Got a question about Customer Measurement, Management, Valuation, Retention, Loyalty, Defection?  Just ask your question.  Also, Feel free to leave a comment.  Want to see the answers to previous questions?  Here’s the blog archive; the pre-blog newsletter archives are here.

Q: I received this article (Norms of Reciprocity) via a friend’s Twitter account.  Very interesting.

A:  Glad you enjoyed it!

Q:  It has made open up my ACT! database, and my Outlook databases and add the metric of Growing / Strong / Weakening / Failed to my normal Sales and Business progress metrics.  If I group those categories and correlate to traditional metrics, it’s impressive how they reflect each other.

A:  Yes, most people are surprised.  It’s a very, very simple idea that seems to work across just about any human activity including crime, attendance, and so forth.  

The more Recently someone has done something, the more likely they are to do it again.  Conversely, the longer since an activity last took place, the less likely the person will do it again.  Often called Recency in Psychology and studied quite a bit.

Q:  Now I have to think about how I really use and apply this. : )

A:  Well, if I can guess you are in Sales from your title, typically one of the best applications is in what Strategic Marketing folks might call “allocation of resources”, which probably translates into “lead nurturing” for you.

Most experienced people in Sales have a sort of “sixth sense” when it comes to thinking about the likelihood of a close happening.  They worry about certain prospects more than others, and a sort of “ranking” or “scoring” happens in their mind.  One of the triggers that frequently comes up in this is “how long” it has been since there was any contact activity with the prospect, and the feeling the longer it has been without sales activity, the less likely the sale is to close.  Sales Managers will often allocate resources based on these kinds of “feelings” they or salespeople have.

The problem with all this “gut feel” is, newer sales people don’t have it, and so probably are not as productive as they could be.  The other is since a lot of this is not tracked in any way, there aren’t any firm “guideposts” and it may be that sales are lost that otherwise could have been made due to a lack of urgency or misdirection.

So, given limited resources, a sales force would generally like to focus on the leads most likely to close, and not work on the less likely leads until the most likely leads have been addressed.  This is the idea of scoring, let’s rank all of our prospects by likelihood to close.

Now, as far as what you might do in ACT! or similar (and knowing nothing about your business), here is what I would do.  Just start informally comparing prospects that close and those that don’t close in terms of these timing issues, “how long since contact” or “how long between contacts” for each case.

Typically you will start to see patterns of some kind, for example:

1. “Prospects who have not made it to 2nd sales appointment within 30 days of 1st contact are less likely to close”

2. “Prospects who take longer than 25 days to respond to proposal are less likely to close; prospects who take less than 10 days to respond to proposal are very likely to close”

and so forth.  Look at important events in the sales process and note the “time since” or “time between” and look for such patterns.

Now, as I said, many salespeople, especially experienced ones, have some sense of these ideas, but they have never been quantified. The advantage to quantifying them like this is you can move to a “trigged contact system” based on them, which I think you can do in ACT! if you have the data.  This conserves salesperson resources and helps them always be focused on where they are most likely to close the business.

So, for example, salespeople (sales managers, if more appropriate) receive a communication each day about any prospects who are coming close to any of these triggers above.

In scenario 1 above, a counter starts on 1st contact and if another sales call has not been scheduled within 20 days of 1st sales call, a reminder goes out saying “you have 10 days to get a 2nd appointment or you may lose this sale”.  In scenario 2 above, sending the proposal triggers the counter, and a sales contact is suggested at 7 days later and 15 days after that.

The optimal timing of these contacts is something discovered over time, and of course depends on the business. But having these triggered messages available to guide salespeople towards which contacts they should be most focused on that day or week is a lot better than nothing.

So instead of a salesperson thinking this:

“Gee, it’s ‘been awhile’ since I talked to prospect George. Maybe I should call him”.

you get this thought:

“I sent the proposal to prospect George 7 days ago, and I need to close him in 3 days, or he becomes less likely to close at all.”

The difference in those two thoughts and the action taken can be a lot of sales - especially with newer sales people, who don’t have enough experience to understand the “rhythm of the sale” in this specific business yet.  If you’d like a more detailed example, there’s one here: B2B Software - Latency Tripwire.

Spreadsheets are usually a great tool for this kind of discovery work.

Hope that helps!

Jim

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If you are a consultant, agency, or software developer with clients needing action-oriented customer intelligence or High ROI Customer Marketing program designs, click here
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Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Lead Scoring and Nurturing

Do you believe human beings share certain fundamental traits that define “being human”?

If so, do you believe that human beings tend to behave in certain ways under certain circumstances?

If so, do you then believe since human behavior has these tendencies, it can often be predicted?

If so, then do you think perhaps the study of Psychology and Sociology might provide you some clues to creating successful businesses, campaigns, products, and services?  While your friends and competitors are all iterating their way into oblivion?

On the web, time and time again, we see the same themes repeating.  Yet with each introduction of a new technology, these themes tend to be treated like a new discovery, even though the theme has been well established in the past.

