During the communication with our clients, we constantly face a particular problem. The client is aware that in the current competitive environment it would be a great advantage to establish the management of the PPC advertisement not on the basis of turnover (overall value of orders), but on the profit margin of orders. This necessity is of the utmost importance to businesses, which have great differences between the profit margins of their individual products. In most firms, the transition to this sort of management of advertisement is being slowed down by the complexity of the implementation of tracking the profit margin orders in Google Analytics. A great obstacle is also the absence of historical data. The data, in fact, start to be collected in G Analytics or Google Ads only from the point of implementation of tracking. A considerable investment needed for this effort won’t be repaid until after several months. In order to make decisions from the collected data, a middle-sized e-shop needs to collect stats for about 3-6 months. Only after that, it has enough data for it to evaluate anything on its grounds.

Why else isn’t it possible?

A lot of e-shops also have a problem with the fact that at the time of carrying out the order = at the time of clicking on “finish order”, they don’t even know what profit margin has the order generated. They know the turnover = final price of purchase, but they don’t know exactly how much money did they make. We are not talking about fixed costs and things alike diluted to a volume of one order. That is the college of financial management of profitability, which is handled by the number one e-shops in the region. We’re talking about segments, for example, pharma, where pharmacies know only approximately what profit margin they have at the time of executing the order, because it is calculated later. For example by ever-changing purchase price, or by the amount of products they have sold. It’s a classic, the more the pharmacies sell a specific brand, the better the purchase price, or the better the reverse bonus they get.

Anything is possible if you put your mind to it.

Or how we found a way to jump over any IT and process obstacles.

We have come up with a solution for you, which gets around all these complications and has several other benefits. Our solution will allow you to proceed to manage your Google ads by profit margin, without you having to apply any complex changes to your web or your information system. The only thing that we need from you is to consistently update (at least on a daily basis) the export of orders with margin and the access to Google analytics. It is good to update the export of orders daily for managing to be the most accurate. We can also apply the managing by margin using our Magic Script Algorithm to the adverts on Heureka.sk or Heureka.cz.

Basic features of the solution:

1. The algorithm will use an attribute model, which we will agree upon, for managing. In principle, we are able to use models offered by the GA Multi-channel funnels comparison tool. If necessary, some attribute models offered by Google ads for conversion: Linear, position-based, time decay, except of driven model. We can also create a custom model if there was any rational business reason for it. The benefit of our solution is the cross-channel attribution, which you can see in Google analytics. In contrast, the attribution of conversion is not cross-channeled. The attribution in Google ads distributes only between clicks from Google ads, it doesn’t take into consideration other traffic sources (channels). 
2. If the margin entry of the order in export changes, it also changes the ground of our management. It is also not a problem if our client writes entries with a delay (of course, with a reasonable one, let’s say 48 hours) to the export. Therefore, this type of management takes the cancellation of orders into account. This feature doesn’t require the client to have any margin entries right from the order creation on the web. 
3. We can evaluate our management very well. Right at the start of the management, we will give you access to the interface, in which we will be able to compare the results of the advertisement before and during our management. It is important to look at the results according to the attribute model, which we have chosen for management together. It is also important to look at margin instead of turnover, since we manage by the margin. 
4. The algorithm is usable and works well for Heureka bidding too. Since we offer cross-channel attribution, this sort of management greatly increases the accuracy of Heureka bidding. Here, in contrast to Google, we face a problem with identifying the click (which product did it specifically come from). To solve this, there are two possible scenarios:

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  • One option is to have a good system of UTM parameters in the feed of every URL. We can work specifically with utm_term and utm_campaign parameters. For example, in the parameter utm_term, there could be a number of the product
  • A more accurate solution is to have a list of sold products with their individual margin in the export of orders. Of course, the ID of products has to correspond with the ID of products in the Heureka feed.

Technical notes:

• the attribution will be using a 30-day “lookback window”
• we will need access to Google analytics
• for the management of Google ads, we will need access to Google ads, the google ads account connected with the google analytics account, auto-tagging turned on on the Google ads account
• we will need the export of orders with margin ideally for the last 365 days. If this sort of export is too big (or its regular updating is difficult), we can also do two things. We can generate the export for the last 365 days once and then maintain the current export for a period, in which cancellation of order could happen (for example last 30 days)