2023-12-22-The_Harris_Poll-AI与相关性的提高_12页_1mb

Report Summary: Achieving Relevancy in Consumer Shopping

Introduction

The report explores the challenges of the "paradox of choice" and details how AI, personalized experiences, and first-party data can enhance shopper satisfaction, build loyalty, and boost business outcomes. It is based on consumer surveys in the US, UK, and Australia.

Key Findings

Consumer Expectations of Relevancy

• Demand for Personalization: 64-67% of US consumers (and similar percentages globally) expect and agree that companies should offer relevant products, services, or experiences tailored to their needs. This drives excitement and increases purchase intent.
• Impact on Shopping: Consumers ranked relevant deals as #1 interest (89% US). Strategies like personalized promotions and relevant checkout offers (64% US) reduce fatigue and encourage repeat business.
• Relevancy Benefits: Nearly half of consumers (50% US) want to shop again with brands that delivered relevant experiences; 55% Gen Z and Millennials believe AI can improve online shopping through features like price comparisons and personalized assistance.

AI Shopping and Young Consumers

• Young Consumer Adoption: Gen Z and Millennials (57%) view inflation-induced stress as affecting decisions but are optimistic about AI's role. 88% Gen Z and 86% Millennials trust AI to enhance shopping via price comparisons, deals, and convenience.
• AI Benefits: AI helps with discovering products, reducing friction, and anticipatory needs, making online shopping more efficient and exciting.

Financial Impact of Irrelevancy

• Cart Abandonment: Between 20-29% of consumers abandon carts or stop shopping due to irrelevant experiences, leading to estimated annual revenue loss of $18 billion for e-commerce brands.
• Checkout Issues: 34% of US consumers face frustrations like time-consuming processes or irrelevant ads. Optimizing checkout for speed, personalization, and contextualization is crucial to reducing abandonment and improving loyalty.

Role of First-Party Data

• Data Importance: Using first-party data enhances relevance, with 75% of consumers preferring companies that use their past item views or cart history. 65-75% say data use positively impacts shopping frequency.
• Business Applications: Data enables advanced targeting through machine learning, improving offer relevance. For example, Rokt's platform processes data to predict engagement, leading to higher revenue—retailers can increase profit by $250,000 per million orders.
• Case Study Insight: HelloFresh leveraged first-party data with Rokt to grow customer acquisitions by 164%, expand globally, and automate analyses.

Overall Conclusion

Achieving shopper relevancy is critical for brands amid economic volatility, as personalized experiences reduce abandonment, foster loyalty, and drive business growth. Success hinges on deploying AI, first-party data, and analytics to streamline shopping, enhance customer satisfaction, and meet rising consumer demands.

Methodology

Surveys were conducted by The Harris Poll on behalf of Rokt in May 2023, involving 6,023 consumers across the US, UK, France, Germany, Australia, and Japan.