The customer would be satisfied with consistency — the metrics of Customer Experience.

The past is where we want to go

The explosion of digital channels has created a fragmented Customer Experience where each channel seems to have its own face to the customer. The majority of shoppers out there are frustrated with the inconsistent marketing experience across channels. Why?

Direct marketers had this all figured out a long time ago while the retailer of the 50s and 60s knew that remembering a customer and keeping files on the best would somehow pay off.  It did!  Direct marketers knew the 40/40/20 rule – 40% of success is based on the right product/offer; 40% is based on the right target audience and 20% is based on the creative.  In other words direct marketing had figured out the analytics necessary to drive acquisition and increase retention.  What’s happened with the digital explosion is that we’ve forgotten our disciplines, if anyone outside the direct marketing community ever knew them.

The fragmented experience is the result of disconnected technology, data and analytics.  With marketing systems running in silos the majority of CMOs are as frustrated as their customers being unable to view customer interactions across channels, and across brands.

We all agree the personal experience we enjoyed more than 50 years is where we want to be now. Isn’t that what all this technology is for?  Corporate leadership wants marketing to become more ROI-focused with clear attributions but marketing is also being tasked to innovate and lead on the digital front to deliver a unified Customer Experience.

We are all looking for solutions and this article is intended to solve one small but important part of the puzzle — the structure of experience metrics in relation to the current state of customer analytics.


Users versus Customers

I’ve carefully listened to strategy conversations where User Experience and Customer Experience issues have been tossed around.  In the end both the UX and CX practitioners are, for the most part, confused.  This leads us to the question of what’s the difference and why do we care.  The difference really is a very important one in order to drive that ‘unified’ and ‘integrated’ Customer Experience.

Now I’ve given you a hint at the difference and where I’m going.

Customer Experience works broadly across multiple touch points and multiple platforms while User experience flows out of usability architecting the touch points of the digital interface.  The point is that the Customer Experience leader today is the multi touch direct marketer of 20 years ago aligning digital, offline, promotion, retail and web store experience into a single ‘voice of the customer’.

The bottom line is that within an optimized Customer Experience world the experience is personalized to increase Engagement, Advocacy, and Revenue

Bot to do this effectively the Customer Experience leader has to enable, within a set of marketing objectives, the existing connections customers and prospects have with other people.

Customer Decision Journey and the quantum leap forward

David Edelman transformed the way we think about this connection process.  We’ve jumped from a linear and progressive analysis to a complicated circumnavigation of the buying process and the analytics that go along with it.

So the funnel is dead and now we all talk in terms of the customer journey, touch optimization, and multi touch aggregated impact.  If only our database were big enough to deliver multiple statistically valid consumer ‘pathways to purchase’ within our RFM segmentation structure!!  Who said this was easy.  And where is this really actionable except in the large corporations with the resources to support both the infrastructure requirements and the necessary intellectual capital.

Where the funnel was simple the concept of the decision journey within a multi-dimensional structure on interconnected experience pathways is daunting for even an experienced marketer to think about.  Ultimately, however we structure our marketing campaigns, the marketing mix really hasn’t changed all that much if you consider, for example, display as an extension of media, email as an extension of direct mail, and so on (you get the idea).  Of course the analytics that tie this all together has changed but again not that much.  We are still looking at the same cross channel implication we looked at 50 years ago.  We just have a lot more touch points to manage and evaluate.

Here’s how we mapped the complexities of “new media” at Brooks Brothers for planning purposes:

Charles de Gruchy - Trading area experience management integrated all customer touchpoints plus customer profiling and segmentation to achieve a set of marketing and sales objectives

Performance metrics – strategic, operational, optimization and experience

Three groups of marketing KPIs tell us what’s working or what needs to change.  These three groups deliver a “direct” metric based on direct measurement of customer behaviors.  I’ve categorized them into the following groups:

  • Strategic
  • Operational
  • Optimization

There is a fourth group I look at as defining metrics for Experience alone but these measures are self-reported and not based on direct measure of customer behaviors.  As a consequence I view this group as indicators and enhancements to the first groups.

The following summarizes the Universe of Customer Experience KPIs as I understand it.

Summary of CX metrics by category

Where does Customer Lifecycle fit in?

The customer lifecycle continues to be the standard planning model for customer marketing with key emphasis on Acquisition and Retention.

Customer Lifecycle Model

Acquisition is still out there to acquire new customer and increase topline sales, brand equity and market share.  The challenge with acquisition is building and rationalizing multiple opportunities that will drive incremental non buyer (new and returning visitors) traffic to the store or the web-site creating opportunities for conversion and sale. But in order to benefit from the associated increase in brand equity the marketer has to be consistent, or in other words, has to stick to the brand proposition and not discount the hell out of the product.

