Applications of artificial intelligence in the CPG sector

AI in CPG sector - Blog

AI Technologies Will Be in Almost Every New Software Product by 2020 – Gartner

Artificial Intelligence has consistently been a buzzword in the last few years. However, merely jumping on the bandwagon without a proper strategy in place may provide disastrous for organizations.

Any value to be derived from AI depends on exactly how it is being leveraged. As AI continues to evolve, it creates opportunities for organizations to improve functioning in their existing software and build new and enhanced products.

As organizations attempt to strategize around how they can use AI for the benefit of their organization, it brings several questions to the forefront- what is the right path to take? What is an ideal first step? How do digital innovation managers move forward with AI?

“Mature brands are also losing (market) share because they don’t use digital technologies to develop, market and sell products as nimbly as younger CPG companies do”
– Boston Consulting Group

But first, let’s dive a little deeper into understanding AI and how it uses various technologies to create practical applications for the CPG industries:

1. AI enables the conversion of raw CPG data into meaningful insights

Making intelligent business decisions is critical for any industry, but particularly so for the CPG segment. Effective decision-making across a variety of business areas forms the backbone of the CPG business.  These decisions have to be made fast and with utmost accuracy.

But how can businesses achieve this when they’re bogged down by massive amounts of data? Coupled with the sheer amount of data is the challenge of not being able to leverage any manner of advanced technology to convert it into actionable intelligence.

This is why AI is particularly important for CPG companies. AI and machine learning come together to create a powerful machine capable of harnessing high volumes of data into meaningful insights that the CPG business can use to improve business outcomes.

a) Trade Promotion Optimization

Trade promotions are a key element of CPG success. However, CPG businesses are constantly struggling to measure the effectiveness of their promotions. This inability to measure effectiveness renders them incapable of making improvements or achieving the desired ROI.

The task of measuring trade promotion effectiveness itself can be rather challenging for most consumer goods manufacturers.

Leveraging the right trade promotion software enables organizations to effectively use data collected from past trade promotions and measure effectiveness based on the analysis, as well as get important recommendations for future promotions.

However, these critical functionalities are missing from most traditional trade promotion software and their shallow insights do not offer much help in terms of improving the performance of promotions.

TPOAn ideal TPO software is one which features advanced analytics that turns data into relevant, actionable insights. The core idea is to enable business leaders to make quick, accurate and highly effective decisions.


  • Run effective promotions that generate high returns
  • Run promotions at the right time and place and for the right products
  • Measure the effectiveness of the promotion and gauge what works and what does not
  • Get relevant insights into running the right promotions from TPO software by leveraging AI to analyze internal data like promotions, past sales and external data elements like syndicated data, weather, events, social media etc.
  • Make accurate sales forecasts
  • Discover important insights and get immediate alerts

b) Marketing

CPG marketing efforts are heavily influenced by a variety of factors. Decision-makers have to take into consideration various market and consumer touch points in order to build an effective and evolving marketing strategy. These touch points range from social media, past sales, special events, holidays, and so on.

With all of these factors to consider and data not being effectively harnessed, it can be rather challenging for marketing managers to optimize marketing spend to generate the best outcomes. Furthermore, a large part of this data is mostly unstructured due to social media. The result is that organizations run marketing and advertising campaigns that require heavy investment but generate little to no impact on sales uplift.

Machine Learning and Advanced Analytics can be leveraged to help bridge this gap between unstructured data and effective marketing campaigns and meaningful recommendations.

AI technologies such as machine learning algorithms and predictive analytics take various trends and data patterns into consideration. This analysis enables marketing executives to make accurate decisions about various marketing aspects:

  • Spending at the right time and place
  • Taking advantage of high-yield opportunities
  • New segments and channels that can be targeted
  • Evaluating if marketing promotions are yielding the desired ROI
  • Gauging if marketing efforts are inadvertently supporting competition and by how much
  • Optimizing marketing spend across all brands based on the BCG Matrix

c) Supply Chain and Operations

Leveraging a combination of an Internet of Things (IoT) and Artificial Intelligence enables executives and agents operating across the supply chain to get insights into the most minute details of their supply chain processes. This end-to-end visibility of supply chain processes enables agents to quickly identify and address issues.

For instance, CPG businesses typically monitor product location and inventory to predict any shortages that may come up in stock and also plan around when they need to get new shipments. If transport management systems are already equipped with AI, this eliminates the need for manual effort, while drastically increasing visibility across the entire spectrum of logistics.

Forward-thinking CPG companies have invested into building custom mobile apps and RFID technology that allows them to track shipments right from the factory all the way to end users.

2. Increased customer engagement

AI can be an incredible tool to drive customer engagement by providing highly relevant intelligence and meaningful insights.

Here are a few instances of how major brands have leveraged AI for customer engagement:

Knorr in South Africa ran a campaign called “#whatsfordinner” using AI to recommend recipes based on ingredients consumers already have in their pantries. Creating campaigns like these build on the power of AI allow businesses to the kind of consumer data they may never have had before, therefore creating brand new opportunities for new and effective business models.

CPG firms are also looking to market directly to specific consumers by providing customized products. For instance, L’Oréal combines the Facebook Messenger chatbot with AI to enable the bot to ask questions to users about their friend so they can find and gift the right beauty products to them.

How can Innovation Managers get started?

This is what it all comes down to. How can innovation managers enable their organizations to leverage AI?

Given that AI is still in its very early stages, the first step should be to align business objectives with AI initiatives and not the other way around. If you find that you have specific business challenges that can be addressed by AI, then start looking at how it can introduce into your business.

As cloud computing also becomes increasingly popular offering low-cost cloud services to businesses of all sizes and nearly unlimited storage, AI continues to have tremendous potential to evolve.

As CPG companies look seriously into adopting AI, they should also spend effort at defining a transformation strategy that aligns with various developments in technology and adds to their existing IT strategy, rather than rewrite.

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