RESEARCH REPORT

In brief

In brief

  • Artificial Intelligence (AI), the combined use of intelligent technology and human ingenuity, is about to take the Retail sector by storm.
  • Retail AI will extend across the value chain transforming marketing, merchandising, customer engagement and supply chain. Consider the possibilities.
  • Robotic sales reps deliver hyper-relevant experiences, make purchase recommendations and answer customer inquiries based on individual customers’ information.
  • AI, machine learning and analytics applications apply an infinite number of algorithms to spot real-time consumer trends or predict customer behaviors.


The state of affairs

Consumers are increasingly comfortable with AI technologies. Forty-four percent of them currently use some type of virtual assistant.i Even those who don’t have access to a Siri, Alexa or Cortana enjoy AI experiences everyday—often without realizing it. Leading websites and social platforms routinely use AI, along with machine learning and analytics, to provide a steady stream of personalized experiences.

Consumers are ready for traditional retailers to deliver the same level of AI-based personalization they enjoy in other aspects of their lives. Our research revealed that 42 percent of consumers feel it is critical for companies to set new standards for service and engagement. Yet, out of 11 industry groups, consumers rank retailers dead last in their ability to continually improve customer experiences.ii

For retailers, waiting to jump on the AI bandwagon is not a winning option. To survive even the next five years, they must pursue AI’s potential today.

Fewer than 20% of retailers have deployed artificial intelligence.iii What’s holding them back? The belief that they lack the data, skills, tools, culture and leadership required.

Winning the AI race

AI presents a golden opportunity to deliver better, more relevant, more personalized—and more profitable—experiences. But many traditional retailers struggle with where to begin. We advocate a three-phase approach:

  • Ready. Build a bench of AI talent—either by developing it in-house or partnering with external agencies/outsourcing providers that have the adaptive talent needed to launch the strategy.
  • Set. Build the right data-management capabilities. This means focusing on data attributes and structures, and identifying or developing ecosystems that will grant access to the data necessary to make intelligence actionable and abundant.
  • Go! Seek opportunities to deploy AI inside their organizations and across the extended retail value chain. Customer engagement is usually a good place to start.

Infographic: Examples of how AI can uncover value for fashion retailers

AI analysis has uncovered opportunities for retailers to communicate more effectively with their customers by speaking the same language and providing better product images.



Retail’s AI future starts today

Given the perceived complexity of AI solutions and the fast-changing nature of the AI landscape, retailers’ hesitancy may be understandable. But that hesitancy will prove costly over the long run. Unless they jump on board, retailers will miss countless opportunities to develop meaningful customer relationships, turbo-charge their operations, and grow their businesses. In fact, a strong AI capability and a data-driven decision-making culture will be table stakes for retailers in only a few short years. Retailers that don’t prepare for this reality today will lose to those that do.

i Accenture Strategy, Global Consumer Pulse Research, 2017.
ii Ibid
iii Accenture Strategy Retail Analytics Research, 2017

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