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






















































Innovation is really re invention or is it just about the process! Direct Magazine June 15, 1996

At one point before I left graduate school I learned that the Peloponnesian War was really a precursor of one of our modern conflicts – the Vietnam War. I learned Napoleon marched his French troops to invade Russia, almost all of his troops died from frostbite, hypothermia and starvation. Hitler did the exact same thing. In the direct marketing industry we are constantly repeating ourselves but we don’t call it best practice and tend to be cautious about adjectives like ‘innovation’.

My partner and I were sitting around recovering from the day. I think it was about 11:00 PM and we were talking about calling it quits for the day.  But our conversation rambled on and into a discussion of analytics strategies. Our head of analytics, Steven Shaw, wandered over to put in his two cents in.  Of course he is a little biased in his point of view but his opinion is that the relationships between ideas, objects and numbers are all predetermined in one fashion or another.  There are no truly new ideas. What we represent as new is really the discovery of something that was already there.

So I asked what does that mean in the end or is this just the blather of three agency hacks. Oops, sorry Steven I shouldn’t have included you!  Brian, my partner, jumped in to say that none of this is really meaningful in that the new idea or the idea of the moment is just that. Where it might have emerged from or been adapted to is more often forgotten or simply considered old fashioned news of another generation.  We’re cool aren’t we?

Steven brought us back to reality and an analysis we were working on for Holt Renfrew. The objective was to understand the characteristics of best customers. The strategy was simple – figure this out and find more.  Not complicated from an analysts perspective but a challenge in the Toronto market where the top end of the file is measured in tens of thousands rather than 100s.  The approach he followed was to first cut the file based on an Arthur Hughes standard view with a ranking of Recency, Frequency and Monetary.  But he knew, in and of itself, that wouldn’t be enough to meet the objective of the analysis.  What emerged was a three step approach: first with RFM; second, to build persona on RFM and third, enhancing the result with modeling to asses specific points of propensity within the best customer group.  He asked the question whether there was any innovation in the process.

My quick off the mark response what that the steps in isolation were standard stuff of our business but the integration of the steps into a strategic progression of understanding of a group of customers behaviors is a significant innovation.  It’s the process that’s the innovation not the parts and pieces.

Brian jumped in to add that as corporate culture continues to degrade from the disciplined strategic planning methods lead by the packed good industry to something closer to organized ad hoc decision it’s the creation and management of process that will deliver a company a strategic point of difference.

Steven and I laughed but we knew he was right!

Things in Toronto were changing and changing rapidly. Business as moving south as quickly as it once came to the city.  Marketing departments were being dismantled with the center of gravity moving to New York and Chicago.       With change came ambiguity and dysfunction to a marketplace that was, frankly, the best run in North America.

Steven again pulled us back on track. We had executed the RFM analysis for Holts. Brian and I both wondered why they hadn’t done this themselves.  Is it that hard? Steven laughed and said no not hard but complicated.  It’s not so much the analysis that’s the challenge it’s the application across customer tough points that’s the problem Holts was a little more confused than most retailers because they believed that monetary was the key driver of next purchase rather than recency.

Steven then remembered a story from his good friend Lester Wunderman – there are a multitude of steps in any direct to consumer program but success isn’t in any one single step but is in the collective.  In other words it’s a successful process that delivers profitability.

Planning - core CRM strategy overview

So the process becomes the innovation today.

Our ramble ended at about 1AM. We know that the Holts project would work.  We were less optimistic about where the practice of business was headed.

What’s in a name 10/12/93

I have often asked myself the question, “What’s in a name?” when looking at what comes out of my mailbox and have concluded that most marketers don’t seem to have a lot of interest in using a name either appropriately or effectively.

Stepping back from the question for a moment, let’s look at where businesses seem to be headed. I have seen repeated, virtually, the same story again and again. The client says, “I need a database”–the magic words. The internal MIS people then embark on the agonizing process of attempting to create the perfect relational database, the kind that will answer every conceivable marketing question with simple, single-page reports at your desk, on your PC, within 5 seconds of the request.  Well, not quite.

Lets take another step back and ask why?

The efforts of so many corporations now recognizing the importance of their customer names are to be applauded. And also for seeing that there is value in those names. Where all of this falls short is in not seeing the what  in the name.

