So cool stuff. Then this one I'm using, I'm using Edgemesh for this is going from best to worst, but our traffic isn't going from best to worst. It's actually going from worst to best. Ah, ha. We have a mismatch, and it's gonna be based off this edge mesh, and you guys will watch, it'll be really fun. We're gonna make a live update with Edge Mesh. There we are. So check this out. Campaign id. All right. Lemme get all this. One UTM, source. Lending page, new user, returning user, returning purchaser, should be good for now. So this is the last 30 days of data. And what we're going to do is use the same last 30 days of data. We're going to do the products. Cool. So we're going to grab that campaign ID. We're going to filter by this campaign ID. So this is my standard shopping campaign from Google, and this is going to be sorting descending by unique users. And what we're going to see here is we have a satin heatless curling set and in our standard shopping campaign with our products starting descending, we have the satin heatless curling set. So we should see satin, biotin, shampoo bar, and strength. The heatless, biotin, shampoo bar, and strength. good. Now watch this. Here's what our low t ROAS strategy is not doing properly. You're going to notice a few things. This is reversed in the four top products. So this is. First four are unique users going down. However, our conversion rate is at an angle that is going this way. It's actually heading up this way. If you look at this kind of bar, the completed checkout rate is also going up. The initiate checkout is also going up here. The engagement is also going up here. So what this should be doing is showing the reverse. I should be seeing more users down here and less as I go up, because this is going from best to worst. But our traffic isn't going from best to worst. It's actually going from worst to best. we have a mismatch between what we have as clicks versus. Point one to 0. 41 to 0. 49 0. 93 and conversion rate. Now, are these numbers, right? Two thirds of all of our sales happen in Amazon, the trends are at an engagement is correct. Active cart user rate is high, but they check out the least. Okay, so is this still working well? Yes, this is a flagship product. And yes, they buy this on Amazon most often. So this is okay because this is literally what started their company. They mentioned it up here. this is where we're actually starting to see a loss. So we need to have a high number of users Are we looking at pages? What are these rows? These are products in the Standard Shopping Campaign engagement on the site. so what I did is I filtered this actually by landing page and then used the filter of the Standard Shopping Campaign ID, which is the 2824, that we're spending 150K on in this last 30 days. it's like saying, If we're seeing more engagement here in the first four, but we should be spending more water on like rice water and then nourishing shampoo bar, Now this is on a 30 day increment. So what we're seeing is this 30 day increments matching what are 30 day increment is in google. if you have a seven day sales cycle, you don't get this in the last seven days until they start to purchase. However, We do get an edge match 70s earlier because this is a 15 minute interval. It doesn't have the data driven split attribution between brand and blah, blah, blah, blah, blah, blah that we normally see. This is all single click results off of unique users who are first time users, not returning users and not returning customers. This is all cold traffic. That's why standard shopping is glorious. The first time we get a return user is down here. And what's nice is that same product, the Satin Helix Curling Sunset Tie Dye, which is the Satin Helix Curling Sunset Tie Dye, when they come back, you can see their engagement is amazingly good. And then it converts at 1. 35, 0. 1. So when they return, much, much, much better results. So that's why remarketing this product and other channels is going to be a good idea because now you get a 71 percent initiate checkout rather than a 56. You get a 52 completed rather than a 47 and you get a conversion rate from those people that come back at a 1. 35, not a 0. 1. So it's literally 10 times better when they come back, which is true, which is why we look at product splits between cold traffic and remarketing. Cause when they come back with a 10 times the engagement and conversion rate, why not spend one 10th or one 20th or sorry, one 10th or two 10ths of your budget remarketing them. We can see that when they come back on their own accord, they convert well. So that's what I'm using edge mesh, which is how much cold traffic, how much warm traffic, but because I could care less about the warm traffic, I just need to push cold traffic because I lose two thirds of the sales stamps on anyway. So I can't tell if they're actually going through, but the trends are correct in by saying is these are wrong metrics, but trending in the right direction, it's going to be a little bit difficult to say, no, the 0. 1 and the 0. 9 convert, the same on Amazon. I would beg to differ. These people are engaging with the site way more often than they are, on this product than they are in this product. Is that the same correlation on Amazon? Is it the same correlation on meta? Is it the same correlation with overall product sales to your business, depending upon the overall traffic to those pages? What is the product media efficiency ratios? So cool stuff. I'm using edge mesh for