Key Takeaways
- Analytics for FMCG companies can support better pricing and price pack architecture decisions.
- Integrating analytics with pricing processes can support more evidence-based decisions.
- Understanding customer value drivers can reveal opportunities in pack sizes, bundling and product innovation.
- Customer-centric pricing capabilities can help FMCG companies improve margins and pricing outcomes.
In the face of economic uncertainty, getting pricing right is increasingly important for FMCG companies. Customers differ in their willingness to pay and value drivers, while demand can vary across categories, brands and consumer segments. Setting the wrong price can put pressure on margins, particularly when consumers become more price-sensitive during economic downturns. Data analytics tools can help FMCG companies analyse customer behaviour, price sensitivity, demand and other factors that inform pricing decisions. So, how can FMCG companies integrate data analytics into their pricing decisions?
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In this article, we explore how FMCG companies can use data analytics to inform pricing and price pack architecture decisions. We explain how customer, market and pricing data can reveal value drivers, demand patterns and opportunities for product and pricing innovation.
At Taylor Wells, we believe pricing should reflect customer value, demand and willingness to pay. This becomes particularly important during a downturn, when customers may become more price-sensitive and compare alternatives more closely. By the end, you’ll understand how FMCG companies can use data to make pricing decisions that better reflect customer needs and willingness to pay.
How Can FMCG Companies Use Analytics to Get Pricing Right?
Analytics can help FMCG companies make better price pack architecture decisions by connecting pricing data with customer behaviour, demand and value drivers. Three practical priorities are:
- Integrate analytics into existing systems and pricing processes. FMCG businesses often have legacy technologies, so the right people, processes and technical capabilities are needed to turn data into useful pricing insights.
- Use data to understand customer value drivers. Data can show what customers value, what they are willing to pay and where unmet needs exist. This can reveal opportunities for alternative pack sizes, bundling and other product innovations.
- Make price pack architecture customer-centric. Pricing and product innovation need to work together. Businesses can use analytics to understand differences in demand, pack size preferences, channel choices and price sensitivity, then develop products, pack sizes and prices that align with those value drivers.
The goal is not simply to add new technology. It is to combine reliable data, appropriate analytics and the right pricing capabilities to make evidence-based decisions. These principles also highlight why successful FMCG pricing requires more than technology alone.
See whether your pricing is under controlUsing Data Analytics to Improve FMCG Price Pack Architecture
FMCG companies often operate across products that consumers purchase frequently, making changes in volume, price, pack size and product mix important drivers of growth. Demand can vary considerably by category, brand, channel and consumer segment.
Consequently, businesses are exploring product and pricing innovation to support growth. Premium products, for example, can create opportunities for FMCG companies to capture additional customer value. However, premiumisation does not work for every product or customer segment. A premium position needs to be supported by sufficient perceived value and willingness to pay. This means pricing innovation does not always require a major change to a product or its benefits.
Consider simpler changes to price pack architecture, such as pack sizes or bundling. For example, PepsiCo has used smaller formats such as 7.5-ounce Pepsi Mini Cans to offer consumers a smaller purchase option.
FMCG product innovation can create stronger commercial outcomes when product, pricing and customer insights are considered together. Effective pricing and product innovation can support revenue and margin performance when they are aligned with customer demand.
So, what should FMCG firms consider when it comes to product pricing innovation? While we recognise that business leaders have considerable knowledge and expertise, we believe that their strategies should not depend only on gut instinct. Evidence should underpin innovation. We recommend using appropriate data analytics to support better pricing and product decisions.
Quality data can help FMCG companies identify changes in consumer behaviour, price sensitivity, demand and market conditions. These insights can then inform pricing and price pack architecture decisions.
Access to data does not automatically produce better pricing decisions. Pricing teams still need to interpret the data and translate insights into a pricing strategy that supports business goals. The following case study shows how AB InBev used analytics to strengthen its pricing capabilities.