Another story — a very large company in this country is trying hard to understand the value of their extensive customer base.  That’s the good news.  By the time they have finished an extensive project (and investment), sliced, diced and dissected their customer base, found common characteristics between groups of customers, built predictive, regression and, maybe, airplane models, what will they have and what more will they really know about their customers?  Well — they will see where their customers live, know their customer characteristics in various forms, know what they buy and what seems to make groups of them buy at single points in time, but will have failed to know the individual or know the name   Think of the long term business risks for a Consumers Distributing, a Sears, or a Zellers should they fail to really know their customers and their customers needs!

Resources, budgets, people are constantly being thrown at the question “Who is my customer” without really ever coming up with an actionable answer. Why?

The answer is in understanding the importance of beginning with a strategy that will engage you in a dialogue with the individual  and not the group.  That’s not realistic you might say. Another story…

A major pet food manufacturer starts a customer club that you join by responding to an ad. Great idea. Next come the coupons and related products and newsletters, but so far they have no information whatsoever (or seem to care less) about me, as an individual pet owner, or even my pets…how many do I have, their preferred food brands, etc. How difficult can that be?

Whether Kraft General Foods, Tupperware or  Sony, direct marketing success tomorrow will be in direct proportion to how well the marketer understands each customer individually and how they want to buy. Remember, the customer has a choice — not simply about their price and product requirements. That choice might not be you just because they don’t happen to shop through the only channel you happen to sell your products through — retail, direct sale or whatever

So what’s in a name?

Simply, understanding the individual, his or her needs, purchase history, lifestyle requirements, and then demographics.  And, understanding that, within your database, their are groups who share the same characteristics.  But what you are starting with is the individual behaviours, before moving to the group.

What’s in it for you?

Whether you are a retailer or a manufacturer the bottom line is the same.  You save money once wasted on untargeted advertising while speaking efficiently and effectively with the people who want to buy your goods or services.

Final story.

A large specialty department store continues to provide only lip service to the idea of understanding the individual, the name.  The consequence is a failure to communicate. and the result  is lost business, business they don’t even know about. Why?  Well this retailer does not really know its customers at all.  They continue to send out unaddressed mail to neighbourhoods that the store managers think customers come from, with merchandise and service offers someone in the marketing group assumed might work, at a time when all other retailers are sending stuff out, too.  In addition,  the 27 customers who responded to one of these traffic builder programs with a phone order were told to come to the store and nobody knows whether they did — or did not!  Not a very disciplined approach.

Whether  Brettons , Holt Renfrew, or Eaton’s, the answer is the same. If you don’t, at least, get into the game, you’ll never learn what’s in a name!

And, can you really afford not to find out?

 Charles de Gruchy remembers how it was

The evolution of customer based analytics Direct News November 6, 1992

Many hard-headed chief executive officers fear half of all money spent on direct marketing to woo new customers is wasted.

Not anymore, say proponents of direct marketing!

Measurable results are possible as techniques evolve

To tally up the effectiveness of individual campaigns, the value of a long-term relationship with a customer or the overall impact on business is becoming a must do.

The bottom line, say proponents, is calculating what a customer is worth over time which opens the door to a profitable, long-term relationship.

Put aside traditional measurements such as cost per order, or cost per lead jump into sales per customer, or customer valuation.

The importance of segmentation

A new word has emerged in the vocabulary of marketers — segmentation!

Our field has moved on to adopting segmentation as a baseline for understanding customer value.  Marketers segment their database to identify key pockets of customer value  and to evaluate the worth of those segments to their portfolio.   Return on investment analysis, which calculates returns on specific campaigns, has evolved to include better targeting of different customer segments; and measuring lifetime value.

Measurement of direct marketing campaigns is becoming more sophisticated for a host of reasons.

For starters, computer technology, hardware and software, has advanced to a point at which marketers can collect, sort and manipulate customer database information with greater effectiveness and reward.

What is more, hard times means marketers want more from each dollar spent on pampering existing customers and securing new ones – precisely the point of interest from which direct marketers start.

The reasoning is, if you do not know what a customer is worth, you cannot be sure how much money to spend to acquire one.

And you certainly cannot decide which media are best in capturing new customers: the mail, tv or a sales force.

Even so, proponents of direct marketing today battle against ceos who remember doling out money during the go-go 1980s to test or start a program, only to get scant returns.

Smart marketers are today coming round to the importance of establishing life-long relationships with their customers. They must develop the science of building relationships with people.

If you look at customers as worth far more to you over time, you will do more to bring them to your side.

And because the future value of customers determines their current worth, measuring that lifetime value analytically helps marketers decide how much they should spend today to turn one-time buyers into lifetime customers.

