Creating an Optimal Pricing Strategy with Data 

Organizations that nail an effective pricing strategy are able to actively respond to market volatility, generate value swiftly and as a result, boost their top-line growth. To be equipped with an effective pricing strategy, CPGs need a strong internal capability that is fueled by data to turn opportunities into value offerings and maximize profits over time. 

There is enough evidence to showcase that collaboration between marketing, sales and pricing functions prompts organizations to achieve their business objectives. Simply put, business functions cannot afford to operate in silos anymore. And companies that have an integrated analytical solution that unifies data to offer insights helps in boosting top-line. 

At the core of this cross-functional approach is a deep understanding of consumers’ journeys. Taking a closer look at the consumer buying patterns using advanced analytics and processes facilitates growth. 

Before we dive into understanding how consumer data can be processed to curate effective pricing strategies, here are some fundamentals of an optimized pricing strategy. 

Basics Of an Optimized Pricing Strategy 

Consumer Insights 

According to Boston Consulting Group, over 75% of CEOs and Operating Officers in the B2B space believe that consumer insight is indispensable in accelerating top-line growth. The current scenario indicates an elevated level of complexity in demand patterns and companies have turned towards data and positively moved away from intuition to create pricing plans. 

Data sourced from channels including point of sale (retailers), digital media, and secondary sales (distributors), should be processed to analyze consumer demand patterns. Through this, organizations would be able to answer questions such as “at what price point does a customer shift to an alternative product?”, “How will a consumer respond if the product price is increased by X units?” and much more. 

From being a solution-oriented tactic, gaining customer insight also facilitates filling up whitespaces by analyzing challenges and offering solutions to customers, thus capitalizing on their willingness to pay for added value. By leveraging data to gain insights into demand patterns, CPGs have the capability to identify and meet demands. However, the challenge here is the data captured is crude, and CPGs are still unable to extract the right insight without the aid of AI and ML. 

CPGs around the world need to harness internal and external data to build and execute pricing and promotion strategies. 

Engaging Retailers in Pricing Discussions 

A key piece in the pricing puzzle is engaging retailers in pricing discussions. 

According to a survey conducted by Nielsen, CPGs that consider retailers’ inputs on category performance, in their pricing discussions, at regular intervals, are able to curate pricing strategies that align with the values of the customers, companies, and retailers. However, data transfer between retailers and CPGs is far and few between. And when it does happen, the data shared often takes longer to decipher as it is usually done manually. 

When the data transfer is done regularly and run through advanced analytics, CPGs have a predictive and prescriptive approach towards pricing. Through regular collaboration with retailers, organizations can manage in-market execution (such as price-adjustment opportunities) and get a competitive advantage by maintaining the right inventory and establishing the most optimal price points. 

Regular collaboration with retailers can help organizations steer away from static pricing strategies and align prices closely to the consumer’s willingness to pay thus generating greater value for the customers. 

Pricing Analytics 

The immense capabilities of pricing analytics with the help of an advanced AI/ML tool help CPG companies highlight gaps and quickly revise prices that customers can resonate with. Thus, they enjoy a competitive advantage by closely resonating with their consumers. According to Deloitte, organizations usually see a performance improvement of 2-4% and an increase in annual sales by 1-2% when they employ data analytics to strike the optimal price points. 

Data analysis through AI allows companies to create multiple and dynamic responses to potential market changes. Using data to determine price elasticities for goods also helps in mitigating scenarios where companies do not breakeven. Therefore, with the help of data and pricing analytics companies establish optimal pricing points across different markets. 

The All-Encompassing Solution for Optimal Pricing 

Companies that focus on boosting their top-line growth require advanced analytical tools that can translate research into decision-making through actionable insights. Along with the strong business acumen that functional heads already possess, the use of data and pricing tools has the potential to catapult CPGs into profit-oriented players in the market.  

Moving away from basic tools (those that rob organizations of their time and efforts) is the first step in boosting the top-line. Data-driven organizations, thus, not only become customer-centric but also technological vanguards to deliver value to their customers. By processing consumer insights using simulations, projections, and forecasting, companies leverage data and resonate accurately with buyers. 

Advanced solutions used to collaborate between promotions and pricing to form an optimized strategy across categories and geographies. The capabilities of such platforms enable CPGs to source data and assess price points that tend to be overlooked. Moreover, they can assess the impact by simulating dynamic pricing systems. By leveraging the power of advanced analytics, companies can maximize top-line growth by responding to changes in customer demand partners and creating a dynamic pricing structure. With the onset of such analytics, CPGs can now take the predictive and prescriptive approach to achieve their pricing goals, manage volume growth & sales, and thus improve profitability.