Consumer packaged goods: Connecting the dots with D2C
A growing number of consumer packaged goods (CPG) companies have been exploring the benefits of introducing a direct-to-consumer (D2C) channel into their business in recent months. , PepsiCo and Heinz are just three high-profile powerhouse examples that spring to mind that are looking to capitalize on a growing customer need for convenience to gain highly valuable first-party data, and build closer relationships with their consumers.
When this data is harnessed with artificial intelligence (AI), we’re seeing businesses use it to optimize processes across the entire CPG value chain, from acquisition and retention, across all their channels.
Although D2C for CPG is still nascent, we’re already exploring some really exciting use cases for AI in a D2C setting for some of our consumer goods customers. Let’s take a look at a few examples of how an AI-driven approach to your D2C data can positively impact your entire consumer goods business.
AI for demand sensing
By getting closer to consumers and encouraging people to buy directly, CPGs are in a brilliant position to collect vast amounts of incredibly powerful data. AI can help you paint a clearer picture of what people are buying, how they behave on your website, who’s likely to make a purchase and, crucially, what content will stimulate them to buy.
But it doesn’t stop there. AI can also automatically feed this data back into your demand forecasts, augmenting it with your traditional sources meaning that you’re no longer forecasting based on just historical demand. With a more accurate forecast, and with a clearer idea of who is likely to convert and purchase a particular product, you can introduce this information into both your campaign and base forecasts.
AI for demand shaping
Traditionally, a CPG that is overstocked with inventory will rely on discounters to help them shift any unwanted stock. However, D2C offers businesses an exciting opportunity to also target specific segments of consumers directly to help clear inventory at a better price point.
In short, AI for demand shaping enables you to activate, or deactivate, your new customer segments depending on what inventory you have to play with, through targeting consumers with relevant products in a highly sophisticated, highly personalized way.
This AI-driven approach has the potential to revolutionize your inventory strategy, which we feel is one of the most interesting aspects of D2C. It’s particularly prevalent for those CPGs who are dealing with perishable goods, who serve retailers that have relatively erratic levels of demand. In these circumstances you may have the problem of often being overstocked, or you may be understocked and have supply issues when the unpredictable retailer comes back asking for more product.
However, with an AI-driven data-led approach to your inventory strategy, you could ensure you have enough quantity to always meet the retailers’ requirements, with your D2C channel effectively acting as a safety net; because you know that you’ll be able to quickly activate your highly targeted micro segments who always buy that particular product. Essentially, what we’re saying is that you can employ different inventory strategies to ensure you’re overservicing your primary channels, at no obsolescence cost of inventory.
This is very much blue sky thinking at this stage, but the potential is certainly there. Similarly, a better, data-driven understanding of costs on the supply side can be taken into account against the cost of acquisition, retention and servicing customers.
Our vision at Peak is to enable CPGs to transform from a reactive to a proactive entity, built upon predictive capabilities. Our acts as an intelligence layer that sits across your systems, at the center of your business, using AI to power optimization and decision making across the entire organization.