Sophisticated pricing strategies are designed and used by the smartest sellers in any industry.
Both online and offline. Including, for example, pricing aggregators and price comparison websites: many success stories have been built on unique pricing insights, leading to growth in revenues, margin and market share. Truly fascinating.
Even in capitalist markets, where pricing is the ultimate mechanism to match buyer and seller of any economic transaction, good old human psychology can obfuscate rational decision making.
Even in otherwise apparently efficient Internet e-commerce complete price transparency is uncommon; academic research and government regulation are mainly focused on the pricing of financial instruments, rather than ‘real world’ products and services.
Caveat emptor. Buyer beware.
Some challenges of the pricing practice
Optimal pricing, even in 2020, is still somewhat more art than science:
- Universities and business schools in their curricula typically only teach basic theory like price elasticity of demand — and not even how to calculate this correctly
- Companies typically adopt non-customer-centric org design, and therefore cross-function topics like pricing lack ownership, leading to ineffective strategies and mis-alignment between the marketing, category and finance teams
- Practitioners, perhaps unsurprisingly due to the previous concerns, typically rely on inefficient rules of thumb like cost+ or competitor+, that are neither data- nor customer-driven.
Is pricing over-leveraged?
Efficient pricing is all about the invisible hand that makes demand and supply meet, within the desired implicit/explicit objectives for the perception of the customer proposition e.g. branding, positioning and value-story.
Perhaps due to the inherent complexity of accurately assessing value-based pricing, and due to the analytical multi-dimensionality of pricing as a topic, only too often the pricing lever is used in emergency, using stop-gap approaches like applying blanket changes across all products.
These do not work: the price perception of each customer, geography and product combination is truly unique, and much more care is required in order to truly extract optimal profit from pricing.
Psychology of choice
Pricing, especially in B2C, works to our psychology of ‘satisficing’ which means saving the effort of a comprehensive, time-consuming comparative search while still being reassured of a ‘good enough deal’.
Deeply, we are aware it may not be the ‘best possible deal’. But it’s still OK, as the time-cost of further searches may be higher than the money-saving in price difference that can be found.
It is a reasonably efficient strategy for both parties involved, even if questionable on the surface: saving time for the customer, winning business for the provider.
Internet websites for booking hotels like booking.com, for example, have been pioneers in pricing innovation specifically around how to display an effective “anchor” (then others, like expedia.com followed suit), leverage psychological triggers accurately, by the book, of how to exploit our ‘satisficing’ — down to the actual wording of the disclaimer. I have shown the details in another post.
Our ‘neural shortcuts’ created by smart-priced hotel booking websites suggest for example to avoid the effort of visiting a travel agency to find a better deal online instead — thus accelerating a secular trend which otherwise would have taken much longer.
Is pricing under-loved?
Good pricing is like the Rolls-Royce of numbers: the ultimate application of analytics in a corporate environment, driven by rigorous detail with well-engineered mechanisms and excellent results.
When done right, pricing strategy can be powerful for a company: discipline can make or break the Profit & Loss of literally any commercial enterprise. Yet, too many still fail at mastering even the basics of it.
I have been building a life-long professional and academic experience of pricing science, which I practice every day at Evo Pricing, the AI system to create value from automated decisions. I hope that sharing my passion will inspire more and more practitioners to start researching and loving this fascinating field!
About the author
Fabrizio Fantini is the brain behind Evo. His 2009 PhD in Applied Mathematics, proving how simple algorithms can outperform even the most expensive commercial airline pricing software, is the basis for the core scientific research behind our solutions. He holds an MBA from Harvard Business School and has previously worked for 10 years at McKinsey & Company.
He is thrilled to help clients create value and loves creating powerful but simple to use solutions. His ideal software has no user manual but enables users to stand on the shoulders of giants.