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Financial Service Sector market analysis – How sales forecasting solutions helped a financial service firm to better manage their inventory and stock

QZ PR templateLONDON: Quantzig, a global analytics services provider, has recently completed their latest sales forecasting study for a financial service client. The financial services industry consists of several organizations including consumer finance firms, hedge funds, insurance companies, commercial and investment banks, and consumer finance firms. These firms help in managing money and another asset for corporations as well as individuals. Their services are primarily related to asset management, investments, accounting, and foreign exchange.

“The sales forecasting solution offered by Quantzig helped the financial service firm to bring about noticeable changes in accuracy by enhancing product development timing to improve sales.” says an industry expert from Quantzig.

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The sales forecasting solution offered by Quantzig helped the client to bridge the service delivery gaps. Furthermore, the solution also helped the company in better managing its inventory and avoid stock-outs and overstock situations. It also assisted the company to anticipate future sales and develop strategies to improve revenue.

Additional Benefits of the Sales Forecasting Solution

  • Enhance product development timing to improve sales
  • Gain relevant market knowledge to devise strategies that would improve the overall accuracy of operations
  • Explore possibilities to increase net income and revenue
  • To know more, request a proposal

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Data Management and Reporting Helps a Retail Chain Streamline Processes

In every organization, collecting and organizing data plays a pivotal role in better understanding the customers andCapture business processes. Consequently, managing and reporting data effectively helps the organization to boost productivity, reduce expenditure, and gain a competitive advantage. To streamline operations, retailers should emphasize on improving the shopping experience to boost customer satisfaction and loyalty. Moreover, to gain customer insights, retailers are leveraging the use of customer data management to enrich customer analytics and operations to deliver consistent and personalized shopping experiences.

Quantzig’s data management and reporting solution helps the client improve shopping experience, sales, and customer satisfaction. In addition, the data management solution helps in decreasing operational costs by eliminating the time spent on manually searching for customer data.

The Business Challenge

A global retail chain was facing challenges in terms of data management to capture their weekly circular information. With a broad customer base and large category of products, the client was facing challenges in analyzing their data and comparing it with their competitors. Also, the client wanted to generate a report for all the merchants and marketers.

Our Approach

To understand the client’s specific business requirements, Quantzig’s team of data management experts collated information from various sources to perform an analysis on buying patterns and results of promotions. Also, Quantzig’s team of data management experts built a database that seamlessly collates the circular information of the client and its relevant competitors on a weekly basis.

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Data Management and Reporting Solution Benefits

  • Better understand the customers and their purchase history
  • Improve shopping experiences, sales, and merchandising by using customer data
  • Increase product portfolio and improve the offerings
  • Determine the frequency and type of sales and marketing promotions

Data Management and Reporting Solution Predictive Insights

  • Identify highly profitable customers in terms of total value of sales, number of sales, and estimated lifetime value
  • Identify customers responsive to promotional offerings
  • Analyze accurate allocation of stock across channels and stores
  • Improved efficiency at the supply chain level

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IR15

Predictive analytics helps retailer improve sales of electronic gadgets and achieve higher profitability

Business Challenge: Improving the sales of electronic gadgets

Our client, a leading electronics retailer wanted to achieve maximum sales and profits in order to beat the competition in the market.

Situation: Need for a solution to achieve a blend of right pricing strategies and promotion strategies

The client wanted to implement a robust solution that could help in accurate demand forecasting, setting right prices, deploying right promotion strategies, and devising profitable pricing strategies.

Solution/Approach: Big data analytics based solution to derive actionable insights

We used big data analytics based solution to implement an end-to-end solution that helped client in achieving desired results. We used predictive analytics for identifying the gadgets that would have high demand. Customer data from social media channels and internal databases were leveraged for accurate demand forecasting and assessing trends in customer behavior. We also devised a mechanism to determine optimal prices and promotions on an hourly basis, based on inventory and competition.

Impact: Achieved competitive leadership and higher profits through improved sales

Client was able to achieve competitive leadership through accurate demand forecasting, ensuring optimal stock levels, dynamic pricing, and by introducing timely offers and promotions. These helped them in achieving a larger sales volume compared to competitors, and hence establish market supremacy.

ir8

27% increase in sales achieved by a leading retail chain through market basket analysis

Business Challenge: Using advanced analytics techniques to assess current performance levels and determine ways of improvement

A leading retail chain, with variety of stores in North America, wanted us to conduct a market basket analysis to assess the current market basket performance and determine ways of improvement.