Norms of Reciprocity is a constant human theme.  You may know the expression of these norms as ”Sharing”.  Web old timers will probably recognize this idea as “Give, then Take” from the I-Sales discussion list as early as 1995.  In various forms, this theme goes back to the beginning of human history, all the way back to the handshake and other greeting gestures.  This same theme is embedded in countless Religions all over the world: “Do onto others as you would wish them do onto you”.  At least a couple centuries old, this idea.

Norms of Reciprocity simply means this: When you do something nice for a human being, help them in some way, this human tends to feel Gratitude towards ”the doer” and tends to do something nice back.  Gratitude drives the desire to Reciprocate, because it’s just what humans do, it’s normal, a “norm”.

Norms of Reciprocity.

The Gratitude cycle doesn’t depend on what the technology is, or if there is any at all.  If anything, technology simply extends the number of humans you can engage in reciprocal behavior with.

I first heard of this theme back in the 1970’s related to the CB radio communities, and it existed before that in ham radio.  Since then, we have been through Compuserve Forums in the 80’s, message boards as early as 1985 with The Well, then e-mail discussion groups, to hybrids like Yahoo Groups, and on into Social Media. 

And in every case, the same rules of successful interaction within these communities always applied, even though the technology was different.  No matter what communications technology the “community” uses, humans find a way to organize it with certain rules. 

And the primary driver of these rules is always Norms of Reciprocity.  Give, then Take.  The rules of successfully participating in any of these communities have not changed at all.

In fact, these reciprocity norms define the meaning of ”community”.  If a “Give, then Take” attitude is not present in a message to the community, then what you have is a message called Advertising.

Advertising has no “Give”, only “Take”.

What does all this have to do with Marketing?

In mass Advertising, it’s extremely difficult to measure the effects of a campaign at the level of Individuals.  You can measure the effects on an Audience as a whole, but not on Individuals.

But when you can measure the impact on Individuals, as you can in many forms of Direct Marketing and on much of online Advertising, now you have the ability to step through a doorway and take advantage of human behavior, including Norms of Reciprocity.

And I think this is where people are getting stuck, including the proponents of everything Social. 

These folks are trying to use Audience measurement models to define the success of (Social) Campaigns targeted to Individuals.   “Social Media” is an oxymoron; it can’t be Social and Media at the same time.

The bottom line is, if you are going to embrace a two-way Social model in Marketing, you must measure the success of this effort differently.  Impressions, reach, size of audience, none of that matters in a model where Relationships - driven by Reciprocity - are the goal.

The above metrics are one-way, broadcast advertising measures.  If “Social” or “Relationships” are to be Marketing models, what’s needed is a way to measure a 2-way exchange, a Relationship.  If it’s the Relationship that’s important, why would you use a “media metric” to measure success?  What you need is a social metric.  A  measure rooted in Psychology, one that addresses Norms of Reciprocity directly.

The question you are trying to answer in Relationship Marketing is not “how many people did I Reach”?  “Influence” or any version of Reach is a crap metric in a Social model; it’s measurement for the sake of measurement.  If it’s Reach you are pegging to, then you’re not Social, you are Media, you are All Take.  There is no Exchange in Reach; Influence is a Social metric Paradox. 

There’s nothing wrong with being Reach-based entity, but just stop calling it Social.  You’re a broadcast tower, a magazine, a newspaper.  Un-Social; Media.  Personally, I don’t think it’s a very good business model, as I said several years ago, unless it goes hyper-vertical to provide context.  That means admitting the “Social as Media” business is much, much smaller than everyone thinks it is.

But let’s say you truly want to be a Social entity or use Social techniques to faciliate Marketing.  Then the real question you need to answer in this Relationship Marketing scenario is: What is the state of my Relationships - Growing, Strong, Weakening, or Failed? 

Why?

Because unless to can define “state”, your Social Marketing efforts are not actionable and you are simply Media.  What you need to know to make Social Marketing work is this: How likely are people to interact with me in the Future?  Because if you know the answer to that question, then you can take the appropriate action against a Growing, Strong, Weakening, or Failed prospect or customer state.

That’s a Relationship.  It’s about the future, not the past.  It’s about Norms of Reciprocity; what I do for or with you today defines what you are likely to do for or with me in the future.  The past is over with; the most important issue is this: where’s the Relationship going?

The question you need to answer in a Social Marketing scenario is not “did they interact with me”, because that’s in the past and there is no Social Power in the past.  The power of Social, the value of ”Give, Then Take”, is in Tomorrow.  Right?  Potential Value.  How much Reciprocity have I earned, what is the Value of this Gratitude in the Future?

The power of Social is not in how many connections you have.

It’s understanding how to make important connections more valuable.

Fortunately, if you use metrics from Psychology rather than Media, the Value and State of your Relationships - Growing, Strong, Weakening, or Failed - are metrics that are not very difficult to measure (example).

Using these Values and understanding Reciprocity, you can then leverage Gratitude and create campaigns that not only Surprise and Delight customers but make a ton of money at the same time.

When you see how well that works, you will want to start segmenting by Relationship State instead of by demographics or other non-Social “Media Metrics” to increase profits by reducing Relationship Friction.

