Price: Maximizing Customer Loyalty through Personalized Pricing

By Cactus Raazi

Price is the primary feature of every transaction—so why is it often treated as an afterthought? Most companies use pricing approaches developed before the internet, failing to harness modern analytics. Your customer relationships vary widely; shouldn't each customer's loyalty to your product or service be reflected in their price?

In this age of increasing price transparency, uniform pricing is no longer sufficient. The best way forward is to create personalized pricing for your loyal customers and resist the constant discounting pressure of internet price aggregation.

In Price, Cactus Raazi invites you to shake loose of your pricing preconceptions. Whether you're a corporate executive or a sole proprietor, you'll see how personalized pricing can improve customer loyalty and turn episodic transactions into recurring revenue. With price transparency and aggressive discounting here to stay, now is the time to refocus your pricing approach on your individual customer.

• Language: English
• Publisher: BookBaby
• Release date: Feb 23, 2021
• ISBN: 9781544506104

Book preview

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Copyright © 2019 Cactus Raazi

All rights reserved.

ISBN: 978-1-5445-0610-4

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To the cynics, who know the price of everything and the value of nothing

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Contents

Introduction

1. Understanding the Markets

2. The Impacts of Electronic and Mobile Commerce: Price Transparency and Competition

3. The Price Is Right, or Is It?

4. Defining Loyalty Pricing

5. Gathering Data to Set Loyalty Prices

6. Pricing in the Future

Conclusion

About Elefant Inc. and Cactus Raazi

Acknowledgments

Introduction

Pricing for the Modern Marketplace

Every commercial transaction requires a price to be set, and while there are many aspects to whether a transaction takes place, price is the fulcrum. A number of elements influence a consumer’s decision-making process—from perceived value, to geographic location, to the smell of a store, to marketing—but no single aspect has a greater impact than price. No matter how nice or how miserable the customer experience is, the price must be right for a transaction to happen.

Price is one of the most obvious and important aspects of a sale, yet the way we think about and set prices has not evolved to account for the many changes in the consumer experience. While we have adopted technological solutions for hundreds of other problems, price has remained mostly a guessing game. This can be seen in the many attempts to fumble through various discounting tactics without much consideration of the individual consumer experience related to pricing.

We’re moving into a world where price is neither constant nor general—a world of dynamic pricing tailored to the individual customer. We now have the technology to set prices that reflect both marketplace conditions and the seller’s relationship to a specific customer. This book is about the future of dynamic, personalized pricing.

How Prices Are Currently Set

Let’s say a fashion company wants to sell a new wool coat. The design is complete, and production is ready, but how do they decide how much to charge for it? In most businesses today, a single person or group of domain experts gather in a room, discuss how much they think people will pay for the coat, and then come to an agreement on the price.

Obviously, these experts will consider several factors, especially the input costs, because no astute business would deliberately sell its products at a loss. They will consider the costs to design the item, the costs of labor and raw materials, and all the other direct and indirect costs of producing the coat. They also might take into account the season and current trends, the price of competitors’ coats, and what the market will bear. With all this information, they settle on a price.

This is the way prices have been set for decades, so why change now?

The answer is simple: Because there’s a better way.

Informal committees of domain experts can settle on good prices but not the best prices. The first issue is that the traditional pricing method is largely an arbitrary process. I’ve been on such committees determining price, so I know firsthand how much guesswork is involved. While the domain experts consider many factors, it is ultimately their human opinion that determines the final price.

The second issue is that this process does not treat customers as the individuals they are. The same price is not the right price for all of your customers. Your customers exhibit different behaviors, so you need to be thoughtful about engaging them on an individual basis. If your customers are individuals, shouldn’t they have individualized prices that reflect their relationship to your business?

Objective Pricing: The Rise of Elefant

In 2014, I was working in the bond business. When trading large blocks of bonds, you start to think very deeply about pricing. Every day, billions of dollars of bonds are traded, and the prices are in large part determined by people—domain experts called traders. To earn a return on their bond trading, banks rely on traders to analyze the data and make educated guesses about the right price. While these experts consider various pieces of information, their guesstimates remain subjective, because the human brain can’t evaluate the total amount of data available.

