The proliferation of smartphones and the rise of e-commerce has impacted consumers’ expectations and shopping preferences. As consumers drive when, where and how they shop and interact with their favourite brands, they’re also looking at CPG businesses and retailers to provide the right product, at the right time, through the right channel, and at the right price.
This challenge, among others, will be the topic of conversation that CPG retailers will discuss on August 14-16, 2019 in Colorado Springs, Colo., for the 2019 GMA Leadership Forum.
The event has a number of informative sessions lined-up, including “The Future of Supply Chain” presented by Daniel Swan, “Consumer Technology and Consumer Behaviour” presented by Lesley Rohrbaugh and “Remodeling Tryst” by Max Elder.
The one session that’s likely on the top of every attendee’s list is “Delivering on the Promise of Data” by Geoff Kelley, Tom Madrecki and Matthias Winkenback. In order to better understand their customers and improve business operations, CPG leaders are turning to data. Data-driven insights about customers exist, yet challenges remain around unlocking its true value – identifying consumer interests and shopping habits that inform how brands can reach consumers, from omnichannel marketing strategies to impactful and ultra-personalized online and in-store experiences for consumers.
Unlocking Big Data
CPG companies have historically relied on third party aggregated data and limited retailer data from a few sources to understand their customers. .But these sources simply do not illustrate the full picture of shopping habits and preferences.
CPG companies have established multiple touchpoints with consumers allowing them to better understand their end buyers and determine when, how and through what channels consumers shop and how to best reach them. These data sources are traditionally saved in disparate legacy systems, making it practically impossible to paint a holistic picture of the customer, which can lead to suboptimal forecasting and lost profit opportunities. To overcome these challenges and improve the customer experience, CPG companies and retailers are turning to innovative technology, such as machine learning and artificial intelligence (AI) to unlock meaningful data to understand customers, automate critical business decisions and improve overall ROI.
Enhancing Demand Forecast Planning with AI
Machine learning and AI technology are enabling CPG companies to streamline data analysis, enabling more informed business decisions. Take demand forecasting for example. This traditionally manual process that took weeks and sometimes even months to complete, was prone to inconsistencies that resulted in excess inventory and increased stockouts. By utilizing machine learning and AI, demand forecast planning can now be intelligently automated to improve product availability, increase operational efficiency in supply chain systems, and most importantly, improve the overall customer experience by ensuring that the products that customers want are available.
Are you planning to attend GMA Leadership Forum August 14-16? Learn how AI can increase forecast accuracy by scheduling a meeting with Rubikloud.