Recently, the topic of “how to maximize the use of ABA data to assist daily operations” on a cross-border forum has been buzzing. Yi Xiaoya opened this post in the spirit of learning, and was surprised to find that most people do not. Know what Amazon ABA is.
You must know that ABA is a necessary skill for a mature operation. The data of many keyword tools comes from ABA. It not only allows you to find the reason for the decline in advertising traffic, understand the brand repurchase rate, but also allows you to push products backwards The market share of keywords is of great help.
Today, Yi Xiaoya will systematically and comprehensively introduce the powerful functions of ABA in Amazon’s operations and how to use ABA to achieve double-effect growth of store traffic and orders.
First of all, what is ABA?
ABA, full name: Amazon Brand Analytics, is an official Amazon feature that contains valuable insights that enable brand owners to make informed strategic decisions about their product portfolios and marketing/advertising campaigns.
Its biggest advantage is that its data is the official statistics of Amazon, which has authoritative and reference significance, and is very helpful to Amazon’s operations. So how to maximize the use of this data?
At present, ABA mainly includes several categories: Amazon keyword search/commodity comparison/population statistics. We can see that the logic of the three modules is user demand data, product data and crowd data. These three modules can generally help sellers and operations determine product development ideas and directions, as well as marketing and advertising strategies.
1. Amazon Search Terms (Amazon keyword search)
Primarily used to discover which of your products are earning the most clicks and conversions on strategic search terms.Evaluate the impact of marketing campaigns by monitoring trends.
This function mainly provides two aspects of data:
The click-through rate and conversion rate of the top 3 ASINs with the percentage of clicks under the keyword search ranking keywords
So, what can we do based on these two data?
First of all, we can screen out suitable main keywords according to our own resource strength and keyword ranking. Some sellers have rich resources, money and supply chain, so we can choose high-ranking high-traffic keywords as main keywords. ; For small and medium-sized sellers, it is wise to choose keywords with relatively low rankings, which can be used as part of the operation strategy.
Secondly, according to the keywords, you can query the detailed links of the top three popular products, and see the overall share of clicks and conversions. This helps us analyze and adjust our strategies. There are generally four situations:
(1) “Click to share” is high, and “Conversion share” is low, indicating that many customers have clicked on the product, but not many people have made transactions, indicating that this keyword has a certain correlation with the ASIN, and you can increase advertising at this time. If you attack this ASIN, it is easy to get high clicks when the competitiveness is stronger than that of the ASIN.
(2) “Click to share” is low, and “Conversion share” is high , indicating that although the word has few clicks, but many transactions – it means that the keyword competition is small and the conversion rate is high. At this time, you can focus on this word.
(3) High “click share” and high “conversion share” indicate that the ASIN has a lot of clicks, and all the clicks have been purchased. The keyword is not only highly relevant to the ASIN, but also the ASIN has a strong sense of the word. At this time, there are two solutions, solution one: avoid its edge; solution two: open an ad group to test the keyword, and observe the conversion rate of the word under the condition of controlling the budget, the conversion rate is low , you can close the ad group directly.
There are two possibilities if the “click share” is low and the “conversion share” is low. First: the word is a big word, even if it is the first place, the click rate and conversion rate of the word will not be very high; second: the word ranks low, indicating that the word is less competitive and has a low conversion rate , do not consider playing.
Second, product comparison (commodity comparison)
Commodity comparison can also be called product comparison. In this module, we can find the product information of the top 5 competing products viewed by buyers during the same period, and the number and percentage of buyers viewing the 5 competing products. For example: Product A is a hot-selling item in the store. The “commodity comparison” report can get 5 competing products related to A, and see the specific information of the competing products and the proportion of the number of times the buyer browses.
This function is more practical, and it is very helpful for sellers to do defensive operations.
For example, if the ASIN that appears here is not your own product, you need to analyze why the store’s order is taken away, and at the same time, conduct a comprehensive analysis of the competing products: whether the price has an advantage, the main picture, whether A+ has no competitive products. , whether the homepage review content is attractive enough, and then optimize it, put your ASIN under these ASINs, and grab traffic orders.
3. Demographics (crowd statistics)
This function will calculate the proportion of orders based on dimensions such as age, family income, education level, gender, etc., and sellers will have a good use of these proportions.
Help us understand the main buyers of the product, and place SD advertisements according to the characteristics of the crowd. For example, the highest proportion of your product purchases is 40-year-old men, then you can place SD advertisements under the products that 40-year-old men will buy, for example: Razors, auto repair supplies, etc. You can even run DSP ads.
2. Help us optimize our products. Sometimes we are unclear about the positioning of the main consumer groups. For example, you think that the main consumer groups of our own products are young women, but through this function, we find that most of the purchasers are middle-aged women. At this time, we You can optimize the products according to the psychological direction of middle-aged women. Maybe the features of the products you want to highlight are fashion and good-looking, then you should change to practical atmosphere at this time.
Help us to differentiate our products. Through the data, we find that the people who buy are obviously inclined to a certain group, such as women aged 18-24, then you can design a product according to other groups, such as 25-34 or 35-44 aged female. Different age groups and different household income levels have different needs of consumers.
The above is the key role that ABA data can bring to sellers in daily operations. As of now, Amazon ABA is constantly updating more functions, and sellers should take the initiative to explore new usages.