Tag: Sales data analytics

data modeling best practices

3 Data Modeling Best Practices to Boost Your Business Results

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To solidify important business decisions with big data, it is important to understand data modeling. With new probabilities for businesses to easily access and analyze their data to boost performance, data modeling techniques are rapidly changing too. More than arbitrarily organizing data relationships and structures, data modeling must connect with end-user questions and requirements, as well as provide guidance to help ensure the right data is being used in the proper way for the desired results. In this article, we have explained some of the data modeling best practices that businesses must follow to improve their outcomes and save time.

Data Modeling Best Practices

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procurement analytics

Top 5 Marketing and Sales Analytics that Managers Must Consider

sales analyticsHaving a marketing and sales analytics metrics provides companies with relevant insights which enable companies to increase revenue and profitability, and consequently improve their brand perception. Ideal sales analytics tools also help managers uncover new markets, new audience niches, areas for future development and much more. However, the challenge here is to identify the best and most important sales analytics metrics for business:

Market size analytics

Having a fair idea about the market size and potential is integral to business. It involves identifying how large the market is for your products and services, and whether there is sufficient growth potential. The size of the market is measured in terms of volume (how many units sold), value (money spent in that market) or frequency (how often a product or service is sold). Data can be collected from government data sources, trade association data, financial data from competitors, and customer surveys. Using the right sales analytics tools help businesses estimate their market size accurately and the sales volume generated from this market.Contact US

Unmet needs analytics

The primary aim of any business is to effectively meet the needs of their target customers. Using sales analytic metrics helps businesses to uncover if there are any unmet needs around your product or service or within your market which you could meet to increase customer satisfaction and revenue. Using various sales analytics tools and other sources including product reviews, qualitative surveys, focus groups,  and interviews, companies can easily identify the unmet needs of their customers.

big data

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

To know more about how our sales forecasting solution helped the financial services client

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Trade promotion

Trade Promotions Optimization for a Leading CPG Manufacturer

Trade Promotion Optimization (TPO) is the process of utilizing integrated goals, factoring in promotion and supply constraints, and predictive analytics for precise promotion planning and increasing client loyalty. With declining sales and intense competitive pressure, the manufacturers in the consumer packaged goods (CPG) industry need a reliable trade promotion optimization (TPO) strategy. The existing attempts at TPO lack depth and are primarily based on qualitative information. TPO is one of the key activities for manufacturers in the CPG industry to increase short-term sales of the products.

Quantzig’s trade promotions optimization utilizes data from various promotions, price points, Captureand sales forecasts to offer actionable insights to the client. Our solutions help businesses generate better forecasts to analyze promotion efficiency of their products. Our ability to derive insights into the impact of trade promotions on consumer buying behavior offers a significant competitive advantage to manufacturers in the CPG industry.

The Business Challenge and Quantzig’s Approach

To improve sales and battle competitive pressure, the client – a leading CPG manufacturer in the US with more than USD 2 billion in revenues – approached Quantzig to perform a trade promotions optimization. The client was struggling with promotion planning and execution due to the seasonal nature of their products. The client’s capability to plan promotions lacked depth and was based on qualitative or incomplete information. Volume planning was not linked to realistic promotional outcomes leading to inappropriate inventory levels and reduced profits. As a result, the client needed to develop a solution that could improve the ROI and overall cost savings.

The primary objective of this trade promotions optimization was to develop capabilities for precise promotion planning and increase client loyalty for their products. The team developedCapture a pricing simulations model that could model sales volumes based on different market scenarios that were needed to replace the instinct-based approach of the category management department.

To meet the specific requirements of the CPG manufacturer, the analytics team analyzed various historical sales data, category and product data, pricing data, and shipment data to offer insights on trade promotion optimization strategy. The research team focused on developing a solution that would improve the client’s promotional executions by combining these optimizations with simulations. The team developed effective pricing and promotions strategy and simulated sales based on different scenarios.

An overview of the data used and models applied are given below

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Business Benefits and Insights

With the objective of improving overall sales and ROI, and to create precise promotion planning to increase client loyalty, the predictive analytics team analyzed promotion efficiencies, based on time of day/month, retailer segments, and region to improve promotion reach and effectiveness and created a promotion plan Trade promotion3options based on levers such as cost, timing, and depth of promotional activities. The trade promotions optimization improved the client’s trade promotion planning process based on accurate volume forecasts and promotional efficiency.

It derived insights about the promotional impact on consumer buying behavior. The client achieved cost savings on packaging destruction costs from seasonal products due to the ability to forecast demand with high accuracy. A better forecast to analyze promotional efficiency helped the client achieve time savings of more than three months in the promotion planning process. The analysts assessed campaign effectiveness based on available data to make dynamic adjustments. The solutions from the trade promotion optimization engagement helped the client generate price simulations and discount offers based on retailer segment and promotional tactics. The team provided the user with accurate baselines and lift coefficients, and the ability to deliver one-off promotion predictions based on numerous pricing scenarios.

