How sellers choose the most appropriate Amazon data analytics tool

There are so many Amazon data analysis tools, but the good and the bad are mixed, how can sellers choose the most suitable operation tool for themselves?

1. Analysis: Analysis is the most critical point in the analysis of Amazon store data, and it is recommended that it is very important for sellers to choose products with high unit prices when selecting products, and try not to do products with low unit prices, because the products do not have enough profit margins and will become particularly difficult in advertising.

2. Market capacity analysis: Secondly, it is also very important to do a good job in researching market capacity analysis, if the capacity of the entire market of a product is 600 orders per day, and your goal is to set a thousand orders per day, it is not realistic. Therefore, it is necessary to research the capacity of the market in advance.

4. Product category analysis: Amazon product category analysis is also very necessary, which is related to the fact that once Amazon product classification is misplaced, or it is not accurate enough, it will greatly reduce the sales of goods.

5. Shelf time analysis: For the analysis of shelf time, do not compare it with products that have been on the shelf for too long. Because it has already seized the market opportunity, we can't make up for the time problem and it's difficult to catch up.

6. Competitive product copywriting analysis: The quality of competing product listing copywriting will affect the conversion rate of your product, which is related to the success or failure of the final operation.

7. Product review analysis: The reason why we should do a good job in review and analysis is, on the one hand, we can know the selling point of the product from the positive evaluation; On the other hand, the key to outperforming competitors can be clearly understood from negative reviews.

8.Sales Trend Analysis: Conduct a detailed analysis of the sales trend of each store.

Scoot Seller Assistant is a very easy to use Amazon data analysis tool, which can help sellers analyze Amazon store data more intuitively. You only need to install the Scoot store data analysis plug-in on Google Chrome in the data assistant of Scoot, and log in to the background to obtain the business data and product data of the Amazon store, which is easy to operate, safe and reliable; All data is displayed in vivid and intuitive charts, sellers can intuitively browse the data and understand product details, making your store data analysis simpler and more accurate!

Amazon's data analytics tools are as follows:

2. Keepa: According to user tracking and understanding, help find suitable products.

4. AMZ Base: It can quickly help sellers search and find products suitable for sale on Amazon.

Data analysis recommends Jungle Scout, which is a must-have software for Amazon data analysis, processing 2 billion data points per day, with a data accuracy of up to 90%, and supporting 17 Amazon sites.

If you want to know more about data analysis, Jungle is the world's leading international e-commerce data analysis tool, which has developed into a business consulting SaaS tool for international e-commerce that is being used by 600,000 Amazon sellers around the world - integrating data selection, market trend research, ** chain function, keyword search and reverse check, listing optimization, automatic invitation and evaluation, and store profit analysis, providing sellers with one-stop service from product selection to operation. <>

Data analysis is based on a certain purpose, through the monitoring of data, processing of data, analysis to guide the work, solve the problem of data monetization process. The next few basic methods are based on the data of the Amazon backend or frontend, and then use excel sheets or formulas, macros, and pivot tables to automatically process data analysis.

1) Trend analysis.

Trend analysis is based on the time dimension, the traffic trend summary, in Excel you can right-click on the chart, "add trend line" to see the account of the overall performance of the site in the near future, after adding data tags, you can monitor the traffic data of specific days at a glance.

We can also conduct a trend analysis of the sales volume of an ASIN in a certain period of time to select products. For example, combined with the inventory sales estimation method and the category ranking estimation method, the date is used as the horizontal axis and the sales volume is used as the vertical axis to make a chart to obtain such a sales chart. This graph can also be combined with the daily rankings, for example, using the daily rankings as a sub-vertical axis and then combining and analyzing.

According to the progressive level of ranking, the trend of sales volume, combined with market capacity, fierce competition, patent issues, and resources at hand, then determine whether the product is suitable to go to **.

2) Comparative analysis.

Through comparative analysis, the differences between the data can be discovered, which can be compared horizontally or in depth, so as to further explore the problems. This comparison can be expressed in the time of year-on-year and month-on-month. It can also be manifested in the comparative analysis between indicators.

For example, for the year-on-year and month-on-month growth of traffic and sales in time, these two indicators can intuitively see the work effect of business personnel. If there is a large increase or decrease in these two indicators, then it is necessary to investigate what is going on.

Or, by summarizing the data of each ASIN in a certain category in a certain period of time in each store, and then pivoting the data. The row label is the product name of the ASIN.

Amazon's data analysis methods can be based on the following aspects: market competition, market capacity, product development trends, its own advantages, promotion difficulty, clearance difficulty, transportation difficulty, and sales target positioning;

In the face of so many data indicators, many sellers will manually find the data they need but it takes a lot of time and energy, but smart sellers are using Amazon data analysis tools to assist operations, and help themselves make correct decisions faster and better.

In order to solve the complex Amazon data analysis problems, Scoot Seller Assistant has developed Scoot Data Assistant, which is designed to help sellers analyze Amazon store data more intuitively and simply, and the main functions include store sales and product analysis, competition analysis, PPC advertising report and other three modules.

As the saying goes: seven points depend on product selection, three points depend on operation, what is the selection method is simple and can be popular? Let's take a look at Lao Chen's sharing.

It can help you dig out the core traffic words of Amazon's competing products, so that the competing ASINs have no secrets in front of you.

2. Assist in optimizing listings4. Save PPC costs

Quest is a multi-task data mining system developed by IBM's Almaden Research Center to provide efficient data mining building blocks for the application development of next-generation decision support systems. The system has the following characteristics: It provides the function of carrying out various mining on large databases

Association rule discovery, sequence pattern discovery.

Many of the analysis tools that we use are some that we are used to using ourselves.

Amazon's data analysis methods include keyword search result volume, review quantity, product profit margin, JS data research, keepa to see through everything, merchantwords to view search volume, Google Trends to view product annual trends and other methods, the specific analysis is as follows:

When you confirm that you are going to buy a product, please use the core keywords of the product to search on the Amazon homepage to see how many search results the product has on the Amazon homepage, and then accurately target how many sellers of the product are doing FBA.

2) Number of reviews:

When looking at the newness of a product, observe whether the number of seller reviews is about a few or dozens of dea-type rocks, if 80% of the sellers have about a dozen or dozens of reviews, then I will give priority.

3) Product profit margins:

Assuming that the search volume and sales volume of a product are not bad, what you need to do is to estimate the profit of the product and see if the profit of the product is within the acceptable range.

4) JS data research:

When conducting Jungle Scout product data research, the main thing is to look at each merchant's estimated monthly sales, review star rating, and whether it is FBA or AMZ self-operated.

5) Keepa sees through everything:

Use the keepa tool to see what the lowest price of the peer product is in history, how many spikes have been participated, the ranking of the product when it was first put on the shelves, what is the way to increase the number of reviews each month, and whether it has been out of stock.

7) Google Trends to see the product trend throughout the year:

In addition to using MerchantWords to see the search volume on the AMZ site, you need to go to Google Trends to see the annual search volume of the product in the world and the country where it was made. In addition to looking at global trends, you can also look at the top five countries in the world.