The outcomes of successful acquisition programs are increased brand equity and market share. The equity builds shareholder value and has a ripple effect across the business in sales, share price, conversion rates and average sale.

Market share on the other hand delivers a wide array of tools to build a better financial positon for the business like pricing power, vendor leverage, and positive energy in the marketplace.

Retention and acquisition go hand in hand because in the end the overarching objective is to keep the customer database healthy.  One of my favorite analysis tools to accomplish that objective is ‘net customer analysis’ which looks at new and returning customer patterns on a daily basis (rolled up to weekly, monthly, etc.) netting out  to what the business has either gained or lost. The region or trading area views are highly compelling during the Monday call.

It’s at this point that analytics must enter the discussion.  Only analytics will find those upward migrators that need a little more attention, or those downward migrators who are at risk of attrition.  Retention, in my view, is an art based on integrating what we know about customer behavior with the fuzzy stuff that defines customer sensibilities.

Sensibility and how do I know we are making money

Customer Experience as an analytics universe adds a few metrics that we might not normally consider important (see Optimization and Experience metrics above).

If we buy that concept the rest is pretty straightforward.  A strategic view of KPIs forces a causal view of the numbers, for example, if ‘x’ happens than my numbers either tank or go up. See, it’s easier already.

A comprehensive approach to customer analytics is always most successful.  Customer Experience analysis is not different and, in fact, requires a strategy, a plan and training to avoid confusion.  We all know how to do that.  In the end the mix and emphasis will need to be directed by the demands of your organization and its stage of development.

Now let’s look at defining what each KPI means:



  1. Traffic — either direct, indirect, or unknown to the web or the store.

Direct – any traffic that is the result of a company action, for example, through the marketing calendar.  This includes all the usual suspects like email, sponsorships, direct mail, catalogs, a call centre program, search display, traditional media, social initiatives, etc.  Simply the activity must tie back to that customer traffic.


  • # of customers (not matched to the customer database)
  • By program, channel, store
  • Sales
  • Average sales
  • YOY change

Indirect — think of indirect traffic as the result of the brand halo.  Marketing programs drive a brand perception.  Alignment, consistency and personalization drive an ever improving/growing positive brand halo and the result is range of traffic unassociated to a marketing program or company initiative. Examples might include product placements, celebrity endorsements, customer initiated positive comments, and viral brand endorsements.


  • # of customers (not matched to the customer database)
  • By program, channel, store
  • Sales
  • Average sales
  • YOY change

Unknown – this is any traffic that can be associated with a source either another site, a promotion or any other associated program.


  • # of customers (not matched to the customer database)
  • Sales
  • Average sales.
  • YOY change
  1. Conversion Rate — the percentage of interactions that result in a completed sales transaction by channel, product, or other segmenting factor. For example. A web page visit is considered converted if the visitor places the order


  • Total the number of completed sales transactions and divide by the total number of interactions handled, e.g. the total number of converted calls divided by the total number of sales calls and with Google Analytics or Omniture.


  1. Rate of Engagement– the spread of an idea, technology or service within an identified prospect of customer population.


  • After defining ‘engagement’ within the organization take the total number of engaged prospects or buyers and divide by the total segment, group, and audience.


  1. Average Order Value (AOV) — the mean value (in monetary terms) for purchases. Reported in aggregate, by channel, segments, seasons and store trading area.


  • Frequently advanced organizations will calculate this on customer segment (e.g. income level, or geography)
  1. Churn Rate – the percentage of buyers who fail to make a repeat purchase or cancel a service


  • Total non-buyers divided by the total number of active customers over a required period of time.
  1. Net Promoter Score (NPS) – the percentage of customers that would recommend an organization to their friends,


  • Measured through customer survey with the key question “How likely are you to recommend X to a friend or colleague?” with an accompanying 0-10 scale. The Net Promoter Score is the percentage of Promoters (9-10) minus the percentage of Detractor (0-6).


  1. Campaign Performance –the return on investment for a given campaign initiative measured in incremental impact on business.


  • (net campaign revenue – marketing expense)/marketing expense


  1. Pages per Visit — the average number of web pages which are viewed during a single visit to the website.


  • More pages viewed frequently indicate higher engagement, a pre-cursor to sale based on the assumption that the site works efficiently. This is a primary metric in all web analytics tools.
  1. Shopping Cart Abandonment — the percentage of times a potential shopper puts an item in a real or virtual shopping cart and then removes it or fails to complete a purchase.


