The standard definition of a Key Value Item (KVI) is “an item which drives the price/value perception for customers.” But we’ve found a wide variation in the actual interpretation and usage across our retailer clients. In this post (the first of three on KVIs) we’ll lay out four common definitions and grades each of them on how well they can actually be put to use.
Why is this important? Every single time a customer sees a price on your shelf, they update their opinions on your price and value equation. Understanding which products have large impacts and which have small is crucial to optimizing your pricing strategies (both promotion and everyday).
A recent HBR article titled “Understanding Fairness is the Key to Keeping Customers” caught our eyes this week. From the headline we expected another rant on what a “fair” price is, conflating ethics with price setting. We were relieved to discover it’s actually a more tactical guide to the perception of fairness in pricing. Customer perception of a price, whether it can be described as “fair” or not, is obviously one of the key drivers of elasticity, and is ignored at retailers’ peril. (more…)
As part of an ongoing conversation with some thought leader clients in the sports apparel sector, we discussed how to best measure PR activities. They were wondering whether, given another dollar, they would invest it in PR efforts or into more tactical advertising campaigns. We converged on three central themes to help shed light on the answer: (more…)
Pricing is complex, which is why we love it. But we also love those rare instances where we can use simple rules of thumb as a shortcut. We’ve been using this one for years:
The current state of retailer pricing sophistication is all over the map. Some, with little investment and low organizational adoption, stay in the low-value early stages perennially. Others develop advanced analytic capabilities which, when paired with the broader strategic context, drive huge financial impacts. Setting aside why these disparities exist, there’s value in exploring how they progress from naive to best-in-class.
In the evolution of pricing analytics there are six core capabilities that retailers must master to not only broaden the scope and applicability of the analytics, but also increase the value delivered. The rewards, however, are large: pricing is one of the single most important levers for immediate bottom-line impact. (more…)
We give a presentation to a roomful of NYU Stern MBA students this week on the state of Marketing Measurement and Accountability. As always, the students had great questions and insights, especially around digital marketing. This time, one of the students asked “in five or ten years, how much of marketing spend will be going to digital?”
It’s a great question, especially if we push it to the extreme and rephrase it as “Could digital be 100% of marketing budgets?”
Our answer? Yes, but only for high-engagement products.
A paper from the National Bureau of Economic Research concluded that the ROI of search engine marketing are “a fraction of conventional estimates” and in the studied company “become very negative.” How can we reconcile this with what our clients believe and the fact that they’re spending millions with Google?
A recent blog got quite a lot of attention recently when it decried the declining profitability of Google Adwords. We’ve been predicting this for a while, but we believe there’s hope on the horizon. (more…)
Imagine you’re in negotiations for a new job, and the hiring manager says “Well, we’ll throw in the ‘gold’ relocation package instead of the ‘silver’” at the very end, and doesn’t ask for anything from your side. How much different do you think the ‘gold’ package is from the ‘silver’ version?
An NYT article finally calls out the unspoken heroes of big data: those who aggregate, collect, cleanse, and validate raw data before they are analyzed. In our hiring process we immediately screen out any resumes that don’t include SQL and advanced Excel skills, even if they will end up working entirely in advanced stats software. Why? Because those who haven’t been elbows-deep in the raw data haven’t seen firsthand how the analytic approach to a problem relies on the data treatments, calculations, transformations are made upstream in the process.
Another day, another incendiary article up in arms about the fact that two people may see different prices at the same website.
The truth of the matter, as usual, is much less exciting as it sounds. We’ve worked with retailers and their pricing strategies as both practitioners and consultants, but we’re continually surprised that no one cares that actual shelf prices at different physical stores can be very different, but the minute that they are different online, it makes the Wall Street Journal.
The short answer is that most retailers with physical stores and online storefronts simply try to match their online prices to their physical store shelf prices. Why? Those we’ve spoken with simply expressed that they wanted to present each customer the same experience online as they’d see in their home store. The easiest way to do that is simply by using IP lookups to guess locations, which are getting more and more precise.