Once you start seeing the cause and effect of true Social or Relationship Marketing, you might even get good enough to see the value of correcting Relationship mistakes before they happen.

Social = Relationship, Relationship = Psychology, not Media.

If you want to do or be Social, then by all means, get on with it already.  There’s already a Model for all this as it applies to Marketing and this model drives profits.  The measurement of success in Social is not unknown and does not require continued mystical thought grazing.  It simply requires you to decide if you are in fact a Social entity and not in reality a Media outlet with fancy new clothes.

If you are starting up a Social entity, the phrase “Norms of Reciprocity” is your gateway to decades of research and testing on humans as Social animals.  This knowledge could save you years of iteration.

If you are already a functioning Social entity, stop gazing into that navel of yours and start publishing quantifiable Metrics from Psychology and Sociology, not Media.  You’ll soon find out whether that Social thing you are doing has Marketing value to anybody or not.

If you are a Marketer trying to leverage the Social in all of us to create and strengthen Relationships, stop looking at Social like Media and demand your vendors do the same.  

Then everybody can skip the million monkey iteration thing. 

Your thoughts on the above?

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Norms of Reciprocity

A conference call with a Potential Client last week jogged my memory on a couple of events that happened during the flurry of Web Analytics conferences this Spring.  Here’s a portion of the call…

PC: “We’ve tried proving the profitability of our Marketing efforts and can’t seem to get the numbers working correctly.  So Jim, what we’d like you to do is take all this data we have, and justify the Marketing decisions we’ve made by proving out the ROI.”

Jim: “I’m sorry, did you say justify?  To me, justify means “find a way to prove it works”.  Is that what you are asking me to do?  Wouldn’t it be more beneficial to analyze the results, and then optimize your Marketing based on these results?”

PC: “Jim, around here we’re pretty clear our Marketing works, and Management knows this.  But Finance is asking for some backup, some numbers to justify the spend, not to analyze it.  We don’t need analysis, we need your ‘expert credibility’ to help us out with this.”

Jim: “I see,” thinking this is not a job I’m going to enjoy.  It’s the old ‘buy an outside expert’ routine, which I detest.

PC: “Jim, the team is united behind this mission, are you on board?”

Jim: “Well, perhaps I could be on board, as long as what you want is an analysis, which may also justify the decisions you have made.  But it might not, so I just want to be clear on what…”

PC: “You  know what Jim?  I don’t feel we’re going to have a fit here, I’m getting you’re not a team player.  Thanks for your time”.  CLICK

Sigh.  I’m actually grateful they hung up, I really dislike explaining to people why I won’t work with them.

And that’s when I remember one of the most interesting moments for me during the WA conference season happened at webtrends Engage.

I was on the “Socialization of Data” panel with a great crew composed of  @jacqueswarren, @anilbatra, @johnlovett, and @bgassman.  We were talking about what web analytics might look like organizationally in the future.  Specifically, we were discussing the “Center of Excellence” concept, where all the senior analysts report to the same person, and this person typically reports directly to the C-Level.

There are many reasons this idea is a good one, but the one I often stress is relieving the pressure, explicit or implicit, on an analyst to produce a certain result from their work.  In other words, to “justify” a program rather than analyze it and get at the truth.

I said something like, ”You really don’t want analysts reporting organizationally to the group they are responsible for analyzing.  This set-up tends to create a lot of pressure on the analyst to prove a program is working by torturing the data to get a desired result.”

And about half the heads in this good-sized auditorium bobbed “Yes”.

These are the people who have been asked to change a date range, to modify a filter, to exclude a segment.  To justify a program by torturing the data into saying what someone wants it to say.

That’s sad.  Really sad.  In fact, it’s downright poisonous to the long-term health of Web Analytics (or any other analytical discipline) as a profession.  It’s a rot from within, difficult to cure.

The existence of ”justification” means the business is really not being run by the numbers.  What it means is the business continues to be run by “gut feel”, and the numbers are used to justify on the backend.

That’s not analytics, that’s a lie.

Depending on your experience, if you work in an environment like this, you might want to look elsewhere for a job, because eventually this game collapses.  It has to, you see; other people can and will get the correct numbers.

Especially in Finance.

And speaking of Finance, here’s the second most remarkable thing that happened to me on the Spring Tour.  I was talking with this web analyst who reported into Marketing.  One day, the CFO said to him, “You know what?  I think you should work directly for me.  What do you think of that idea?”

After an initial heart attack, the analyst said OK.  And he is so much happier, giddy in fact.  He loves his job again, really is fired up to get to the desk in the morning.  Why the change?

“The people in Finance get it, they understand what I have to say.  Nobody asks me to fudge the data in Finance, ever.  They just want the truth - good, bad, or otherwise.”

Funny how that works; I know exactly what he means.  If you are a profit-driven Marketer - and you can prove it - the CFO is truly your best friend.  Because a CFO gets Profit Math.

Then Web Analytics Maturity Models started getting a lot of attention due to the release of a new one from webtrends.  So I’m looking through the model and suddenly these two experiences from the Spring tour above pop into my mind.  I think:

You can have the best processes and procedures on the planet, but if you also have this Justification thing going on, if your analytical org chart is designed to fail, these Maturity Models are all just crap.  Literally.  A gigantic waste of time for everybody.

