How Pricing Analytic Solutions for Oil and Gas Industry Helped With Discount Strategies for Retailers?

What You’ll Find in this Case Study:

• Highlights of the Case Study
• Game-Changing Solutions for the Oil and Gas Retailing Business
• Challenges of the Retail Client
• Solutions for Industry
• Impact Analysis of Quantzig’s Pricing Analytics Solutions
• Key Outcomes
• A Broad Perspective on the Role of Price Analytics in the Oil and Gas Sector
• Key Takeaways of Pricing Analytic Solutions in Oil and Gas Industry:

Highlights of the Case Study:

Why is pricing analytics important?

This tool is indispensable in the software business, where dynamic market conditions demand precision in pricing strategy. In this sector, customer segmentation is intricate, and value-based pricing is essential for aligning product offerings with diverse customer needs. By leveraging pricing promotions and understanding price elasticity, businesses can strategically manage customer acquisition costs, ensuring sustainable growth. Furthermore, comprehensive analysis of product development efforts and augmented product value facilitates the creation of compelling value propositions, enhancing perceived value and driving customer loyalty.
This tool solves critical challenges by providing structured pricing data, guiding businesses in making informed pricing decisions. Through relative preference analysis, companies can fine-tune their offerings based on consumer preferences, contributing to value maximization and meeting customers’ needs effectively. Understanding paying capability ensures that pricing metrics are tailored to the target market, optimizing revenue management.
Moreover, this tool addresses customer retention concerns by evaluating customer churn and cultivating brand promoters. By integrating market research into pricing strategies, businesses gain insights into market demand, supporting demand-based pricing and identifying pricing opportunities.
In the software business, where operational efficiency is paramount, this tool aids in planning effective strategies by considering consumer spending trends, forecasting demand, and managing operating expenses. It differentiates between passive and loyal customers, enabling businesses to focus on profitable channels and maximize customer lifetime value.
In a nutshell, it is crucial for the software sector, addressing complexities in customer behavior, supply chain management, and market dynamics. By incorporating various price analytical types, such as psychological price points and Gabor-Granger price modeling, businesses can stay competitive in a rapidly evolving market, ensuring sustained profitability and customer loyalty.

Tools to conduct pricing analytics

• Pricing Analytics Platforms:
Specialized pricing analytics platforms, such as Zilliant or Pricefx, provide comprehensive solutions for software businesses to analyze pricing data, implement pricing strategies, and optimize revenue. These platforms often incorporate features like customer segmentation, value-based pricing, and predictive analytics. They enable businesses to leverage structured data for informed decision-making, ensuring effective subscription management and maximizing customer lifetime value.

• Customer Relationship Management (CRM) Systems:
CRM systems like Salesforce or HubSpot play a crucial role in price analytics by capturing and organizing customer data. This includes information on referenceable customers, customer acquisition costs, and lifetime value. These systems contribute to effective customer segmentation, helping businesses tailor pricing strategies to individual customer needs and paying capabilities, ultimately enhancing customer loyalty.

• Business Intelligence (BI) Tools:
BI tools like Tableau or Power BI facilitate the visualization and analysis of pricing metrics and market research data. Through dashboards and reports, businesses can gain insights into consumer behavior, purchase behavior, and market demand. These tools empower companies to identify pricing opportunities, plan pricing strategies, and optimize revenue management based on real-time information.

• Machine Learning and Predictive Analytics Software:
Machine learning tools, including Python-based libraries like scikit-learn or dedicated predictive analytics software like RapidMiner, enable businesses to implement advanced pricing analytics models. These tools can analyze large datasets to predict pricing elasticity, forecast demand, and dynamically adjust pricing strategies. For example, they can help in understanding customer churn patterns and identifying psychological price points for different customer segments.

How pricing analytics improve profitability?

• Optimizing Pricing Strategies for Value Maximization:
This tool enables software businesses to optimize their pricing strategies by incorporating factors like value-based pricing, price elasticity, and relative preference analysis. By understanding customer segmentation and their perceived value of the product, businesses can align their pricing decisions with the value proposition offered. This strategic alignment not only attracts more customers but also justifies premium pricing for products with augmented value, contributing to increased average revenue per user and overall profitability.

• Efficient Customer Acquisition and Retention:
Through the analysis of customer acquisition costs, lifetime value, and customer churn, this solution aids in crafting effective customer acquisition and retention strategies. Businesses can identify the most cost-effective channels for acquiring customers and implement dynamic pricing to retain loyal customers. By minimizing customer churn and maximizing customer lifetime value, companies ensure a stable revenue stream, positively impacting overall profitability in the long run.

• Dynamic Pricing Adjustments for Market Responsiveness:
This tool empowers businesses to make real-time adjustments to pricing based on market demand, supply chain dynamics, and operational efficiency. Utilizing demand-based pricing and forecasting tools, companies can adapt their pricing decisions to match consumer spending trends and seize pricing opportunities. This agility in pricing strategies ensures that businesses remain competitive and responsive to market changes, ultimately enhancing overall profitability.

• Operational Efficiency and Cost Management:
This tool contributes to operational efficiency by providing insights into operating expenses and profitability by channel. By identifying profitable channels and optimizing pricing decisions accordingly, businesses can streamline their operations and allocate resources effectively. This not only reduces unnecessary costs but also ensures that pricing strategies align with operational efficiency, directly impacting the bottom line and improving overall profitability.

Pricing analytics Types with Examples

• Descriptive Pricing Analytics:
It involves the analysis of historical pricing data and patterns to gain insights into past performance. In the software business, this type of analytics helps in understanding the effectiveness of previous pricing strategies and identifying trends. For example, by examining average revenue per user over different time periods, businesses can assess the impact of pricing decisions on overall revenue.