Objectives lead the way

Of course, successfully measuring direct marketing campaigns, say proponents, calls for establishing key objectives beforehand.

Virginia Greene, direct marketing manager with Go Direct Marketing in Vancouver, says direct marketing exists precisely to build long-term customer relationships.

For this reason, Greene’s clients aim at developing a business strategy and not simply holding a campaign or two.

‘If you want to do a simple mailing, go somewhere else,’ she says.

Much depends on whether companies are looking for immediate results from direct marketing approaches – in the case of fundraising groups, for example – or whether companies are only looking for leads they can follow up, as with an automaker.

Much also depends on whether marketers are focused on developing a product, a market, choosing media or a host of other variables.  Whatever the objective, measurement tools help establish whether it can be attained at the end of the campaign. Moreover, they help decide how those objectives might be altered to increase profits should the effort be repeated.

For example, a telephone company might see value in looking to secure three-year contracts for cellular phones from new customers during a campaign.

If so, Greene says she can employ tools to measure the return to the client at the end of the campaign, indicating, for example, $10,000 was spent to bring in $100,000 worth of new business.

Do not fail to know your customers

Of course, objectives are only meaningful if marketers know who their customers really are.

Steven Shaw who runs our analytics effort at Salter, de Gruchy is very straightforward in his view of customer metrics.  He starts with Recency and goes from there. ‘So many agencies start with demographic or psychographic segmentation then become lost trying to establish customer value.’

Using segmentation as a customer valuation process to develop a useful and exact customer profile serves this task.


Your best customer is in front of you right now!

Marketers, for the most part, know their own customers are their best prospects for future sales, that is, if they know how to take advantage of prospect responses and mapping high value customer behavior.

Despite this fact, most companies have marginal capture rates and limited systems for managing their customer data  – containing names and home addresses, for example – and generally not one they can sort, track and manipulate for greater impact.  They have little idea what their lists contain, what to do with them, or whether they work for the company.

‘If you don’t have the right names on your database, or have rented a bunch of random names, you might as well use broadcast media,’ Shaw says.

Segmentation and the value of the top 20%

Segmentation entails organizing your customers based on their recency of purchase, frequency of sale and monetary value identifying the best value segments to respond to a particular product or offer.

Using this kind of analysis marketers can then buy outside lists, build alliances with strategic partners and optimize results  by picking out only those segments that are predicted to work.

Marketers in packaged goods, faced with declining brand loyalty in hard times, recognize the key to survival may be a matter of focusing on the top 20% of customers who buy 80% of products.  If a company can identify them through segmentation, and succeed in keeping them a customer for only a year or so longer by pampering them, that could well mean increased profits and future sales.

Elsewhere, a specialized financial publication might be mailing to a national weekly magazine’s list and find few responses.

It could then use segmentation to pick out only those names reflecting a preferred set of customer characteristics. Or it could use Statistics Canada data to find only those households with above-average incomes.

Better targeting during mailing opens the way to better response and retention rates around the corner.

But it’s not just about customer retention

Of course, no wise marketer will pamper his/her best customers without going after new ones!  Dave Taylor, Toronto-based chairman of Taylor Tarpay Direct Advertising, put it this way:

‘The danger is you will end up reaching to the converted, and deal with an ever-narrowing market niche because you gradually penetrate that entire market. If so, you won’t be bringing in the heathen.’

At some point, Taylor warns, marketers have to assume the risk of going after new customers that are not as productive as are ‘hot names’ early on.  Establishing which customer value groups are more prone to buy your products through segmentation may also help decide which media to use when choosing advertising channels.

Dave asks, ‘Why not use in the future what has made your products profitable in the past?’

And, there is value in the middle of the file

As managing partner of Salter de Gruchy Direct, I am consistently making a single point to our clients that, ‘short-sighted marketers are missing cross-selling and up-selling opportunities’ every day in their customer file.’

I strongly believe that while ‘It’s fine to be well-positioned,’ if you ignore deciding how to retain customers, then you might well go out of business in time.’ Direct marketers are indeed throwing away money if they profit from a new customer and then let them slip away.

The fact is, loyal customers deliver a useful income and profit stream that far exceeds the value of their original purchase. There is much to be gained from retaining a customer and selling to them for years to come.  But these customers are created.  They don’t just walk in the door!

Record and book club marketers know this lesson well. One of the ways they woo new customers is by offering six books for one dollar. Initial responses may well lose them money. But profit will come on purchases club members make down the road.

So Where’s This All Going?

