I hadn’t expected this to be a trilogy. When I posted Prediction and Predictability, it was just some internal discussion document I’d written a long time ago, that somehow found its way to the light of day. Ironically, given the title, I had no idea that anything more would become of it.
But like George Lucas and that crazy standalone space story he had lying about, very soon, there were obvious questions that needed to be explored – and eventually, the demand for a whole three-parter.
Admittedly, Mr. Lucas was fulfilling the wishes of moviegoers around the world, whereas I simply asked if I should “turn this into a Trilogy” on LinkedIn and, very kindly, one person said yes. You might say that’s nothing like the same thing but I think, principally because of the way I’ve worded the second paragraph, the comparison still stands.
You see, words matter. Big time. I wrote something about the power of words here. They are the bricks with which we build meaning and understanding. There are whole branches of science that believe they even shape the way we think.
And they’re being weaponised like never before. Okay, not like never before, but certainly more routinely than ever before
Before we get into that, let’s re-cap the story so far, through the medium of The Marketing Textbook:
You’ve looked at your list of customers and looked at where and how they differ. You’ve defined those groups and and chosen those you wish to contact. Using our friend Ed Mayer’s analysis, you’ve now determined your audience, something he suggests can contribute upto 40% of the success of any campaign. In short, you’ve chosen the people whose Attention you feel you can gain.
You’ve looked at each pf these groups, analysed their various profiles and tried to understand what may best motivate each group. You’ve decided what the offer should be to most effectively reflect those motivations. Again, Mayer suggests that, done well, this should make up another 40% of your campaign’s success. The key metric at this stage is level of Interest you can generate.
And now, the next bit: the execution. Specifically, what words and pictures, tone and format are going to take your campaign from being merely eye-catching and attractive to becoming compelling enough to achieve the best level of success? Mayer states that this is where the remaining 20% of a campaign’s effectiveness lies. Words must take us well beyond the constraints of simple communication at this point. They’re there to create Desire. Finally, we must also ensure we finish off with an effective Call to Action.
At this point, ‘old-school’ marketers would be gleefully deploying a wide range of linguistic and literary tricks of the trade to create a favourable image, to flatter the reader, to build credibility, to suggest like-mindedness, to build towards a USP. In short, to construct all the elements of face-to-face salesmanship, to take a curious prospect and point them towards the life-affirming status of customerhood.
Look at any 1970s press ad and, once you’ve tried to ignore the almost constant casual sexism – and, sadly, more besides – you’ll see that writing ad copy used was very often a protracted attempt to schmooze the reader into submission, with florid language and ridiculous metaphors. Even ads for bread could use up three columns of text to luxuriantly, verbosely, disproportionately extol the virtues of the open sandwich:
“The Danes call them smørrebrød. But never mind that.”
All this self-importance from a time of fewer distractions and greater attention spans has contributed to a lingering stereotype of marketing presentation being a little insubstantial, superficial… …’fluffy’. Like any stereotype, that may well be based on a kernel of truth but it isn/t really a fair depiction, especially without the consideration of context.
Time – the availability of it to the reader – seems to be a key reason behind the changes to the words to which we most-demonstrably respond…. Sorry, I’m in the wrong decade to structure a sentence like that. I’ll try again:
Today, we expect punchier words. Shorter sentences. Day-to-day language and less ‘correct’ grammar. If that means less nuance, so what? And it’s nothing new – the further back you go, the longer ads seemed to go on for.
It’s easy now to lampoon even famously ground-breaking ads from the mid-20th Century for the length of their prose, their seeming ‘over-production’ but again, context plays a part. They were consumed in an age where time and attention were more abundant, where you had a whole five seconds to lure the reader into deciding whether or not to read on for the full half-minute. To quote Obadiah Yorkshireman, “Luxury!“
The actual ‘Lily The Pink’
Yes, even in those heady days, there were still limits to attention. Go back even further to the 19th Century and you see ads for the most utilitarian products, like soap, that were billed with the same sort interminable of ‘step right up’ repetitive hucksterism and dubious claims that you only really hear from boxing emcees these days. People back then must have had attention spans that ran into minutes! The very distinctive selling style from this time was memorably satirised by The Scaffold in the 1960s, a treatment which really was “most efficacious in every case”.
It seems inconceivable today that anyone could write a strapline like “It is a truth universally acknowledged that a man in possession of improving prospects must be in want of a better soap“. But in the context and era-defining phrasing of the recently-published ‘Pride and Prejudice’, it could have been the 1813 equivalent of “Got Milk?“.
Back in the 21st Century, we’re now expected to get the whole ad done with in five seconds. How do you realistically establish credibility, demonstrate need, get to the Unique Selling Proposition and give your Call To Action time to land in that time? You have to edit it right down. and make every character count. It’s not just fewer, shorter words, it’s the maximum level of promise you can elicit from what remains – and for that to happen, there’s been a grammatical evolutionary advance.
Remember, we’re in the business of ‘promise’ here and this was almost always conveyed by description; how something was, how it made you feel. ‘Luxurious‘, ‘Tasty‘, ‘Confident‘, ‘Unbeatable‘. The product was represented with the most flattering describing words (adjectives) available whereupon the consumer was simply invited to appreciate that description and, if they agreed – how could they not? – do the obvious thing and buy into it. Literally. The virtues of the product were used as a means to appeal to – and unlock – the discerning customer’s critical faculty. The language might have become slicker over time but we were still mostly flattering the reader into submission.
With less time to process all this impeccable logic into two-stage flattery and recognition, even the loveliest descriptions quickly become little more than a mushy word soup, just as Jane Austen would have become to our Boomer parents and grandparents. How can we continue to assume that flattery gets you everywhere, if you don’t have time to do all that? More recently, all we really have time for is just to tell people what to do.
Adjectives have become dinosaurs, Verbs are their mammalian heirs.
As you’ll remember, ‘doing words’ are not adjectives but verbs. They’ve always been there, evolving where their natural advantages allow but more recently, they’ve begun to out-compete slower, more cumbersome forms. Linguistically, we seem to be experiencing little short of a mass extinction event, a transition from the Adjectivian into the Verbian era, which is every bit as profound as the end of the Austenian eon, long ago. There’s an old political adage that says “if you’re explaining, you’re losing” and it follows that if you don’t then wish to ‘explain’, you won’t need to describe. It’s quicker and, it seems, more productive merely to instruct.
Many commentators have remarked at the growth of the verb-based slogan in the last decade over the adjectival equivalent, particularly its apparent suitability for political slogans. Thus ‘Take Back Control‘ out-performed ‘Stronger In‘ in the 2016 Brexit referendum. Later that year, Trump’s ‘Make America Great‘ pipped Hillary’s ‘Stronger Together‘. In 2019, Boris Johnson told you he’d ‘Get Brexit Done‘ while Jeremy Corbyn’s Labour were, as it transpired, unconvincingly ‘On Your Side‘. When we were faced with the stark uncertainties of the Covid-19 pandemic in the spring of 2020, the measures required of us were boiled down to similarly short, verb-led maxims. We now expect that such comms will follow this simple but clearly effective format and, inevitably, the same is true of marketing messaging.
