Can AI transform the
Retail industry?

Find out how



Every Retailer needs AI to survive

Gartner predicts 77% of Retailers will adopt AI by 2021. We can help you stay ahead of the curve.

Data Technology can help your business build and implement an AI Strategy that will help you navigate the challenging local market conditions and potential global recession.

Using AI, we can help you improve connections with the end consumer, optimize your product range, and provide the operational efficiencies that will enable you to deliver to the right location on time.

AI Analysis for Retail Executives

Consumers are more connected and informed than ever before.

They demand that retailers understand their ever-changing shopping habits and provide excellent customer service.

At the same time, it is critical to optimise stock and inventory to deliver to customers the products they want with the efficiency they’ve become accustomed to.

This can only be achieved by identifying opportunities to decrease costs, increase operational efficiencies, and ensure a frictionless customer experience.

Data Technology can help you leverage your customer data to better understand how their needs have evolved and how your organisation can adapt to a changing marketplace.

Retail and AI

Watch Kroger’s Testimonial

“Work that would typically take weeks to code up, Data Technology can do in an hour. It gives us time back so we can focus on more important aspects of the business problem.”

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Challenge 1
Solution 1
Empowered Consumer
Empowered Consumer
The Empowered Consumer is more connected must evolving needs and habits in order to provide excellent customer service and win the majority of their wallet share.

See Solution

  • Predict next customer CRM stage: (e.g. activation, regular, high value, decliner, dormant, churn) to determine the strategy of future marketing comms
  • Customer satisfaction: using surveys and reviews data, predict sentiment for your customer base
  • Based upon prior purchase history: predict the number of days to next order
  • Influence consumer buying decisions: by identifying the most effective products to present to each individual based on their historical data (purchases, web searches, etc.)
  • Attribute the value of conversion: across digital channels to ensure digital marketing spend is being used effectively

See Challenge

Challenge 2
Solution 2
Product Assortment & Supply
Product Assortment & Supply
To predict the range and price of stock and inventory required to provide shipping to customers who want to purchasecertain products and have them delivered their terms.

See Solution

  • AI-Driven Demand Forecasting: using a range of historic data sources to inform the level of future demand
  • Forecast returns: Predict the probability of return for every item purchased through all channels
  • On-shelf availability: for each SKU by actively detecting or inferring potential lost sales situations at the earliest opportunity to drive corrective action
  • Promotions Optimisation: Identifying the best SKUs and best promotion strategy (e.g. rebate, discount, BOGOF, etc.) to achieve targeted revenue or volume
  • Price Optimisation: Identification of optimal price points influenced by multiple factors such as Item, brand, sub-category, category, location, product affinity, competitive and demographic

See Challenge

Challenge 3
Solution 3
Operational Efficiency
Operational Efficiency
To identify opportunities to decrease costs and at the same time increase the operational efficiencies to ensure a frictionless customer experience.

See Solution

  • Identify best sites: to open, expand, reduce, or close stores based on strategic goals without cannibalisation of existing store sales
  • Predict staffing levels: for fulfilling orders, customer service and shipping as demand changes
  • Minimise time: and cost to deliver shipments
  • Predict channel volumes: e.g. call center or in-store footfall. Helps to predict staff resources required for any given trading day
  • Identify store: foot traffic to predict staff resources required for any given trading day

See Challenge

All AI use cases underpin increasing revenue, reducing costs and delivering excellent customer service

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AI Success Stories

  • 01 / 04

    “By integrating aspects of machine learning across all of our daily processes, we’re changing the way tests and studies are carried out and embracing the 21st century way of analysis with new data sources, new technologies, and consequently, new ways of working”
    Director of Innovation & Data

  • 02 / 04

    “The biggest impact is that we are now making warehousing decisions in an informed and precise way”
    Senior Business Development Manager

  • 03 / 04

    “Work that would typically take weeks to code up, DataRobot can do in an hour. It gives us time back so we can focus on more important aspects of the business problem”
    Director of Data Science

  • 04 / 04

    “Our platform saved a large US retailer over $2 million a week over the holiday shopping season with AI-driven planning of staff hiring and scheduling for their distribution centers”
    US Global Retailer