  • Measured through a custom configured 3rd party analytics tools.
  1. Cross Channel – defined as the percentage or frequency a buyer crosses channels to make a purchase.


  • Frequency of the behavior measured in # by period by channel of last purchase and percentage of total active file, group and segment
  1. Visitors, new vs. returning percentage — refers to the mix between visitors who are new and visitors who previously visited and are now returning for another visit.


  • This is a basic measure in all 3rd party analytics tools
  1. Frequency – is exactly what it sounds like. The number of repeat visits or purchases completed by day, week, month, annual.


  1. Items per Order – the average number of products or services added to a sales order


  • The total number of unique items ordered divided by the total number of orders


  1. Offer participation — looks at the performance of the offer strategy, for example, expedited delivery, free shipping, bonus products, etc.


  • Take the number of offer participants and divide by the total contacted.


  1. Sales per buyer and visitor — the average revenue a company derives from a single customer or visitor over a defined period of time.


  • Total revenue divided by the total number of unique buyers or visitors over time period as required.


  1. Cost of Sales – costs associated with selling products or services


  • Sum of all sales costs including sales salaries plus marketing expense.
  1. Marketing Expense – costs associated with activities to promote the company, brand, products or services


  • Sum of all related marketing costs including advertising and resources both internal and external.
  1. Service Costs – costs associated with supporting the customer’s use of the product or service.


  • Total ongoing costs required to do business including product/service support, infrastructure, product development.
  1. Cost per Interaction – business costs required to process or handle a given item, for example, call centre, customer contact/interaction, order, click, etc.


  • Total of $ invested in each activity divided by the number of associated activities that were completed.
  1. Self Service Rate – the percentage of all customer interactions that are completed using self-service channels


  • The number of customer interactions completed without sales assistance, divided by the total number of interactions handled by the organization across all assisted channels.
  1. Cost of Acquisition (COA) – the cost required to gain a new customer.


  • Total $ invested in acquisition marketing divided by the total number of new customers.
  1. Cost of Retention – the cost required to keep an existing customer


  • The total $ invested in loyalty, retention, points programs, pricing mark downs making the product more attractive to repeat purchase divided by the total number of customers who were offered these incentives
  1. First Contact Resolution – the number of customers whose question or request is resolved on the first attempt.


  • Typically measured by a post-interaction survey asking buyers if their issue has been resolved.
  1. Average Handle Time (AHT) – the average time it takes to handle a call, chat, email or other interaction. Includes time spent directly on the interaction and follow-up time to finish the sale, e.g. delivery, special services.


  • Calculate the average amount of time taken to handle a customer interaction from start to end when all follow up work is completed.
  1. Initial Training Time – is the amount of time required to get a new employee up to speed and become productive?


  • Count the total number of training days or hours required for new employees possibly including re training time for current employees.
  1. Content Effectiveness – the average number of site self-service answers viewed per buyer, non-buyer or visitor.


  • Available through all 3rd party analytics providers
  1. Escalation % — the percentages of buyers, non-buyers or visitors who start using self-service but escalate their issue to assisted service because they were unable to achieve resolution.


  • Available as a standard report with most 3rd party providers, e.g. RightNow CX.
  1. Channel Costs — the cost of a customer interaction per channel of communication.


  • Costs associated with a specific channel



  1. Customer Satisfaction (CSAT) — mean satisfaction score of customers for a given experience.


  • Measured through a customer survey that asks customers to rate their satisfaction with X on a defined scale with adjectives that range from ‘Not at all satisfied’ to ‘Very Satisfied. Often measured by interaction type.
  1. Customer Effort Score (CES) — a score that determines the relative effort required by the customer to work through an interaction.


  • Measured on a defined scale through a post-interaction survey.
  1. Emotion Scoring — a linguistic analysis of free text comments on social interactions.


  • Use of a scoring algorithm will codify individual comments on a scale of positive to negative. Scoring can be done on an individual interaction basis, aggregated to an individual level over the full life-cycle, or can be aggregated by segment or across the brand.
  1. Average Resolution Time — the time it takes to resolve a customer problem.


  • Typically this number is segmented by contact driver (why someone is calling) or channel (phone, chat, email, etc.). How to measure: The meantime, beginning when the customer first brings the issue to attention and ends when the issue is fully resolved.
  1. Channel Accessibility — For each channel (Web, Mobile, Email, Social, etc.), the channel should be “Accessible” to persons with disabilities, e.g. screen readers


  • Audit against accessibility standards






















































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