• Predictive Pricing Analytics:
It utilizes statistical models and algorithms to forecast future market trends and customer behavior. In the context of software pricing strategy, businesses can use predictive analytics to anticipate changes in market demand, enabling proactive adjustments to pricing decisions. Forecasting demand and consumer spending trends can guide companies in preparing for market shifts and optimizing pricing strategies accordingly.

• Prescriptive Pricing Analytics:
It provides actionable recommendations based on data analysis. In the software sector, businesses can use prescriptive analytics to optimize pricing decisions by considering factors such as customer segmentation, price elasticity, and relative preference analysis. For instance, prescriptive analytics may suggest personalized pricing promotions to different customer segments based on their historical purchase behavior.

• Dynamic Pricing Analytics:
This tool involves real-time adjustments to pricing based on various factors such as market demand, supply chain dynamics, and operational efficiency. In the software business, dynamic pricing can be implemented by considering factors like customer churn, subscription management, and changes in market demand. For example, a software company may dynamically adjust subscription prices based on customer loyalty and changes in market demand, ensuring competitiveness and revenue maximization.

Game-Changing Solutions for the Oil and Gas Retailing Business

Despite a decline in fuel use, customers continue to consider the cost of fuel when choosing which retailer to visit. Therefore, fuel retailers must remain vigilant about their competitors’ prices and promotional policies. Considering the price while bidding for customer attention is more critical than ever.

Quantzig can assist retailers in analyzing rival pricing and discount strategies to determine the best prices. Effective discounting methods directly impact profits, business expansion, and customer loyalty. The technologies also allow price adjustments in response to anticipated client demands without affecting organizational profitability.

Unlock unprecedented growth with Quantzig’s cutting-edge pricing analytics solutions. Harness the power of data-driven insights to optimize pricing strategies, maximize profitability, and stay ahead in today’s dynamic business landscape. For a tailored approach to elevate your pricing game,

Oil Pricing Analytics Challenges of the Retail Client

A leading Saudi Arabian oil and gas retailer approached Quantzig because it was facing intense competition from competitors offering products at significantly reduced prices. Our client needed pricing optimization, competitive benchmarking, and real-time monitoring of price gaps for each of its product groups and consumer segments. The client wanted to leverage Quantzig’s custom pricing analytics tools to assess discounting methods and implement correct pricing structures across channels.Some of the critical issues that were negatively impacting the client were as follows:

• Variations in consumption behavior
• Fluctuations in the prices of oil and gasoline
• Rising costs of retail dealers and distribution
• Refining revenues and expenses
• Lower costs and incentives offered by competitors

Oil Pricing Analytics Solutions for Industry

With AI, Quantzig could extract patterns and trends in consumer behavior and provide the client with a solution for calculating oil prices. Quantzig also used a data-driven strategy to estimate demand, flow, and price to maximize profit. Besides that, AI helped with risk management to help control volatility and uncertainty inherent in the oil and gas industry.

To create highly effective regional pricing and discount strategies, Quantzig also implemented a data-driven methodology for price optimization that uses predictive analytics and AI-based approaches. Our experts also looked at the client’s existing price structure and coupled it with marketing and sales data to construct an algorithm that anticipated customer behavior.Implementing a real-time discount dashboard created by Quantzig enabled managers or sales agents to respond to increases in sales volume. The client conducted a univariate analysis to understand the individual impact of discounts, price, and other variables on sales. It also devised a simulator to dynamically design discounting and pricing strategies for individual products and customer segments.

Impact Analysis of Quantzig’s Pricing Analytics Solutions

The ability of Quantzig’s pricing analytics solution to increase sales and profit margins has been steadily recognized by our clients as it helps to identify the best discount strategies while considering all production-line costs. Advanced analytics, which combines engineering, data science, and computing capacity, helped the client achieve its goals. Our solutions had the following impact on our client’s business:

• Optimized pricing and discount strategies
• Provided a useful decision-making tool to the client and the sales team for real-time pricing fixing and discounting
• Offered real-time visibility of price fluctuations
• Increased retail discount transparency by leveraging pricing analytics technology

Key Outcomes

The client approachedQuantzig to leverageits expertisein pricing analytics solutions to improve its retail sales margins. The client’s top concern was analyzing the regulatory norms governing the market environment. To correctly price their products and boost the profitability of their retail products, our client also needed to understand the pricing methods of its competitors and apply appropriate price models.

Quantzig was able to help the client achieve these goals with the implementation of a decision-making tool. This tool gave the client real-time insights that helped them determine optimized pricing and discount strategies.

A Broad Perspective on the Role of Price Analytics in the Oil and Gas Sector:

The energy sector is very volatile, with prices changing daily. Therefore, it is necessary to keep abreast with the latest geo-political developments which impact the industry. At the same time, keeping a close eye on the competitors and consumers is crucial. Keeping track of multiple variables is a tough challenge for stakeholders in the oil and gas sector, which the adoption of advanced analytics solutions can ease.

Quantzig’s solutions take into account all the multiple variables such as market trends, supply and demand, and competitor landscape to arrive at pricing and discount strategies that are likely to maximize profits for the client.

Key Takeaways of Pricing Analytic Solutions in Oil and Gas Industry:

Quantzig’s solutions enabled the following benefits for the oil and gas retail client:

• Implemented an automated system for real-time pricing fixing and discounting
• Optimized pricing and discount strategies for maximum profit
• Enabled the client to remain competitive and relevant by evaluating competitors
• Ensured adherence to regulatory norms
• Provided visibility on inventory to plan pricing and discount strategies
• Helped the client retain valuable customers