SmartForecast for CPGs: Revolutionizing Decision-Making with AI
In the dynamic landscape of the Consumer Packaged Goods (CPG) industry, the collaboration between brands and retailers is vital. Central to this partnership is the joint plan for pricing and promotions—a process often bogged down by inefficiencies and uncertainties. Traditional forecasting methods can be time-consuming and complex, leaving stakeholders grappling with cumbersome tools, indecipherable results, and the daunting task of accounting for unpredictable external factors like competitor moves.
This challenge, however, presents a prime opportunity for the integration of groundbreaking technology: generative AI (genAI) and traditional Machine Learning (ML) forecasting models. At Tickr, we harness this powerful combination to transform how CPG companies approach forecasting, making it faster, more accurate, and importantly, more understandable.
Automation and Intuitive UI
Our approach starts with automating the forecasting process. By minimizing the input required from the user, we make complex analytics accessible. Our user interface is designed for clarity and ease of use, ensuring that insights are just a few clicks away. For example, here you just need to select the metric to forecast and the timeframe for analysis… and we handle the rest.
From these initial inputs, we’ll provide a rich set of insights, starting with identifying external economic factors that might affect your forecast.
The process completes after seconds with a robust forecast along with an explanation of influential factors and historical patterns, as well as a chat interface to ask about the patterns uncovered by the machine learning model.
AI-Powered Insights
The true power of our system lies in its ability to uncover and explain hidden patterns through ML models. It goes beyond just presenting results; it interprets them. For instance, our AI can link the price of soda to market trends (“the price of sugar is rising and this will likely lead to a 5% increase in prices across the category”) or use transaction data to predict the timing and impact of a competitor promotions (“your competitor usually runs a promotion on the 3rd week of June”), all within a few seconds. Our AI doesn’t stop at internal data analysis. It actively searches and qualifies external factors, offering a comprehensive view of the market. This holistic approach allows for accurate predictions about competitor actions and market shifts, forming the basis of robust forecasting. This level of analysis was previously unattainable in such a short timeframe.
Scenarios That Speak to Reality
Another innovative feature is the AI-powered identification of the most probable scenarios. Whether it’s predicting a competitor’s promotion schedule or anticipating price fluctuations, our system provides actionable insights. This foresight is invaluable in crafting strategies that are not just reactive, but proactive. In our scenario builder, you can simply select the metric(s) to be forecasted and the timeframe, then let AI identify the top 3 most likely scenarios.
The system creates the scenarios (incorporating predicted competitor moves and external economic changes), then analyzes how these will affect your sales and volume. These are all then presented in an easy to navigate interface.
Building Team Competency through AI
We believe in empowering teams, not just with data, but with understanding. Our genAI acts as a bridge between complex ML models and business decision-makers. It’s akin to dining in the chef’s kitchen: you’re part of the process, you see the magic happen, you can influence the outcome, but you don’t need to be a chef yourself. This approach invites interaction and builds confidence without overwhelming you with technicalities.
Trust Through Transparency
The cornerstone of successful partnerships is trust, which is fostered by transparency and understanding. Our SmartForecast lays the groundwork for this trust, enabling stakeholders from various partner companies to comprehend and have confidence in the forecasts that are generated.
At Tickr, we’re not just offering a forecasting tool; we’re offering a new way to approach CPG decision-making. Join us on this journey and redefine the way you forecast, strategize, and succeed.
- Publish Date
- March 4th, 2024
- Abstract
- This article explores how Generative AI (genAI) can enhance traditional Machine Learning (ML) in solving complex problems faced by CPGs and Retailers. By providing common sense summaries of the patterns uncovered by ML as well as providing a way to dialogue with ML models, genAI can build your (human) team's intuition about root causes, deepen trust between CPGs and retailers around forecasts, and increase alignment on complex pricing and promotional strategies.
- Authors
- Tim Williams