1. What is the “difference” in price?
Price “discrimination” (pricediscrimination) is essentially a price difference. It usually refers to the difference between users when the provider of goods or services provides goods or services of the same grade and quality to different users. Different sales prices or charging standards are implemented between periods. If an operator sets different selling prices for the same goods or services to several buyers without justifiable reasons, this constitutes price “differentiation” behavior.
2. Classification of price “differences” on the Amazon platform. The price “differences” commonly used on the Amazon platform are generally divided into the following categories:
(1) Age (for example, 20~30 years old Stage layer is separated from customers in the “30+ age” stage layer);
(2) Region (for example, customers in California and Florida are separated from customers in other states);
( 3) Occupational (e.g. separate students from non-student customers).
Due to the transparent information of Amazon online transactions, the use of price “differentiation” methods on the platform is not to obtain the “excess profits” expected from traditional physical transactions, but to allow some customers to obtain a “feeling of special treatment” , thereby facilitating transactions. Amazon also has obvious differentiation categories for its Prime members, such as half-price Prime members specifically for students and half-price season cards for seasonal shopping. Sellers can also actively use price “differentiation” strategies. , to improve operational effects.
3. How to construct a price “difference”
First of all, you must confirm what type of price “difference” you need to construct. The confirmation method comes from the order information. Or the results of data analysis. The price “differentiation” method of regional type is the most common and common.
Summarize all the order information of the store you operate, and then grab the “state” column of the logistics information in the order. You can intuitively see the market positioning and regional positioning of your store or product.
In the downloaded order report, you can find the “State or Province” column, and then use the filter function of the Excel table to get it. The regional distribution of customers in our store.
After downloading the order report, we can start to analyze the regional distribution of customers. Taking Figure 6-5 as an example, 12% of the customers are from California, and 6% of the customers are from California. From Texas, 6% of customers are from Florida, and 6% of customers are from New York State, then a total of 30% of the customer geographical distribution can be determined. On this basis, you only need to add something like this in the 5-point description. In “If you live in California/ Texas/Florida/ New York/ Pennsylvania/ Illinois, you can get a XX% discount. Please provideus with the order number through e-mail” (If you live in XXXX states, we can get it to you xx% discount).
When customers see this information, they will send the following emails. If the number of similar emails gradually increases, it means that the price “differentiation” strategy has been successfully implemented.
Of course, you can also appropriately state the reasons for the preferential treatment, such as we have specific warehousing and distribution points in these states, or these states have transportation cooperation with our suppliers, etc. Such regional price “difference” does not matter. It will make customers from other states feel unfair, and it can also promote transactions for customers in specific areas. Note that Amazon’s 5-point agreement prohibits blatantly adding preferential information, but “price differences” are exceptions and can be done. Use it during the period when the listing is growing. After the product listing grows to a certain stage, you can change the 5-point description to other content)
In addition to dividing the customers of the entire store, you can also translate a certain CATX. CA performs price “differentiation” based on the regional distribution of customers for a specific product, and the customer proportion distribution is not the same as the first pie chart. If we are selling a certain type of sweater, and when we find that the temperature in a state with a large proportion of it is rising rapidly, we can give appropriate discounts to the customer groups in the area. The reason can be “sweaters are out of season and are on clearance sales”, thus Further improve product conversion rate.