Challenges of Using Data Analytics in FMCG Pricing
While analytics offers numerous benefits, it also comes with challenges. Gathering quality data and integrating new technology with existing systems can be difficult.
Effective product innovation and pricing optimisation require more than new technology. Digital analytics will not improve pricing outcomes on its own. Businesses also need the right processes, systems and people to interpret the data and apply insights to pricing and product decisions.
Price pack architecture aims to offer customers a range of products, pack sizes and price points that align with different needs and levels of willingness to pay. Customers differ in their purchase motivations, which can influence product demand, preferred pack sizes, channel choices and price sensitivity.
This is why product innovation and pricing are closely linked. Treating these functions separately can create disconnected strategies and make it harder to align product, pricing and customer decisions.
Three Ways FMCG Companies Can Use Data Analytics
Here are three ways FMCG companies can incorporate data analytics into their pricing and product decisions:
1. Integrate data analytics into existing FMCG systems and pricing processes.
Many businesses operate with legacy technologies that are difficult to replace. The right people and technical capabilities can help businesses address these challenges. For example, employees or external partners with technical expertise can help identify and resolve data challenges as they arise. When appropriate analytics are combined with the right people and processes, businesses are better positioned to turn data into useful insights.
2. Use data and analytics to understand your customers’ value drivers.
Data from the current portfolio can help product innovation teams understand what customers value and how willingness to pay varies across products and segments. It can also help identify unmet needs. Additional market and consumer research, alongside advanced analytics, may be required to develop a more complete understanding of customer needs.
Identifying unmet needs can reveal opportunities for price pack innovation. Bundling and alternative pack sizes can create additional options for customers and may increase willingness to pay when they address a specific customer need.
3. Make customer-centric price pack architecture decisions using analytics.
Commercialising price pack architecture innovations also requires collaboration across teams. Once the right people are collaborating across analytics and product innovation, a specialised pricing team can help translate these insights into pricing decisions. Even a strong product can underperform commercially if its price does not reflect customer value, demand and the company’s margin requirements.
A well-structured pricing team can support better price management processes and help businesses identify margin improvement opportunities. As pricing capabilities mature, businesses can identify further opportunities to improve margin performance and manage emerging pricing risks.
AB InBev: Using Analytics to Strengthen Pricing Capabilities
Anheuser-Busch InBev (AB InBev) provides an example of how an FMCG company can integrate analytics and technology into its pricing capabilities.
AB InBev aimed to identify an ideal price for individual SKUs and develop a framework for making pricing decisions across product levels and regions. The company already had some pricing capabilities, but its processes were unstructured and varied across markets. It therefore needed to scale these capabilities.
AB InBev worked with Tredence, a provider of artificial intelligence and data science solutions, on a 10-week project across several markets. The partnership helped AB InBev scale its pricing capabilities and address the technical challenges involved.
AB InBev and Tredence developed automated models to calculate price elasticity using a range of internal and external data sources, including AB InBev’s revenue, sales volume and sell-in prices.
The models also incorporated external sources, including market research, income data, public health information and sports-related data.
The initiative strengthened AB InBev’s use of analytics as part of its pricing approach. The company developed a more data-driven framework for pricing decisions, providing a foundation for scaling its approach across markets and product levels.
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Bottom Line
FMCG companies can use data analytics to support better pricing and product innovation. However, identifying the right price pack architecture requires more than technology. It requires reliable data, appropriate analytics, customer insight and the pricing capabilities to turn those insights into action.
To overcome these challenges, businesses need to integrate analytics with existing systems and use customer and market data to inform pricing decisions. When these capabilities work together, businesses have a stronger evidence base for improving pricing and margin performance.
The objective is not to replace pricing judgement with technology, but to give pricing teams better evidence for making commercially sound decisions.
For a comprehensive view and marketing research on boosting the capability of your company, download a complimentary whitepaper on How To Improve Product Pricing.
Are you a business in need of help to align your pricing strategy, people and operations to deliver an immediate impact on profit?
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