Dynamic Pricing - What It Is and Why It's Important
By Mike Carlton
Guatemalan Crafts Market
One of our sons lives in Guatemala. When Ruth and I visit Oscar and his family she loves to go to the big outdoor Guatemalan craft markets. She’s a big fan of the brilliant colors and native designs they incorporate into much of their work.
While the connection is not obvious at first, observing the business model of these craft markets holds some important lessons for marketers and agencies.
How They Work
There is nothing revolutionary here. Markets like these have been operating since the beginnings of human commerce. There are lots of vendors and lots of competition. Each has a booth to display his wares. Very importantly, there are no price tags. Not on anything. Each craftsman attends his stock within his booth and stands ready to engage with potential customers.
When a shopper approaches the merchant immediately makes a split-second mental judgment about the economic capability of that particular prospect. He observes not just how they look and how they are dressed but also how they speak and carry themselves. Instinctively, with just the few snippets of data he is taking in, his mind jumps to what he believes their pricing tolerance might be. And the prices competitors are asking. That is his first big decision. And it is all based on external considerations.
His read on us is right on target. As North American tourists Ruth and I present a different economic potential for him than the Mayan farm woman with a bunch of kids that preceded us in his booth. His ample experience guides him well.
Once something in his booth catches Ruth’s eye her first reaction is to pick it up, look it over and then ask the craftsman the price. His mind quickly switches to his second big decision. Instantaneously he determines how badly he wants to sell that item. What are his costs for it? What are his cash flow needs? How much inventory does he have of that item? Is it likely that there will be more demand for it next week because of a holiday? All of this going on in his head in a fraction of a second.
Then, combining the data he has from both his external considerations and his internal considerations he tells Ruth a price. One that he believes Ruth will accept and at the same time meet his business objectives. And of course a price that allows him enough negotiating room to assure the profit he would like.
Now that is not a standard or list price. It is a unique price. His offer to Ruth is probably quite different from what he sold the same item to someone else yesterday and what the price he will likely offer to others tomorrow.
After a bit of expected price negotiation a deal is made and money changes hands. Both Ruth and the merchant are satisfied.
And I had just witnessed dynamic pricing in action!
Simply stated, dynamic pricing is tailoring the price to the specific characteristics of each distinct situation. There is nothing particularly sophisticated or new about it. It is the natural and normal way business has been conducted for eons.
Yet modern marketers and agencies seldom use dynamic pricing. Fixed pricing is the norm. With published prices for marketer’s products and a standard price per hour for agency service. When you stop and think about it, most pricing today is kind of on auto-pilot. It is simple. It is easy. And it is egalitarian.
Yet we have to ask the question; Are marketers and agencies missing sales and profit opportunities? And failing to maximize their potentials?
In Sales 101 we learned that for every transaction both the buyer and seller have an optimum price.
For the seller his optimum price is one that is high enough to allow a fair profit yet low enough to not scare off sales. He knows that raising his price from that optimum will reduce sales, and profits along with it. And in addition he knows that reducing his price may increase sales but will reduce both unit and overall profit. So he enters each opportunity with a predetermined optimum price.
For the buyer her optimum price is one that is the same or lower than the value she expects to receive from the purchase. If the price is higher than her optimum number, there is no sale.
This of course is based on her perceived value (both functional and psychic) and varies from individual to individual and from situation to situation.
And a sale is only made when the seller’s optimum price and the buyer’s optimum price coincide. When they do there is a sales transaction.
When you stop and think about it that is how all sales work. Whether it is a minor consumer product or a giant industrial purchase the meeting of optimum prices is the trigger for the transaction
The Problem with Scale
That raises the question; If dynamic pricing is so historic and so natural why is so much business transacted using fixed pricing?
The answer is simple. Fixed pricing is easier.
The Guatemalan craftsman carries all of the data he needs for dynamic pricing in his head. He owns the business and can make all the decisions. On the spot. He doesn’t have management or committees to deal with. It is 100% his call. And the scale of his business is easily within the grasp of one person.
But as businesses grow it is clear that the kind of data that is needed for dynamic pricing generally just isn’t widely available to all who need it. Without that information and the processes to apply it intelligent decision making by others just won’t work.
Not many businesses would want to turn pricing decisions over to front-line people who do not have the information necessary to assure the business maximized both sales and profits. After all, the sales people of most organizations have no access to the specific internal considerations or the specific external considerations that impact each sale. Nor are the resources necessary to calculate the optimum pricing for their company’s products available to them.
So we have fixed pricing.
Pricing Based on Averages
Thus, as they scaled and could not use dynamic pricing, most businesses adopted fixed pricing strategies based on averages. Since they could not make independent judgments for each sales opportunity they built their optimum pricing models on likely averages derived from their knowledge of potential customers and the market’s competitive situation. These averages were based on the behaviors of sizable groups. And those averages were the foundation for the price tag or sticker price.
But as we all know, averages (and medians) represent something like the mid-point. For everyone in the measured group that is above the average there is someone below the average. Few people are spot on the average.
This almost guarantees that for some prospective customers in the group the sticker price is above their optimum, thus negating a sale. And for others in the group the published price is below their optimum, thus minimizing profits.
Money on the Table
The next question is gigantic.
How much money is the inability to do dynamic pricing costing your clients and your agency?
