From the initial display to the final purchase, the product needs to go through three traffic filters, that is, three traffic conversion processes. Traffic consumption occurs in each conversion link. This also indirectly reminds us that if the initial display is not enough and the traffic is not large enough, the few traffic will be filtered through three filters, and the number of purchases converted in the end will be very small. This is also the reason why some products with low natural rankings or unwilling to invest in advertising have basically no orders.
The first conversion “search one click” is a concept of effective click-through rate, that is, the proportional relationship between the number of product displays and the number of times the product is clicked. We call it the effective click-through rate (CTR). The number of displays is the number of times the product is displayed to the user. This index does not take into account the click-through rate. It is a machine display and cannot ensure that buyers will definitely see it. For example, two products appear on the first page of a keyword search at the same time. Their display numbers based on this keyword are the same. If one product ranks first on the homepage and the other ranks last on the homepage, then their effective click-through rates must be very different.
The first conversion consumes the most traffic among the three conversions. For this first conversion, we need to focus on optimizing two parts: the first part is the main picture, price, title, number of reviews and star rating of the seller’s product. These factors ultimately determine whether consumers click directly into the product details page to learn more or close the page after taking a look; the second part is the ranking of the product. If the product is on the second/third page and the number of displays is very small, it is extremely difficult to convert it into sales; even if the product is on the homepage, it is not ranked in the top three or top five, and the clicks it can get are extremely limited.
For the last two conversions, “click to add to cart” and “add to cart to purchase”, people usually think that the conversion rate can be calculated directly according to the ratio of “click” and “purchase”, which is too hasty.
Based on consumer habits, sellers should not change any product details at will. Some consumers are likely to look at the product details page again when purchasing after adding the product to the shopping cart. If the product details page changes at this time, it will greatly affect the conversion rate of the “add to cart to purchase” link.
In addition, according to the above theory, when consumers click on the product details page through advertisements, they may not buy the product even if they are interested in it. Instead, they choose to add the product to the shopping cart first and then buy it on another day. Then the advertising data for that day will only show clicks but no purchases. Sellers will think that the performance is very poor, but this is actually an illusion. For example, Amazon sellers all know that before the big holiday promotions, the advertising data is very ugly. The reason is simple. Consumers are adding to carts but not buying, waiting for the big promotion to reduce the price before buying. Advertising monitoring and observation in terms of time period is also very important for sellers. Don’t judge the effectiveness of advertising easily.