But here’s the bit that’s often missed: you can’t just tell people anything and expect them to do it – there has to be something in it for them. Remember ‘feature’ and ‘benefit’? That’s still very much a thing, possibly more than ever. So the other stipulation in this new era is that the verb must convey some form of advantage. ‘Make‘, ‘Build‘ and ‘Save‘ all imply the construction or retention of something worth having. ‘Get‘ goes even further; it suggests the acquisition of something worth having. The only downside it has is that it’s harder to adhere to a promise of something being acquired – what if you can’t actually give the thing you’ve mentioned to everyone who read it?. Conversely, making and building things is a process, expected to take longer, which may even be revised thereafter, so it’s much harder to suggest that such a promise isn’t being kept.
Obviously, the other words have to convey some sort of positive outcome. Three words seems optimal but Subway and Alamo have boiled their straplines down to two. “Eat Fresh” and ‘Drive Happy‘ are notable for using only a verb which conveys the things their customers do, paired with a stated advantage imbued in that brand. Both choose not to turn the second word adjective into its correct adverbial form (“freshly” or “happily“).
An actual 1970s soap ad. Spot the sexism.
Back to that hypothetical 1813 luxury soap ad channelling Miss Elizabeth Bennett’s narrator: such a brand would, throughout that century, have extolled at length its highly-acclaimed (but unverified) efficacy, just like Mrs. Lydia Pinkham’s’Vegetable Compound’. By the mid to late 20th Century, its tone would have changed to mirror a more aspirational time, in which even a brand of soap constituted a lifestyle choice. It would also stop being marketed at men because as a household item, only women would be responsible for its purchase. It might suggest an exotic, even ethereal provenance and address psychographic rather than utilitarian benefits. Full-page glossy magazine ads would be filled with nouveau-riche couples smiling confidently, while not using the product, with terms like ‘secret weapon’ and ‘jet-set freshness’ punctuate the lengthy prose before a small picture of the product, suitably lathered, to remind you what’s being sold.
In contrast, such a soap, would now find itself continuing to connote aspiration and success but having slipped to mid-market affordability – or even lower. Social ads now feature a suggestively-posed, provocatively-cropped pair of same-sex, ethically diverse, naked millennials in a bathroom with the ironic headline ‘Get More Lathered’. Obviously, its true market is still 30-to-50s, as it always was, but something has to cut through our heightened defences, to divert eyeballs just long enough to make another 0.05% think it worthwhile clicking for more. Obviously, any hint of sex is a proven way to do that and, given our more enlightened times, we can all pretend that it’s not prurient anymore but inclusive and challenging. Whatever, dude. I made you look.
Again, I’m possibly exaggerating a little for satirical effect – but not by that much. Marketing literature has always been easy to parody because it has always had to be easy to distinguish and recall. Remember: the reason why so many of these historical campaign are so easy to poke fun at now is because, then, they worked.
Some suggestive soap. Possibly more compelling than advertising it in the style of Jane Austen.
Any marketer worth their salt will know the value of segmentation and many will be practising it to some extent – but are you doing it properly?
A few weeks ago, I shared a discussion document, about the ability to predict demand curves across segments – and how it was beneficial to work with a greater number of smaller segments, to aid predictive ability.
But this is only half the point of Segmentation. It’s all very clever to be able to decide which segments will and won’t reward the cost and effort of contacting them but that logic ignores one massive extra variable, which can change everything – the fact that you don’t have to say the same things to the whole list.
Having gone to some trouble to understand and divide up one’s customer base, it doesn’t exactly make a lot of sense to stop there. If we now know what makes the people in ‘SegmentX’ different from ‘SegmentY’, why aren’t we incorporating that knowledge into our messaging?
If we were working in a face-to-face environment, this information would inform our choice of words. A well-known long-standing ‘good’ customer will, of course, be received quite differently to a new face, not quite sure if they’re in the right place. You wouldn’t use the same salesmanship to sell to an elderly lady as you would to a teenage boy. You’d incorporate all the context you have at your disposal.
So why would you expect to gain the best response from an activity that puts the same words and pictures in front of every recipient on the list? The larger your database, the greater the potential to identify distinct differences across the list – and speak to each segment in a context that far more accurately reflects their part in the customer life-cycle.
By that, I don’t just mean the ‘textbook’ groups of Prospects, Triallists, Current Customers, Lapsed and Cold – although that would be a start. There’s also the possibility to identify ‘Risers’, ‘Fallers’ distinctly from the ‘Non-Movers’ (people who are continuing to exhibit consistent purchasing behaviour). At a time of flux in the wider economy, how many of your customers are suddenly struggling to afford the things you offer and are cutting back? How many are now doing well – or have down-traded from a more expensive competitor – and seem to be making a flurry of unexpected purchases? How do you understand these segments? And how do you best stimulate them?
Instead of your brand being simply the same version of itself, whoever is reading – like an old comic book from the analogue age – it should really inhabit a ‘multiverse’, where different audiences view it in different ways and you ensure it engages with each of them accordingly.
Of course, we do practice some context-driven differences in our messaging – but it tends to be informed by the medium, not necessarily the recipients. We’re likely to word our social activities differently because we’re aware of demographic and behavioural biases across them: younger, sharper messaging in Instagram and more professional-sounding, commercially-aware content on LinkedIn. Largely this is based on assumptions of the profile of each medium and, rightly or wrongly, rarely verified by any analysis of the populations themselves.
So, what of email messaging or, more importantly, expensive direct marketing? How are they best served by a ‘once size fits all’ approach to large quantities of very different people?
When this happens, we tend to write imprecisely and blandly. The effect is like Christmas Day television: suitable for all but a bit….boring It can also risk sounding inconsistent, or even self-contradictory to some parts of the audience – but if there is no seemingly viable alternative, we arrive at a ‘lesser of all evils’ fudge. It can result in a *targeted mailing*, which – and I’m exaggerating only a little for the purposes of satire – can read a little like this:
Dear Sir/Madam/Non-binary Identifier
You’ve been a Prospect/Customer of ‘GenericBrand’ for a number of months/years so, like everyone else, you’ll be delighted to learn of today’s exciting announcement.
And, like everyone else, your purchase history and product choices suggest you’ll be really interested to learn about our offer – which we’re also making to anyone else who’ll read it.
Still, we know that this is just right for you because, on balance, this is right for everyone, based on our knowledge that the last time we did this sort of thing, it proved to be a few percentage points more popular than anything else we’ve tried.
Please respond ASAP, to genericbrand.com/genericlandingpage and you too can redeem this great offer – just for you!
Very often, the justification for this sort of uninspring guff is that the polar opposite seems even worse. Using our ‘knowledge’ of the recipient to appear to be a benefit to them seems to be an exercise in proving our omniscience – which can easily scare the reader into wondering what the hell else this company knows about them.
Dear <TITLE> <FORENAME> <SURNAME> of <ADDRESS_1>
We’d like to thank you for being a fan of ‘GenericBrand’ since <TIME_CREATED> on <DATE_CREATED>. Because of your affinity to our brand over the last <DAYS_SINCE_CREATION> days, we think you’ll be interested in this message!
Also, given the fact that, in that time, you’ve placed <TOTAL_PURCHASES> purchases, worth <LIFETIME_VALUE>, we think you’re ideally suited to this offer – <TAILORED_OFFER_1>. We hope you agree, it’s the best offer we’ve made you in <DAYS_SINCE_CREATION> days!
To redeem it, all you have to do is visit genericbrand.com/tailoredoffer/1 and be fully confident that your next purchase – number {<TOTAL_PURCHASES> + 1} – with GenericBrand will be the best you’ve ever made with us!
And, it’ll be with you at <ADDRESS_1> in <POSTAL_TOWN> in no time!
