Haystack EU 2023: Learnings and reflections from our team
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Dynamic pricing (also known as demand pricing, surge pricing, and time-based pricing) is basically as it sounds: flexible competitive pricing. The price of a product goes up and down with current market demand and other external indicators according to complicated pricing algorithms, with the goal to sell the same items to different groups of consumers at different prices.
How fast can prices change? Dynamic pricing is based on machine-learning analysis of real-time data, so It could be only a matter of minutes. However, “in retail, dynamic pricing lets you arrive at optimal prices over the course of weeks or months rather than minutes or hours,” says dynamic-pricing expert Seth Moore.
Dynamic pricing can take various forms, adjusting for:
Some industries apply pricing rules extensively. You’re probably aware of this going on with airline tickets, ride-sharing services (maybe you’ve been hit by Uber’s surge pricing), the hotel industry, retail shopping, and entertainment. Many of these adjustments are done in real time, such as with Uber rides during rush hour, while others reflect changing market trends dictated by the changing seasons and other factors.
The variable-pricing scope can be huge. Every day, Amazon, for example, changes its product prices an average of 2.5 million times, and, according to one study, may change prices significantly — by up to 20% — to account for competitors’ prices at the time.
Dynamic pricing is implemented slightly differently depending on the use case. For instance, when implementing it in some brick-and-mortar stores (e.g., Kohl’s), it takes the form of computerized shelf signs showing prices that can be instantly changed based on supply and demand. And then there are online retail store pricing tools: managers might decide to adjust item prices based on historical purchases, cart abandonment, or other rationales.
Despite its modern incarnation, dynamic pricing strategy originated waay back in the 1980s. When the arrival of budget options in the airline industry began chipping away at American Airlines’s comfortable margins, the company set up a new way of pricing its tickets. By making ticket prices on low-demand flights cheaper and tickets on high-demand flights more expensive, American was able to rise above the challenging market conditions in the not-so-friendly skies and compete with other airlines’ lower prices.
Since then, all the airlines have adopted a dynamic pricing model, and the algorithms that determine their prices have become more complex. To optimize flight prices, a modern dynamic-pricing model considers the exact times and days that air travelers book their tickets. In 2020, Skyscanner reported that simply booking a flight on a Thursday instead of a Monday could mean getting a lowest price.
A strategy for flexible pricing is simply a company’s chosen pricing method among the various types of dynamic pricing.
A company could charge higher prices on in-demand items or services that are flying off the shelf while cutting their price points on less-popular or overstocked items, for instance. In addition to demand, companies implementing dynamic price increases or reductions typically consider how much competitors are charging for the same items and whether it’s the right season. In order to determine the pricing strategy for an item during any given time period, these types of variables are factored in and then applied to prices by rule-based algorithms.
Companies implement their dynamic pricing strategies in different ways, but regardless of the variables they use, and whether they employ real-time pricing or not quite as timely changes, data-science-driven price optimization is a business practice that can inspire strong ethical concerns among consumers.
To some people (e.g., folks on a budget who are paying attention), like those who were charged by Ticketmaster up to $5,000 for a 2023 Bruce Springsteen concert ticket during the peak pricing time period, it seems that dynamic pricing fluctuations are focused on using machine learning to maximize profits to the complete detriment of the company’s reputation.
You could argue that the business ethics of personalized pricing have always been a gray area. One company draws a line, while another is willing to make different pricing decisions that cross the line in the name of profit. And now, the scientific-data-based world of algorithms that allow companies to confidently make quick pricing changes has added a new decision-making twist. What company wouldn’t want higher profit margins if they can conceivably get them without losing customers?
Is there a use case that can realistically maximize the effects of dynamic pricing without offending customers? As consumers have become more attuned to moral causes, they may be taking a closer look at your business’s selling conduct, including whether and how you’re deploying dynamic pricing.
Remember, the goal of using a dynamic pricing strategy is to maximize profit, not create loyal customers. In a dynamic pricing model, regard for the individual customer experience or collective negative impact is almost non-existent.
The tech sector is particularly vulnerable to questions involving morality. With the amount of data available and the use of AI encompassing components like data mining, intelligent algorithms, and neural networks, tech companies are awash in money-making innovations that may be ethically questionable and best kept under wraps.
Some ethical concerns about dynamic pricing include:
For some companies, the tides may be beginning to turn in a more ethically correct direction. One study found that in 2021, 32% of US and EU businesses said they would not introduce dynamic pricing. However, the jury is still out: another 27% were still evaluating.
“The challenge is to use dynamic pricing in a way that builds customer trust and aligns with consumer perceptions of fairness,” says Deloitte. “Success depends on a dynamic pricing mechanism that provides visible benefits to the consumer and aligns price with value delivered in a consistent and predictable manner.”
Is there a way to use technology to assess the right market price, maximize profit, and also recognize the importance of consumers not as data points who can maximize profit but human beings who are likely to be loyal and valuable customers when treated well?
In other words, can you implement an ethically sound dynamic pricing strategy?
It would be safe to say maybe.
In dynamic pricing’s favor: shoppers are already used to paying different prices from time to time because online retailers often offer promotional pricing and discounts based on the statuses of their supply chains. So you could argue that conceptually, dynamic pricing isn’t that far off.
Meanwhile, let’s look at one alternative way online retailers can be dynamic in the name of increasing their revenue: ethically oriented dynamic discovery.
“Dynamic discovery” — hmm, what the heck is that? It sounds a lot like dynamic pricing, and it’s also focused on maximizing profit. But no; it’s fundamentally different.
Instead of using customer data to make continual price adjustments, dynamic discovery uses consumer data to present the target online shopper’s most relevant products, deals, and discounts while maintaining the same item pricing across the board for everyone.
In this era of new consumer consciousness about Big Data ethics, making the jump from a business model that embraces dynamic pricing to a dynamic-discovery-oriented approach can help safeguard your business. Set prices delivered “dynamically” can also help you build stronger relationships with your customers and become a more trusted brand.
If you’re looking for a more decidedly ethical alternative to potentially consumer-alienating dynamic-pricing practices and your business needs to increase conversions and ensure economic efficiency, consider checking out Algolia’s discovery capabilities.
At Algolia, we specialize in guiding users to the right place, whether they do that through our intuitive search API or our holistic dynamic discovery feature.
For the ecommerce industry, using more than 50 data points, our discovery software identifies the right deals, discounts, and special offers for relevant customers. There are no smoke-and-mirrors price changes — no frequent SKU price increases and decreases — simply your best competitive fixed prices delivered more effectively.
So yes! You can create an awesome organic shopping experience with static pricing that never makes your shoppers question your ethics. Ask our account team about dynamic discovery or start building out a new site-search solution free.
And if you’re interested in more information about dynamic-pricing options, check out our continuation of this topic: How dynamic pricing software can help your ecommerce business thrive.
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