Category Archives: Digital Analytics

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:

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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”?

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Is Your Digital Budget Big Enough?

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

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

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

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

1.  Got Causation?  How success is measured

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

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

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

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Does Advertising Success = Business Success?

Digital Analytics / Business Alignment is Getting Better

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

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

Is Marketing Math the Same as C-Level Math?

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

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

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

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