There is – as always – a better solution in between the extremes. Data will always drive these distinctions but salesmanship is still storytelling and, as any film-maker will attest, ’show, don’t tell’ is the best way to go about it. Customers don’t want to be beaten about the head with how much you know about them; they want to know that they’re understood. The data you have is the key to demonstrating that understanding.
Let’s take the ‘Risers’ and ‘Fallers’ idea. Having arrived at a data-led definition of each group, you populate them both with the accounts that meet those criteria and you cultivate an offer which you hope will most clearly chime with their perceived requirements. How do you then go about communicating each one to each group?
First the ‘Risers’. They’ve suddenly started to purchase more but whatever brought about this change may easily be reversed. Their activity needs to be acknowledged and their new-found confidence thanked. In an unstable market, you can’t expect them to simply remain with you indefinitely – you need to protect this new business.’:
Dear <FORENAME>,
You’re amazing!
We’re so pleased to learn that you’ve become such a friend of ‘GenericBrand’ over the last few months. In a changing world, we hope you agree that we can offer you the choice and quality you require – and always the value you deserve!
To thank you for your support, we’d like to offer you <RISERS_TAILORED_OFFER>. We have a good thing going – and we hope we can take it to the next level!
Just go to genericbrand.com/nextlevel– and this offer is yours!
Let’s continue to be amazing – together!
The ‘Fallers’ are giving you the opposite problem. They may like your brand just as much as they always did but can’t justify maintaining their spend. The last thing they want to feel is rejected or forgotten. If they do, they’ll find someone else who values them. Find an offer that reflects this difficulty and reassure them that they’ll always be welcome and that you will continue to value them:
Dear <FORENAME>,
Hi,
We all know this is a challenging time and we’re listening to customers’ stories everyday. Like many of them, you may feel that the way you buy is changing – and we’d like you to know that we want to be part of those changes.
We’d like to offer you <FALLERS_TAILORED_OFFER> to help you make the most of your purchases – and to assure you that we’re here to help in every way we can.
All you have to do is go to genericbrand.com/heretohelp and, together, we can change the way we work – and take on the challenges we’re all facing.
Let’s do this together!
As any superhero aficionado will tell you, “with great power, comes great responsibility”. Very often, the ability to manipulate a database of tens – or even hundreds – of thousands of customers feels like an awesome power. It certainly provides a level of insight and understanding that’s difficult to gain in any other way. It’s therefore every marketer’s responsibility to make those insights matter, by informing the very best content it can.
Don’t just listen to me on this, consider the proclamation of one of the founding fathers of direct marketing. The 40/40/20 Rule’ is a principle established by Ed Mayer in the 1960s which states that 40% of the success of a marketing campaign is based on reaching the right audience, 40% on the offer you make to that audience, with only the remaining 20% based on various other factors such as its presentation and format.
You may be great at the first 40% and I’m sure you’re constantly agonising about the final 20% but are you doing enough to make the middle 40% as good as it could be?
Racehorse Handicapping: Predicting the Unpredictable?
The role of a horseracing handicapper is to ensure that each horse in a race is carrying enough weight to offset their differing capabilities and their varying levels of form. It’s seen as a vital task because it means that, in theory at least, champion horses in the peak of their form are matched more evenly with their less illustrious competitors, ensuring a more tightly contested, less predictable race.
Taking the logic to its natural conclusion, the handicapper will only have done their job correctly if all horses in a race cross the line at the same time. While it’s possible (but still unusual) to have a dead heat in a two-horse or, in extremely rare cases, in a three-horse race, it’s functionally impossible for this ever to happen in a race involving a larger number of horses.
Famously, the Grand National is never a close race, using the definition of closeness as the difference between first and last places – indeed many horses fail to complete the course each year and the favourite rarely wins. There are just too many horses, too many obstacles, there is too much distance and arguably, there is too much that is unusual about the preparation to ever confidently hope to call a winner, let alone be able to harmonise the finish across the whole field. In probability terms, there are simply far too many unknown variables to trust any form of predictive modelling that would ever enable a handicapper to achieve the ‘Holy Grail’ of all horses crossing the finish line at the same time. In the face of such overwhelming statistical evidence to suggest its basic futility, why is handicapping necessary?
The answer is that ensuring a dead heat is not the point of handicapping at all. Handicapping is there to offset perceived differences in horses’ abilities and form. It acts as a regulator for betting, ensuring that favourites will not be favoured by the betting public by as wide a margin and that ‘dark horses’ will be viewed less darkly than they would be without handicapping. It serves the industry behind the sport, not the sport itself. There is no handicapping in Athletics purely because the sport exists primarily as a discipline to discern which athlete is the fastest (and by how much). Only the overlay of betting leads to the necessity of handicapping – something which many might see as a perversion of the conventions of pure sport.
Uncovering the ‘real’ reason behind the point of handicapping seems rather dull, irrelevant and perhaps even a little dispiriting but the subject is still of value because it acts as an interesting analogy that mirrors the issues of what can and what perhaps can’t be predicted – and to what extent, the distinction between the two states may become blurred.
Direct Marketing & Parallels with Racehorse Handicapping
The role of a Direct Marketer is to predict, accurately, the event of each customer choosing to make a purchase from an offering in a given time-frame – or not, as the case may be. As with handicapping, various models exist to discern the factors that most affect future behaviour. As with handicapping, these models are widely accepted as being able more reliably to predict the general level of behaviour than would otherwise be the case. As with handicapping, there are far too many variables to translate such improvements at the individual level. At this point, even the offer to give away £1,000 of vouchers with every £10 order will still only yield a certain percentage of response – it will not motivate every customer into action, often for a variety of what appear to be illogical reasons.
It may be suggested that the ‘Holy Grail’ of Direct Marketing is just as simple and just as unobtainable as the race where all horses cross the line together. It is an activity which is segmented using a profile which can determine only those customers who will order.
In reality, for this to occur, not only must this segmentation yield a 100% activation rate for the successful segment, but it must also be shown that all other segments will always yield a 0% activation rate – a practical impossibility.
Just as a handicapper may occasionally achieve a 2-way dead heat, a Marketer may occasionally achieve a 100% activation in a segment with a very small sample. In that circumstance, the Direct Marketer’s expectation is always that that offer, made more broadly, must be transferrable to other segments, uplifting their performance. The activity is then repeated through various other segments with the expectation that it keeps performing profitably until it fails. In short, the ultimate goal state of a Marketer can therefore never happen, as another sale can always be found.
Even if a model existed to find just the people who would only ever respond to a given stimulus (its magnitude), it would still be akin to believing “this is all the sales you can ever make”. It would be perfectly efficient, of course but it doesn’t necessarily mean that revenue is increased by all that much. It just clarifies the process of when to stop chasing the extra sales.
In reality, this a problem we’re highly unlikely ever to face. Customers are people and people are (at the individual level) incredibly difficult to predict. The ‘Holy Grail’ state just shows us what a perfect level of predictability would look like, which is useful when it comes to comparing and evaluating our own methods.
Applying a Predictive Model in Direct Marketing
As a contrast to the imaginary problem above, real-world examples of response rates across the segments of an activity tend to adhere to a more familiar principle: the law of diminishing returns.
This is taken from campaign data from a previous Spring/Summer campaign, using segments driven by our prior ‘Points Analysis’ method of segmentation and recorded from response codes given during telephone orders. For this reason (as it therefore ignores web orders from that campaign), the percentages are not relevant here, just the shape of the curve.