Online retailers have indeed been adding to their arsenal of price discriminating data- whether the browser type, location, history, etc. But one of the great things about competitive markets is that they erase the “ethical price” debate: if Orbitz happens to think that you’ll pay an extra $10 for a hotel room and you’re not, simply move over to Priceline. Or if they happen to be right, go ahead and book on Orbitz- there has been no coercion or misinformation, and no ethical breaches.
But in the end it’s a tempest in a teapot, because we’ve yet to see any online price discrimination tactics that change price by more than 5-10%, and most often it simply reflects the price you’d get if you actually entered the nearest local store.
In some sectors changing price isn’t as easy as a new shelf sticker. But that doesn’t mean it’s acceptable to communicate your price thoughtlessly, as APS did below. While I’m sure it’s that the power company’s cost structure is changing, blaming conservation efforts is not just artless, it’s bad for business. And using “allowed to implement a new charge” does little except angers customers as they pay their bill.
I once asked a contractor about those Central Vacs that have some houses have, and he shrugged and said “I’ve ripped just as many out as I’ve installed.” We’ve seen just as many retailers pull out their retail pricing optimization software as they’ve installed, because you get outcomes like the below: (more…)
As firms grow in sophistication with their pricing capabilities, at some point they exhaust the opportunities that internal to their company, and start looking outside to explore the dynamics of the industry. That’s where they first encounter game theory, though many struggle with how to apply it to their strategy.
What is game theory?
In short, it’s the idea that the landscape is made up of rational players, and that they will act on their own and react to your decisions over time.
So how does that apply to pricing?
It’s easiest to start with a thought experiment: What if they were as smart as you are? Here’s a case study from a recent engagement. (more…)
A client recommended this blog post summarizing the main components of price promotion measurement. Across industries, our experience is that lift and halo almost never offset the markdown, cannibalization, and pull-forward effects. That said, promotion is a critical marketing lever, and avoiding it entirely is a pretty bad idea.
As companies continue to try to actually deliver on the promise of “Big Data,” we’ve seen a number of them fall flat on their faces in sometimes very public ways.
- In this article, a business school professor and Big Data expert has a spooky experience firsthand.
- And when firms sell their customer data (or even appear to do so), the response can be immediate, vicious, and public. An online poster to the huge online community Reddit posted this:
-I used a throw away hotmail that averaged maybe 10 spams a day that I’ve had for 5 or so years.
-I went to Geico.com and used their “Get Free Rate Quote.”
-The quote was $854/6 months.
-I said damn, that’s a lot. I had 1 speeding ticket when I was 19, -I’m currently 31 and drive a Nissan.
-I didn’t further my search at that time and put it on the back burner.
-I checked my hotmail later, 1,019 emails in 4 days, a letter in the mail from Gieco, an advertisement in the mail from Geico, other car insurance mail magically appeared in the mail.
-I called Gieco and asked them to chill the fuck out. They said they don’t do that. I said that’s funny you do.
-I went to Esurance. $92 a month and no increase in spam mail. Just the constant barrage of shit from Geico.
- In the same vein as Prof. Johnson above, I paid the fee to get a look at what Acxiom knows about me after this article in the NYTimes. The process was so complex that it became clear that the entire process was simply for PR purposes. It required mailed physical checks (what year is it? no credit cards, no online system at all?), email confirmations to a person rather than a system, and locked, encrypted PDFs. And after coming out the far side of the process, I received only the bare basics- the last 5 addresses I lived at, family members, etc.
So what’s the bottom line? Companies leveraging big data must:
- Drive the biggest insights from the aggregated data. (Trust us, there’s gold in that data)
- Be overly cautious about how it’s being used whenever it is precise to individuals.
- Fully disclose what they keep, and allow anyone to opt out. The small numbers of opt-outs will pale in comparison to the value of avoiding bad press.
If it doesn’t happen with self-regulation, it won’t be too long before an external force intervenes- either through consumer revolt, or worse, government intervention.
Analytics should rarely live alone- they should support (but not replace) a broader ecosystem of decision inputs. But we can empathize with a common challenge- “what do I do when I’m being told two contradictory things?”