Worse than Scrap Learning.

Now, I’m not picking on webtrends here, because I like their model.  But what I don’t see in this model or the others is anything about properly Managing Analytical Cultures, like these org chart conflicts that drive Justification.  Not sure if this issue belongs in Governance, or Domain Expertise, or some other place.  I know the IT side has established “formulas” for Maturity Models, so maybe this org chart stuff doesn’t belong in the Maturity Model itself.

But this issue of reporting structure needs to at least be addressed in Maturity Model supporting documentation.  What good is it to have all the gears turning properly if the analysis itself is faulty, and drives continued poor decision making?  What kind of Maturity is that?

Speaking of chaos, if you’re in web analytics and find out your area has been targeted for downsizing but you would like to stay with the company, here’s an idea.  Head down to Finance and ask them if they would like their own web analytics person.  You might be surprised at the response.  After all, what is it most of the people in Finance do?

That’s right, Analysis.

What do you think about this issue?  Have you ever been forced to Justify?  Are you asked to run reports with “special parameters” for some programs?  To bury or exclude certain reports?

Got any good data torture stories?

Does this organizational topic belong in the WA Maturity Model?  If not, how would you handle it, where does it belong?

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Analyze, Not Justify

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

Q:  First of all thank you for your help.  I have some questions I would be pleased if you answer them for me.

A:  No problem!

Q:  1. RFM analysis - is it possible to use some other ranking technique rather than quintiles? Using quintiles for bigger databases will cause many tied values, isn’t it a problem?

A:  Sure, you can use it any way it works best for you.  There is no “magic” behind quintiles, you can use deciles or whatever works best. It’s the idea of ranking by Recency, Frequency, and Value that is the key concept in the model.

I’ve seen dozens and perhaps hundreds of variations on the core RFM model, depending on how you classify a “variation”.  One change that’s common is changing the scaling, as you mention above, to accommodate the size of the database.  Smaller databases use quartiles or even tertiles.  Larger databases, choose the ordered distribution that meets the need.

A more common modification is to convert “M” to different types of “value” depending on the business model.  Instead of Sales, people fine-tune the financial side by using Net Sales, or Gross Margin, net out discounts, etc.  Or they use non-sales representations of value tuned to the business model - ad revenue per visit, total days of activity, that kind of thing.

Further, what can happen is the analyst or marketer will begin  to see patterns underlying the RFM cells - in sales, response, location, merchandise, source, or some other customer variable.  This leads to cross-tabbing RFM score with other variables, and discoveries are made which lead to customized versions of the RFM model.

For the most part, I envision this work really as segmentation, meaning the scoring is not really modified - it’s the population the scoring is run on that is modified.  So for example, you run separate RFM scores for customers who are primarily  hard goods buyers versus primarily soft goods buyers.  This approach to scoring is sometimes referred to as RFM-C, where C = category. 

Or for large, ongoing campaigns, you can cross-tab RFM score by source of the customer.  This leads to “weighting” the value of campaigns not by Sales or Response, but the long-term profitability of the customer - you see campaign sources “clustering” in high or low RFM scores.  Some campaigns generate weak customer profiles, but the volume justifies doing them, as long as they are kept “reigned in”.  Other campaigns generate high value profiles who are “slow starters”, and might be killed if you only looked at Response and not RFM Score.  So the scores begin to play more of a role as a “standard” way to view customer value across categories, campaigns, channels, etc.  

This approach to scoring can eliminate a lot of the “gut feel” legacies that can happen in marketing and merchandising.  Sure, go with your gut, but let’s use a standard way to compare the results of your gut feel and produce a “gut check” comparison.

Q:  2.  I am planning to add user complaints and suggestions to RFM analysis.  Each complaint will decrease the user score and then cause to organize promotions just for users who had a complaint recently.  Is it a good approach to add it to RFM analysis?  (I am not sure but some are using this method.)

A:  I’m not exactly sure I know what you mean by “add”, but I think I get the gist of what you’re trying to accomplish.  In fact, this project sounds like an example of a company actually trying to “do something” about customer engagement and experience instead of the usual navel-gazing.  I have done these kinds of “apology campaigns” before and they can be very profitable, especially for most valuable or highly engaged customers.

The scores only are predictive on a single behavior being scored, so I would not involve 2 different behaviors (purchase and complaint) in the same score, since the result would be defeating to the purpose of the score.  I would not “adjust” a score directly based on a different behavior; I would score this behavior separately - and then use the scores in tandem to make adjustments in execution.  If you really want to use multiple behaviors simultaneously in a model, you need to move up the modeling food chain to regression.

As an analyst, you can of course “add” to the RFM scores any way you wish.  You can add any characteristic as a “tag” to a score but I would not involve these characteristics in the scoring itself, unless they *are* the score.  But from the perspective of a Marketing person who has to use the scoring, I would not want you to “corrupt” the scores themselves, but rather to segment by other variables and then examine and use the scores to act.

