How do you use AI to forecast demand and allocate inventory for promotions?

1 What is AI and why use it for promotions?

AI is the ability of machines or software to carry out tasks that usually require human intelligence, such as learning, reasoning, and decision making. AI can help you enhance your promotion performance by allowing you to analyze immense and complex data sets from multiple sources, like sales history, customer behavior, market trends, weather, and competitors. It can also generate precise and detailed demand forecasts for each promotion, taking into account various factors like seasonality, elasticity, cannibalization, halo effects, and stockouts. Furthermore, AI can optimize your inventory allocation and replenishment across different channels, locations, and time periods to reduce overstocks and out-of-stocks. Lastly, it can evaluate the effectiveness and profitability of your promotions so that you can learn from the results to make better decisions in the future.

2 How to use AI for demand forecasting?

Demand forecasting is the process of estimating the future demand for a product or service, based on historical data and other variables. It is essential for promotion planning, as it helps determine the optimal price, quantity, timing, and duration of promotions. However, demand forecasting can be challenging when dealing with promotions, as they introduce uncertainty and variability in customer behavior and market conditions. AI can help overcome these challenges by providing advanced statistical and machine learning models that capture complex and nonlinear relationships between demand and various factors. It can also provide real-time and dynamic forecasts that adapt to changing data and scenarios, as well as scenario analysis and what-if simulations that compare different promotion strategies.

3 How to use AI for inventory allocation?

Inventory allocation is the process of distributing available inventory among different channels, locations, and time periods based on expected demand and business objectives. It is critical for promotion execution in order to ensure availability and visibility of promoted products and maximize sales and margins. However, inventory allocation can be complex, particularly when dealing with promotions as it requires balancing service level, inventory cost, and markdown risk. AI can simplify this process by providing optimization algorithms that consider forecasted demand, inventory constraints, transportation costs, and service level targets to find the optimal inventory allocation and replenishment plan. AI can also provide prescriptive recommendations to suggest the best actions and adjustments based on current and projected inventory levels, demand patterns, and performance indicators. Additionally, it can alert you of potential issues or opportunities such as stockouts, overstocks, markdowns, or uplifts.

4 How to use AI for promotion evaluation?

Promotion evaluation is the process of measuring and analyzing the results and effectiveness of a promotion, based on the predefined objectives and metrics. This process is essential for promotion improvement, as it helps to identify the strengths and weaknesses of your promotion strategy, as well as learn from customer feedback and insights. However, conducting a promotion evaluation can be challenging, particularly when taking into account factors such as seasonality, competition, and customer loyalty. AI can assist in this process by providing causal inference methods that can estimate the incremental sales and profits generated by each promotion, controlling for confounding factors and counterfactual scenarios. Additionally, AI can be used to create attribution models that assign credit for each promotion outcome to different drivers such as price, display, feature, or media. Natural language processing (NLP) tools can also be utilized to extract customer feedback and sentiment from various sources like reviews, surveys or social media.

5 How to implement AI for promotions?

Implementing AI for promotions requires a combination of technical, organizational, and strategic capabilities, such as reliable and relevant data sources, robust and scalable AI platforms and tools, skilled and collaborative AI teams and partners, and clear and aligned AI goals and metrics. To optimize your promotion performance, it is important to define objectives and KPIs that are aligned with your category strategy and customer value proposition. Additionally, you should identify data sources and requirements in order to ensure their quality, completeness, and consistency. Furthermore, you should select AI models and methods that are accurate, robust, and interpretable. Finally, test AI solutions and recommendations to monitor their performance, impact, and feedback. By applying these best practices, you can leverage AI to enhance retail category management skills while delivering more value to customers and stakeholders.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?