Situation: Lack of visibility on current performance levels and improving product lift

Client wanted to understand the trends on the market basket performance, seasonality effect based on days of sales, and impact of store size and other factors on the basket performance.

Solution/Approach: Market basket analysis solution based on regression analysis

We conducted a deep dive analysis on the current performance on the various product baskets and impact of other factors. We implemented support, confidence and lift analysis which used regression analysis for assessing impact of store size on the basket size and value. We also defined various scenarios for market basket combinations and resulting profitability.

Impact: Increase in sales up to 27%

Client achieved in-depth analysis on the basket performance along with combinations that work well and have better lift. We also implemented a statistical model based impact analysis technique that helped clients in deriving insights to focus only on factors that impact the sales volume and value. Based on this the client was able to increase its sales up to 27%.

IR24

Assortment planning and process improvement delivers 7-10% increase in sales and 5-10% gross margin gains for leading retail chain

Business Challenge: Challenges in maximizing profits.

A leading retail chain, with variety of stores in North America, wanted to evaluate the ways to improve its profit levels, and wanted us to conduct an analysis on their merchandise assortment planning.

Situation: Issues with determining the right merchandise assortment based on performance.

The client wanted to analyze product performance to determine which products to keep/add/drop, finalize master assortment, identify key items to be in focus and help setup the process for on-going assortment planning needs.

Solution/Approach: Devised a mechanism to determine the most profitable assortment plan.

We analyzed existing assortment and its performance, gathered and analyzed customer behavior and perception insights, evaluated the impact of listing or delisting of items and analyzed switching frequency and demand transfer probability. We also provided insights to determine which items should be stocked, substituted, and removed to maximize sales or profit.

Impact: Improved process for assortment planning and increased sales and gross margin gains.

The client received an improved process for assortment planning. They enhanced their simulation capability for assortment scenarios and impact of change. This helped them achieve reduction in wastage of unused SKUs and enhancing customer satisfaction and return on investment across months. The overall outcome was 7-10% increase in sales and 5-10% gross margin gains.

IR23

30% increase in sales achieved by supermarket through implementation of new store format

Business Challenge: Evaluation of potential store format options.

The client wanted to evaluate the potential store floor format options and understand which option provided the best growth opportunity.

Situation: Stagnation in revenue due to outdated store layout.

The client was facing stagnation issue in most of its outlets leading to a drop in revenue. To tackle this situation and improve revenues, the client wanted to implement new store concepts that could enable higher sales and revenue.

Solution/Approach: Data analytics on store and customer data to determine the best store layout.

We conducted a complete assessment of the client’s existing store format to gain insights on potential strengths and limiting factors. This information was combined with results from data analysis of customer data to develop insights on the correlation between customer perceptions and the store layout. We used cluster analytics for identification of the most profitable customer segments and evaluated the potential of different floor format options in relation to the identified customer segments. Based on this analysis, we recommended on implementation of the store format that had potential to achieve maximum profitability.

Impact: Increase in sales by 30%.

The client was able to increase the sales by 30% by implementing the recommended new store concept.

IR23

Sales analytics and loan to value modeling improves traditional channel based sales by 53% for insurance provider

Business Challenge: Improving traditional channel sales

A large multinational insurance provider wanted to improve the insurance sales through its traditional channel of agents and brokers in the face of competition from online sales.

Situation: Losing traditional channel sales due to competition from online channel

The client sold corporate, auto and home insurance through a network of insurance agents and brokers. A recent survey conducted by the client revealed that there was a steady decline in the number of its customers buying policy through this traditional channel as compared to online channel. As a result its sales team and structure was losing efficiency and attracting fewer new clients. The client wanted a solution which helped in creating the right sales and marketing strategies for its field sales team and bring in new clients.

Solution/Approach: Financial analysis, customer profitability analytics, loan to value modeling and sales optimization

We used pricing analytics and modeling applications to create segments of customers, map the right products to right customers in order to provide tailored offers, and create flexible best-fit pricing models which could appeal to vast majority of the customers. We also used loan to value modeling to evaluate the potential customers, and identify the most profitable ones to target.

Impact: 53% improvement in revenue from traditional channel

The client was able to identify the customer segments most likely to respond to its sales and marketing pitches and least likely to default. Based on this information, the client created tailored solutions for each segment, and trained its sales team the best offers for each segment. As a result, the revenue from traditional channel improved by 53% over the next 6 months.