Marco Bertini

Oded Koenigsberg

<article-ideainbrief class="article-ideainbrief">
 <h4 class="ideainbrief-title">Idea in Brief</h4>
 <div class="ideainbrief-contents">
  <h5>The Problem</h5>
  <p>Many companies use algorithms to set prices and adjust them in real time so as to maximize profits. But constant price changes can alienate customers, undermine their loyalty, and damage brand reputation.</p>
  <h5>The Cause</h5>
  <p>Pricing algorithms rely on artificial intelligence and machine learning to weigh variables such as supply and demand, competitor pricing, and delivery time. However, they often fail to consider the ways that frequent price changes affect customers psychologically, making them question the motives of companies and the value of their products and services.</p>
  <h5>The Solution</h5>
  <p>To better control what dynamic pricing says to customers and how it impacts customer relations, firms should develop a proper use case and narrative for implementing algorithms, assign an owner to manage them, set and monitor pricing guardrails, and act quickly to override the automation when necessary.</p>
 </div>
</article-ideainbrief><p>On June 3, 2017, blue lights flashed toward London Bridge as police cars responded to reports of a terrorist attack. They blazed past thousands of people who were enjoying a Saturday night at restaurants and pubs in the area. Many of those who were out on the streets, sensing danger, attempted to order an Uber and head home to safety. But for 43 minutes after the first emergency call came in at 10:07 PM, Uber’s dynamic pricing algorithm caused rates in that part of the city to jump more than 200%.</p>

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<p>More and more companies are relying on pricing algorithms to maximize profits. The use of artificial intelligence and machine learning enables real-time price adjustments based on supply and demand, competitors&#8217; activities, delivery schedules, and so forth. But constant price shifts have a downside: They may trigger unfavorable perceptions of a firm&#8217;s offerings and its brand.</p>
<p>It&#8217;s vital, therefore, to understand and manage the signals being sent by the algorithms. The authors offer real-world examples of companies that have succeeded in this endeavor and others that have not. And they recommend four steps to avoid harm: Determine an appropriate use case for algorithmic pricing and explain its benefits to customers; designate an owner to supervise and be accountable for the system; set and monitor guardrails, both to protect against wild surges and to learn how price changes affect all aspects of the organization; and override the algorithms when necessary.</p>

The Pitfalls of Pricing Algorithms

More and more companies are relying on pricing algorithms to maximize profits. The use of artificial intelligence and machine learning enables real-time price adjustments based on supply and demand, competitors’ activities, delivery schedules, and so forth. But constant price shifts have a downside: They may trigger unfavorable perceptions of a firm’s offerings and its brand. It’s vital, therefore, to understand and manage the signals being sent by the algorithms. The authors offer real-world examples of companies that have succeeded in this endeavor and others that have not. And they recommend four steps to avoid harm: Determine an appropriate use case for algorithmic pricing and explain its benefits to customers; designate an owner to supervise and be accountable for the system; set and monitor guardrails, both to protect against wild surges and to learn how price changes affect all aspects of the organization; and override the algorithms when necessary.

The Pitfalls of Pricing Algorithms

Summary.

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