CPG Execs:
Stop wincing, start winning with AI

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Every time a stock shot of an empty store or warehouse shelf popped up in your news feed in the past few months, we know your thoughts immediately turned to your own supply chain.

You’re already keenly aware that the key to avoiding this scenario lies in all that data you’ve been building up. But so far, wrangling it has caused you more headaches than it’s cured. And you’re not the only consumer packaged goods exec to feel that way. In fact, only one in three of your peers thinks their company is doing a good job at leveraging data and analytics to better forecast market demand and better anticipate customer needs. 

And yet it’s hard to argue with the bottom-line results of a data-driven approach. The use of AI and advanced analytics has been shown to generate at least 10% in revenue growth for CPG companies, achieved through the three Ps of prediction, planning and personalization.

All three are vital in competing in the continuum that includes everything from e-commerce behemoths and traditional brick-and-mortar channels to smaller, nimbler specialists. Harnessing the wealth of data that you already have at your fingertips is where you’ll find those all-important and actionable insights that can turn things to your advantage.

Human smarts: the heart of artificial intelligence

One of the biggest myths about AI applications, in the CPG industry or elsewhere, is that machines are in control. The truth is that AI is at its most effective when it is used to augment human action and support accurate, efficient and confident decision-making. 

You know your business. You know your market. Consumer behaviour, on the other hand, is notoriously hard to predict, especially these days. AI takes some of the mystery out of the equation. But how do you take the mystery out of AI?

Even those ahead-of-the-curve CPG companies that have already started playing around with AI haven’t gotten very far with it. When asked why, they give a variety of reasons, many of which can be attributed to the sheer complexity of the process involved.  

Here’s the good news: creating powerful machine learning models is no longer relegated to the exclusive world of coders. It now comes nicely packaged in a clear, intuitive SaaS platform that can be deployed quickly and easily. 

Prepping for the “next normal”

Beyond the peaks and valleys of a crisis economy, three KPIs remain high atop the watch list for most if not all CPG companies: new customers, increased cross-sell/upsell and reduced customer churn. Even a small rise in any of these can translate to huge gains in revenue.

Ensuring product availability and limiting inventory shortfalls (without overstocking) are among the shopper-facing strategies that can help nudge all three KPIs upward. Utilizing AI and advanced analytics can play a major role in developing sales and customer insights, optimizing inventory, analyzing consumer trends and more, all with the ultimate goal of improving and accelerating decision-making at every level. 

The predictive capabilities of AI algorithms are game-changing in a business-as-usual climate, but they’re downright essential when a major industry shift occurs and shakes consumer demand to the core. According to the latest data (supported by plenty of anecdotal evidence), e-commerce is here to stay. But with it comes a substantial uptick in consumer fickleness. Brand loyalty has taken a nose-dive of late; brand availability, on the other hand, is stronger than ever, driving a full half of new brand purchase decisions made earlier this year. A responsive supply chain is therefore not an option for CPG companies moving forward — it’s an absolute must.

AI: the way forward

Agility and resilience. Two concepts that have been on the tip of everyone’s tongue over the past year. And the CPG industry is no different. Adapting to shifting customer demands is paramount to surviving and thriving in the market of today and tomorrow.

Those who will be leading the charge will be the ones who unravel what AI has to offer: better and faster forecasts using existing data, more accurate insights into changing consumer segments and trends, the opportunity to create personalized experiences that resonate with customers’ ever-shifting behaviours and preferences, and the ability to plan ahead more efficiently to make an uncertain world more uncertain. 

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