For example, if these complaints are in the customer account, you could score the customers on some other behavior such as purchases and include the RFM score in an account field, then cross-tab score to complaints.  For example, “Give me every customer with a high RFM score AND at least 2 complaints”.  Or lever off the complaints, “Of customers with at least 2 complaints, what are their RFM scores?”

Or, as discussed above, the complaint idea is an opportunity to create a custom RFM-style score for complaints.  Recency and Frequency are still important, but there is no Monetary Value.  Time frame may also be different for complaints than purchases, for example, past 30 days or past 3 months as opposed to a full year or longer.  You could generate this “RF” score and then use it in combination with the RFM score to drive different messaging to people by both:

1.  How engaged they are in some behavior

2.  Intensity and level (overall Frequency) of complaints, where the more Recent a complaint has been made, the more likely it needs to be addressed in some way.

Customers with high scores in both areas would be both most valuable to the company in the future AND at highest risk for defection.  This is, of course, an extremely valuable target from a Marketing perspective and one that should be addressed with great care.  Sending these people “normal” e-mail communications, for example, is much more likely to accelerate to defection than retain the customer.

Depending on your business model, for these highly valuable and likely to defect customers, you might want to skip e-mail or snail mail and get the President of the company to phone them!

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Hacking the RFM Model

We started talking audience segmentation and content at the eMetrics Summit, and specifically the “shootout” format from the old days.  You know, 10 vendors on the stage at the same time taking questions from the audience.  Those sessions were both educational and hilarious at the same time, as the vendors side-swiped each other on topics like accuracy, how visitors are counted, cookie structures, and so forth.

But that was back when the technology was in flux, and now that issue has settled down a lot.  Braden brought up the concept of returning the “shootout format”, but more on the business side.  You know, get some practitioners, vendors, and consultants up on stage and have them thrash out stuff like:

1.  Attribution - does it really make sense to even bother with attribution at the impression / click level when there is often not a strong correlation to profit?  I mean, just because someone sees or clicks on an ad does not mean the ad had a positive effect; in fact, it may have had a negative effect.  Why not go straight to action or profit attribution, instead of using creative accounting?

2.  Why is there so much focus on real time measurement and so little “taking action” in real time?  What’s the point of reporting in real time and then having monthly meetings to take action on performance?  Why not take a gut check on the numbers at noon each day and if you are behind target, do something now?  If your org will not “act now”, then why measure what happens “now”?

3.  Does tracking page views and visits really matter in all but a few models?  If your KPI’s are worth anything, why would you look at visits or page views except “forensically”, to troubleshoot a problem revealed by the KPI’s?

4.  Why do people spend so much time measuring really small, insignificant ideas while ignoring the “big levers” they could pull that would really make a difference?  Is it possible people don’t really understand the business model they are operating in and just measure a lot of meaningless stuff ”because they can”?

The panelists could define the problem (if any) and provide potential solutions and work-arounds for these challenges.  What do you think? 

Would you like to see “shootouts” between experts on these topics?  What other business / marketing topics would you like to see shootouts or group discussions on?

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

eMetrics “ShootOuts” We’d Like to See

The latest shiny object where Coupon Proneness comes into play is the “shopping cart recapture” program.  Mark my words, if it is not happening already, these programs are teaching customers to “Add to Cart” and then abandon it, waiting for an e-mail with a discount to “recapture” this sale - a sale that for many receiving the e-mail, would have taken place anyway. 

The best way to measure this effect is to use a Control Group.

When I hear people talking about programs like this (for example, in the Yahoo analytics group) what I hear is “the faster you send the e-mail, the higher the response rate you get”.

That, my friends, is pretty much a guarantee that a majority of the people receiving that e-mail would have bought anyway.  Hold out a random sample of the population and prove it to yourself.  There is a best, most profitable time to send such an e-mail, and that time will be revealed to you using a controlled test.  The correct timing is almost certainly not within 24 or even 48 hours.

That is, if you care about Profits over Sales, and trust me, somebody at your company does.  They just have not told you yet!

When you give away margin you do not have to give away on a sale, that is a cost.  Unless you are including that cost in your campaign analysis, you are not reflecting the true financial nature of the campaigns you are doing.  If you are an analyst, that’s a problem.

If you are using cart recapture campaigns, please do a controlled test sooner rather than later.  Because once your customers have Discount Proneness, it will be very painful to fix.

For that matter, if you are an online Marketer in a multi-channel company, you should be regularly using controls because they are the gold standard in Marketing Measurement / Campaign Attribution.

At some point, your boss will be more concerned about attributing Profit than attributing Sales.  Would be nice if your response to this question was, “Yea, we’ve been looking into that”, wouldn’t it?

If you’d like to hear more about this topic and see some example data on what these scenarios look like, you can attend this webinar:

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

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.

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Got Discount Proneness?

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

Q:  I’m a social media consultant, facing the interesting challenges of measuring success, and wondered, what are your thoughts on social media measurement and life time value? The two seem to go together, but if anyone has thought about it, you would have.  Would love to know your thoughts.

