AI is turbo-charging Consumer Packaged Goods

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Consumer Packaged Goods

Helping Consumer Packaged Goods companies turbo charge their Supply Chains with AI
Our customers include companies in the food, beverages, personal and household care, consumer durables, luxury goods, apparel, sports and recreational products. They have become true partners for retailers, managing key accounts more effectively than ever than before by using data for visibility, predicting demand, trends etc. and sharing insights with their retail partners thus turning their supply chains into a competitive weapon.
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0of executives say they won’t achieve their growth objectives without scaling AI.0of executives believe they risk going out of business in 5 years if they don’t scale AI.

Consumer Packaged Goods

Established consumer packaged goods (CPG) brands are fighting to stay relevant, retain their share of wallet, contain costs whist maintaining their competitiveness against rivalry from smaller, aggressive, nimble, low cost disruptors. These competitors use some of the best tools and Social Selling techniques available to drive their products to market. Well establish brands in the CPG space are also faced with having to protect their brands against counterfeit goods, fraud, and other risks.

Data Technology can help you transform your CPG business to help you combat these risks and win by leveraging your most valuable data assets using Enterprise AI.

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Challenge 1
Solution 1
Consumer Engagement
Consumer Enagement
Today’s consumers have zero tolerance for issues, want to be able to purchase on demand and instantly, they are more mobile than ever, and speed and accuracy are essential. They are also more likely to view health, wellness, and fitness as top spending priorities than in previous years. CPG brands need to adapt to these trends in order to positively engage with and influence consumer buying decisions.

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  • Achieve marketing ROI: across digital and traditional channels
  • Improve customer satisfaction: using surveys and reviews to gauge sentiment for the entire consumer base
  • Predict next purchase: based on previous order history and customer segmentation
  • Anticipate next customer: CRM stage (e.g. activation, regular, high value, decliner, dormant, churn) to determine the strategy of future marketing comms
  • Hyper-personalise and identify: the most effective products to present to each individual customer based on historical data

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Challenge 2
Solution 2
Product Assortment & Supply
Product Assortment & Supply
The leaders in the CPG industry must use AI to predict the range of products on-shelf, their optimal price points, and sales of new products entering the market and the effect of the disruptive competitors in the market. In addition, Data Technology helps CPG customers’ to deploy AI-driven Demand Forecasting which informs manufacturing and shipping levels required to fulfil customer demand – by store, date, and SKU.

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  • Predict sales of product: innovation and new product launches before they reach the market through AI-based forecasting
  • Minimise over-production: and out-of-stock scenarios using a range of historic data sources “reverse supply chain” by predicting the probability of return for every item purchased across multiple channels
  • Improve on-shelf availability: by each individual SKU and store and drive corrective action before an issue arises
  • Use Price Optimisation and elasticity: to identify optimal price points influenced by multiple factors such as item, brand, category, and more

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Challenge 3
Solution 3
Operational Efficiencies
Operational Efficiencies
Data Technology’s CPG companies are adopting AI to better identify opportunities to decrease costs while increasing their operational efficiencies to ensure a frictionless customer experience.
One of the biggest challenges the CPG industry faces is determining how much product inventory — and the types of products your company need to in order to meet consumer expectations. Data Technology can help you deploy Automated machine learning to help your business improve your ability to predict consumer demand for goods.

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  • Predict staffing levels: for customer service and distribution centres as demand changes
  • Identify and negotiate: with the most cost-effective manufacturing and delivery partners
  • Improve employee retention: with AI-based HR analytics
  • Enhance predictions of delivery times: for improved operational efficiencies
  • Identify metrics: for mutually beneficial partnerships across the supply chain that are individualised to each retail banner and geography

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

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AI Success Stories

  • 01 / 03

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

  • 02 / 03

    “We want to understand our customers to drive better customer experiences, make their lives easier or give them an overall better customer experience. We do this at 84.51 by making the AI platform available to all of our 200 Data Scientists”
    Head of Enable The Science

  • 03 / 03

    “The AI platform allows our data team to efficiently determine and use the best machine learning model for any supply chain problem”
    VP of Advanced Analytics & Data Engineering