Customer Value vs. Valued

Customer Valued?

In our age of automation and AI, marketers risk becoming detached from how their business practices, products, and services are perceived by their customers. Marketers have it all wrong by focusing solely on customer satisfaction or a willingness to recommend: these measures do not capture the customer’s relationship-based perspective. Customer satisfaction or willingness to recommend are thin, shallow, “last click” based, and largely transactionally-oriented.

The customer can be momentarily satisfied with their last transaction (product or service): it delivered a promised benefit. But that is, by definition a transactional experience, and often devoid of any emotional richness.

In working through these distinctions with our clients, the notion of customer value (or customer lifetime value, aka “CLV”) can be the polar opposite of whether the customer feels valued.

From a financial or marketing perspective, a company’s approach to customer value is formulaic: extract maximum value from the customer. The metrics take many forms: ROI, ROAS, narrowly targeting, and upselling to name a few. But this “share of requirements” approach (i.e., siphoning off more revenue from the same customer) is entirely transactionally driven. There is no “emotional stickiness” created with the customer from a single transaction, or even from multiple successful transactions.

From the customer’s perspective, feeling valued creates an emotional connection which is deeply internalized and an incredibly powerful sticky magnet for retention.

As a CMO, how would you answer this question from the customer: “Does this company appreciate my business?” If you don’t know, consider path-to-purchase or other in-depth insights work. Test new programs. Test reward structures. In what ways can your company demonstrate to the customer that their business matters – that they themselves are valued?

Even highly satisfied customers can be quickly dislodged by a competitor who can, for example:

  • Offer products at a lower price
  • Offer products with more features/benefits
  • Offer products that appeals to more users
  • Offer products that have more use cases
  • Deliver products in less time
  • Leverages variety-seeking behavior or changing tastes

In email automation and drip campaigns, we have learned that with more personalization comes better response – and a greater likelihood of consumers responding to offers. But everything now comes through as personalized (except for the occasional misfire, like “Dear {FirstName}”), which slowly erodes that competitive edge. But all of this plays in the transactional space, devoid of motivation or emotion.

In our client work on customer value, we have noticed that measures related to the customer’s perception of his/her worth to the company is a far better predictor of customer retention than “shallow” measures of satisfaction or willingness to recommend. One measure (NPS), in particular, is especially weak in this area. Correlations with purchasing are always the lowest. This really should come as no surprise, since it is a thin ‘report card’. Management teams gain some comfort by following the herd who also uses NPS, but it provides little actionable insight into the underlying value equation.

We urge CMO’s and marketing leaders to think about longer-term results and to focus on the customer’s perception of their relationship, rather than the transactional value extraction approach embraced by many marketing organizations today.

As Peter Drucker famously noted, the purpose of business is not to make a profit; it is to create a customer.

Relevance – The Missing Ingredient in Digital

image young woman

A quick Google search of the words “relevance” and “marketing” turned up very few useful or informative hits. I found this surprising. Too much digital communication (email, banner ads, YouTube teasers, etc) fails to connect to the consumer in a meaningful, relevant way, which I classify as:

  • Emphasis on noise over meaningful communication (“spray and pray”)
  • Failure to truly understand the decision maker’s pain points
  • Absence of clear product differentiation in communication
  • No linkage between pain points and solutions offered by the marketer
  • Missing emotional connection with the decision maker

Relevance can be a squishy term because what may be relevant to the marketer is not necessarily relevant to the consumer. Too much digital content is devoid of the connection between the product (or service) and real customer needs. Advertising language is often lifted from the marketer’s vocabulary and not from the customer. That’s because no one has bothered to speak to the customer to hear what is relevant. The approach is “Here are the facts – the consumer will obviously get it!”

In digital, we hear about “performance marketing” and “brand marketing”, and these are certainly useful constructs in the business of optimizing digital spending, but more fundamentally we are missing major opportunities to demonstrate our role as “market makers” between customers and sellers. Marketers assume that all features or characteristics are relevant, when in reality too many are not.

Many advertisements on YouTube, for example, don’t connect because the narrator or situation fails to describe the product or link to an end-benefit (even after our attention exceeds the first 5-10 seconds). The same is true for linear or embedded ads on TV or radio. The branding is often held back until the very end. At that point, the advertising has either served to confuse the viewer or waste their time by failing to connect any relevant branding with the story that that was told in the previous 25 seconds. In many cases the storytelling or virtue signaling is more prominent than the brand itself. The consumer must process images, messages, and a story line into something personally relevant that then, in turn, must somehow be linked to a brand benefit. Automobiles, pharmaceuticals, and health care advertising frequently wander into these dead ends. This approach is a complete waste of ad dollars.

