Earnings on Marketplaces Using an IT Approach
Posted: Tue Jan 07, 2025 6:05 am
Vladimir Mamut, founder of the designer children's clothing brand Lucky Child, said that 98% of his company's revenue comes from marketplaces, but it was not always like that. The exponential growth of the Wildberries and Ozon platforms in recent years, changes in the advertising model, the rapid development of competitors and mistakes in planning advertising campaigns cost the businessman millions in revenue.
In the article, the expert shared his experience and told mexico whatsapp phone number about the holes through which sellers' money leaks out and how the owner can control the marginality on marketplaces through an IT approach.
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Plan-Actual Analysis: Where You're Going Wrong When Forecasting Demand
The first basic tool I use to analyze sales on marketplaces is the plan-fact analysis, which includes analytics of planned demand and actual sales. Here, a problem often arises: the forecast does not match sales. Why does this happen? The difficulties begin in the planned demand parameter. Much here depends on the quality of the hypotheses that you have built and based on which you made the calculation. There are three typical mistakes.
Mistake #1 . Subsorting logic. We implement weekly planning. By the beginning of the week, we received 100 items and sold them all. This means that we will order the same amount for the next week. But we did not take into account that the product ran out on the third day (4 days of sales out of 7 days were not included in the calculation) and in the next order we were again supplied with 100 items, although the demand was higher. An elementary parameter is how many days the product was in stock during the week. But many do not take it into account, and the demand data is distorted.
Mistake #2 . Demand went up because of promotions. I often fell into this trap and see this mistake in others: "We're in high demand: let's urgently order what we're in high demand." In reality, at this point the sales department is simply dumping goods through promotions, lowering the price. As a result, you order what you were selling cheaply, to the detriment of your margins.
Mistake #3 . Sales and analytics on their own. Customer orders in 1C are demand, but we “lose” demand, since we upload the supply to the marketplace to 1C based on the availability of goods. Case: the team has a sales manager and a production plan analyst or a buyer. The sales manager takes sales data from the marketplace and, based on this data, calculates how much goods need to be brought in for the next period. Then this demand is uploaded to 1C. Based on it, the supply and shipment to the marketplace are formed.
The production plan analyst or the buyer takes demand data from the system, calculates the turnover of goods and decides what to buy. If some goods are out of stock and the data on them did not go to 1C at the first step, the manager turned the primary demand into the fact of the availability of goods. Result: in 1C the data on the primary demand on the site is incorrect, the planned demand is calculated incorrectly.
Where to get money for business and how to manage finances? Experts from the educational platform for entrepreneurs "Kurs" will tell you .
In the article, the expert shared his experience and told mexico whatsapp phone number about the holes through which sellers' money leaks out and how the owner can control the marginality on marketplaces through an IT approach.
Subscribe to RB.RU in Telegram
Plan-Actual Analysis: Where You're Going Wrong When Forecasting Demand
The first basic tool I use to analyze sales on marketplaces is the plan-fact analysis, which includes analytics of planned demand and actual sales. Here, a problem often arises: the forecast does not match sales. Why does this happen? The difficulties begin in the planned demand parameter. Much here depends on the quality of the hypotheses that you have built and based on which you made the calculation. There are three typical mistakes.
Mistake #1 . Subsorting logic. We implement weekly planning. By the beginning of the week, we received 100 items and sold them all. This means that we will order the same amount for the next week. But we did not take into account that the product ran out on the third day (4 days of sales out of 7 days were not included in the calculation) and in the next order we were again supplied with 100 items, although the demand was higher. An elementary parameter is how many days the product was in stock during the week. But many do not take it into account, and the demand data is distorted.
Mistake #2 . Demand went up because of promotions. I often fell into this trap and see this mistake in others: "We're in high demand: let's urgently order what we're in high demand." In reality, at this point the sales department is simply dumping goods through promotions, lowering the price. As a result, you order what you were selling cheaply, to the detriment of your margins.
Mistake #3 . Sales and analytics on their own. Customer orders in 1C are demand, but we “lose” demand, since we upload the supply to the marketplace to 1C based on the availability of goods. Case: the team has a sales manager and a production plan analyst or a buyer. The sales manager takes sales data from the marketplace and, based on this data, calculates how much goods need to be brought in for the next period. Then this demand is uploaded to 1C. Based on it, the supply and shipment to the marketplace are formed.
The production plan analyst or the buyer takes demand data from the system, calculates the turnover of goods and decides what to buy. If some goods are out of stock and the data on them did not go to 1C at the first step, the manager turned the primary demand into the fact of the availability of goods. Result: in 1C the data on the primary demand on the site is incorrect, the planned demand is calculated incorrectly.
Where to get money for business and how to manage finances? Experts from the educational platform for entrepreneurs "Kurs" will tell you .