SANTA CLARA, Calif.--(BUSINESS WIRE)--DataStax, the real-time AI company, today revealed findings from a new survey1 that underscore the impact of highly relevant recommendations for companies looking to build consumer confidence and drive recurring sales. These recommendations, such as highly personalized product recommendations or next best actions, are generally delivered through machine learning and artificial intelligence (AI) technologies.
The survey, conducted by Wakefield Research on behalf of DataStax, found that nearly 3 in 4 consumers (72%) trust a company more when they receive relevant recommendations. Additionally, nearly half (49%) say they’re extremely or very likely to return to companies that provide such recommendations, suggesting this service is a must-have for businesses.
“Any business looking to captivate and engage their customers absolutely must be thinking about how they can leverage new AI technologies to provide customers with accurate, relevant recommendations,” said Davor Bonaci, executive vice president, DataStax. “The most impactful of these recommendation engines are fed by powerful machine learning algorithms that help to identify patterns and trends in real-time that are often too complex or subtle for humans to detect. The ability to analyze and respond to real-time user behavior with authentic, personalized recommendations and next-best actions is what sets the leaders apart.”
But Consumers Don’t Always Understand AI
While most consumers clearly value the impact of relevant recommendations in their daily lives, they’re often unclear on where those recommendations come from. The survey revealed that 65% of respondents do not realize product recommendations from online retailers are powered by AI, and nearly 2 in 3 (64%) don’t recognize that song or movie streaming recommendations are powered by AI.
But that doesn’t mean consumers aren’t seeing the value of streaming service recommendations. In fact, the survey found that the top benefit of relevant recommendations is time saved when finding something to watch (41%), while another 30% cite that it ensures they don’t waste time on content they wouldn’t enjoy.
Many consumers look to AI to help identify new products and navigate the purchase process. Survey results showed that three-fifths of shoppers (60%) take advantage of relevant recommendations they come across while browsing or shopping online, including 54% of millennials who call these recommendations a great benefit.
Likewise, a report from McKinsey & Company underscored the correlation between excelling at personalization and increased revenues: “Companies who excel at demonstrating customer intimacy generate faster rates of revenue growth than their peers. And the closer organizations get to the consumer, the bigger the gains. Research found that companies that excel at personalization generate 40% more revenue from those activities than average players. Across US industries, shifting to top-quartile performance in personalization would generate over $1 trillion in value. Players who are leaders in personalization achieve outcomes by tailoring offerings and outreach to the right individual at the right moment with the right experiences2.”
Check out the research findings infographic and learn more about the impact of real-time AI here.
1Asked among 1,000 nationally representative U.S. adults aged 18+
2McKinsey & Company, “Next in Personalization 2021 Report,” Nidhi Arora, Wei Wei Liu, Kelsey Robinson, Eli Stein, Daniel Ensslen, Lars Fiedler, Gustavo Schüler, November, 2021
DataStax is the real-time AI company. With DataStax, any enterprise can mobilize real-time data and quickly build smart, high-growth applications at unlimited scale, on any cloud. DataStax delivers the Astra DB cloud database built on Apache Cassandra® and the Astra Streaming event streaming technology built on Apache Pulsar™. Hundreds of the world’s leading enterprises, including Verizon, Audi, ESL Gaming and many more rely on DataStax to unleash the power of real-time data to win new markets and change industries. Learn more at DataStax.com.
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