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Consumer goods: how to set up your insight-driven strategy

Giuliano Maria Fabbri

More and more companies in the FMCG (Fast Moving Consumer Goods) industry are exploring solutions to predict their demand more accurately.

For these companies, becoming more accurate in their forecasts means taking a more proactive approch towards their target market, i.e. being able to understand the needs of their consumers even before they arise.

Today, adopting machine learning solutions and tools based on Artificial Intelligence is an option available for all companies, cross-industry, in order to start an innovation path of analysis, management and activation of the most effective data.

In fact, according to a recent study by McKinsey, the accuracy of manual through manual predictive systems on the market demand is  60%, while it might even rise to 90% when using AI and ML systems.


Fast Moving Consumer Goods manufacturing: the challenges

What are the main challenges that the operators are facing? Our everyday life is radically changing, which means that consumers are also drastically changing their purchases and customer journeys.

The consumer are more and more fluid and unpredictable

Nowadays consumers are increasingly demanding, looking for a unique, frictionless shopping experience. Not only that: the purchase intentions are often impromptu and multi-device, while the brand loyalty is lower than ever.

For this reason, it is essential to satisfy and even anticipate their needs.

The amount of data to collect, analyze and understand is increasing

The amount of available data is much bigger and it comes from totally different entry points, making the process of  collection, analysis and segmentation much more laborious and fragmented, while disempowering a data-driven vision and strategy.

The competition is increasing

The global and digitized market has increasingly fragmented demand, allowing both large and small players to satisfy specific niches and work on omnichannel experiences.

The complexity of technologies is increasing

In order to comply with both consumer requests and regulations, manufacturers, e-shops and retailers must adopt technological solutions in their corporate stacks.


Data-driven opportunities for consumer goods

Luckily, there are many possible actions you can take in order to face these challenges:

  1. Martech solutions and the application of AI let you create tailor-made purchase paths, improving the relationship with your digital customer, focusing on loyalty and experience.
  2. Technology and AI also allow an ever more accurate collection of data, crossing and harmonizing online and offline information, combining data from different platforms. Not only that, they also help you to analyze and segment this data, to find coherent clusters, creating custom audiences to nurture with dedicated messages.
  3. A new trend is emerging, especially for new generations. Thanks to the great abundance of alternatives, people are starting to look more at quality and at the product itself, rather than the brand. On one hand, this could be a problem for love-brands that are no longer certain of their customers’ loyalty; on the other hand it provides great room for improvement for followers and emerging brands. This is because consumers are comfortable with online shopping, open minded when it comes to trying new products, services or brands.
  4. It has never been easier to reach a global audience by setting strategies and testing individual markets, modeling your offer accordingly, and expanding your business volume.


AI-based strategy: how you can activate it

If you manage to carefully keep an eye on new trends, you will have full control over your brand. In fact, online searches are the touchstones of all of your activities related to brand awareness, especially those social actions with ambassadors and influencers, but they can become crucial in terms of supplying physical stores and logistics.

Thanks to our proprietary Trend AI tool, you can measure the impact of specific actions, both expected and unscheduled.


Here are some real use cases showing potential of trend detection and research data expansion in different sectors:

  • in the wine world, a famous sparkling wine brand created a campaign with some influencers and, through Trend AI, was able to map the impact of this action, noting significant peaks in branded searches;
  • speaking of sports devices, a famous producer of smartwatches for sports performance has identified geo-localized research trends for the different kinds of device, according to the physical activity associated (running, trekking, cycling, etc.). Following this analysis, the stores in the area were supplied with the most suitable product based on the research;
  • one of the most well-known brands of slimming creams wanted to understand what the real seasonality of summer was, overcoming the “bias” of its team: users begin to worry about their costume fitting already at the end of February and not in May, as the previous surveys claimed. This way, product promotion campaigns started being scheduled well in advance, taking advantage of the whole period of interest.