Predictive Analytics: Opening new data horizons for the CPG Industry

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The CPG industry has undergone some sweeping changes over the last few decades. Globalization, coupled with the free flow of information via the Internet, has brought in both opportunities as well as greater competition. For CPG companies today, the world is their market. Yet, they need to work that much harder to sell their products and predict sales cycles.

The new reality has created several challenges related to the supply chain, demand forecasting, and inventory management. Given the immense diversity of users, markets, and channels, the CPG industry needs to grapple with huge volumes of data and contend with products that have a relatively shorter shelf life. Traditional analytics processes have somewhat limited utility in analyzing this data

Predictive analytics can help CPG industry leaders make faster and well-informed decisions. Here are some ways in which the CPG industry can benefit from predictive analytics.

Real-time Data Insights: Predictive analytics platforms can mash up real-time and historical data to improve speed and accuracy of decision-making. For instance, real-time data on consumption of marketing content, both in structured and unstructured formats, can help guide marketing decisions on a real-time basis. If a particular online commercial or a pop-up contest is performing well, predictive analytics could help guide how best this success can be leveraged across new channels or portals, so that the campaign delivers maximum ROI.

Accurate Sales Forecasts: By merging various data sources (sales, marketing, digital, demographics, weather, etc.), predictive analytics can greatly improve the quality of sales forecasts. Businesses can gain a much better understanding of underlying demand drivers. This is in sharp contrast to traditional prediction techniques that rely heavily on isolated and aggregated sales figures, which can be quite misleading.

New Product Development: Predictive analytics techniques can help generate valuable insights and create deep understanding of consumer tastes and preferences, which could inform new product development. It could also guide decisions around rollout strategies to ensure that there is optimum weightage to each retail channel to ensure maximum ROI.

Optimizing Marketing Budget: Marketing channels today are highly fragmented due to the multitude of options available as well as highly personalized audience preferences. The effective use of predictive analytics can help CPG marketers design highly targeted marketing campaigns that are deeply aligned with shopper insights. Predictive analytics can help provide a much deeper understanding of customer behavior in the shopping cycle, enabling the creation of pin-pointed personalized offers that can significantly improve response rates.

Better Inventory Management: A strong inventory management strategy can be a cornerstone of success for CPG companies, especially those that deal in products with much shorter shelf lives. Too much inventory means that excess stock has to be discarded past the expiry date. Any shortfall in inventory could mean lower sales and could also put a dent in the brand image if the product is unavailable to buyers. Predictive analytics can help ensure optimal inventory levels and help identify cost reduction opportunities.

When used effectively, predictive analytics certainly has the power to transform CPG businesses in every way, right from how they source inventory, how they market their products to how they decide on new product lines.

Blog Author: 
Satyakam Mohanty
Data Science
Predictive Analytics


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