, at the Gala, etc.), I try to ask myself, what is the most critical issue facing the web analyst community right now?  Then, at the show, I ask everyone I run into what they think about this issue.

There’s lots of issues to choose from.  Career path I think is a big area of discussion, given the mergers in the space and trend towards outsourcing.  Then there’s the “we don’t get no respect” thing; senior management doesn’t seem to listen / understand / act on the information provided.  And one of my favorites from the past is still out there, data torture - people being pressured to manipulate data to reach a predetermined analytical outcome.

But seems to me, more important at this juncture is trying to resolve why there is so much written about the importance of “the customer” but very little measurement at the customer level.  Think about it.  Customer experience, customer centricity, the entire social thing, it’s all about customers.

But when folks wants to trot out “proof” that this or that approach is the road to the promised land, they analyze impressions, visits, clicks, etc.  Visitor-level stuff.  Does that seem like the correct approach to you?  Seems to me, if you want to provide knowledge about customers, you should measure customers.

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But What is an Impression Worth?

Seems like coming up with a value for social media has become a cottage industry, for example, $3.60 Facebook Fan Valuation Is Just the Tip of the Iceberg.  These values are often derived from what is paid for online media.  So you have to ask, if someone is basing the value of a Facebook fan on the value of impressions generated, what is the real value of those impressions?  Because unless this is known, the whole framework is faulty.

Just because you pay $5 / CPM for impressions, does not mean they are worth $5 / CPM, does it?  Do people really still have that kind of mentality?  Is the price of the media equivalent to its value?

For example, I’m sure you have heard of multi-million dollar campaigns that generate very little lift in sales.  Happens frequently in fast food, for example.  What is the value of that media?  Is it the millions paid?

What really blows my mind about this approach is it’s so offline, so old school PR. Do the folks who put forth these kinds of models believe nothing has changed in 50 years?  What happened to the whole rap of online being “different”, that you can’t measure it like offline, blah blah.

Except when it’s convenient to do so?

If you want to know the value of a Facebook fan, why not measure the value of a Facebook fan?  Because it’s hard, and would require organizational discipline?  Too bad.   Substituting the kind of models used in the example above for actually measuring the value of a Facebook fan is misleading at the very best.

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Optimizing for Customer Value

The following is from the February 2011 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: Thank you for creating this useful website!

A: You’re welcome!

Q: When figuring out retention rate for an annual or a 8 months life time cycle period, how do I pick the starting period?  Do I look at their first orders on a date?  Or I pick a time frame such as one month?

A: It depends on:

1. What kind of “retention” you are talking about, the definition, which is probably impacted by the audience for the data

2.  What you will do with the retention data, what kind of decisions will be made and actions be taken because of the data

You should always ask these questions above  when someone requests “retention data” – or any other kind of analysis, for that matter!  For example, there probably is a huge difference in what you would provide to the Board of Directors for an annual benchmark and what you would provide to Marketing people for executing campaigns.

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When Does a Visitor Need a Coupon?

The following is from the November 2010 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: First off, I very much appreciate you sharing all this wonderful content on your blog and conferences such as eMetrics.

A: Thanks for that!

Q: My question is a simple one, but I think the answer may be hard: When does a visitor “need” a coupon?  *Need* defined as: visitor would not have placed an order unless presented with the coupon.

A: Hmmm…methinks we’re going to have to define a few concepts and be clear on the goals to make sure we are nailing this down… visitor versus customer, sales versus profit, etc.  In other words, answer is not hard, but could be complex without defining context.

Q: It’s still a mystery to me why so many retailers seem more than willing to hand over all their margins to Groupon or give coupons to basically all visitors.  I am curious whether you would approach this question using  observational data (eg web analytics) or experiments (eg AB testing), or both.

A: Right – is a mystery to me too!

There are certain situations where this approach might be appropriate, but the problem with much web “marketing” (which often is really just advertising without much thought about marketing) is often there is success in a narrow or special situation.  Then the pundits jump on and say “if you’re not doing this you are stupid”, regardless of the business situation and / or without recognizing the special circumstances that are driving success.  This is all the real Marketing stuff people leave out; understanding why it works, under what circumstances, for which segments, involving which products.

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