The number one role of on-site advertising is to drive sales. We can make an analysis of long-term advertising ideas based on the growth attributes of the product itself and the strength of the supply chain.
We first divide listings into three stages: new listing stage, growth stage, and stable stage.
In the new-on-shelf stage, ads can bring a lot of exposure to drive sales and significantly improve rankings; in the growth stage, ads can help analyze the product’s matching keywords and market positioning; in the stable stage, ads can Boost sales.
Because this section talks about the long-term operation ideas of on-site advertising, it needs to take the overall cost and overall revenue as the reference objects. The decisions that can be made under limited costs are as follows.
1. When ACOS is low to a certain limit, the website will be opened for a long time.
The pure numerical calculation is very simple, that is, whether the advertising expenditure plus the cost of the product (including logistics costs, production costs, etc.) is lower than the selling price. If it is lower than the selling price, advertising should be opened for a long time, but this The calculation of pure numerical cost ignores several elements:
(1) The fluctuation of the review generated by the advertising order to the overall review.
This element involves the proportion of reviews generated by listing orders. For example, the proportion of review products is 1% and the existing review score is 3.7. The average daily sales volume of natural ranking is 100, ACOS is 5% and the average daily advertising fee is 10 US dollars, the unit price of the product is assumed to be 10 US dollars. Then the daily order amount brought by advertising is 200 US dollars, and the advertising order volume is 20. On average, one review is generated every 5 days, with an expected review value of 3.7, and the total daily order volume of the product is 120.
Assume that the gross profit margin of the product is 8%, then the gross profit margin of the advertising order after excluding advertising costs is 3%, that is, the profit of natural traffic in a single day is 100×10×008=80 US dollars, and the natural volume of advertising in a single day The profit amount is 20×10×0.03=6 US dollars, the total profit in a single day is 86 US dollars, advertising accounts for 6.9%, the expected value of reviews generated in a single day is 1.2, and the expected score is 3.7 points, of which the expected value of reviews generated by advertising orders is 0.2. Accounting for 16.7%. Considering that the listing itself may obtain high scores through abnormal methods such as direct reviews and reviews in the early stage, it can be considered that as the number of normal reviews gradually increases in the long term, the review scores of the listing itself will become lower and lower. In other words, we It increased the risk of review fluctuations by 16.7% to obtain 6.9% profit, which will become very unfavorable when advertising cannot drive product rankings (because as advertising orders gradually increase, the probability of negative reviews will also increase become larger). Therefore, even if advertising costs no longer account for the majority in pure cost calculations, the advertising budget must be controlled based on existing review scores. Otherwise, the greater the sales volume, the greater the probability of negative reviews.
(2) Whether the search field occupied by the advertisement itself conflicts with the existing search field.
Search for “braided wedge sandals” and you will get the following interface. The seller has advertised this sandal. This is a popular sandal. Its advertising order is 1st, and the natural search order is 1st. It is the 4th one in the 2nd row, but if you look closely, you will find several operational errors.
The price of the products exposed through advertisements is actually $14 higher than the products exposed through natural exposure. Especially in a page with a large number of repetitive products, price is a very important factor, but the operator obviously did not operate it well. .
At the same time, the A9 search engine naturally exposes black, and the advertisement exposes silver. We might as well take a look at what products the 6 reviews under the listing correspond to. The product name is “FISACEWomensBraided Mid High” Wedge Sandals Casual T-Strap Wedge Heel Sandal Shoes”.
We can notice that 3 of the 6 reviews are direct reviews, 1 reiew is related to black, and 2 reviews are related to gray. Then we know that under the “braided wedge sandals” keyword, black is more competitive than other colors, otherwise the A9 algorithm will not prioritize black for exposure. Therefore, the best-selling products of this listing should be black and gray, otherwise the review would not only be about black and gray; but the operation exposed silver without thinking, which not only violates the exposure logic of A9, but also violates the sales logic of the product. Finally, we can Notice that this page does not actually use ads to help product exposure, because naturally exposed listings have the following advantages:
The color conforms to the A9 search exposure logic and is a hot-selling color.
The price is the lowest price of the top product, shown as $13.99, which has a crushing advantage.
So, in the above situation, exposing the product under “braided wedge sandals” is tantamount to superfluous. At this time, even if the ACOS is reduced to less than 5%, it is not as efficient as natural exposure. Therefore, in the operation of long-term advertising, operators need to pay real-time attention to whether the advertising exposure itself conflicts with the natural exposure of the product, and each keyword combination needs to be checked one by one.
2. When the product listing is not successful (the average order quantity is successful, no advertising will be opened.
Regarding the growth of the product, unless it is some hot product, the growth of the product is cyclical. The first wave of growth is that the Amazon A9 search algorithm finds suitable search fields for listing titles/keywords. This part can be accelerated through automatic advertising. When the search field is found, its matching degree can be enhanced through manual advertising. Finally, observe whether the words “Customers who bought this item also bought” appear below the listing. If this recommendation column appears, then the product is already in a stable period, that is, it is in the slow growth period of the second wave. Will it appear in the third wave? The growth depends on the quality of competing products and the review scores of its own listing.
Take the top 10 products in the casualjackets sub-category as an example. The product title is “Women’s Slim Fit One Button Office.” “Knit Blazer Jacket, Made in USA (Small-3XL)”, related recommendation columns have appeared.
Then the product has occupied its stable ranking in the A9 search algorithm, and the review score is extremely high without appearing. In the case of low or sudden FBA shortages, the sales volume will not fluctuate greatly in a short period of time. In this case, the operations are as follows:
(1) Close the ads with higher ACOS related to the listing
(2) Start paying attention to the review scores of your own listings and the review fluctuations of your competitors’ listings.
(3) You can urge or submit reviews under appropriate circumstances (after the listing is stable. , the improvement of high-quality reviews is the first priority).
(4) Start marketing operations (YouTube celebrity, review website promotion, etc.)
3. Listing only. New advertising.
The biggest difference between this decision and point 2 above is that it will be decided based on the speed of the product’s isting growth.
Whether to continue to do on-site advertising exposure. The second point is that advertising exposure will not be allowed until the product isting no longer grows. There is a big difference in the judgment logic between the two.
In the process of product growth, sometimes “” is displayed below the listing. Customers who bought this item also bought”, and sometimes “Customers who viewed this item also viewed” will be displayed below. For example, a product with an average ranking under the small category casualjackets, the product title is “Poplover WomensLightweight Jackets with Hood Quick-Drying Outdoor” Windbreaker”, its listing interface and the fields shown below.
This shows that the Amazon A9 algorithm has not found the search field matching the product, which may be due to the lack of selling points of the product itself. For this type of product, when the advertising operation has not been effective for a period of time, and you find that the recommended column below it is not “Customers who bought this item also bought”, you can set automatic advertising at a lower price or simply turn off all advertising operations and directly Waiting for the natural traffic of Amazon’s A9 algorithm to help it match.