Becoming able to answer this question could be the most important marketing issue of this decade.
Personal Relevance Marketing
During the past few years marketers have made great advances in gathering specific information about individual customers so they can communicate with them in more personally relevant ways. The sales payoff of this is big.
Data on the behavior of individual customers linked to marketing automation and dynamic content delivery are rapidly moving us to a marketplace where each customer can be communicated with as a unique individual rather than as an average person within his demographic group.
Marketers today can gather an incredible amount of data about each person.
When you stop and think about it, many marketers already have much of the data that can begin moving them past dynamic content delivery to the next step which is dynamic pricing. Sophisticated new tools to connect all the dots are now emerging. That can open unexpected doors.
It is sort of like we are half way there. Dynamic content delivery is becoming commonplace. Dynamic pricing can be the next big step in personalizing the entire relationship with each customer.
For the first time, big data holds the promise to be able to scale and institutionalize in an almost unlimited way the kind of information and real time decision making processes that the Guatemalan craftsman uses so effectively for dynamic pricing.
But like any emerging concept, accepted definitions and successful marketing applications of big data are still a bit elusive. Wikipedia defines big data as; “A collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools.”
While Oracle has this to say about it; “The term big data draws a lot of attention, but behind the hype there's a simple story. For decades, companies have been making business decisions based on transactional data stored in relational databases. Beyond that critical data, however, is a potential treasure trove of less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information.”
And of course, technology is just a part of it. Social scientists must necessarily play a key role too. There is a crying need for insightful talented people to plot the relationships of all kinds of data into meaningful understandings of each individual and weave all of that into real time intelligence
Dynamic pricing is not a pipe dream. Auctions, both traditional and online are one subset example of dynamic pricing. And for years broadcast media and airlines have been practicing it. Today’s unsold TV spot has no value tomorrow. Nor does an unsold airline seat the moment the door closes. Customers understand how this works. And they have accepted this kind of marketplace.
But these examples, and most other pioneers, are basing their dynamic pricing decisions primarily on internal considerations. Few marketers are integrating much external information about the individual customer. Yet.
Let’s take a look at a hypothetical airline. It already knows how many seats have been sold on each upcoming flight. This is an internal consideration. And they presumably have very sophisticated software to predict the optimum price for each seat both today and almost minute by minute until the plane is boarded. We see this internal dynamic pricing at work when we go online to book a trip.
On the external consideration side the airline also already knows a lot about each customer. Is she a member of their frequent flyer program? Is she Silver, Gold or Platinum? How many points does she hold? Where does she regularly fly to? What class does she usually chose? Her aisle, window and legroom seating preferences? How far in advance does she usually buy her ticket? The credit card she generally uses? How often she changes flights? And on and on.
So, it is not a great leap to see what additional insight more external information on that individual can provide. Not only specific demographic and psychographic data but also lots of soft information that sharpens the individual behavorial profile of that singular person.
By coupling the internal data with the growing wealth of external information predicting the optimum price in that customer’s mind becomes easier.
And that opens the door to offering that individual customer a price that is tailored just to her. A price that is driven by both internal and external considerations. And while it may be different from the price being offered to others, it is a price that likely brings the marketer’s optimum price and the buyer’s optimum price more quickly into alignment.
And voila, we have dynamic pricing based on internal and external considerations.
At the same time, dynamic pricing raises several concerns. Perhaps the two most important are privacy and equality.
There is an inherent conflict between individual desires for privacy and the promise of big data. So far there is no clear picture of how much privacy people are willing to relinquish in order to have personally relevant communications and pricing. And interestingly, surveys to date seem to show that younger generations are much more comfortable having public access to their personal information than more senior generations. Just where public feelings on data privacy will shake out is still open to question.
The other major issue is equality. Deeply ingrained concepts of fair play expect that everyone should pay the same price for the same purchase. This egalitarian spirit can quickly come into conflict with dynamic pricing’s different prices for different people. Once again this is a major social issue that is yet to be settled definitively.
Where To From Here?
At this point the obvious question is: While this may be interesting, what relevance does this have for agencies?
The answer to this question is really up to the leadership of each agency? And this answer can be on two levels.
First, from the agency’s own pricing standpoint. Many agencies continue to be caught in the standard price per hour of service model. Each client pays the same rate even though the value received may be very different.
While there has been some movement to value and market incentive pricing, most agencies still primarily get paid by the hour. Prices calculated on a fixed published schedule.
If judicially applied, dynamic pricing can offer agencies another pricing approach.
The second opportunity is in the pricing of client products. An agency that spontaneously explores ways for clients to improve sales and profits has a much better chance of gaining the ear of senior client management. So openly examining the concept of dynamic pricing with a client can help move an agency from being viewed as just a commodity provider of communications solutions to the higher position of being an insightful business advisor.
Obviously, everyone is plowing new ground here. There is no proven track record. So movement toward a business model employing dynamic pricing should be undertaken only after careful consideration and testing.
The Next Big Thing?
It is not likely that Advertising Age, Bloomberg Businessweek or Harvard Business Review will ever do a feature story on what sophisticated marketers and advertising agencies can learn from an obscure Guatemalan craftsman.
But is it possible that linking the time-tested common sense practices of that craftsman with the real time capabilities of big data technology just might make dynamic pricing the next big thing in marketing?
Could it be that what is old is new again?