Conversely, some features are immediately relevant because they connect to obvious end-benefits. Amazon’s One-Click checkout feature or FreshDirect’s automatic re-ordering are great examples. They mimic the in-store checkout experience: I hand my credit card to the register clerk and don’t have to think again. Amazon and FreshDirect don’t have to talk about it: One-Click has multiple end-benefits: I don’t have to fumble for a credit card, enter a delivery address, and my window is already known. In short, I don’t have to think at all – and can get back to the more important work I was doing before I placed my order. Amazon and FreshDirect become directly relevant because they save me time – something of great value to us all.

Industry experts, the Advertising Research Foundation, and others all generally agree that content and creative account for as much as 70% of the impact of advertising. Too many of us are focused on the shiny object of ROI and targeting, when in reality what consumers want is something that is relevant and meaningful and that makes their lives better.

Don’t forget this fundamental tenant of advertising: do your research, uncover unmet needs, and make it relevant!

Reframing Marketing Research Spending as an Option-Creating Investment

If you have been in business long enough, you know that the hard work of research is sometimes seen as optional or discretionary by some management teams because it’s hard to calculate the true ROI of research. But we’re thinking about this all wrong. Companies should be thinking about research as a way to separate winners from losers, and move the winners to market as quickly as possible at the lowest possible total cost. So let’s flip it around and consider the value of research using an investment framework.

Business spending and investments fall into three broad buckets, which are:

Infrastructure investments that include the costs of standing the business up and keeping it running at a baseline level. This includes the sunk costs of office space, utilities, computers, distribution centers, manufacturing, and support staff. The business cannot run without them, and the ROI cannot be easily calculated because it’s the paid-in capital needed to get the flywheel spinning.

Variable cost investments include all short-term spending to promote the company’s products. ROI calculations work best in these situations because there is a beginning, a middle, and an end to the spending and the program that is being run. The ROI question is: when I spend a dollar, how much will I get back (in the near term)? For example, advertisers and media companies obsessively focus on maximizing ROI by targeting (i.e., MTA), which is amazing but does little to identify promising ideas or address business strategy: it’s simply optimizing ad spend.

Option creating investments are by far the most interesting! These investments are made for marketing research. An “option creating investment” lets me put a little money down on the table to give me the option of owning something later that is worth much more. If I spend money for an “option” but it’s not going to pay off, then I walk away and let the option expire. Alternatively, if I have a winner, I am in the money. If I put $2 million down and I get back $20 million, my ROI is 10x and it’s time to exercise my option. The product moves over to the ROI category, supported by variable cost investments.

The other option is, of course, launching a product that you did not test and watching it fail spectacularly. All you have to be is right. But if you’re wrong and you’re the CEO, you might be looking for a new job!

Here’s a quick example. Let’s say we have 10 ideas, and each one of them costs $5K to test. Half of them move on to an R&D product development phase at $75K each, and these all move on to a product evaluation phase at $15K each. Two of these then move forward to test market at $500K, but only one of them performs well enough for a regional launch costing $2MM. All in (including the losers) I have spent $3.5MM.

The launched product achieves $10MM in Year 1 sales at a gross margin of 60%, or $6MM. My ROI (including the cost of all my losers) is 171%. If I have two winners, my ROI is even better at 343%. And I am not breaking out the cost of research alone, which is much smaller – I am including all of the costs associated with the launch.

Option creating investments can also be made in customer satisfaction research to identify additional ideas to insert into your screening programs. Over the course of time, the amount of money you may spend in research testing will be rounding error compared to the amount of money made by the winners.

Knowing what won’t work is as valuable as knowing what will by researching effectively. Well-designed research will continuously feed successful business performance and yield great ROI!

 

My thanks to Jay Kingley of Centricity for helping to shape this thinking!

Curation: The Next Wave of Marketing

Choice Overload vs. Curation 

Whenever we go to Amazon, or Netflix, or any other site, we are immediately presented with dozens, if not hundreds, of choices. Many of these choices are randomly selected by the retailer based on past purchase behavior across the buyer’s digital mesh. Across multiple devices, the company knows our age, sex, and geographical location, and perhaps can algorithmically make some deterministic assumptions about what we like or don’t like.

But that has yet to translate into something that is presented to the customer as a reasonable choice set. It is no wonder that consumers feel bombarded by choice. They are simply overwhelmed.