Hence the adage, known sometimes as Segal’s Law: ”The man with a watch knows what time it is. The man with two watches is never sure.” (more…)
I love Derek Thompson at the Atlantic. But this article compares “attention” and “users” across marketing vehicles, which ends up having very little to do with marketing ROI for advertisers.
The largest advertisers are not dumb- they utilize advanced statistical modeling and toolsets to optimize their marketing spends pretty precisely. So why do they still spend so much on print? Because it works.
The true story is more complex and nuanced than the charts suggest. If I were to show these to the large advertisers, they would say “Yep. So what?” They know that ”attention” and “users” are not equivalent across marketing tactics. TV controls the whole screen with video and sound, while a little box next to your facebook page is easily ignored, and radio catches you in your car- when you’re less likely to change channels.
But at the end of the day, they simply don’t care much about the mechanism of how or why different ads work. There is enough evidence and proof that they do work, and they work differently, but they drive sales and margin, often with positive ROIs.
We’re pretty passionate about pricing, and I’d like to think that when we win a client’s business it’s because we offer answers that better address the critically important, but sometimes subtle, nuances in pricing. (more…)
It’s this kind of aggravating nonsense and irresponsible writing that sets the field of marketing measurement back years. And infuriatingly, it is read by a lot of people.
The first paragraph: “Measuring marketing spending used to be pretty easy, at least in theory: You’d run a big ad campaign and then see if your sales rose. If they did, great. If not, then you wasted your money.” (more…)
The NYT has a great article on the state of promotion pricing in retail. JC Penney is trying to get “off the drug” of discounting and promotion, and is seeing the expected sales losses in doing so. However, the article misses the game theory effects that are emerging among retailers in the space. The dynamics are such that they’ve set up a perfect Prisoner’s Dilemma, and predictably, all are losing. (more…)
There’s no shortage of coverage of late for “big data analytics” and the hype around it: Forbes’ “How Target Figured Out A Teen Girl Was Pregnant Before Her Father Did” and The NYT’s “How Companies Learn Your Secrets”. For the moment we’ll set aside whether this is new (we don’t think so), whether bigger data equals better data (nope), and whether the future will look very different than the present (not likely). Instead we’ll focus on how new grads should best prepare for this burgeoning marketplace.
A Fortune-50 Retailer CEO was facing slowing store growth and a declining economy, and was accelerating price increases across the store that were growing the bottom line. ”What’s the value of being in a duopoly if it’s not pricing power?” he asked. And after all, his pricing analytics team continued to show generally inelastic price elasticity, indicating he could continue to raise prices. Yet after much debate he backed off his wholesale price increases over time- why? (more…)
Haven’t The Terminator, and I, Robot taught us that there will always need to be a human at the controls of the robot army? Even as we build analytic algorithms for our clients, we tell them that they are guides, not replacements, for our judgment.
Here’s a great article on price-matching bot behavior on Amazon’s marketplace, and how it can lead to a $15 book listed for over $2MM.
Download the below in a 1-page whitepaper on circular ROI.
There’s been a lot of noise in the advertising industry about the impending death of print as an advertising tactic, and it’s certainly hard to argue with ongoing circulation declines from data at ABC and NAA. However, the ROI on circulars is actually increasing. Why?
When we assess our clients’ capabilities in Pricing Analytics, we use a framework that points out strengths and weaknesses of the system, rather than focusing on a single component. We’ve seen too many demonstrations where the math becomes bleeding edge but the business gets no benefit. The equivalent problem in a factory would be to double the production machinery floor, but keep shipping capacity the same.
In short: Your pricing strategy is defined by the WORST performer in the chain, not the best.
So what do we look at to determine the total pricing effectiveness? (more…)
Many of our clients have trouble striking the balance between the Art (their intuition and gut feels) and Science (analytical results and ROI) of their marketing plans. As a rough starting point, here are the three most important times in which to ignore the analytics: (more…)
Even more evidence of retailers struggling under the continuing assault of in-store price scans is here at the Chicago Tribune. A while back we predicted this would happen. Next up: doubling down on in-store service (or, back to the basics of retailing).