A:  Just to be clear, the following is specifically about social for use as a Marketing platform, not as a utility or a way to keep in touch with people.  Interacting with other people can create a lot of value - emotional value for the participants.  There are obviously lots of great uses for social platforms and I’m sure there is more to come in that area.  The question is: does any of this make sense as “media”?

Social has different faces.  So let’s specify for the purpose of the starting the discussion we are talking about social as an advertising media.  Then we will get into social as PR, social as Service, and so on down the line.

From a business perspective, I think people are over-thinking social as media, worrying about measuring what they really can’t measure.  If you have a clear objective, social media is just another source of visitors, with the same kinds of issues - how much traffic do I get relative to cost, do they convert, and so forth.  Which means you measure LTV just like any traffic source that generates activity.

That doesn’t mean there is not more value created from social media.  It just means the additional value is difficult to measure when you have a clear objective, so I view that value as a “bonus”.  If social traffic is working for you at some acceptable level relative to cost, that’s great because the actual benefit is greater than what you are measuring.  This, by the way, is true of all advertising.

Then you have social as PR, a way to “get the word out”.  People have been measuring PR for decades and the standard is to compare this “earned media” to paid media in terms of value of the exposures, e.g. if you believe a page in a magazine has a certain value then a full-page review in that magazine has the same value.  And probably a higher value, since it’s not “advertising” coming from the company, it’s (hopefully) non-biased content.

That’s the way it used to work.  You send your new Consumer Electronics product to a  magazine editor and maybe it gets reviewed.  If the review is a full page and it’s positive, and a full page ad costs $30,000, well by golly you just got yourself $30,000 worth of PR.

I suspect that is the way we end up measuring the value of social media as PR, and it’s probably the most reliable measurement.

If you are on the 3rd side of social, the customer service / input from community side, then social has the same value for these tasks the previous channels had - what is the value of solving a customer problem?  Of getting input from customers?  The value created is channel agnostic, so if you can answer the question for the phone, you can answer the question for Twitter.  The problem is, most people can’t answer the question for the phone either, so asking the question about Twitter amounts to a lot of navel-gazing.

What worries me quite a bit about the Service side of social is companies have had access to all this information about broken processes or poor product design for decades, and they have largely ignored it.  All they had to do is some analysis of call center data tic lists and they could identify and act on their “Top 10 Biggest Customer Issues”.  But they did not.  So there is a much larger organizational issue here, regardless of social media - what is the process we use to identify and act on poor customer experience? 

The bottom line is WOM has been around forever, and the measurement of it has always been controversial, so the measurement issue is not new to Marketing.  The fact online has more “data” then we usually have is helpful.

If you have a specific question or challenge to the above, I would be glad to respond to it. Dialogue is always helpful when you are dealing with new concepts and ideas!

Q:  I see social media as far more than a source of site traffic.  From a commonsense and anecdotal point of view, it’s ideal for building relationships, whether business or personal (and in most cases, both - the line is blurry between the two.

A:  If you look at the *relationships* as opposed to the technology, certainly message boards and e-mail distribution lists, some of the oldest  technologies on the Internet (The Well was founded in 1985), would qualify as Social Media, wouldn’t they? 

And “the rules” for proper engagement in those communities have been well established for a decade.

Interestingly, the “rules” people talk about with regard to Facebook and Twitter and so forth - “doing social media right” - are the same as were first published in the FAQ’s for these older communities.  People measured the value of participating in these older versions of community using goals, and I’m pretty sure those same ideas apply to Facebook, Blogging, Twitter, and anything else “community” that comes along, regardless of the technology.

Community and sharing are not new, they are the *very foundation* of the Internet.

Q:  Having said that, I must have another look at your book, to refresh my memory about how to measure LTV and how that could be done in social media.  In some ways, it should be easier because there are so many measurement points, but on the other hand, each interaction needs to be given a value as most of the interactions aren’t sales.

A:  Now it gets more complicated - is an interaction media itself, or just a vehicle?  Must an interaction create value?

You are speaking as if a channel itself can have LTV, and that is not a concept I can embrace.  In the context of LTV, the interactions themselves do not have value; what has value is the emotional output of those interactions; how people feel as a result of them.  

Just because I interact with something or someone does not mean there was value created.  So just counting interactions (remember Hits?) is not likely to be very useful, unless you are selling media, which is a different story.  Media does not have LTV, visitors / customers have LTV.

LTV implies a goal that has value, right?

If someone contacts me though my blog or Twitter and asks me to speak at a conference, the value of participating in the community is the value of speaking at the conference.  This really has nothing to do with the number of interactions I’ve had; I had the right interaction with the right person which resulted in the request.  If enough of those events happen, the aggregate value of emotions created in the community is the sum of all those values; it really has nothing to do with the number of interactions.

LTV requires a goal of some kind.  Counting “interactions” (or for that matter, “followers”)  doesn’t mean a heck of a lot unless those interactions result in reaching a goal of some kind.  Interaction for the sake of interaction itself isn’t really a goal, you need an endpoint.

Just because I broadcast a message to 10,000 people, doesn’t mean value was created; action must be taken to create value.

