Measuring dis-Engagement

Engagement Matters – Until it Ends.  Right?

Here’s something that continues to puzzle me about all the efforts around measuring Engagement and using these results as a business metric or model of online behavior.

If Engagement is so important to evaluate – and it can be, depending on how you define it – then doesn’t the termination of Engagement also have to be important?  If you desire to create Engagement, shouldn’t you also care about why / how it fails or ends? And if the end is important, what about how long Engagement lasts as a “quality” metric?

Seems logical the end of Engagement might matter.  Let’s call it dis-Engagement.  Simple concept really: of the visitors / customers that are Engaged today (however you define Engagement), what percent of them are still Engaged a week later?  3 months later?

Whatever dis-Engagement metric you decide to use, a standard measurement would create an even playing field for evaluating the quality of Engagement you create.  From there, a business could invest in approaches producing the most durable outcome.

Since Engagement is almost always defined as an interaction of some kind, tracking dis-Engagement could be standardized using metrics rooted in human behavior.  Recency is one of the best metrics for an idea like this because it’s universal, easy to understand, and can be mapped across sources like products and campaigns.  Recency is also predictive; it provides comparative likelihoods, e.g. this segment is likely more engaged than that one.

Plus, using Recency would align online customer measurement with offline tools and practices.  This could have implications for ideas like defining “current channel”, e.g. customer is now engaged with this channel, has dis-engaged from that channel.

Taking this path brings up a couple of other related ideas, in line with the discussion around customer journey and entwined with the whole customer experience movement.

Peak Engagement

Let’s say there is Engagement, and because we’re now measuring dis-Engagement, we see Engagement end.  So, is Engagement a one-shot state of being, meaning the value should be measured as such?  Or, does longer lasting Engagement have value, and if so, what about when it ends? Shouldn’t we want to find the cause of dis-Engagement?

Continue reading Measuring dis-Engagement

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss

Marketing Responsible for Customer Experience?

 The Data

According to this survey, Marketers are not now really “responsible”  for the customer experience (whatever responsible means in this context) but will be over the next 3 years.  If it was just the vendor (Marketo) trumpeting this idea, I’d be more skeptical.  But this vendor hired the Intelligence Unit from The Economist organization to do this work and the report includes the actual questions, meaning you can check for bias.  Population is 478 CMO’s and senior marketing executives worldwide, seems decent / not cherry-picked.

So I will cut the vendor some slack.   Questions though, right?  Just what is customer experience, in particular for the purposes of success measurement?  How does it fit with related ideas like Customer Journey / LifeCycle and Engagement?  Certainly if the above is a significant macro trend we ought to sort this all out first?  And of course, putting some analytical rigor (structure, process, and definitions?) in place to support the effort ;)

The Story

I know a lot of marketing people who have either had this authority for years (multi-channel database marketing) or are moving in this direction, so the results make sense to me.  To be clear(er), “experience” for these people reaches all the way back from UX into fulfillment and service.  So when they talk about experience, they are talking visitor and customer; not just navigation and landing pages, but also shipping times and return rates.

Perhaps increased access to customer data is revealing the significant impact customer experience in this larger sense has on long-term customer value?  This idea, coupled with increased focus on accountability (also covered in the survey) could be driving this trend.

Worth the read, only 20 pages long with a lot of charts.  Here’s 4 snippets to hook you:

Continue reading Marketing Responsible for Customer Experience?

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss

Do NPS / CES Feedback Metrics Predict Retention? Depends…

Survey Says?

Several questions came in on the ability of surveys to predict actual behavior, covered in the post Measuring the $$ Value of Customer Experience (see 2. Data with Surveys). My advice is this: if you are interested in taking action on survey results, make sure to survey specific visitors / people with known behavior if possible, then track subjects over time to see if there is a linkage between survey response and actual behavior.  You should do this at least the first time out for any new type of survey you launch.

Why?  Many times, you will find segments don’t behave as they say they will.  In fact, I have seen quite a few cases where people do the opposite of what was implied from the survey.  This happens particularly frequently with best customers – the specific people you most want to please with modifications to product or process.   So this is important stuff.

You’ve Got Data!

Turns out there’s a new academic (meaning no ax to grind) research study out addressing this area, and it’s especially interesting because the topic of study is ability of customer feedback metrics to predict customer retention.  You know, Net Promoter Score, Customer Effort Score and so forth, as well as standard customer satisfaction efforts like top-2-box.

The authors find the ability of any of one of these metrics to predict customer retention varies dramatically by industry.  In other words, you might want to verify the approach / metric you are using by tying survey response to actual retention behavior over time.

Continue reading Do NPS / CES Feedback Metrics Predict Retention? Depends…

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss

Measuring the $$ Value of Customer Experience

 Marketing IS (Can Be?) an Experience

Early on I discovered something from the work of leaders in data-based marketing business models: they were always very concerned with post-campaign execution – not only from marketing, but also through product, distribution, and service.  I thought this strange, until I realized they knew something I did not: when you have customer data, you can actually identify and fix negative customer value impacts caused by poor experience.

This means you can directly quantify the value of customer experience, budget for fixing it, and create a financial model that proves out the bottom line hard money profits (or losses) from paying attention to the business value as a result of customer experience.

And critically, this idea becomes much more important as you move from surface success metrics like conversion and sales down into deep success metrics like company profits. Frequently you see the profit / loss from “marketing” often has less to do with campaigns and more to do with the positive or negative experiences caused by campaigns.

Examples

You might think taking the time to provide special treatment to brand new customers would always encourage engagement and repeat purchase.  You’d be wrong.  Sometimes this works, sometimes this does not work, depending on the context of the customer.  Does it surprise you to find out customers often do not want to be “delighted”?

Continue reading Measuring the $$ Value of Customer Experience

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss

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.

Continue reading Is Your Digital Budget Big Enough?

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss

Omni-Channel Cost Shifting

One of the great benefits customer lifecycle programs bring to the party is unearthing cross-divisional or functional profitability opportunities that otherwise would fall into the cracks between units and not be addressed.  What I think most managers in the omni-channel space may not realize (yet) is how significant many of these issues can be.

To provide some context for those purely interested in the marketing side, this idea joins quite closely to the optimizing for worst customers and sales cannibalization discussions, but is more concerned with downstream operational issues and finance.  Cost shifting scenarios will become a lot more common as omnichannel concepts pick up speed.

Shifty Sales OK, Costs Not?

Why is cost shifting important to understand?  Many corporate cultures can easily tolerate sales shifting between channels because of the view that “any sale is good”.  On the ground, this means sourcing sales accurately in an omni-channel environment requires too much effort relative to the perceived benefits to be gained.  Fair enough; some corporate cultures simply believe any sale is a good sale even if they lose money on it!

Cost shifting  tends to be a different story though, because the outcomes show up as budget variances and have to be explained.  In many ways, cost shifting is also easier to measure, because the source is typically simple to capture once the issue surfaces.  And as a cultural issue, people are used to the concept of dealing with budget variances.

Here’s a common case:

Continue reading Omni-Channel Cost Shifting

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss

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?

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss

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:

Continue reading Digital Customer Analysis Going Mainstream?

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss

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

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss

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.

Continue reading Marketing to Focus on Customer. Analytics?

Share:  twittergoogle_plusredditlinkedintumblrmail


Follow:  twitterlinkedinrss