Tag: Pricing analytics


Retail Supply Chain and Marketing Analytics – Connecting the Dots, Driving Growth

The one industry that is highly unpredictable and prone to disruption is retail. Proponents of this sector strive to wade through intense competition, high customer expectations, manage multiple channels and wide array of product offerings among several other challenges to create a competitive advantage and maintain their market position. To stay abreast of competition and latest trends, retailers must devise strategies based on insights and analytics to understand the business and anticipate customer behavior.

Analytics collects data from various channels used for marketing and combines it to provide a common direction that helps to extract analytical results which deliver actionable insights to drive the firm’s marketing efforts to the fore. It comprises of technologies and processes that assist marketers in ascertaining the success of their marketing efforts, by measuring performance through ROI and effectiveness.

Making Inroads into Retail Supply Chain

Advanced marketing strategies and analytics such as customer analytics can help tone down the anxiety in a significant business area like retail supply chains. Insights derived from historical as well as real-time data can help retailers understand customer behavior and segment them accordingly.

The adage “Customer is the King” is gaining importance in today’s competitive market environment. Increasingly, retailers are tailoring messages and creating a customized experience for the customers, to which the latter are responding in a favorable manner. Personalized marketing encompasses more than just mentioning customer’s name in an email, for example, personalized follow ups and insights derived from previous purchases and point-of-sale terminals can help build customer loyalty. Additionally, firms can use customer data to device practice scalable pricing and understand customer expectation in order to maximize retail ROI. Pricing analytics go hand in hand with personalized marketing so as to create happy consumers and build loyalty.

The sole purpose of analytics and big data is risk management – to foresee and mitigate possible risks, thereby creating significant savings in retail supply chain. With the help of data- external and internal- firms can develop strategies based on insights that help in supplier management, assessing store performance and effectiveness of marketing campaigns and marketing channels.

The Quantzig Approach

We, at Quantzig, track latest developments and innovations in the industry through different sources and methodology, reach out to key stakeholders and marketing experts in order to understand the market scenario. We help clients understand and identify fluctuations in consumer interests and devise insights based marketing tactics and strategies to stay ahead of the competition.

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70% loss reduction achieved by leading FMCG company by implementation of multi-factor price forecasting methods

Business Challenge: Implementation of a robust price forecasting mechanism.

The client wanted to develop a robust price forecasting mechanism that could help them negotiate better rates with suppliers and optimize future raw material inventory levels.

Situation: Lack of visibility on future prices and negotiation support.

Client was experiencing a lack of visibility on future Pyridine prices resulting in budgeting issues and supply chain fluctuations. In addition, the client also did not have access to fact based insights that could enable them negotiate long-term contracts with suppliers at individual category or product levels.

Solution/Approach: Pricing analytics solution enabling dynamic pricing at SKU and product levels.

We developed a multi-factor price forecasting model capturing various macro and micro-economic factors including Pyridine specific demand and supply factors. This model provided accurate price forecasting information and insights for improving supply chain efficiency.

Impact: Reduced levels of losses and improved supply chain efficiency.

Our model helped client in reducing losses by 70% in the first year along with improved supply chain efficiencies and optimized Pyridine inventory levels.

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9-11% sales growth achieved by a leading supermarket through implementation of pricing analytics

Business Challenge: Implementation of a robust pricing analytics solution

A leading supermarket chain in the US wanted to conduct a pricing analysis exercise for its grocery line of products that had premium as well as standard variants.

Situation: Reliance on traditional price setting methods resulting in reduced sales than competitors

Client had seen frequent change in competitor pricing and wanted to understand the impact on own products and also decide on optimal pricing for both premium and standard variants.

Solution/Approach: Price analytics solution enabling dynamic pricing at SKU and product levels

We conducted an in-depth analysis on the current demand, actual sales, and SKU performance. We constructed models to analyze price elasticity and sensitivity across the SKUs and variants. We also created scenarios to simulate the price change impact in relation to competitor pricing levels as well.

Impact: Improved sales growth through implementation of retail pricing strategy

Client achieved visibility on current SKU performance, demand and price variations. Also, they were able to implement a robust process based on price elasticity model for better understanding of impact of changes in competitor pricing. The key benefits achieved include reduced wastage and inventory cost for low performing SKUs, resulting in overall sales growth of 9-11%.

data and analytics

Oil company improves pricing process and efficiency by implementation of pricing analytics solution

Business Challenge: Implementation of robust pricing model.

A leading energy client wanted to develop price model to better manage the impact of price changes on its business.

Situation: Setting up analytical models for price modeling.

The client wanted to improve its visibility on the oil market prices and based on this, setup analytical models for data based insights.

Solution/Approach: Pricing analytics solution for accurate price forecasting.

We collected data on oil market prices and changes in global oil market. We determined the optimum price points for maximization of profits and assessed price sensitivity based on production and supply, and effect of competitive pricing. The solution enabled clients to accurately forecast prices based on factors affecting price changes in future, as well as assess the impact on the margins.

Impact: Improved pricing mechanism and better control over volatility of supply demand conditions.

Client was able to gain visibility on oil market based on the statistical model. They were able to precisely track and forecast price impact on margins. Our solution helped the client in improving the pricing mechanism and establish better control over changes due to supply and demand issues.


Implementation of pricing analytics helps leading telecom operator improve revenue growth

Business Challenge: Implementation of a robust pricing analytics solution.

A leading telecom operator in APAC region wanted to implement a robust model for determining right pricing ranges using data analytics based solutions.

Situation: Reliance on traditional price setting methods resulting in reduced revenue.

Client was facing issues with implementation of robust pricing strategy in correlation with actual customer data.

Solution/Approach: Pricing analytics solution based on call data records.

We developed a subscriber oriented pricing strategy by conducting in-depth analysis on the customer call data records. We made efficient use of call flow and usage data to enable the client in deriving optimal pricing levels based on past customer data and also to simulate the new prices to assess the expected success rate.

Impact: Improved revenue growth through implementation pricing analytics.

Client achieved improved revenue through implementation of customer oriented pricing strategies. Our solution also helped the client in developing scenarios based on the adjusted price levels and simulated possible outcomes before actual implementation.