Direct marketers everywhere act in a similar way. Scarce resources are used to get customers in the first place. The profit comes from future relationships with customers they have successfully brought on board.

Once marketing objectives are set, and customer lists are productive, companies are increasingly using return on investment analysis to project paybacks from specific campaigns.  They do this by taking the total dollars spent, and total revenue received, and figure the total return on the program.

This is key because, for all the hoopla surrounding direct marketing, bottom line CEOs want to know whether the job can be done, within budget, and when they can expect a payback.

John Wright, director of direct marketing at Toronto-based Promanad Communications, argues companies are also measuring marginal returns on investment, or the profits possible from pursuing different audiences.

As Wright puts it: ‘Let’s say you ask whether to send 100,000 pieces of mail or 75,000 pieces during a campaign.

‘Traditional return on investment analysis calls for costing both efforts and calculating the likely response rate overall to figure out the return,’ he says.

Wright says in a profitability analysis, what is considered is how much profit is wanted from each person approached, adding what is then determined is how many people will be marketed to based on that calculation.

‘You can decide between sending mail to 45,000 people and 45,001 people because you know the incremental profit possible from each person you approach.’

Greene says she can tell a fundraising client how much money the company will bring in at the beginning of a fiscal year, within a 5% margin of error.

The fundraiser will know the cost of bringing in new donors, and of getting past donors to repeat their generosity.

‘With that type of data, you can say if you mail to 1,000 people, 18% of them will respond by each giving you $37.50 on average,’ Greene says. ‘And if you mail yet again later on, you will receive so much from them.’

Likewise with credit cards for department stores.

Greene says an in-depth study of customer relationships can identify how much existing cardholders spend annually, and how many years they have held cards.

Using various calculations, the department store can then estimate how much each new cardholder recruit will spend on average over how many years.

What’s this Lifetime Value thing?

Shaw notes that an ‘analytical tool gaining in popularity is measuring lifetime value of customers.’ This allows marketers to measure how many responses they might gain from a campaign, how many they might retain over time, and how they might estimate the current worth of future profits.

Ted McGregor, the Toronto-based direct response manager at Radio Shack, says the electronics retail chain has a mainframe computer in Barrie, Ont. capable of tracking responses and calculating the lifetime value of customers.

But why is measuring lifetime value specifically useful? Most marketers rely on using profit or loss per response to decide which mailing will solicit the most prospects.

But this approach overlooks future profits from repeat customers. Nor, unless you measure marginal returns on investment, does profit or loss per response employ scarce marketing dollars to best effect.

In the insurance business, calculating the lifetime value of a policyholder is crucial to drumming up new business.  The exercise calls for defining the present value of a future stream of net contributions to overhead and profit expected from the new policyholder.  The lifetime value model focuses on the future, that is, spending behavior and the cost of retaining customers, and reselling to them over their entire projected lifetime.

Keeping in mind that future dollars are worth less than what they are today, the future value of a customer must be discounted to arrive at an equivalent present value owing to inflation and the cost of capital.  Of course, proponents of direct marketing caution that lifetime value calculations are not for everyone.

A case in point: the Lexus division of Toyota Canada runs an upscale direct mail campaign to lure prospects for its luxury car models.

Wayne Jefferey, general manager at Lexus, says developing and refining the car maker’s customer database is key to the success of the campaign in finding exclusive car buyers.

‘Most people send out direct mail and hope for the best,’ Jeffery says. ‘You can’t do that.’  He says the car maker spent a lot for software to measure the effectiveness of the direct mail campaign, but found response rates did not climb as a result.

Jefferey puts this down to the small size of Canada’s luxury car market. Only 45,000 luxury cars were sold in the country last year, and 3,900 were sold by Lexus.

‘We get to know our customers by name,’ he says.

I argue only larger, established companies are looking to lifetime value calculations with seriousness.

I’ve often asked who ‘In the real world, who is doing lifetime value?’  ‘Not many. Most companies are not even to the point of operating an electronic database let alone implementing a standardized customer valuation tool like CLTV’

And in the end?

Measuring the effectiveness of direct marketing is made easier by thinking of one’s long-term relationship with a customer as a brick wall.

Each effort to make that relationship is a brick. And the foundation of that relationship is the product on offer – that attracts customers in the first place.

As more and more companies come to lay the foundations for future relationships with their customers, the worth of measuring progress along the way grows.

Companies are coming slowly but surely to see the worth of measurement tools. And as their popularity grows, so, too, do the efforts of direct marketing practioners to make those tools ever more sophisticated and accessible.