AI will help retailers to maximum profitability, says GlobalData

AI to help retail and FMCG to extract value from large data sources

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AI will help retailers to maximum profitability, says GlobalData Predictive analytics can help retailers achieve efficiency, and scale their data analytics programs.
By  Mark Sutton Published  June 19, 2018

Artificial intelligence (AI) and machine learning will be the next step for retailers to take to obtain maximum profitability, according to GlobalData.

The data and analytics company said that AI can help retail and FMCG companies to unlock the value of huge volumes of data that they hold on customers.

AI efforts can build on the achievements of big data and analytics (BDA) programs, GlobalData said, helping organisations to scale up their focus on customers or other areas of efficiency. While many enterprises hold a colossal amount of customer data, only a handful are able to fully utilise this data. Machine learning and predictive analytics will enable organisations to enhance decisions related to supply chain management, customer behaviour, staff allocation and other areas where they can make efficiencies.

Rena Bhattacharyya, Technology Research Director at GlobalData, said: “While most analysis related to understanding market trends, achieving greater customer personalization, and improving operational efficiency can be performed with BDA methods, AI in many cases is less cost intensive and faster - at times even instant. Intelligent machine learning systems can replace expensive armies of data scientists and provide solutions or product recommendations in an automated way. The timing of the analytics is crucial, since opportunities for cost savings or additional sales are frequently limited to minutes or even seconds.”

GlobalData said that many use cases for predictive analytics have come out of the initial experimental phases of AI adoption by FMCG companies. For example, thanks to the integration of machine learning, eBay is now able to help sellers on its platform with solutions ranging from delivery time to fraud detection. It can also discover gaps in inventory of a particular product and alert related sellers to stock up on that item, as well as make price recommendations based on trending events automatically.

Procter & Gamble used deep learning technology to create a skin advisor service for its Olay brand. After screening millions of selfies and spotting key age characteristics, Olay’s service can provide women with personalized product recommendations based on skin analysis.

Leading retailers including Amazon, Alibaba, Lowe’s and Tesco are developing their own AI solutions for automation, analytics and robotics use cases. At the same time, many retailers have not implemented any AI solutions yet and are likely to fall behind their competitors.

“AI is the path to maximum profitability. It will be the technology platform that reaps the biggest rewards. Retail and FMCG companies looking to launch AI-based solutions should start by understanding the needs of their target customer base, focus on providing an omni-channel experience, and strive to achieve cost savings through greater efficiency,” concluded Bhattacharyya.

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