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:

“If you don’t accept accountability for being measured in terms of your contributions and outputs, then you are viewed as a cost centre.  If you aggressively pursue an agenda of accountability and transparency, then you’ll be viewed as a trusted partner and adviser.”

“A positive customer experience across all touchpoints is increasingly seen as a company’s most valuable asset.  And, more than any other function, marketing is responsible for managing it – across the customer life cycle.”

“Engagement, which used to be seen as more about branding and awareness, is increasingly perceived as key to the loyalty and advocacy stages of the customer life cycle. An engaged customer is one who sticks around.”

“Metrics will become broader and more comprehensive, focusing on top-line revenue and overall engagement more than efficiency and brand awareness.  Those who define engagement as brand awareness are less likely to think marketing needs to change.  These are the “traditionalists”, who see their main job as creating an engaging brand story.”

Ideas for You

If the conversion rate for a campaign is high, but 90% of responders do not interact again within 3 or 6 or 12 months, are these responders “engaged”?  For more info, start tracking open / clicks to emails by months since last open / click – you’ll see the pattern.

From analysis above, take a look at those customers who are still engaged – what was the first category or product purchased, do you see the pattern here?  How powerful would it be for merchandising & marketing to know specific products actually create engagement?

OK, now think about what you have.

What would happen if you crossed / pivoted these two ideas?  Could you create a matrix that would map the likelihood of engagement and customer value based on campaign and product?  Sure you could; it would look something like this.

Can you imagine the value this knowledge would add to the process of buying or creating products, deciding which campaigns to spend more or less on, or discovering the root cause of defects for business process teams working on customer satisfaction?

Summary

You now know engagement likelihood can be predicted using campaign and product, and this type of work does not require a degree in Statistics or “big data” infrastructure.

The above is only the beginning of course, but this approach allows you to get started with some very powerful yet simple tools.  Imagine a next step where you go beyond the simple campaign / product management described above and start feeding these “engagement variables” into the programmatic media buying process.  What’s the bid for a campaign / product combination that creates super-engaged, future best customers 70% of the time?

Further, the data collected from using these simple customer models is like rocket fuel for more advanced predictive modeling / machine learning.  If you have real data on a few  core drivers of engagement, you’re sitting on a pile of kindling you can use to fire up the more advanced techniques.  The PhD modelers will think they’re dreaming when they see a data set that includes actual outcome data for several engagement variables.

Some marketers will resist the trend towards being responsible for customer experience – we know this from the survey.  The challenge with that stance is this: marketing decisions are often the root cause of engagement problems.

Once this idea bubbles to the surface, I think it will be hard to resist getting on board.

Update:
Looks like Adobe and Microsoft Dynamics CRM will be helping out with this challenge!