We are presented, every day, in multiple contexts, with too many choices. We are presented with too many choices when we read digital publications. We are presented with too many choices when we look at the social media feeds of LinkedIn or Facebook. We are presented with too many choices when looking for a TV show or a movie. Humans are simply not capable of synthesizing hundreds, if not thousands, of choice alternatives when they are presented as a mass (mess?) of individual decisions. Our cognitive capability collapses under the weight of all of the choice decisions that must be made when presented with too much choice.

Companies generally, and advertisers and media assets in particular, have failed to make the leap from choice to curation. This is a huge opportunity for marketers in simplifying the marketing message, making the overall customer experience that much less burdensome and taxing, and draws the consumer closer to the value proposition that attracted the consumer in the first place.

As a general rule, consumers do not like other people making decisions for them. A good case in point is grocery shopping. Yet, in urban environments, direct delivery makes much more sense due to the many obstacles for grocery shopping in congested cities. A grocery shopper doesn’t have to fight city traffic, load up a car, drive to and from their apartment, or leave and subsequently enter parking garages to get the week’s groceries. One of my former clients, FreshDirect, learned early on that their business model wasn’t solely built around the ability to deliver high-quality produce at reasonable prices. The secret ingredient were their drivers. The drivers knew their customers at a personal level, and were able to create a curated experience by making sure that certain things were done to the customer’s exact specifications.

Why is curation so hard? E-commerce has not figured this out at all. Not long ago I ordered tires for my road bike from Amazon. On a subsequent login, Amazon suggested other road bike tires I might be interested in — for a product category purchased annually (at best). The lack of synchronization between recommendations, purchase frequency, and my likely need was stunningly dumb. Yes, Amazon is enormous, yes they make lots of money, but they still have not moved the needle on the concept of curation in any meaningful sense. What if Amazon had a viable competitor that really understood curation?

On the flipside, one of my favorite examples of curation is Spotify. Once again, one would think that Apple (iTunes) would have figured this out long ago, but Spotify is a wonder. If I want music for concentration, there is a curated playlist. If I want calming classical in the background, there is a curated playlist. Do they get it right all the time? No, but they are pretty close most of the time.  And I don’t mind if they miss. AN 80% hit rate is pretty good to me. At least there are humans involved in the decision-making process. OK, yes, perhaps also an algorithm, but at least it is a collaborative effort.

Marketers would be well advised to start thinking about how to anticipate the kinds of products and services that customers will be looking for in a world where choice is overly abundant. Curation is one of the ways that marketers can demonstrate that they are tuned in to what customers are seeking, rather than blindly and programmatically jamming messages at them without any thought to the choice overload that they create. Does the marketer want to convey something meaningful, or add more noise? So far it has been the latter.

I hope that more marketing and advertising initiatives will consider the notion that humans are very, very good at intuiting what other humans might like or enjoy. The concept of curation can form a  much-needed bridge between the antiseptic world of algorithmic decision-making and true human connection.

Simple Ways to Start Your Analysis

Simple Ways to Start Your Analysis

Looking for a quick way to get started understanding the results of your research?

Projects that are survey research-based can be daunting. So can projects that involve the analysis of sales, promotional activity, advertising, or other marketing-related activity.

We live in a world of complexity and big data. Simple guidelines and a keen eye can reveal patterns that you might have otherwise overlooked. Here are a few tips to help you start analyzing your project:

Take a walk through your data.

Scroll through the data and see where values  “pop” – that is, where are they high and where they are low? Do your tables flow in the same way that you think about your business? If so, you will begin to see numbers that imply relationships. As a result, visual outliers can become major insights.

Compare those who are interested versus not.

In the research business, we refer to this as “acceptor-rejecter” analysis. If, for example, you have a five-point purchase scale, group the “fours” and “fives” and compare them to “ones” or “twos”. Throw the neutrals in with the rejecters to compare positives vs. everyone else. Are there larger differences? If so, What do you infer?

Mine the gap.

The benefit of acceptors vs. rejecters is that you are looking more vs. less extreme. The difference between them is valuable in identifying a compelling story. Typically, this is done in the form of point gaps. A large gap between acceptors and rejecters points to an insight.

Sort your data.

If you have attributes of various features or benefits, sort them from high to low and compare the acceptors and rejecters. Or compare demographic groups, such as Millennials vs. Baby Boomers. Sort them on ratings or point gaps. Larger point gaps can identify attributes that are choice drivers.

Think linearly.

Array groups you are interested in analyzing by order of magnitude. For example, a variable like education is easy: college educated vs. not. For income, create low, moderate, and high income groups, and compare across. The same is true for other continuous variables, like age. Be clever, use medians and not means.

Your eyes will easily see patterns, especially if interest is correlated with your dependent measures.

These little baby hacks will get you on your way!

Surveys & Forecasts, LLC