First, I have to tell you how you downloaded this data report, because for example, this report was downloaded directly. Normally, the data report should be downloaded once every 7 days, so you can compile the total monthly data. For example, data from number 1 to 7, you have to download it on the 8th, because Amazon has an advertisement and an attribution period for SP ads. Everyone knows that for the last 7 days, it's 7 days of data, right?Your click was ordered today, then 7 days later, that person bought it. If this person bought it within 7 days, they all counted the deal, so this has a 7-day attribution period, so we can see that we read this report for 30 days, the last 30 days. But you'll notice something very strange here. It shows 7-day sales and 7-day total orders for one reason, and then we can take a look at this one, and this picture is particularly obvious. Amazon reports a range of his attribution period for the last 7 days. For example, I'm under September 3. The order data for the last 7 days should be in the range from August 28 to September 3, so we need to understand this question before we can talk about how to read this data report, so we generally recommend once a week for our data report, so we can split the month into 4 weeks. After four weeks, you add this data report together and then accumulate the data.

OK, let's just start by directly talking about what I think of this data report, because it's not cumulative, so I just ordered a report. Watch first. For example, we don't need to look at the start time or end date of the ad set. This is something we need to read. Since we have many advertising campaigns for one product, we need to use the ad mix to see them together. We look at ads not only at a certain advertising campaign, but at the whole, but at all the advertising activities under this product. Because products do, and many stores have more than one product, there will be many combinations, so this is the best way to differentiate an advertising campaign. That is, the ad mix needs to be kept here first, then the campaign name and currency are not needed, and the ad group name is not needed, and then the retailer in the US doesn't need it. They can run it without care, and then match the type, right?You can leave these out of the question.

Here's the point. We need search terms, because in the end, we read this report just to see what words we want, or what words we can use to type alone, or what, right?Then we can do the amount of impressions here, and then we don't need the amount of clicks, and then we don't need the cost per click, we don't need the cost, the 7-day total sales, we don't need ACOS, we don't need the total number of orders for 7 days, total sales, we don't need the number of orders, and then delete all of them later, so we don't need it. Then you'll find right, right?All of a sudden, we have so many fewer things; these are the only useful things we have, right?

Why don't we need ACOS and those, because at that time, after we can go through the data perspective ourselves, we can see that we can give him another formula separately. Based on this kind of data, we can still calculate an approximate calculation, and we can still calculate ACOS. Because there's another reason for this, it's because we're advertising, right?Some of our automated ads have manual ads. For example, if you're running automated ads with ABC keywords, you're also running, so they're probably running in manual ads too, right?We may be very confused when the data report comes down. It may be that the order is placed here, and we can usually do a data split and data perspective together, so we can better understand where our advertising is spent, and then which keywords can bring us good conversions. We have to maintain this kind of phrase carefully.

Then we can just click on the filter button. Select all the points to filter. After clicking on the filter, the ad group will drop down. We can choose any product; here we can just select any product. Good. For example, let's choose a random selection, then an ad set. I select it first. Remember this is an ad set. I only read all the data under this product, then I just copy all of this, add a supplementary table here, and then we just paste it as a numerical value here. Once pasted, it all comes out. Then is the first ad mix name still needed?You don't need it, just delete it. We know which one of these products is fine, for example, your search term, right?Now it has hits, costs, and data, so what are we doing here?Actually, we also need to do a data perspective here. For example, after selecting this one, we can click on an insert, then click on the pivot table, then go to a new subpage, then we click on all of these here, and then it accumulates data here. For example, the first keyword may be automatically included manually, or in a wide range of manual formats, right?It's everywhere, then it accumulates data and puts it all here. The pivot table is like this, then just copy one more, then create a new one, then change it to a numerical value, then pull it over, then it's here, and the summation phase is out, right?The sum is calculated, the number of clicks, how much money it costs, and then the total number of orders and total sales are all calculated. This is all the data.