I knew there had to be a better, more objective method to determine bond prices. I asked myself: Why rely on human guesstimates when pricing can be determined objectively through pure analytics?

First, pricing must be objectively based on data, as opposed to subjective opinion. Second, pricing must drive toward a particular objective—a specific company goal, whatever it may be, from building recurring revenue streams to ensuring sufficient return on capital.

I first explored this idea in relation to bonds, because that was my area of expertise, having worked in bond trading since 1998. I also realized that a shift to objective pricing based exclusively on data could apply to many products and services. This concept was the seed that sprouted into my data analytics company, Elefant.

At Elefant, we ingest a huge amount of data, and then we use software to analyze that data to set prices in line with specific objectives. In the pricing of bonds, for example, the objective is a minimum return on capital or return on equity. While we built our business to work in a variety of domains, we started with bonds. After we buy a bond from a customer, we hold it on our balance sheet for some period of time before selling it to a different customer. We use analytics to figure out how long we will likely hold the bond, which in turn helps us determine the right price. (For the majority of products, I believe the right price is the one that, at time of transaction, maximizes customer loyalty over the long term. Bond trading, however, is a unique situation. Traders have regulatory and fiduciary duties that require them to buy and sell at the best price at the time of transaction, meaning they are not allowed to make decisions based on a longer time frame. Thus, the objective in this case is return on capital or return on equity, instead of loyalty maximization.)

Using artificial intelligence (AI), we do hundreds of transactions a day with no human intervention. Elefant’s success since our founding in 2015 is proof that this data-driven, future-forward model of determining price works. In fact, we were recently named to CB Insights FinTech 250, a list of 250 of the top startups applying a mix of software and technology to transform the financial services industry, which includes everything from peer-to-peer lending to robo advisors. We’ve already achieved a 2 percent market share among bond dealers. In comparison, the largest dealers each have between a 6 to 10 percent market share.

I have no doubt that, slowly but surely, this objective, data-driven approach will become the standard way of pricing not just bonds but many goods and services. There will remain some exceptions, however, specifically in auction and exchange marketplaces, which have a different price-determination process.

A World of Pure Price Competition

We live in the era of choice. Consumers are no longer restricted to the products that appear in a given store, city, or even country. For any given product or service, consumers can access countless global options via the internet.

The major risk of selling in the digital age is that most goods and services will be sold like commodity items, purchased on price aggregation websites or through browser extensions that scour the internet for the lowest possible price. This means that many products or services will be presented as similar and will be compared based on price, despite production differences.

I term this phenomenon brand homogenization, which is a step below commoditization. Brand homogenization is what happens when non-commodity goods—like clothing or furniture, for example—are stripped of their identifying characteristics and are thus treated like commodities in the purchasing process. One of the largest catalysts to brand homogenization is aggregation websites, which allow customers to filter products or services based on desired features. Once all the choices have been filtered to a subset of options that are all sufficiently acceptable to the customer, the determining factor becomes price. Thus, within the subset of acceptable options, the purchasing process reflects that of commodities.

The pure price competition created by brand homogenization—as facilitated by aggregation websites, browser extensions, and discounting platforms (such as Groupon)—will erode both a company’s pricing power and marketing message, a nasty double whammy.

The airline industry is the perfect example of the dangers of brand homogenization. More than perhaps any other industry, airlines have devoted tremendous resources to determining the highest price for any seat on any plane at any time. For many years, the airline industry was the absolute leader in price optimization for revenue maximization. They were the pioneers of charging different people different prices for the same good, an airline seat.

Despite airlines pouring countless dollars and hours into revenue-maximization price theories, the current state of affairs in the airline industry is horrible, in large part because flying has become a homogenous experience. The colors on the plane might change, but the core experience—traveling safely from point A to point B—remains the same. Because there is virtually no difference between the various airlines, the vast majority of air travelers use aggregation websites like Expedia, Priceline, and Kayak to find and purchase tickets. If a customer has a choice between a flight with