“Know thy customer” is the first commandment of business, for good reason. A company without a customer base is like a preacher without a congregation: at best, mislabeled. At worst, useless.
But an edict from on high does not a business strategy make. The natural follow-up question is of course: How do you know what your customer wants? And much more importantly: What are they willing to pay for it? In this age of e-commerce and the constant flow of information, big data may be the best answer to both questions.
This idea was pondered in a recent presentation by a Berkeley Teaching Fellow who speaks regularly at Silicon Valley Innovation Center. His presentation, part of a Leading Digital Transformation (LDT) program at SVIC, examined the impact of new technology in understanding customers and pricing dynamically to match their individual needs. Drawing on his wealth of experience and a series of case studies, our speaker showed that innovative companies are leveraging scores of data to segment their customers, continuously optimize prices, and increase revenue — all without ever changing a thing about their products or services.
Pulling the levers of profitability
The factors that determine profit are the same across every industry, from the biggest retail giant to the leanest software startup: production costs, product differentiation, competition, the timeless dance of supply and demand. Not least among these levers of profitability is pricing. By tweaking the variables in creative ways — cutting costs here, acquiring a competitor there — a company strives to max out its bottom line.
But optimizing these profit factors is no easy feat, especially when it comes to pricing. What one customer is willing to pay might be very different from another, and so a business must make some sacrifice to sell to them both at the same price (that is to say, one of those customers would have happily paid more). As before, this disparity between customers’ ideal price points is a burden shared by all industries. But in addressing this burden, those lean software startups — who have direct, personal, and unprecedented access to their customers — may have a leg up.
A traditional business practices price discrimination in traditional ways: sales, volume discounts, and loyalty programs (to name a few) are all ways to capture a broader customer base across multiple price points. A company like Groupon, which launched in 2008 as a “group coupon” platform, exemplifies this approach. By letting local businesses post discounts that would apply only if enough people bought in — a volume discount leveraged by the collective bargaining power of strangers — Groupon was one of the first companies to recognize technology’s potential for variable pricing. Today, the company goes far beyond group coupons: among other offerings, they use advanced AI to “power supply-demand matching” on an individual level.
Which brings us to:
Using data to price dynamically
Dynamic pricing, which means constantly adjusting prices based on various factors, is not a new concept. The airline industry is infamous for shifting ticket prices up and down, seemingly at random, in the months leading up to a given flight. Or take a more modern example, the ride-hailing platform Uber, which adjusts the cost of trips based on current demand using a system called surge pricing. Uber has denied rumours that they also charge more when your phone’s battery is low, but they do know when your battery is low, and they do know it affects your willingness to pay.
And Uber is not the only company that knows more about you than you think. The incredible proliferation of smartphones over the past decade, combined with leaps in AI and machine learning technology, has led to a world of endless — and endlessly useful — customer data. A typical smartphone app might keep track of not just your battery level but your precise location, contacts, connections, physical motions, device model, and much more. All this information can be used to profile you and, well, is there a nice way to say “gouge you for all you’re worth?”
Let’s take a closer look at the airline industry, where new tech is reshaping old habits. The California-based startup FLYR, founded in 2013, runs a continuous dynamic pricing platform for airlines. When a consumer searches for a flight, FLYR’s system factors all the information it can about the request (the sales channel, current market conditions, competitor prices, and more) and the individual (their user profile, customer segment, product interaction, what have you) to show them a personalized price designed to maximize revenue. This is all automatic, in real-time, and constantly getting better — thanks to the ever-growing data set being run through ever-improving algorithms. The company boasts its customers will “never be constrained by static, pre-filed fares again.”
The punchline is that FLYR’s price determination technology first took flight as a fare protection service for consumers. Travelers could pay a small, dynamically-determined fee to lock in the price of an airline ticket before committing to a purchase; then, if the ticket price was higher when they decided to buy, FLYR would refund them the difference. That FLYR has pivoted exclusively to dynamic pricing for airlines tells you all you need to know about where the profit is to be found.
In other words: never again will price-wary travelers be constrained by static, pre-filed fares. They — and consumers across all industries being reshaped by new technologies — will increasingly pay the price their data dictates. Nothing less, nothing more.
Well — maybe just a little more.
Dynamic Pricing Key Concepts And Takeaways
- The cost of a product is not always related to its price. What matters is not the value created for a customer but the value captured — i.e., what they’re willing to pay above cost.
- Static pricing inevitably leads to missed profit opportunities. Price discrimination practices like sales are an effective way to capture different customer segments and create additional revenue.
- Dynamic pricing means price discrimination on a real-time, personalized basis. By using technology like data-gathering apps, AI, and machine learning, companies can directly control access to their customers and glean incredible insight into their willingness to pay at any given moment. Profit will follow for free.
In this article, we review a dynamic pricing session provided to executives during a February 2020 SVIC Leading Digital Transformation (LDT) program. Taking the form of meetings and workshops with top Silicon Valley companies, the program is a journey of inspiration and learning. Apart from providing participants with personal connections to standout figures in the field of innovation, it teaches them how to achieve business growth in times of disruptive technological change.