As with the ‘Holy Grail’ curve above, it starts off steeply, implying that this is a clear way to predict the responsiveness of one group over another. However, as the trendline (I’ve used a logarithmic trendline, by the way) progresses along the segments, it flattens so that by the lower segments, it almost represents an admission that the model can’t really say if the second to last segment contains significantly more predictable customers than the last segment.
Using the ‘revenue-building’ logic discussed above, this uncertainty can be (and often is) presented as a positive feature. As long as the responsiveness is at a profitable level, this ‘long tail’ becomes something of an asset, as it assures the Marketer that more sales can be added, with a positive ROI until the point on the axis where the curve touches the break-even point of response. The fact that these sales happen to come with decreasing levels of efficiency may be seen as a price worth paying.
One rather fundamental problem in the collation of the above chart was that the response metric was based on order-level, not customer-level responses. At this point, we need to be rather pedantic: the issue of predictiveness relies ultimately on the response of an individual to a stimulus, which is then grouped by the segments of similar individuals. Using the principles of RFM (the categorisation of customers by Recency Frequency and Monetary Value), order-level analysis conflates the effects of both R and F, when we require them to be viewed in isolation. To illustrate this point, consider that one hundred orders from a given segment may imply one hundred responding customers but it could in reality translate to just one very responsive customer – or any combination of reciprocal factors between.
Since then, we’ve adopted the more standard Binary segmentation model, which ensures the monitoring is at the customer-level, preferring the percentage metric ‘Activation’ (customers who ordered in a given season as a percentage of customers stimulated, by category) over the more traditional, order-level metric ‘Response Rate’ (orders received using a given response code as a percentage of catalogues circulated with that media code). The uncertainty factor of one customer ordering a hundred times versus a hundred customers ordering once each has been subsequently removed. We can now monitor precisely how many customers have ordered, as well as the number of orders those customers have placed, collectively and individually.
The Activation performance of the Binary list for the most recent Spring/Summer campaign, expressed for each group shows a similar curve, implying the same adherence to the law of diminishing returns as the older Points Analysis-derived curve above.
Once again, the asymptotic (flattening) curve implies a longer tail beyond the limits of the mailing list, which, using the methodology of the Binary process (with its allocation of decreasing points for customers ordering increasingly further back in time), also implies that further revenue can only be attracted at a less efficient rate. In effect, it’s almost telling us that after a certain point, we can mail anyone using this rationale and we’ll probably get the same return, whatever it is. This is hardly what you would call a predictive model.
All this is implied but none of it can be taken for granted, just as no segment that yields 100% Activation ever implies that the ‘Holy Grail’ has been achieved – there is always the question “what further potential is there?” to answer. It’s clear that we need other means of predictiveness to unlock the secrets of the deeper recesses of our mailing list.
The Limitations of the Binary System
Largely as a result of the paranoia/healthy scepticism (call it what you will) of putting all our eggs in the basket that is Binary segmentation, we have, since adopting Binary, also endeavoured to add a wider pool of customers to our recent mailings selections than merely those segments suggested by that system. It’s not unusual or ground-breaking to do so; it’s a practice that’s routinely done by even the most faithful proponents of Binary segmentation and it’s called deep-diving.
Using our previous (semi-proven) Points Analysis system as our deep-dive axis, we mailed representative samples from these deeper segments of customers and named them groups -1 to -5, in accordance with the Binary nomenclature.
What we found was that a huge proportion of the -1 group customers were activated (far more than we had anticipated), the equivalent of the Group 12 Binary segment, i.e. the best segment of the ‘Good’ portion of the list. Thereafter, the activation rate dropped massively for the -2 segment and continued to tail off gradually through to the -5 segment.
Perhaps it should come as no real surprise that there is a significant increase in activation in any Binary analysis from the 1 segment to anything that is essentially the ‘best of the rest’. I have to presume that a known increase in activation at this point in the list is not only common but probably also a phenomenon that is to be expected. Conversely, I have no idea if the level of disparity at this point is generally as great as we have found it to be. I rather suspect it isn’t.
There are two benefits to this figure being so notably high, which represent the twin roles of predictive segmentation I have already outlined. Firstly and most prosaically, it represents almost 7,000 activated customers and almost £300,000 of additional revenue. Secondly, it gives us a definition of customer type that we know we can continue to stimulate efficiently and it strongly indicates at what point this metric provides segments that are inefficiently stimulated. It also calls into question the wider viability of a system that seems to ignore a cohort of customers who are capable of yielding half as many activations as those it selects.
Ordinarily, as the Direct Marketing wheel turns and the results of one campaign’s test shape the standard practice in the next campaign, thoughts turn to the question of what methodology to test next. With such a statistical disparity as this, it’s also difficult to escape from the conclusion that the Binary model as it stands may not be wholly suitable for our requirements. This is not to say that the practice hasn’t been worthwhile or indeed that the notion of measuring campaign performance at the customer level isn’t of value. In fact the opposite is true: With ever more ordering methods, media codes as a means of recording performance are dying and, even if we could resurrect them, we would return to the same non-relational order-level analysis that tells us nothing about the customers on whom our business depends.
I would always advocate a customer-level metric, even if I might always wish for a method of segmentation that is more clearly suited to our list profile. The reporting disciplines required and indeed the limitations that customer-centricity can have on budgeting for additional in-season activities are all, in my view, a small price to pay for the insight the analysis can give to actual customers. As we move inexorably to a more sophisticated multi-channel interaction-based data model which encompasses customers’ web visits, email responses, retail transactions and even social media activity, it is clear that our basic ‘currency’, the only differentiating factor we have, to analyse anything of significance will eventually (and then always) be at the customer level.
Having said that, if we’re at the point of re-drawing the boundaries of what constitutes ‘very good’ customers from ‘good’ and so on, we can also have an eye on what shape of curve we’d like it to produce, based on recent customer behaviour tracked against information known about customers before that activity occurred. As I have already outlined, the process of measuring the performance of an activity has two basic roles: to assess both its magnitude and its efficiency. A curve that simply emphasises the magnitude of success is too steep and does little to imply where further success might be found. A curve which places too much concentration on efficiency tends to be too horizontal and very quickly can become practically non-predictive.
Obviously, there will always be customers who are more responsive than others in any database so it’s true to say that any curve will show degradation. In fact, as it’s a symptom of a correct profiling methodology, activation curves should have a degrading, downward-sloping shape from customers who are predicted to be the most responsive, down. It’s also fair to presume that if you measure a list against any given single metric, there will always be a ‘best of the rest’, chosen using a different metric which may out-perform the usual list, so at some point a secondary or even a tertiary segmentation metric should be considered. A problem can occur if those segments suggested by other metrics out-perform the primary-metric segments by too much. This may imply that a better, more appropriate primary profile would have included those names in the first place, something which would ensure the risk of missing such customers from a future campaign is minimised.
An Easy Win: Challenging the Timeframe
One way to improve the primary metric we have (Binary) may be to re-define that timescale of the selection. The version of Binary that we’ve adopted is based on Yes/No (or 1/0, hence the name ‘Binary’) classifications for a customer’s ordering profile over each of the last four six-month seasons. It is entirely predicated on the fairly standard assumption that a customer is a customer from the date of their first order until exactly two years beyond the date of their last order. By extension, anyone on the list who hasn’t ordered for over two years must be considered a lapsed customer and is removed from the house list. They may continue to be contacted, but only as part of a reactivation programme.
