Nowadays, online shopping has become a normal part of many people's daily lives. This means that entrepreneurs need to understand and keep up with it, as it means increased sales channels, a larger market, and a response to changing customer behavior. At the same time, since online sales don't involve direct interaction with customers, collecting data to understand them is crucial for the sustainability of the business
It is well known that good organizational management requires the analysis of both internal and external data to inform decision-making. Decision-making based on data analysis is certainly better than making decisions based on feelings. Data collection and analysis can be diverse, depending on the organization's objectives. For example:
• Customer data : Analyzing existing and new customers, identifying customer segments, purchasing habits (high/low), and frequency of purchases. This impacts the allocation of sales staff to each customer, allowing for more effective management of sales personnel.
• Sales channel data: which sales channels are most successful and the best-selling products in each channel.
• data : Analyzing salespersons, identifying top-selling employees and products, comparing targets, and determining performance.
• Sales data : Comparing daily, monthly, yearly, or even historical data.
• Data categorization: Data can be categorized according to the organization's management style and affects data entry into the system. If the existing data doesn't meet the needs of a particular analysis, the data recording format may need to be adjusted to facilitate analysis.
To illustrate this further, we have an example of data analysis for a buy-and-sell business, which can be divided into the following main areas:
1. Selling products
• What are the top 10 best-selling products, categorized by brand, category, type, etc., depending on each company's perspective? Once this information is known, the sales manager can develop strategies.
• Which products are highly profitable with high margins? Calculating gross profit by product would be very helpful.
• Which products haven't sold well in the past three months? (Eliminate seasonal products, as some may not sell year-round.)
• Which products are unprofitable or have low margins, and may even result in a loss on gross profit? Typically, buy-and-sell businesses have clearly defined purchase costs. Averaging the costs of selling and management by product is highly effective in identifying low-margin products that should be discontinued. Some managers might argue that certain products must be sold due to high competition and low margins. Management should consider developing new strategies that don't rely on price competition to ensure organizational sustainability, or exploring new products with fewer competitors to achieve higher margins.
2. Distribution Channels: Retail Stores or Shops/Sales
Typically, buy-and-sell businesses need a shop and sales team to help sell and distribute their products. These can be collectively referred to as distribution channels, as nowadays there are both online and offline channels. Most companies sell through multiple channels to make it easy for customers to purchase their products. Online channels include selling on the company's website, through marketplaces like Lazada and Shopee, via Line@, and Instagram, etc. Offline channels include selling through physical shops, catalogs, booths, and sales representatives/distributors
Data analysis typically considers distribution channels, such as:
• Which distribution channel generates the highest revenue?
• Which channel has the highest cost of goods sold?
• Which channel yields the highest profit margin?
• Profit/Revenue x 100 for each channel, comparing which channel provides the highest profit margin to focus on specific distribution channels.
3. Inventory
• How long have the products been in stock? Categorizing stock into 30-day, 60-day, 90-day, 120-day, and over 120-day periods would be very helpful, especially for businesses dealing with perishable goods. Strategies for managing stock and selling it before it expires are crucial.
• Analyzing data for stock management, such as:
– Indicating stock status: which products have more, less, or equal stock levels compared to customer orders, or sales projections
. – Identifying which products have been in stock for extended periods, categorized by 30-day, 60-day, 90-day, 120-day, and over 120-day periods.
Data management and analysis are crucial in today's world. If businesses have ready-to-use dashboards that can analyze sales, customer, and product data in detail, as well as profit and loss and inventory levels, it can help reduce the risk of overstocking, unsold goods, and poor decision-making
For SMEs lacking expertise in data management or analysis, they may consider using the services of R&D BI companies that are members of the Chamber of Commerce. These companies can provide consulting and implement business data dashboards (Business Analytics/Big Data Analytics), design and develop business intelligence solutions and big data analytics solutions, and management information systems for executives, etc. Furthermore, they offer a free 60-day trial of their intelligent sales reporting system and a 10% discount on all training courses for Chamber of Commerce members. (See details here)
Ref. How to Manage Data to Take Your Business to the Next Level – Smart to Know
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