The client was able to create an effective promotion planning with the help of trade promotion optimization which helped improve customer loyalty. There was an increase in ROI and improvement in cross-selling and up-selling based on targeted promotions and pricing. The historical sales were broken into base, incremental, and total sales and incremental sales were mapped to the set of individual promotions and campaigns. The solutions helped the client develop an optimized annual plan for strategic promotions based on profit, volume, and revenue.

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Order fulfillment

Order Fulfillment Optimization for a Leading Electronics Retailer

From managing the performance of the sales force and improving the ability to process more loads to utilizing the optimal technologies, organizations, especially in e-commerce, have a number of challenges to overcome while optimizing their order fulfillment processes. Though the increased customer preference towards e-commerce helps the online retail industry improve revenues, the rising demand for faster deliveries makes it extremely difficult for players in this market space to provide a better experience for the customers. With the intensifying competition, the failure to make faster deliveries will result in a significant decrease in an organization’s revenue shares.

By providing effective insights, Quantzig’s order fulfillment optimization solution helps businesses make better decisions and also aids in improving various business processes including inventory Capturemanagement, supply chain visibility, and merchandizing. With a clear understanding of the client’s business processes and requirements and leveraging our expertise in data analytics, we also offer actionable insights to enhance supply chain effectiveness, network optimization, category tracking and consolidation, demand planning, and tail spend optimization.

The Business Challenge and Quantzig’s Approach

By realizing the need to deliver better customer experience to improve revenues, the client – one of the leading online electronics retailer in Australia and New Zealand – collaborated with Quantzig to develop an effective solution for order fulfilment optimization to reduce the delivery time and also decrease costs of priority orders, which would, in turn, help them enable the faster delivery of online orders. With more than 600,000 products under 117 categories, the client received almost 2800 online orders every day, including priority orders, where customers paid for the delivery. As a result, there was a need to implement a store-to-door model, which would help them fulfill online deliveries much faster. Additionally, with more than 250 retail outlets, the client also had to identify the right store to source the delivery of priority orders.

The primary objective of this order fulfillment optimization was to identify the challenges involved in optimizing the delivery process. By analyzing Capturethe historical sales data and segmenting the order history, the analysts at Quantzig also helped rationalize the shipping cost by identifying the priority orders to be delivered from the stores.

To meet the specific requirements of the leading online retailer for electronics, our supply chain analytics team developed an effective solution based on the identification of influencers from the analytics data collected from various segments. Moreover, to gain a clear understanding of the business requirements, our analytics experts also considered various parameters including footfall, cost of shipping, and the volume of inventory left in the store.

Business Benefits and Insights

With the objective to help the leading electronics online retailer deliver better customer experience through faster fulfilment of online orders, a team of supply chain analytics experts with significant experience in offering insights through similar order fulfilment optimization assignments, offered an effective solution to reduce the delivery time and deliver better experience for loyal, high-valued, and new customers.QZ-Fulfilment2 By developing a random forest decision tree based approach, this order fulfillment optimization solution also helped identify the influencing factors for customer ratings in each segment and also approximated a cost function to recognize the right store to fulfill the order. Additionally, by analyzing the factorial combinations resulting in good reviews, we built a classifier that also helped identify orders to be fulfilled from the stores.

Furthermore, by analyzing the historical sales data and segmenting the order history into four classes based on fulfillment source and fulfillment ratings, this order fulfillment optimization helped identify the interconnected problems resulting from the new model. Additionally, this supply chain visibility assignment also offered recommendations such as to serve the new, high-valued customers whose product is available at the nearest store, and paid for faster delivery to a location nearer to the store compared to the warehouse, with store-to-door delivery services.

In a span of just eight weeks, this order fulfillment optimization helped the leading online electronics retailer was able to reduce the delivery time of priority orders and identify the right source of delivery for each order.

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sales data

Food retail chain improves sales productivity through implementation of sales data analysis based solution

Business Challenge: Effective implementation of targeted marketing. The client wanted to improve the effectiveness of its targeted marketing efforts by developing an understanding of the customer segments.

Situation: Lack of in-depth insights from sales data

The client was facing challenges in making the maximum use of sales data and deriving insights on customer profile, in order to develop strategies to improve sales productivity.

Solution/Approach: Sales data analysis solution to understand customer behavior and trends

We deployed data analytics techniques to conduct in-depth assessment of the sales data and develop customer segmentation by means of products, customers, brands and SKUs. The segmented data was further analyzed to derive insights on sales trends and customer behavior. We also helped the client in developing key performance indicators for effective measurement of sales productivity.

Impact: Improved sales productivity through targeted marketing

Based on the trends at an individual product, customer, brand and SKU levels, the client was able to develop clear understanding of the customer segmentation. Based on this, they improved on the marketing efforts at an individual segment level resulting in better sales productivity.