The fact that the Binary system is based on a two-year model and the fact that it was adopted by ‘mainstream’ catalogue operators such as Littlewoods and La Redoute seems to have a fair degree of compatibility. I have always been (and remain) dubious that the simplistic ‘two year rule’ applies as strongly in a niche market such as our own. As a ‘safety net’ against pinning our performance on adhering to it, I ensured that our mailings included a ‘best of the rest’ deep-dive, based on high point-scoring customers (who would therefore have been mailed under our previous segmentation model), who, being outside of the Binary segments would therefore have been inactive for over two years.
As we have seen from the most recent data, this 30,000-deep segment yielded a response (and therefore a Return on Investment) performance, similar to the ‘12’ group in the standard 4-season Binary model. Evidently, our less Recent, more Frequent and/or higher Monetarily-valuable individuals were able to outperform most of their more Recent counterparts. The cut-off at two years has always seemed arbitrary and inappropriate for us – and these figures appear to support that position. Recency is therefore not necessarily ‘king’ in a niche market, even if it may be considered as such by more mainstream operators.
To corroborate this view, perhaps it’s helpful to contrast the characteristics of a mainstream proposition and a mainstream customer with those propositions in a more niche market context.
Mainstream v Niche: Some Observations
Mainstream catalogue companies have tended to define their core markets more by the way they choose to buy (i.e. by choosing not to walk into a shop) far more than by the type of products they buy. They are in competition with a far wider section of the market, selling standard products to a broad section of the public. Light fittings, pyjamas, holiday footwear and all the other day-to-day offerings were always generally available on any high street or in a plethora of other catalogues or websites, in which there is usually massive competition. It is therefore difficult for them to create a sense of what their brand represents beyond their pricing, the quality of their merchandise and their service – certainly no-one can define their range as a whole as representing and supporting a ‘lifestyle choice’. Even before the further commodification of retail by search engine and affiliate sites, their offering was often close to being commodified by the presence of so much competition.
It is easy (and perhaps fair) to conclude that they must therefore adopt a ‘plenty more fish in the sea’ approach to customer retention over acquisition. If customers are that easily acquired, and if retention can prove to be so difficult, it follows that it is seen as far easier to entice a new customer than it is to win back one who has not been back for a relatively short amount of time. It’s dangerous to suggest they acted arbitrarily in arriving at two years as the determinant of dormancy; it seems reasonable to expect that it was driven by their data, suggesting a parameter that was appropriate for their purposes.
Conversely, niche market businesses tend to define their customers by a specific activity or affinity, which is to a greater or lesser extent important to all of their customers. They may find that the percentage of customers willing to buy remotely in that market is far higher than in general (historically) because of the relative lack of credible alternatives. Broader ranges of products that appertain to that activity or affinity may be more difficult to build, depending on the obscurity or the scope of that activity or affinity. Wider competition will always be present but, at their strongest, these niche markets are filled with customers who define their interest as a ‘lifestyle choice’. These brands do not just purvey goods, they represent or even define a lifestyle.
In a niche market, almost by definition, there aren’t quite so many ‘other fish in the sea’ and even customers who have been lapsed for a number of years are a far greater prospect to approach once more than any attempt to trawl for a fresh batch. If customers are not so easily acquired, and if retention proves less difficult than in the mainstream sector, it follows that it is disproportionately easier to entice an older customer than it is to acquire a new one. It seems clear that these markets inherently find the mainstream parameter of dormancy at two years to be inappropriate for their purposes.
Extending the Binary System from Two Years to Three
The Binary system’s strengths are its customer-centricity, its ability consistently to predict the difference in response between more regular-and-recent and less regular-and-recent customers and its scalability. Its weakness is the fact that we can prove that it has omitted perfectly responsive customers. Perhaps this can be corrected by using its scalability to ensure that they are re-admitted into the process.Under a four-season (two-year) standard model, the categories are defined by fifteen groups, which is the number of permutations of order activity (or inactivity) across four seasons. One point is awarded for the least recent reported season (four seasons ago), there are two points for an order three seasons ago, four points for orders from the penultimate season and eight for the last season. The number of points awarded doubles, the more recent the season, which seems like an arbitrary system but is actually an ingenious mechanism to ensure that every single permutation is represented by a different number of points.
In this way, we may contend that Recency is a vital factor in predictive modelling whilst also expecting to target customers that are patently less Recent in profile. The crucial point being that we have evidence that suggests we cut off responsive customers too readily by adhering to a ‘two-year rule’. By re-introducing segments of longer-dormant customers, we become able to evaluate their relative value – and therefore the predictiveness of this wider flavour of Binary analysis. Like the current four-season model, there’s also the thorny issue to consider of how many high-performing customer segments that even this model may continue to ignore.
We can’t turn back time but we can simulate the conditions of a six-season Binary selection. It is possible to re-order the customers we may have selected for the current Autumn/Winter campaign using a six-season Binary model. From there, we can identify not only which customers were mailed but also which customers placed an order in the current campaign and compare them with the equivalent responses using the usual 15-point, four-season Binary model. With six seasons, the number of permutations of orders increases from 15 to 63.
This hugely increases the level of granularity that the list analysis can give and will also help to establish the importance of the 5th-last and 6th-last season on predictiveness for a forthcoming campaign. Using four seasons (two years), the Binary graph for Activations from the current Autumn/Winter campaign to late November looks like this:
The same response data under a six-season (three year) Binary grouping shows a similar degradation but with more definition between high-performing and low-performing segments.
The added granularity helps to provide more evidence of predictiveness at each end of the Binary spectrum. Almost two hundred more customers are classified in groups which yielded an Activation rate of over 40% than in the 15-point model and over six hundred more customers are classified in groups which yielded less than a 10% Activation rate. If a 10% rate was shown to be the break-even point for inclusion, then this information would identify names who the Binary model would not predict a sufficient response. If no other justification could be found to mail those names, then that information could demonstrate a saving of unnecessary expenditure.
A ‘Health Warning’ for Any Model of Segmentation with a Single Axis
As we’ve already seen, demonstrating a suitably stratified segmentation model is only the first requirement of achieving a fully-optimised list. We must also ensure that no other potentially responsive segments are omitted. I’ve also highlighted the almost inevitable need for some subsequent segmentation criteria to exist beyond the reaches of the primary (in this case, Binary) model. Not only should this process stimulate as many as possible of the remaining responsive segments (a ‘best-of-the-rest’ group), it should also seek to test other responsive techniques beyond that.
A good example of that methodology would be the segmentation of customers, irrespective of Binary and Points, who have previously ordered during a Sale for a mailing of a Sale Catalogue. This is based on a given principle (that a customer is a known Sale responder). In the field of probability, this is known as Conditional Probability: where a given condition already exists, results in outcomes with a higher degree of probability and therefore predictiveness. The methodology appears sound but the result may or may not agree but either way, the results of that decision will shape our future selections.
Currently, our preferred secondary metric is the Points from our long-standing ‘PointsAnalysis’ table, which was created for our previous segmentation technique, where customers accrue 100 points every time they order, gain 1.5 points for every pound they spend and lose a point for every day that passes without an order.
In order to pursue this line of segment development, we will need to more clearly record what segments were used and on what basis. Where transient variables such as Points are used, the figures at the date of segmentation need to be written back to the database to enable better, easier analysis and cross-reference between the segments used and their eventual performance.
