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By Shraddha Thuwal
September 10, 2023
Historical Data shows previous patterns of demand and supply examples include sales records, customer orders, inventory levels, market share, pricing, promotions, seasonality, and outside variables. For your forecast, you must collect enough data to span an appropriate time range and frequency. For instance, you want at least 12 months of historical data in order to anticipate monthly demand for a whole year. Additionally, you must organise and clean up your data, eliminating any outliers, mistakes, or missing numbers that can affect your forecast.
Table Of Contents
- Historical Data for Demand Forecasting
- Importance of Historical Data
- Sales Data
- Customer Data
- Identity Data
- Descriptive Data
- Quantitive Data
- Qualitative Data
- Market Data
- External Data Sources
- Contribution of Historical Data
- Storage of Historical Data
- Retention of Historical Data
- Conclusion
Historical Data for Demand Forecasting
It is essential to comprehend the importance of demand forecasting. Manufacturers can effectively allocate resources, link inventory levels with expected demand, and optimise their production schedules. As a result, expenses are decreased, customer satisfaction is raised, decision-making is improved, and profitability is eventually boosted. However, it can be difficult for producers to estimate future demand with any degree of accuracy. These difficulties emphasise the necessity for reliable forecasting techniques that can deal with the changing nature of demand trends. In order to overcome these difficulties and increase demand forecasting accuracy, historical data is crucial. With the use of these insightful historical demand patterns, producers may spot trends, seasonality, and other demand-influencing elements.
Importance of Historical Data
Understanding previous demand patterns and behaviours requires using historical data as a point of reference. It gives manufacturers a foundation for recognising recurring patterns, seasonality, and changes in client demand.
Manufacturers may decide wisely regarding resource allocation, inventory control, and production levels by using historical data. A data-driven approach to demand forecasting is made possible by historical data, allowing manufacturers to increase forecast accuracy and streamline their processes.
Sales Data
One of the most basic categories of historical data utilised in predicting is this one. It contains data on sales volumes, income, and purchasing trends of customers over a certain time frame. Sales data helps discover any repeating trends or seasonality and sheds light on prior demand levels.
Customer Data
Customer data includes details on specific clients, including their purchasing patterns, interests, demographics, and behaviour. Additionally, segmenting their client base, understanding demand variances across various consumer categories, and customising their projections are all made possible by customer data analysis for manufacturers.
Identity Data
| Name | Both first and last |
| Mailing info | Physical address to which you can send packages or mail. |
| Digital Contact info | This includes both the email address and the telephone number. If the customer has a preferred method, it should be noted. |
| Social Media | This includes both the social media profiles that the customer uses on different platforms, as well as information about which platform they prefer. |
| Personal Information | Birthday, account info related to your company. |
Descriptive Data
| Professional details | The Current company name and their position within it. |
| Family info | Marital Status |
| General lifestyle | House, Car, Hobbies, etc. |
Quantitive Data
Data that can be measured is known as quantitative data. The majority of this data relates to consumer contacts with your business, whether they occur in person, over the phone, or on your website. Since this data always comes down to numbers, CRM metrics are where it is most frequently used.
The number of purchases that the customer has made with your company.The average value of their purchase history.The frequency of their visitations to your website.The average amount of time they spend on your website.How often do they engage with your company on social media?
Qualitative Data
Comparatively, qualitative data tends to be more descriptive. Customers’ attitudes, motives, and behaviours that are related to purchase decisions are typically included. Since it is hard to quantify this information, businesses frequently employ surveys and feedback enquiries to obtain it directly from customers.
Market Data
Market data includes details regarding competitive performance, market trends, and general market circ*mstances. Data on market size, market share, price trends, and market dynamics are all included. Manufacturers may better grasp the external elements affecting demand and incorporate them into their forecasting models by analysing market data.
External Data Sources
Manufacturers can use external data sources in addition to internal data sources to improve the accuracy of their forecasts. This includes information from market research studies, government statistics, industry publications, social media trends, and other pertinent outside sources. Additional context and insights into market trends, consumer behaviour, and developing patterns are provided by external data.
Contribution of Historical Data
- Demand trends: Manufacturers can discover recurrent demand patterns like seasonality, cyclicality, or trend-based fluctuations with the aid of historical data. Manufacturers can modify their projections to take into account anticipated variations in demand by recognising these trends.
- Data-Driven Insights: Long-term patterns in demand may be found and analysed using historical data. Manufacturers benefit from its aid in comprehending changes in consumer preferences, market dynamics, and market trends. Manufacturers may modify their plans and foresee changes in future demand by recognising these tendencies.
- Evaluating forecast accuracy: The validity of demand forecast accuracy may be verified using historical data. Manufacturers may evaluate the accuracy of their forecasting models, pinpoint areas for development, and enhance their future predictions by contrasting the predicted values with the actual historical data.