If I know I get one conference invitation for every 1000 interactions, then I have a way to keep score, but the interaction itself is simply a way to count.  If the value of speaking at conferences is known, then I know the value of participating in the various communities.

But let’s say you are really focused on the idea that the interactions themselves have value - generate Awareness, Interest, etc.

If you want to value interactions, you’re back over to the “media” side, and media has no LTV; the LTV resides in the actions taken as a result of the media interaction.  Counting interactions implies there is value in the impression created by the interaction (or why count them?); this means they are media.  Lots of people will see these comments or Tweets and an impression will occur.  Good.

If you want to take social as a media, I think the value of participation - if there are not specific goals (like a sale) - will be expressed like PR is, in terms of “impressions”.  Nothing wrong with that.

But, on the average, a single media impression (of any kind, online or offline) has little value - and this is true especially in these social environments where quantity is always stressed over quality (number of followers, number of accounts).

This is why “weight” is so important in media - because you need an absolute ton of these impressions to create any value.  With rare exceptions (Yahoo home page takeover?) it’s very difficult for the web to achieve weight in the offline media sense - the web simply is not built for that kind of mission.  

So that means it is going to take a tremendous amount of work to scale “social impressions” to the point where they are effective.  The exception will be highly targeted micro-environments where you have a very high quality audience for the message.

How else could you get scale?  Well, you could run Display ads across the base of all  interactions, of course.  And this is where you run into a paradox with the current ad-supported social business model; let’s follow this out to the next step.

If you think there is value in counting interactions, this means the social interaction *itself* - the actual Comment, the Tweet, etc. - is advertising, and so makes no sense as a vehicle for ads.  At best, these other ads dilute or distract from the content that is doing the real work in this scenario - the interaction.  More likely, the ads are simply annoying and completely out of context in the environment.

From my perspective, the very definition of social excludes it from ever becoming an effective carrier for advertising.  As I wrote in a blog post on this topic, participants are likely “Too Engaged to Pay Attention“.

I can already hear people squealing, “But Jim, social is a hybrid, it’s all of the above.”  That’s a convenient perspective, isn’t it?

Because as long as social is “everything”, there is not a right way to measure the Marketing value Social creates, is there?

It’s one thing to measure Social activity, there are a number of tools and you can spin endless variations on the data.

The more important question for consideration is this one: Why should the measurement of the value created by Social activity be really any different than what we already know how to do?

Comments on this? 

P.S. See you at eMetrics in San Jose?  I’ll be teaching the Site Optimization Course and delivering the 1st Brand Signaling Clinic.

Also will be looking for “user input” on a sample of WAA Certification Test questions.  Interested?  Be on the lookout for more info at show.

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Measuring Social Media Value

For example, did you even know there is a peer-reviewed journal called Marketing Science, which calls itself “the premier journal focusing on empirical and theoretical quantitative research in marketing”?

Whoa, say what?

This journal is published by the Institute for Operations Research and the Management Sciences, and articles are the work of premiere researchers in visitor and customer behavior from the best known institutions around the world.  In case you didn’t know, “peer-reviewed” means a bunch of these researchers (not including the authors, of course) have to agree that what you say in your article is logical based on the data, and that any testing you carried out adhered to the most stringent protocols - sampling, stats, test construction, all of it.

And, most mind-blowing of all, they show you the actual math right in the article - the data, variables, formulas, graphs - that lead to the conclusions they formulate in the studies.  You know, like this:

So, the opinions coming from Marketing Science are probably a lot more reliable than say, the average blogger in the echo chamber.  Know what I’m saying?  And here’s a surprise, the findings in these  articles often contradict what is passed off in the blogosphere as “common knowledge” by the digerati.

In case you are thinking, “Well, these lab coats can’t possibly be exploring anything that would be interesting to me“, take a look at some article titles in the Mar - Apr 2009 edition of Marketing Science:

* Website Morphing

* Real-Time Evaluation of E-mail Campaign Performance

* Optimal Bundling Strategies in Multiobject Auctions of Complements or Substitutes

* Path Data in Marketing: An Integrative Framework and Prospectus for Model Building

* Click Fraud

 Or article titles for the Jan - Feb 2009 edition of Marketing Science:

* Quantifying the Long-Term Impact of Negative Word of Mouth on Cash Flows and Stock Price

* Going Where the Ad Leads You: On High Advertised Prices and Searching Where to Buy

* Content vs. Advertising: The Impact of Competition on Media Firm Strategy

* My Mobile Music: An Adaptive Personalization System for Digital Audio Players

Tell me you want to put more faith in your RSS feed than in what these folks have to say in Marketing Science.  What blogger shows you the math?  What Research for Press Release piece passed around the echo chamber shows you the survey questions, the sample distributions, the confidence intervals?

But wait, there’s more.

