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CPG Assortment Analytics

Written By: Gargi Sarma  Introduction:

Companies in the fast-moving and dynamic consumer packaged goods (CPG) industry always look for new and creative methods to stay one step ahead of their rivals. Using analytics for CPG selection is one such approach that has grown in popularity. Businesses have found this potent tool to be a game-changer as it offers priceless insights into consumer behavior, market trends, and product performance.

To improve and optimize its overall assortment strategy, a company's product range is systematically analyzed through CPG assortment analytics. This approach explores the nuances of consumer preferences, market demand, and competitive positioning in addition to just stocking shelves with goods. Through the utilization of sophisticated data analytics and technology, businesses may make well-informed decisions that foster expansion and optimize revenue.

The process of leveraging data to optimize product placement and selection inside a retail store or online platform is known as CPG assortment analytics. This facilitates the decision-making process for CPG brands and retailers regarding which products to carry, how much to carry, and where to display them on the shelf or website.

Challenges in CPG Assortment Analytics:

Figure 1: Wallet shifts during a pending recession (Source: NielsenIQ)

For example in Figure 1, businesses are confronted with obstacles arising from the consumer recessionary attitude in light of the current global financial turmoil and the significant consumer reset of the previous three years. Most Europeans perceive the recession as a constraint and feel slightly worse about the state of the economy than they do about the world economy. The wallets of consumers will keep changing. Reductions that were greater than expected at the start of the year have led to a growing emphasis on at-home consumption as opposed to consumption outside the home in spending intentions.

Product assortments are analyzed in consumer packaged goods (CPG) assortment analytics in order to maximize product offerings and satisfy customer demand. CPG Assortment Analytics has many obstacles despite providing insightful information.

Figure 2: Challenges in CPG Assortment Analytics

  • Integrity and Quality of Data: CPG businesses frequently work with disjointed data that comes from a variety of sources, including market research, sales, and inventories. It can be quite difficult to integrate this data and guarantee its validity.

  • Adaptive Customer Preferences: It can be difficult for CPG companies to stay on top of the most recent trends because consumer preferences can change quickly. It's possible that analyzing past data won't always predict future desires.

  • Promotions with Seasonality: Unpredictable demand fluctuations may result from promotional activity and seasonal variations. Planning ahead and accurately forecasting these variations is essential to maximize assortment.

  • Complexity of the Supply Chain: The supply chains for CPG goods are frequently intricate, involving numerous suppliers and channels of distribution. A smooth supply chain and effective management of this complexity are necessary for assortment planning to be successful.

  • Competitive Environment: CPG businesses must keep an eye on rivals' tactics and adapt accordingly. Decisions about assortment can be influenced by the behavior of competitors, which can affect consumer preferences and market dynamics.

  • Dynamics of Channel and Location: Distinct selection techniques may be needed for various sales channels, such as online, brick-and-mortar, etc. A more detailed approach to assortment planning is required because local preferences and demographics are significant factors.

  • Privacy and Data Security: Managing customer information and market research necessitates a strong data security strategy and adherence to privacy laws. Preserving confidence and safeguarding confidential data is essential.

  • Adoption of Technology and Analytics: It might be difficult to integrate cutting-edge analytics tools and technology into current systems. Success depends on ensuring that these tools are properly deployed and integrated throughout the company.

  • Interdepartmental Cooperation: Assortment planning calls for coordination between the supply chain, marketing, and sales divisions, among others. Making sure that goals are aligned and that communication is successful can be difficult.

  • Ever-changing Economic Landscape: Shifts in the economy, such inflation, can have an effect on consumer buying habits. CPG businesses must modify their assortment strategies in response to the current state of the economy.

A comprehensive strategy that incorporates advanced analytics, technology integration, and a thorough comprehension of customer behavior and market dynamics is needed to address these issues. Effectively adapting plans to current market conditions and real-time data is essential for success in the ever-changing CPG industry.

Transformative Capabilities of CPG Assortment Analytics:

Let us look into the possible effects of value-diluting complexity and the common places where it can appear are highlighted by examining the usual value chain of a CPG manufacturer (Figure 3).

Figure 3: Complexity-good and bad-occurs throughout the value chain (Source: McKinsey & Company)

Analytics has become a game-changer for businesses looking to maximize their product offerings because of its ability to run complex algorithms and provide data-driven insights. Here are some of the capabilities.