- Analyse prior changes: Manufacturers can analyse prior demand changes and determine their reasons using historical data. Manufacturers can modify their forecasting models and create backup plans to lessen the effects of future changes by recognising the causes of demand volatility.
- Enhancing projections: Manufacturers may develop data-driven forecasts and increase the precision of their projections by incorporating previous data into demand forecasting algorithms. It offers a strong basis for comprehending historical demand patterns, seeing trends, and coming to wise conclusions to optimise operations and resource allocation.
Storage of Historical Data
- Historical data can be stored in a variety of ways, including databases, spreadsheets and text files.
- It is important to choose a storage method that is efficient and scalable so historical data can be easily accessed and analyzed.
- There are many options available for storing historical data.
- The best option for a particular organization depends on the specific needs and requirements.
- Storage capacities have increased significantly in recent years and cloud storage has taken much of the burden of storage administration from many enterprises.
- However, large organisations with strict compliance requirements and privacy controls also have options to store historical data in a private server or data centre.
Retention of Historical Data
Some organizations are required by law or regulation to retain historical data for a certain period of time. For example, businesses in the financial services industry are subject to Financial Industry Regulatory Authority (FINRA) rules, which require the retention of business records for varying lengths of time depending on the type of record. Other organizations may have internal policies for how long historical data should be retained. For example, a company may keep financial records for seven years or customer service records for five years.
Conclusion
It is important to consult with legal and compliance teams to determine how long historical data needs to be retained. Once a decision has been made, it is important to have a plan in for how historical data will be stored and managed over time. Because data storage requires resources to maintain, data lifecycle management (DLM) is recommended to ensure that data is not maintained without good reason or for longer than necessary and that it is properly archived or disposed of as appropriate.
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Author
Shraddha Thuwal
Shraddha Thuwal worked as a content writer at WareIQ. She actively contributes to the creation of blog posts centered on eCommerce operations, fulfillment, and shipping, in addition to providing insights on various strategies and techniques tailored for eCommerce sellers. With an impressive track record, Shraddha boasts over two years of content writing experience, spanning a spectrum of industries including logistics, supply chain, and media.
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Footwear Brands: How to Manage Returns Effectively With Wareiq’s Returns QC Solution In the footwear industry, post-purchase experience plays a pivotal role in determining a brand's success and customer loyalty. As e-commerce continues to grow, so does the volume of returns, presenting a dual challenge of maintaining high customer satisfaction while managing logistical efficiencies. For footwear brands, managing returns effectively is not just about handling unwanted or unsatisfactory products; it involves a comprehensive strategy that encompasses customer service, logistics, quality control, and financial implications.Effective returns management can significantly impact customer retention and profitability. A smooth, transparent returns process enhances customer trust and promotes a positive brand image. However, ineffective returns strategies can lead to increased operational costs, inventory mismanagement, and damaged customer relationships. 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Sustainable PracticesAdopt environmentally friendly practices in the returns process by minimising packaging use, encouraging customers to consolidate returns, and finding ways to refurbish or recycle unsellable returns.Implementing these strategies improves the efficiency and cost-effectiveness of the returns process and enhances customer satisfaction and loyalty, creating a competitive advantage in the dynamic footwear market and repeat business.WareIQ's Returns QC Solution for Footwear BrandsTo address the complexities of returns management in the footwear industry, WareIQ offers a specialised Returns QC (Quality Control) solution that is tailored to meet the specific needs of footwear brands. This innovative solution incorporates several key features designed to streamline the returns process, ensure product quality, and enhance customer satisfaction:1. Automated Returns ProcessingWareIQ’s solution automates many aspects of the returns process, from initiation to final disposition. This automation includes the generation of return labels, tracking of return shipments, and updates to inventory levels. Automation helps reduce human error and speeds up the processing time, making the returns process more efficient.2. Integrated Quality ControlCentral to WareIQ's offering is its robust quality control system that inspects returned items to ensure they meet the brand’s standards for resale. This system uses advanced scanning and imaging technologies to assess the condition of the footwear, ensuring that only items in appropriate condition are restocked.3. Real-Time Data and AnalyticsWareIQ provides real-time analytics that allows brands to monitor and analyse return rates, reasons for returns, and customer feedback. This data is invaluable for making informed decisions about product improvements, inventory management, and customer service strategies.4. Customisation OptionsRecognising that each footwear brand has unique challenges and requirements, WareIQ’s Returns QC solution offers customisable options to address specific logistical and operational needs. This flexibility ensures that brands can optimise the solution to better suit their business models