The Research Committee at the WAA has been working hard on a program to open up some of these influential resources to WAA members.  You can see the beginning of those efforts here.  Expect more in the future as the effort ramps up.  The knowledge sources currently in the hopper are these:

By the way, if you are a WAA Member and would like to participate in reviewing these articles for the WAA Membership, volunteer for the Research Committee.  Contact Christopher:

christopherb “at” criticalmass.com

Now, you don’t have to agree with what folks who publish in Journals like these have to say, but as an analyst, I sure want to know what they think, see how they arrived at those thoughts.  And gut-check my own reality against them. 

Because the analyst’s mission is truth seeking, finding better truths.

Can you afford to ignore some of the most respected Marketing researchers in the world when formulating your hypothesis?

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Marketing Science (Journal)

What if what the media / agency complex has been telling you all along about online advertising is not really true.  What if Advertising  - from the end user (visitor) perspective - performs a fundamentally different job online than it does offline?  What if the entire game is different than you think it is?  Might that explain why it’s so difficult to get any agreement on the value of online advertising?

Please bear with me; see if this makes any sense to you.

Offline, it’s important that you remember an ad.  That’s because you are rarely in a position to take advantage of or act on the ad when you are exposed to it - unless you are sitting in front of a computer.  Awareness, Recall, all those nice measurements the offliners do are important for offline Advertising, because the job of offline Advertising is get you to remember it so you can Act on the Advertising when you are in a position to do so.

Online, you can immediately investigate the products or services advertised, get 3rd party opinions, and so forth.  You can convert Awareness to Intent and Desire in a matter of moments, if not take Action as well -  if you are interested in what is being Advertised.

The fundamental answer to every question you have about online advertising might be really simple, if you think this way:

Online Ads are Navigation

They are not Advertising, in the traditional sense of offline Advertising.

Content sources serve the role of traditional Advertising online.

Not the ad itself.

Online, the Web Site is the Ad.

Offline, Advertising sets up Awareness but it doesn’t have much to do with fulfilling Intent or Desire.  That’s why you need tremendous weight (GRP’s) with offline ads.  You have to pound messages into people’s heads so that when they are standing in the grocery aisle, or thinking about credit fraud, or whatever it is, they remember your offering.  “Ah”, you say.  “I’m Aware of a proposed solution to my problem.”  Now you can move down the road to Intent and Desire through examining the offerings, doing some research, asking friends or co-workers, etc.

If you are on the web and see an Ad, you have immediate access to “the answers” to any question you might have about the subject of the ad.  So the ad is just Navigation.  The Ad doesn’t have to be remembered, so is promptly forgotten.  If it’s relevant, it will be pursued.  If not, nothing.

If you think about it, this is the underlying reason why Frequency capping became popular in Display.  Online ads simply don’t carry any “weight” with them - if you’ve seen the ad 5x and you still don’t care, then you just don’t.  This is not true offline, because chances are you never had the opportunity to follow through with Intent and Desire like you can online.  So offline campaigns can run and run and still deliver incremental behavior, because there is such a lag in the Action phase.

Not so online.  If you are interested, you simply Navigate though the ad and it’s over.  There’s no reason to remember the ad.  If you do, that’s nice, but it doesn’t really matter.

And that’s why all the traditional measurements of offline advertising are meaningless online.  Because unlike any other Advertising out there, Online Ads are Navigation.

Stick with me for a story.

In the early days of ads on the web, click-through rates on Display ads were very high.  Display ads were pronounced to “work” and it was off to the races.

But here’s the thing.  This was before there was anything like a functional search engine.  So, ask yourself this question: Was the functional utility of this early display advertising for the user actually Advertising, or is it possible the true utility was Navigation?

In other words, the “value promise” of the ads was not the message of the ad as much as “Hey you, there’s a web site over here you might not know about”.  Recall, this was the age of “surfing” the Internet.  Discovery was the driver; people would click from one site to the other based on ads or links just to see what was out there.

Fast forward to the age of Search.  As search rises, click-through rates on display advertising begin to plummet.  And this should be no surprise, if online Ads are really Navigation.

A Search engine more closely aligns with the web medium where Navigation is a critical functionality.  Surfers found it much more rewarding to Search for what they were specifically interested in rather than “surfing” a random chain of sites.  It’s much more efficient, wastes less time, gets better results.

Later, you have the addition of Pay-Per-Click advertising, which you could argue is really not Advertising at all in the traditional sense; it’s Supplemental Navigation.  PPC ads say, “Here’s another site you might be interested in based on your search phrase“.  In that way, PPC ads are just like the early Display ads.  Except they provide more Value to the end user.  They work better.

If you think of Online Ads as Navigation rather than Advertising, does some of the conflicting information you have seen on the effectiveness of different channels, formats, and creatives become easier to understand?  Would some data help?

So, how can you act on this knowledge?

To me, this all means the most effective way to optimize Marketing Productivity is to think of different media not in terms of reaching different audiences, but in terms of stimulating different behaviors. 

This is the fundamental idea behind my Marketing Bands Model.

Let me know what you think.

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Online Ads are Navigation

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

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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.

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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.

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Take your brain out for some exercise, will ya?

Have a question on Customer Valuation, Retention, Loyalty, or Defection? Go ahead and send it to me here. If on the topic above, you can leave a comment on the post:

Marketing Jump Ball