The Consumer Products industry is in a state of flux, as consumers increasingly embrace health, beauty, convenience, sustainability, and premium products. Established consumer packaged goods (CPG) brands are fighting to stay relevant, retain their share of wallet and maintain their competitiveness.
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The Consumer Products industry is changing faster than ever before in history. AI helps companies better connect with the empowered consumer, optimize their range of products in order to deliver to customers when and where they want them, all while improving operational efficiencies. AI empowers you by leveraging your own data about your customers to better understand how their needs have evolved and how your organization can adapt to a rapidly changing marketplace.
- Achieve marketing ROI across digital and traditional channels
- Improve customer satisfaction using surveys and reviews data to gauge sentiment for the entire customer base
- Predict time to next purchase order based upon prior purchase history and customer segmentation
- Anticipate next customer CRM state (e.g. activation, regular, high value, decliner, dormant, churn) to inform the strategy of future marketing comms
- Hyper-personalize and identify the most effective products to present to each individual customer based on historical data
Product Assortment and Supply
- Predict sales of product innovation and new product launches before they reach the market through AI-based forecasting
- Minimize 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 Optimization and elasticity to identify optimal price points influenced by multiple factors such as item, brand, category, and more
- Predict staffing levels for customer service and distribution centers 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 individualized to each retail banner and geography
AI Use Cases in Consumer Packaged Goods
AI-driven CPG companies are seizing every opportunity to use data to analyze changes in customer behavior and shopping habits to ensure the right product assortment, promotions, and for direct to consumer (DTC) personalized communications are executed. At the same time, CPG companies are transforming from traditional forecasting methods to become AI Demand Forecasting driven to ensure the highest level of accuracy so the product is always available when the customer expects to purchase.
Today’s consumers have zero tolerance for issues, want to be able to purchase what they want when they want it, and are more mobile than ever. 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.
Product Assortment and Supply
The CPG industry and its companies are using AI to predict the range of products on-shelf, their optimal price points, and sales of new products entering the market. In addition, AI-driven Demand Forecasting informs manufacturing and shipping levels required to fulfill customer demand – by store, date, and SKU.
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 what types of products — they need to in order to meet consumer expectations. Automated machine learning can help CPG businesses improve their ability to predict consumer demand for goods.
DataRobot Helps You:
Execute AI-based decisions
DataRobot can significantly increase the number of AI machine learning solutions that are deployed within your CPG business to help you gain a strategic focus on the consumer products brands with the strongest returns.
Increase AI adoption using existing headcount
With the lack of data scientists available for hire, DataRobot can help you transform your skilled business analysts into AI Producers. Guardrails built within the DataRobot platform ensure you can safely democratize AI across your organization.
Transform your business from descriptive to predictive
DataRobot helps transform your business from one that makes decisions based on past events to one that makes strategic decisions based on what will happen in the future.
Be more personalized with customer engagement
With models that continuously learn from past behavior, DataRobot can help easily predict the next best offer for your customers.
Increase accuracy for the demand of your products
One of the biggest challenges CPG companies face is determining how much product inventory and what types of products they need to have on hand in order to meet the expected demand from consumers and retailers. DataRobot helps retailers improve their ability to predict consumer demand for goods using automated machine learning.
DataRobot’s platform makes my work exciting, my job fun, and the results more accurate and timely – it’s almost like magic!
I think we need to take it upon ourselves in the industry to build the predictive models that understand what the needs and wants of our customers are, and go through the whole curation process, become their concierge.
At LendingTree, we recognize that data is at the core of our business strategy to deliver an exceptional, personalized customer experience. DataRobot transforms the economics of extracting value from this resource.
We know part of the science and the heavy lifting are intrinsic to the DataRobot technology. Prior to working with DataRobot, the modeling process was more hands-on. Now, the platform has optimized and automated many of the steps, while still leaving us in full control. Without DataRobot, we would need to add two full-time staffers to replace what DataRobot delivers.