As part of my reconstruction of a six-season Binary in Excel, I have been able to identify customers mailed with and responding to the Spring/Summer Deep Dive catalogues. I have also been able to reverse engineer their historic Points level at around January 15th, based on their November Points and their known activity since January. This graph is what that analysis suggests. I can’t guarantee perfect accuracy within each Points band but I can say that the totals for each group match those given by a report for the activity of groups -1 to -5.
These responses strongly suggest that there are responsive customers to be found outside of the 4-season Binary model we employed in that season, bearing in mind that the Activation level for Binary group 1 was 4.6% and the “-1” Deep Dive group yielded around 18% Activation.
Conclusion
There’s nothing wrong with mailing across multiple axes of segmentation, as long as the hierarchy is established (if a customer qualifies for a segment in each method, which one wins and which method is left with the rest?) and as long as each segment is performing well. Curves which become too horizontal may still be predictive at the level of each category but also show that the method itself has begun to lose its predictiveness at that point. Thought should be given to the point in the list/on the axis at which one model is abandoned and another is given free rein to replace it.
For example, using the derived ‘live’ data for the current campaign below, comparing six-season Binary with Deep-Dive, based on Points, it may be concluded that, long tail or not, groups 1-4 should not be mailed but those quantities replaced by the best of the rest on the Points scale.
There are of course too many variables to merely prescribe a ‘one-size-fits-all’ answer here. Issues of quantities of names available within each group together with associated AOVs and break-even Activation levels all play a part. The main issue at this stage is that we give ourselves the impetus, and the tools, to break away from a single system of segmentation, as long as our focus remains at the customer level.
Whatever we do, it should be a far more scientific process than simply betting on the horses…
I read a great article recently (see below) in ‘The Drum‘, a great resource for stories in the world of Marketing, in which it is argued that the notion of ‘purpose’ is now essential to brand development.
I won’t lie, there’s a bit of buzzword-heavy guff in it – the type that often gives Marketing its ‘fluffy’, superficial stereotype. Nevertheless, there’s an important point to be made here. Here’s my (less guff-ridden) translation:
In the beginning, brands were all about ‘identity’ (like, who owns this *branded* cattle?). Basically, a measure to guard against theft became a means to discern quality and provenance, when goods were mostly commodities. Brands offered logical reasons not to buy the cheapest.
With the advent of consumerism, greater choice and, in time, the construct of ‘lifestyle’, brands had to move beyond mere identity and gain a ‘personality’, to win the affections of more discerning buyers. They began to appeal less to logical faculties and more to emotional states.
Inevitably, consumerism leads to over-consumption. Inevitably, ‘lifestyle’ and demographic segments become ever-more fragmented. Thus, a recognition of the excesses of brands and a market, now a greater sea of identities has led to differentiation by responsibility. Brands now need a ‘purpose’.
Of course, cynics may suggest that this is all bandwagon-jumping and not ‘social responsibility’ at all. You have a point – there’s a profit motive. But what’s interesting/important is the fact it’s happening at all – a reflection of society more than it is of brands’ ‘purpose’.
After all, when was bandwagon-jumping ever not an intrinsic part of advertising/marketing? Every good salesperson reflects/amplifies qualities they see in their customer, like a fairytale mirror. Marketing doesn’t drive change, it reflects it and, occasionally, accelerates it.
‘A prerequisite for brands to have purpose’: M&C Saatchi on passions and diversity
As you may have seen previously on an earlier blogpost, we’ve been awaiting the arrival of the brand new CSG website and we’re finally pleased to say: here it is!
As you’d expect, the site is designed to smartly alter its layout, depending on the dimensions of the screen on the device you’re using so it looks equally impressive whether you’re accessing it on a 27-inch desktop machine or an old iPhone – and everything in between!
The information is designed to be easier to navigate, immediately helping you to distinguish between our commercial and domestic services. Further innovations such as a quote calculator for domestic collections (similar to the function on our Oil Monster site) are expected to be added in due course.
The new site features far more interactive information about CSG, especially our four core values: Customer Service, Innovation, People and Heritage. We’ve even commissioned a short video to explain our commitment to each of these ‘pillars’ that hold up everything else that CSG does. You can view these short vignettes on our About CSG page.
You can read more about the innovations we’ve developed that mean we can treat some waste streams that others can’t. In addition, there are case studies that highlight the ways we fit the needs of two of our most high profile clients and there are lots of short, informative biographies on various members of the CSG team.
As before, there’s also a comprehensive list of our accreditations and other documentation for you to download – as well as a handy guide to finding the right EWC codes for your waste requirements.
Last (but by no means least!), this very blog is now fully incorporated into the site, giving you a thoroughly seamless experience whenever you check back here every Monday morning, keen to catch up on our every blogged word – that is what everyone does, isn’t it?
However you choose to use the CSG site, it’s here for you and always will be – and we hope you like it!
The new CSG website changes its layout in response to the screen dimensions of the device you use to view it. Photo: Paul Bentham
Over the years, I’ve spent many a frustrating hour explaining why online selling is coming/is here/is here to stay/is just in its first phase and so on. I’ve debated it internally as a marketing strategy when people were still getting used to email and as a fact of life and within BETA Council meetings when certain people were hoping to ‘ban’ it (how, exactly?!). I even found myself having to defend it at the end of a speech to the National Equine Forum! When it comes to e-commerce, I’m quite firmly planted in the ‘Pro’ camp.
And yet, not everything in the virtual garden is rosy. Chiefly, look at the way digital marketing is measured and made accountable.
Once upon a time, you’d spent £X on a direct marketing campaign, divide the number of orders it yielded into the number of customers contacted and get a Response Rate. You’d also divide the revenue it brought into the aforementioned number of orders yielded and you got an Average Order Value. All you needed was a trustworthy ‘quote the code’ response mechanism. You knew how many copies you were sending out so, aside from all the sales, you also got a lovely source of comparison data. Then, using something called segmentation, you could have even more nerdy fun, all the time seeing how much money you were making.
Compared to retail, which struggled to tie a transaction to a name in a database (although that’s more achievable now), all this customer-centric data was a revelation. Information that became knowledge, which, as we all know, is power.
And then along came the Internet – simultaneously the biggest blessing and the greatest curse to hit direct marketing. Yes, it offered 24-hour, borderless trading, much greater agility in presenting one’s offering, a promise of cost-free mass mailing, something called social media and so much more lovely data! How many people viewed page 26 of your paper catalogue? No idea but I know how many online views we got for each of the products it features.
Online selling offered nothing short of a revolution of data and visibility – if marketing went from the Medieval era of retail to the Renaissance of direct marketing, the web quickly whizzed us through the Industrial Revolution and straight into the Space Age. Cosmic, man! ‘Newer’ equals ‘better’, doesn’t it?
Well, yes and sometimes no. This myriad of metrics may look like your friend but it can often give you useless information – or worse still, misleading data that fails to alert you to a problem. Sure, if customers want to buy online, you have to operate in that space but e-commerce tends to make a huge mess of your internal reporting – for two main reasons:
1) There’s no clear link of ‘cause and effect’ between your stimuli and your incoming orders like there used to be, which means you can’t make solid conclusions about your effectiveness and efficiency quite so easily. Consider the paradox that spending more on offline material increases web orders because, guess what, people will always do what suits them and not follow the ‘rules’ of whatever tidy flow-chart we might be tempted to think they inhabit. Now, if a sale depends upon both a stimulus (to compel a customer to order) and then a referral (where they may need to find your site as a means to place that order), do you credit the offline activity or a Google Adword for that sale? What if there are more than two stages to the process? Even if you know when all of this is happening, how do you decide to attribute each of those sales?
