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How AI and Machine Learning are Creating Custom Products and Experiences for the Masses
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Research: Retailers Face Data Disconnect, Challenges With AI Adoption
We worked with Adobe to survey 150 C-level executives from large retailers, and we found that while many are thinking about the future of data in their organization, few are using it to its full potential. Shortcomings around connecting data, implementing AI and machine learning and applying insights beyond the marketing department were the most common issues.
Data Unwise: Insights on unlocking where retailers can go next. A research study by Publicis Sapient and Adobe.
Summary
Research Key Findings
Retailers are investing more in data: Early investments in customer experience and leveraging data for marketing are already paying off for large retailers, with organizations planning continued investments as they look ahead. Almost all respondents said they planned to expand their customer experience budget over the next fiscal year and were confident in linking customer experience investments back to ROI.
Despite confidence, retailers still have some work to do: While retailers are beginning to see early success, AI and algorithmic retail programs are still underutilized, with data capabilities only being applied to measure certain areas of the customer journey. Certain data sources are also going underutilized, or are still in experimental phases – leaving retailers with potential missed opportunities to connect with consumers.
Company culture is a challenge, but core to transformation: Employee adoption, a shortage of AI skills, evolving privacy regulations, and internal friction/lack of understanding of AI programs were among the biggest challenges retailers faced when implementing or expanding AI programs. However, retailers are taking a proactive approach, turning to leadership to help build initiatives to change the narrative and inspire acceptance.
“60% of retailers feel that they’re ahead of their competition on AI, but in reality, only pockets are actually ahead of the curve and many don’t understand what true data maturity looks like.”
Hilding Anderson , Head of Strategy, NA Retail
The study surveyed 150 C-suite leaders to measure the level of data maturity in the retail industry today. Research focused on how large organizations (+$2 billion in revenue) are leveraging artificial intelligence (AI), machine learning (ML), algorithmic retailing, customer data platforms (CDPs) and other technologies to drive revenue and enhance the customer experience.
The survey found that while a majority of retail organizations are investing more in data and analytics and feel like they’re ahead of their peers when it comes to AI adoption, they’re really only scratching the surface when it comes to using data in a way that provides deeper, more actionable insights.
“A lot of retailers don’t have an integrated tool set where they can action against data models that are creative. This takes time and investment, but our findings suggest that retailers are overconfident,” Hilding Anderson, head of retail strategy, North America, Publicis Sapient, noted in the report.
Data as a disruptor
Retailers are seeing initial ROI for their investments, but need to dive deeper into the data to drive growth in the future. As AI and algorithmic retailing become more established, retailers are left to figure out how to gain more clarity and maximize value, while reducing internal friction and creating a culture of change within their organizations.
- Dan Peltier and Amy Onorato contributed to this article
Data Unwise: Insights on unlocking where retailers can go next. A research study by Publicis Sapient and Adobe.
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