  • SKU Suggestions for Cross-Selling and Upselling: Understanding customer preferences is essential to seizing upsell and cross-sell opportunities in the ever-changing CPG market. Utilizing past data, customer behavior, and industry trends, assortment analytics makes suggestions for SKU combinations that optimize sales. Businesses can carefully bundle offerings, encouraging customers to investigate and purchase additional items, by choosing products that complement one another.

  • Avoiding Stock Outs: Nothing irritates customers more than finding products that are out of stock. This problem is aggressively addressed by CPG Assortment Analytics, which uses real-time data to forecast and avert stockouts. Businesses can proactively modify their assortments to maintain stocked shelves and high customer satisfaction by closely monitoring inventory levels, demand trends, and supply chain dynamics.

  • Optimizing Routes for Effective Distribution: For CPG companies, the distribution network is essential, and route optimization plays a key role in reducing expenses and optimizing productivity. Combining assortment analytics with logistics data allows for the optimization of delivery routes, which lowers costs associated with transportation and guarantees timely product availability. Businesses can optimize their supply chain operations by taking into account variables like demand density, traffic patterns, and delivery timetables.

  • Forecasting Techniques for Accurate Scheduling: The key to effective assortment planning is precise demand forecasts. CPG Assortment Analytics uses machine learning algorithms to examine past data, current market conditions, and outside variables influencing demand. As a result, businesses are able to eliminate waste, reduce excess inventory, and match production with actual market demands thanks to an improved and more flexible forecasting model.

  • The Next Best SKUs to Find: Remaining competitive requires anticipating changing consumer demands. CPG Assortment Analytics uses customer behavior and new trends to discover the next best SKUs, going beyond traditional forecasting. Businesses can develop new products or versions that align with changing consumer preferences by utilizing predictive analytics, which gives them a competitive advantage in a market that is changing quickly.

Current trends in CPG assortment analytics:

Figure 4: Percentage of Companies Using CPG Assortment Analytics

  • Data-driven decision-making: To decide on their assortments, CPG companies and retailers are depending more and more on data from multiple sources, including market research, shopper behavior data, and point-of-sale data. They can use this information to better understand consumer preferences, spot trends, and tailor their product offerings to meet the needs of their target market while maintaining profitability.

  • Focus on personalization: Assortment analytics is being used to give customers more customized shopping experiences. Retailers can personalize their assortments to each customer by analyzing data on their tastes and past purchases. This can boost sales and foster client loyalty.

  • Emergence of omnichannel retailing: As online shopping continues to grow, CPG companies and retailers must take into account how their assortments will show up on various platforms, including mobile apps, physical shops, and websites. They can guarantee that clients receive a consistent experience regardless of the channel they choose to shop through by optimizing their product offerings with the use of assortment analytics.

  • Application of machine learning (ML) and artificial intelligence (AI): ML and AI are being utilized to create increasingly complex assortment analytics systems. Large data sets can be analyzed by these instruments, which can also spot patterns that are invisible to the human eye. This can assist retailers and CPG brands in making even better choices regarding their assortments.

  • Emphasis on sustainability: People are becoming more and more interested in purchasing goods from sustainable firms. Retailers and CPG companies can utilize assortment analytics to find and highlight sustainable products in their assortments, which will help them draw in more business and enhance their reputation.


  • The global CPG assortment analytics market is expected to reach $3.2 billion by 2027, growing at a CAGR of 12.3% (Source: ResearchAndMarkets).

  • Investment in personalization technologies for assortment optimization is expected to reach $8 billion by 2025 (Source: Gartner).

  • The use of AI/ML in CPG assortment analytics is expected to increase by 50% in the next three years (Source: Accenture).


CPG assortment analytics stands out as a crucial tool for businesses looking to achieve sustainable growth and competitiveness in a time when data is king. Businesses may gain important insights, optimize their product portfolios, and remain ahead of the curve in a constantly changing market by utilizing data analytics. Adopting assortment analytics is not just a smart move, but also a must for anyone hoping to succeed in the competitive consumer goods market as it continues to change.

About RapidPricer

RapidPricer helps automate pricing, promotions, and assortment for retailers. The company has capabilities in retail pricing, artificial intelligence, and deep learning to compute merchandising actions for real-time execution in a retail environment.

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