Here’s some data we were told was 100% reliable, earlier
2) Most of the data on which you depend isn’t generated internally any more, raising questions about its reliability. Data collation is now usually subcontracted to the very digital channels you use: Google, Facebook, Twitter, whatever SEO ‘partner’ you’re using, Remarketers, Affiliates, email handlers and so on. At best, they’re all innocently taking sole credit for potentially the same order (see above); at worst, it becomes a case of paying a bunch of turkeys who keep telling you it isn’t Christmas. You can’t replicate their data (which usually forms the basis of their charges) but you do know that if you add up all the ‘sales’ that each of them claims to have led you to, you should be turning over far more than you actually are. Something is amiss but you’re next to powerless to find out any more than that.
You have paralysis by analysis: more information than you can handle and less knowledge than ever before – and a nagging feeling that somewhere along the line, some of this lack of clarity is hurting you.
If you think this is just me checking into middle age by having a rant about the object of my prior fascination, you may have a point but bear this in mind: clients like The Guardian have started to sue agencies that they believe are misreporting their own performance stats. The incoming Chief Brand Officer of Proctor & Gamble recently gave a blistering speech in which he told the digital ad world in no uncertain terms to clean up its act, provide the transparency that clients always used to expect or kiss goodbye to the promotional budget that supports P&G’s $65bn worldwide sales revenue. There’s a sense that a fightback has begun against the charlatans and snake oil salesmen and that, in time, better regulation of one form or another, will follow.
To answer the incendiary question I initially posed, the Internet hasn’t gone too far – it has indeed, as Karen Carpenter once sang, only just begun. The Web has, in a human generation grown from a preposterous daydream to dominating most forms of marketing. Inevitably, its forms of regulation and control have struggled to keep pace. Perhaps they always will.
Whatever happens next, an important lesson is there to be learned: it’s still selling, the same as it ever was. Just because it’s on the Internet doesn’t mean the same basic rules, disciplines, checks and balances that we came to expect in the analogue world shouldn’t continue to apply.
Look out for my next column, about the difficulties of applying simple rules to resolving customer disputes, in the September issue of the ETN, out September 1st.
We were pleased to welcome a new member of the team to our Cadishead office, last month. Daryl Tunningley joins us as a Marketing Executive, giving particular focus to our online activities.
Daryl, 26, hails from York and grew up around one of Britain’s most picturesque cities, although he jokes that the downside to all that historic splendour is that “you spend a lot of time dodging the tourists!”
He began his career curating website content at Persimmon, the house builder, at their Leeds office. Before long, he’d developed the role to such a degree that he became their Marketing Co-ordinator. “I just developed an aptitude for marketing, combining my writing skills with an appreciation for good design but above all, applying common sense and logical thinking to make improvements based on what the analysis was telling me.”
Marketing is a field which has attracted some strong stereotypes over the years, with many still believing it to be the domain of brash, risk-taking ‘Mad Men’ types, too often full of their own self-importance. In fact, in most companies, day-to-day marketing has undergone something of a quiet revolution over the last decade. Since the arrival of the Internet, search engines and, more particularly, social media, it’s now a department awash with very detailed performance data, measuring every click and every view of every piece of content available. Someone has to sift through this tidal wave of information and turn it all into knowledge, which in turn informs the strategy.
A typical analytics dashboard, showing a tiny fraction of the data available to today’s marketing teams. Photo: www.kaushik.net
You sense this is a role perfectly suited to Daryl. He speaks precisely and unhurriedly, favouring clarity over brevity, suggesting a level of thoroughness that the marketing dinosaurs of the past would find irksome. “I like the fact that my role gives me an end-to-end view of the whole business. This gives me a better chance to understand every part of the process and ensure I can support each one in the best way possible.”
Daryl’s capability for self-teaching is not restricted to his working life: he plays his Fender Jaguar electric guitar “when I can”; his musical ability another product of his auto-didacticism. He also reads widely, with particular interest in Science Fiction and History, “mostly European and any period from Medieval to Modern. I find it fascinating to see how – and why – it is that we are where we are at this point in time.”
Perhaps most surprisingly, Daryl’s embrace of the world of social media comes to an end when it’s time to go home. “I don’t engage in social media at all in a personal capacity”, he tells me, which at first seems an odd paradox but on explanation, becomes perfectly logical. “I remember hearing once that ‘chefs never cook’ and that explains how I feel about it. Social media is a powerful tool but I view it as a means to lead people to the content on our site. The analytical aspect of it all is the most interesting feature for me.”
His next big project is to co-ordinate the design and build of the new CSG website, in production later this year. Needless to say, the ability of the site to provide as much meaningful data as possible will be at the top of his wish-list.
In the meantime, he’s still in the process of increasing CSG’s reporting capability and analytics. If you happen to be the first person who’s taken the time to read as far as this, the last sentence of this blogpost, he’ll probably know all about it.
As HMV, Blockbusters, Jessops and many others have found recently, if something can be downloaded these days, there’s far less demand for the physical version of it. While we’ve certainly noticed that we don’t sell the same proportion of books and DVDs that we used to, thankfully, most of our range needs to be a physical item because riding and horse-owning are physical activities – although I’m sure that if anyone was able to perfect a way of downloading a way to a groomed horse or a mucked-out stable, they’d never have to worry about money again!
On the one hand, we’re thankful that we’re not in an industry that is so vulnerable to digital alternatives but on the other, it’s a mistake to think that we’re not in any way affected by the changes to the way that the public consumes information digitally. Take for instance the case of the humble catalogue. Like most companies that were working in ‘mail order’ before the World Wide Web was even a glint in Sir Tim Berners-Lee’s eye, the catalogue still holds a special place in our hearts.
Catalogues gave us the opportunity to find new customers, to try new things – to become the business that we are today. We’re so proud of our roots and the progress we’ve made since then that any visitor to our admin offices today will find our staircase adorned by pictures of every main catalogue we’ve ever produced.
On the other hand, catalogues are incredibly time-consuming to produce, eye-wateringly expensive to print and post, they’re always one mistaken detail or broken supplier promise away from making us look like liars or idiots for months on end – and many people would say they’re not particularly environmentally responsible.
As much as we’re proud of our catalogue heritage, only a misty-eyed nostalgic would claim that catalogues don’t have their difficulties. Certainly, there have been many times over the years when looming deadlines or unreliable technology have raised our stress levels and we’ve had to console ourselves with the thought that ‘if it was easy to do this, everyone would be doing it’.
In rather a sharp twist of irony, the arrival of the internet as a shopping medium has all but proved that old throwaway line. Distance selling online is now much easier (and cheaper) for small traders than paper and, guess what? these days, it often does seem like ‘everyone’ is now selling equestrian products online. The battleground for us to compete for your affections these days is, it seems, not in the letter-box any more but in the virtual world.
In the 29 years we’ve been producing brochures and catalogues, we’ve seen the number of other companies doing the same thing go from two or three in the 80s to perhaps twenty or so ten years ago and back to two or three again today. It’s even conceivable that there will be no other equestrian-specific paper catalogue worthy of the name by this time next year. We won’t know until then but the fact that it’s even possible is astounding enough.