and customer base.5. Seamless IntegrationThe solution seamlessly integrates with existing logistics and ERP (Enterprise Resource Planning) systems, ensuring that information flows smoothly between returns processing and other business functions. This integration helps maintain data integrity and provides a holistic view of inventory and operations.6. Enhanced Customer ExperienceBy streamlining the returns process and ensuring that customers receive timely refunds or exchanges, WareIQ's solution helps improve the overall customer experience. Transparent communication throughout the returns process keeps customers informed and helps build trust and loyalty.By leveraging WareIQ's Returns QC solution, footwear brands can not only handle returns more effectively but also turn the challenge of high return rates into an opportunity for enhancing customer satisfaction and operational efficiency.Case Studies: Footwear Brands Leveraging WareIQ's Returns QC SolutionSeveral footwear brands have adopted WareIQ's Returns QC solution to address their challenges with returns management. These case studies highlight the effectiveness of the solution in transforming their returns process, enhancing customer satisfaction, and improving operational efficiency:1. Brand AA prominent sports footwear brand faced high return rates primarily due to sizing issues and customer expectations not being met. After integrating WareIQ’s Returns QC solution, Brand A reported a 25% reduction in return rates within the first six months. The automated quality checks helped maintain the integrity of returned items, ensuring that nearly 95% of returns were restocked and resold, thereby significantly reducing waste and improving profitability.2. Brand BA luxury footwear brand struggled with managing the returns of high-value items, which required meticulous quality control to maintain brand standards. The introduction of WareIQ’s customised quality control system allowed Brand B to enhance its product reassessment process, increasing customer satisfaction by ensuring that customers received products in pristine condition. This also elevated the brand's reputation for quality and customer service.3. Brand CFaced with logistical challenges with reverse shipping and restocking, Brand D leveraged WareIQ’s integration capabilities to synchronise their ERP systems with the Returns QC solution. This enabled real-time data flow and analytics, which improved inventory management and reduced return processing times by 40%.4. Brand DThis rapidly growing online footwear retailer used WareIQ’s analytics tools to gain insights into the reasons behind returns. The data collected led to changes in product descriptions and sizing information on their e-commerce platform, which reduced return rates by 20% and enhanced customer trust and retention.ConclusionEffective returns management is pivotal for the success and sustainability of footwear brands in today's market. As demonstrated by the integration of WareIQ's Returns QC solution across various brands, this approach can significantly improve operational efficiencies, reduce costs, and enhance customer satisfaction. The solution's ability to automate processing, ensure rigorous quality control, and provide valuable data analytics transforms a traditionally cumbersome and cost-heavy process into a strategic asset.By embracing advanced technology solutions like WareIQ's Returns QC, footwear brands can effectively address the myriad challenges associated with high return rates. This not only supports a positive customer experience—encouraging loyalty and repeat purchases—but also aligns with broader business objectives such as sustainability and profitability. As the footwear market continues to evolve, the brands that will thrive are those that leverage innovative technologies to enhance their returns management processes, turning potential setbacks into opportunities for growth and customer engagement.Frequently Asked QuestionsWhat are the typical return rates for footwear brands online?Online footwear brands often experience return rates between 20% and 30%, primarily due to sizing issues and customer expectations not being met. This rate can vary widely depending on the type of footwear, the brand's target demographic, and the effectiveness of its sizing guides and product descriptions.How does WareIQ's Returns QC solution enhance customer satisfaction?WareIQ's Returns QC solution enhances customer satisfaction by streamlining the returns process, ensuring faster processing times, and maintaining communication with the customer throughout the process. This transparency and efficiency directly improve the customer's experience and perception of the brand.Can WareIQ's solution integrate with existing logistics systems?Yes, WareIQ's Returns QC solution is designed to integrate seamlessly with existing logistics and inventory management systems, providing a cohesive and efficient workflow. This integration helps maintain data accuracy, reduces the risk of errors, and enhances overall operational efficiency.What are the cost benefits of implementing WareIQ's Returns QC solution for a footwear brand?Implementing WareIQ's solution can significantly reduce the costs associated with handling and processing returns by automating many of the labour-intensive steps involved. Additionally, the improved efficiency can reduce the turnaround time for getting products back into inventory and available for sale, minimising the financial impact of returns.How does real-time analytics from WareIQ help manage footwear returns?Real-time analytics provide footwear brands with insights into return patterns and reasons, aiding in better stock management and preventive measures for high-return products. This data allows brands to make informed decisions about product adjustments, marketing strategies, and customer service improvements.What measures does WareIQ's solution include to prevent fraudulent returns?WareIQ incorporates verification checks and quality control assessments to identify and reduce fraudulent returns, ensuring that only legitimate returns are processed and restocked. This helps protect revenue and maintains the integrity of the brand’s inventory. May 14, 2024
