How to Sell AI to CPGs
In CPG, AI has the power to deliver meaningful, quantifiable business benefits - driving efficiencies that positively impact the P&L, unearthing transformative consumer insights, and increasing both customer and consumer satisfaction. Identifying where those opportunities lie, understanding the depths of unique business problems to solve, and building not only solutions, but also future state visions can be seminal for tech companies to close AI CPG deals.
Here’s an example of a use case for a CPG that demonstrates a thorough understanding of the brands and elucidates an intuitive technical solution. The more relevant and specific the use case, the more compelling.
Consider demand forecasting. This is a common use case, often discussed in broad strokes in conjunction with sizable potential ROIs. To make the case to business unit or functional owners, it may be helpful to offer a discrete example like the following:
Say a CPG with multiple personal products brands offers travel size products. Let’s assume that for this company, these travel size SKUs are high margin with unpredictable volume and a 3 month shelf life. Demand fluctuates greatly, often leading to one of two dreaded situations: U and D or OOS. Moreover, there is ample competition. OOS could lead to losses of loyal consumers to a competitor, negatively impacting share and average LTVC.
What makes demand forecasting difficult for these travel size SKUs? For one, timely travel data. Specifically, booked travel data as well as trending origins and destinations. Search trends for travel are an obvious data source (Skyscanner API), but search trends don’t necessarily translate to bookings. Published booking data (e.g. from airlines and hotels) from financial reports lag, reducing reaction time.
With AI-enabled customer data platforms, feeding ARC data into the platform would allow decision makers and demand forecasters to identify YoY and MoM changes in booking data in real time (or near real-time). This data would also surface origin and destination trends. For brands in competitive situations, securing a head start in planning can drive incremental volume and share gains. Demo’ing how easily these insights are surfaced and visualized in a CDP could be eye opening to business leaders who may assume they need an army to access and aggregate raw data, write queries, analyze results, build data-driven strategies, and create visuals to support business case development.
In the above use case, not only could this CPG more accurately increase or decrease production volume of travel size SKUs expeditiously, it could also be more surgical in optimizing distribution by markets and channels. Additionally, brands could tailor messaging and promotions for these SKUs to target both popular outbound hubs, inbound destinations, and airports en route.
Tailored use cases signal to stakeholders that sellers understand their business objectives, their role, their KPIs, and are invested in helping solve their unique challenges. This approach builds trust, credibility, and strengthens partnerships among all parties involved in bringing complex AI platform deals across the finish line.