This puts us in a tricky position. We know that when we launch a catalogue, sales go up sharply. Would all of these sales still happen if we suddenly stopped putting ink on paper? We’d rather not find out if that’s the case by just trying it, in case it proves to be a big mistake. There’s also the question of catalogue size to consider. It’s great to be able to produce over 200 pages of products and, in doing so, show off the breadth of our product range simply by inviting customers to ‘feel the width’ (which is something that websites still struggle to convey). This is all well and good but at 200+ pages, many of them will contain the same popular-yet-unchanging products that we’ve printed ten or twenty times or more. Should we really worry that you might think that we don’t sell ‘old favourites’ in products like haynets or water buckets or grooming kits if we don’t keep showing you that we do?
‘The Same as Usual: A4, about 150 pages, a full selection of Spring stuff’
‘Just new stuff and good ideas – I expect you to still offer everything else’
‘You know what? I don’t even need a catalogue these days. I’d still order!’
At the time that I write this, it has elicited 72 responses:
32 people (44%) chose answer ‘a’: keep the status quo.
35 (49%) went for ‘b’: a version with fewer pages and a smaller range in print
Just 5 (7%) plumped for ‘c’: the paperless option – no catalogue at all.
While I’d like to thank those 72 people for their help, we have to be a little careful here – it’s not what a market researcher would call ‘scientific’ but it’s interesting, all the same. It proves nothing but it does lend support to the theory that we could significantly cut down on the amount of paper we produce without adversely affecting our ability to tell you what great products we can offer you.
We know what proportion of our orders are placed via our website but we have to be a little careful not to presume that all those orders were only brought about by the website, not the catalogue. In short, we don’t want to take for granted that you will order from us even if we don’t send you a catalogue. Why should you? It’s our job to entice you to order and if we don’t do that bit properly, why should we expect you to order at all? To inform our view, we’ve looked at what’s happening with paper in other industries and other markets.
Catalogue companies like Joe Brown’s and M&M Sports have dabbled in smaller, thinner catalogues. We may not know what those exercises have proved to them but the fact they’re even doing it indicates that they’re at the same crossroads that we are. Where the old-fashioned ‘big books’ still exist, they appear more likely to come with a price, albeit a nominal price and I even heard a rumour (and it’s only that so don’t quote me) that Argos may be getting away from 1,000+ pages, in favour of developing their very impressive smartphone app further. If that does happen, it’ll surely be another nail in the coffin of the old-style ‘doorstep’ catalogue. So, against all this background – and more besides, we’ve decided to keep in step with innovation and produce a smaller, slimmer Spring/Summer catalogue (see below).
It’s probably only a matter of time before we decide to do the same with its bigger sibling, the Autumn/Winter catalogue. Some may suggest that we’re even seeing the beginning of the end of paper catalogues as a means of customer communication. I’m not sure about that; there were many similar predictions about the impending demise of paper around the time of the ill-fated ‘dot-com boom’ nearly fifteen years ago. Just like the famous old Mark Twain quote, it turned out that rumours of the catalogue’s death were ‘greatly exaggerated’, the lesson being that just because someone has said that something is on the way out, it doesn’t mean that they’re right. It’s a good thing to remember but at the same time, let’s not forget that nothing lasts forever. Mark Twain did eventually die, so you could say that those ‘exaggerated’ rumours, although inaccurate at the time, would come true sooner or later…
Last week, we were concerned to read a thread of comments on the Horse & Hound Forum in which we were the subject of some criticism. Our new website was the topic and it received most of the comments but other points were made which were not particularly complimentary. I won’t pretend it was a wonderful way to spend half an hour but it was a valuable use of time nonetheless.
Yes, it’s fashionable to greet criticism with a fixed smile as “an opportunity to improve” – which is perfectly true – but it doesn’t make the process of reading it any more pleasant. Having said that, I’ve also felt that any retailer who can’t receive honest criticism, however brutal, shouldn’t really be in retail. Anyone who sells their products to consumers exists purely because they are able to impress enough people to stay in business. It’s not a difficult rule to live by – in fact it couldn’t really be any simpler – and you can’t really be surprised at what happens when it proves too difficult to achieve. Actors and other performers have to learn to handle bad reviews when they perform their art to the paying public so why shouldn’t retailers expect the same accountability? Of course, you can’t be in business for very long before you encounter your first criticism.
One the one hand, you have to expect it; on the other, you must never ever dismiss it when it comes. Any company that justifies doing nothing about criticism because some was expected is on the slippery slope to complacency and arrogance. Neither can you always just start doing whatever it was that provoked the complaint. We have a responsibility to all our customers and merely correcting what one person is unhappy about may not necessarily be the right thing for everyone else. What matters most at this stage is how we respond to our critics and where we can use their comments as a force for improvement, which is precisely why I’m writing this.
It would have been very easy for us to do the traditional, very British thing, which is to close ranks and still attempt to do the right thing, but in a secretive manner, to avoid ‘washing dirty linen’ and to ‘save face’. In a world of blogging and social media, companies are increasingly finding that that doesn’t work. We need to take guidance from the experiences of super-injunction-seeking celebrities who find that the harder you try to contain a story, the more you fail. The sensible alternative, it seems, is to invite more comment and to be seen to respond to it properly. There is at least an inherent honesty here. Everything is “in the open” and everyone “knows where they stand”. When we as customers deal with others, we all want to be able to use those phrases, so why is it so surprising that it applies here as well?
Since last Thursday, we’ve begun to work with Feefo, a company who specialises in providing feedback for mail order and online retailers. With clients such as MandMDirect and Joe Brown’s on their roster, they have a lot of credibility in the world of catalogues and (I hate this term, but…) ‘e-commerce’. Anyway, we sent them information about some recent orders: customers, products ordered, email addresses. Feefo then sent each customer the following email. It was entirely left to each recipient whether or not to respond:
It’s early days I know, but from the results I’ve seen so far, it seems that people are largely satisfied, with around 95% of respondents indicating that they are either ‘Happy’ or ‘Very Happy’. While this is a little more reassuring to us, I don’t want you to think we’re happy that ‘only’ the other 5% aren’t happy with us. There are plenty of issues raised in the experiences of the remaining 5% that, once addressed, could be of value to every customer. The secondary benefit to this survey is that it invites you to say why you’re unhappy, which is absolutely vital to us to help us decide what to do about removing the problem, if we can.
One of the problems I have with trusting the chatrooms too much is that people tend to just say that something is bad or wrong without having to explain why they think that way. I do of course have to concede a point here: why should they have to explain anything? Chatrooms are for people to say what they like (within reason) and are not there for the benefit of snooping marketers like me, looking for nicely reasoned and qualified feedback. I appreciate that when we look at these threads, it’s just a digital version of sitting with our ear to the door of your tackroom. You are of course entitled to speak freely and you’re entitled to your opinion of us and everything else, however you’ve arrived at it. It is however the worst of both worlds for us to read firmly negative comments and then have little or no ability to do anything constructive to repair the situation.
I’m grateful to anyone who takes the time to explain why they think we’ve done something badly and I extend that gratitude to you, if you wish to share your views. We’ll be looking to do something similar to gauge the views of people browsing the site and I’ll be actively encouraging feedback via our Facebook page and our Twitter account. I believe that I can also add a polling widget to this blog, although I’d value your comments more. With regard to our website, our website partners are also closely involved in making whatever improvements we can. Will we always enact every suggestion or remove every irritation we read? I can’t promise that but I can say that if we know we can’t, or won’t, we should always tell you so. If we didn’t do something we should have done, I’d also expect that we should be clear and honest about that. I’m struggling to think of instance where we have failed to be open in the case of any of the above but of course, if your experience is different, I’d be glad to know. Thanks for your time and for any feedback you can give. It’s always appreciated.
Resonation 
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