But keep in mind that this is also from the last 7 days, so I said you need to do it again in 7 days, and then accumulate all 4 7 days, which is equivalent to the last month. Because of the number of hits from the previous 7 days and the number of orders in the last 7 days, there is actually a slight mismatch between these 2 data, but you can also take a rough look. Let me first demonstrate to you, for example, can I lose to ACOS here, right?At that time, did I know how to use algorithms?Converted, right?It's nothing more than whether you want this keyword or not; I'm just these few numbers. What does conversion equal?What does ACOS stand for?It's the same as spending divided by sales, spending divided by sales, right?Then the conversion is equal to the order divided by the number of clicks, then we just exchange these two for a percentage, then we just drop down and double click. In this way, we can see that the current data is out. After it comes out, we can do a descending order here, we can click to filter, then perform a descending order with one click. The descending order is over, and then we delete it, so we can take out this data report. Doesn't this seem much better?

The dense ones will be much better than the data report we first came up with, so how do we do it here?Very simple. The customer search terms here are actually just these two. Some of them were decided by a friend, or if they need to be removed; we can just look at F4 first, right?Just look at F4. Nothing, nothing at all, these are words like no orders haven't been converted, right?So you can do it 10 times 8 times if you don't have to pay for that much of your budget, right?If you look at your conversion rate over 10 times, right?If you want to convert within 5%, you can consider 5 or more times. You can consider omitting these, but it's generally recommended to check the relevance of these keywords. If the correlation is really bad or relevant, but you can directly delete it. If you click it a few times, you can actually give him a chance to not use it first, or not finish it all, because you still need to run the data. Some of the bids that were implemented are a bit wrong, so it's not easy to place an order. Therefore, there is no need to deny it. We will choose whether to reject the ASIN more than 10 times. This directly accurately denies the ASIN. The beginning of b0 is the ASIN, and the ASIN can also simply reject the ASIN.

Then, in fact, careful friends should be able to find out, because there are also many keywords in it, and there is one thing called what is the root of the word, right?These keywords are probably cumulative below like the ones below, right?1,1,1. It's all point 1. 1 connection doesn't seem to cost much, doesn't it matter?But it's possible that there are keywords that come up based on which root word. This keyword takes up most of our budget. In this case, we need to do a data analysis. Further data analysis is needed, or you can use software like AI. You can split it up, that is, which of these root words cost a lot of money, and then when these root words are denied, we have to choose the phrase negative, right?
Negative is a good phrase to use, right?If it's a certain word, let's say we say heels, right?Should I have heels, right?I just put heels in; the direct negative phrase would be all no. As long as this heel is included, it won't appear. Of course, I wouldn't reject this term, because it's a big word for this product, and I definitely wouldn't say no to it. Let me just say that I haven't screened the following data; everyone can go to their own reports to screen them, and then negate a phrase. Because if the phrase denies a particularly large number of keywords, there is no need to talk about accurate denial. Accurate denial is particularly simple. That is, if you reject the AB word, for example, the AB keyword, that is, AB, and you remove AB. That's it.

Then even if we get our data here, then these need to be negative. Once we've done the negative, we have to see which words we need to put out and type, so we can select all of them, or not, right?Let's select all below, then select all and then do a filter, right?To convert data formats, we can click Conditional Formatting, and then there's something in between, right?How much are we at ACOS?How much is the lowest?0.01%, 0.01%, then, let's say I'm only considering within 30%, right?I'm only considering 30% or I only want to see 30% or less, and then I probably think my conversion should be greater than 5%. Then given how much 5% ~ 200%, why 200?Because some people may have ordered two orders, maybe 200 is also possible. Have you screened it out. After screening, we'll do another screening, choose a color, and then choose red. That is, all keywords containing ACOS below 30% and then a conversion rate higher than 5% are here, and there are also some fixed bids, right?You can also choose to target these ASINs. Then these keywords are probably the ones you need to focus on. You are currently converting words that are good at this stage, then you probably need to consolidate these terms, or try to look at the number of previous clicks a little more, which is equivalent to once or twice, so you don't need to read too much; there's no data.