There are two main scenarios where tracking value is essential:
The classic one for online stores. You need to record the revenue that comes through checkout in the cart on your website. Suppose a person put three items in the cart and made a purchase for 2,400 UAH — this exact amount is passed as the conversion value. Without it, the system simply doesn’t understand which order brought more money and which brought less.
When you need to evaluate the quality and profitability of other types of conversions. The most obvious example is phone calls. In most online stores, more than half of orders come via phone. If you set up value passing for the “call” goal, Shopping campaigns will start optimizing with this data in mind. From my experience, the return increases several times — the system understands which audience is worth fighting for.
There’s one more, trickier option. Imagine: sales through the cart are sluggish, but people are actively adding items. In this situation, you can first “teach” the algorithm to find those who add to cart, then gradually switch optimization to completed orders.
This is working with micro-conversions, and there’s a nuance here: if you don’t have experience ramping up ad accounts through intermediate goals — test this approach only with minimal budgets. One wrong move, and the Smart campaign automation can “go off the rails.” I’m serious — we’ve broken accounts more than once.
What is conversion value: importing margin into value
According to Google help documentation, conversion value is the revenue from selling a specific product or the profit you make from that sale.
Now an important point that often causes debate. I recommend passing margin to Google Ads, not the full product cost. But — and this is key — only when you have the entire accounting mechanism already set up. For example, you maintain a CRM, clearly understand your expense structure: cost of goods, logistics, packaging, returns. At the same time, advertising costs are usually not included in margin — it’s practically impossible to calculate at the start.
It’s a different matter if you’ve been advertising stably for several months in a row and already roughly see the ratio of expenses to revenue. Then the calculation becomes a manageable task.
But if you’re just launching, don’t know what share of margin advertising will “eat up,” or it’s technically difficult to implement passing of net profit — don’t complicate your life. Pass full revenue (that is, the product cost with all markups, without deducting expenses) and work calmly with it. This is not a mistake — it’s a working approach. Bothering with margin only makes sense when you have 1,000–2,000 stable sales per month and this number doesn’t drop due to seasonality.
The “E-commerce Purchase” goal option
Second important point. If you’re working with the “Order via cart” goal, you need to set up one of the tracking options. The first is e-commerce in Google Analytics with transaction recording. A transaction here is not just a button click or link follow. It’s a full-fledged order through the cart, where the system gets much more data: which products were bought, in what quantity, for what amount.
For Google Analytics, we set up specifically e-commerce. At the start, the basic version is enough — the enhanced one can be connected later. The main thing is to pass the revenue amount that the user left when placing an order through the cart. This is a mandatory condition.
Why is this needed in practice? Suppose, besides paid Google advertising (CPC), you have other channels working. You launch shopping ads, connected free listings in Merchant Center. Sooner or later you’ll want to understand how profitable each invested hryvnia is — both in paid advertising and in organic traffic (whether Google Shopping or classic search results). Without e-commerce, you simply won’t see this. Remember — you need it.
Purchase tag
The second tracking option is the purchase tag in Google Ads. Functionally, it partially overlaps with e-commerce, but it has its own significant advantages. Now I’ll show you in an ad account example how this works and why bother with additional setup.
Essentially, the purchase tag is an analog of the transaction from e-commerce, but “tuned” for the Google advertising system. And the key advantage here is the speed of data transfer.
Let’s compare. You’ll see more or less relevant statistics in the ad account (clicks, impressions, etc.) approximately 3 hours after the event. Transactions from Google Analytics are pulled with a delay — from half an hour to several hours. And transactions imported into Google Ads from Analytics can “load in” with a delay of up to three days (with specific attribution models — usually within a day).
The purchase tag solves this problem: data about conversions and their profitability gets into the advertising system much faster. For automatic bidding strategies, this is critically important — the quicker the algorithm gets feedback, the more accurately it optimizes campaigns.
What to do in practice? If your platform (CMS, website builder) allows you to install the purchase tag — set it up. If the technical capability is not yet available — work with transactions from e-commerce, that’s also a working option.
But as soon as you grow to 200–300 conversions per month (and ideally — from 500 and above), I recommend seriously considering moving to a platform that supports the purchase tag. Reality has changed. A year or two ago, you could calmly live on transactions — everything worked perfectly.
Today, the speed at which the system receives information about conversions and their profitability plays a decisive role in advertising campaign effectiveness. All this fuss with settings is needed for one thing — to increase the return on every hryvnia invested in advertising and get more orders for the same money.
Setting up the purchase tag
How is the purchase tag set up? There’s an important nuance here that I want to tell you about in more detail. Actually, it’s quite simple. In the ad account, click the plus sign to create a new conversion.
Select the source — “Website.”
Next in the settings, you must specify the category — “Purchase.” This is a fundamental point: the Smart Shopping system must clearly understand that it’s dealing specifically with a purchase tag, not some other goal.
For clarity, I’ll name this test conversion “Test” so as not to duplicate names of existing goals. In the value field, we select the option “Different value for each conversion” — exactly like this, because we need to create a goal similar to transactions in e-commerce, where each order brings a different amount.
I’ll tell you about the scenario with the same (fixed) value a bit later, but for now let’s continue with dynamic. The “Count every conversion” item we leave unchanged — by default everything is set correctly. Click “Create” and “Continue.”
After creating the conversion, the system will offer several installation options. If your site can pass data to Data Layer — you can fine-tune everything through Google Tag Manager. If you don’t use Tag Manager, you can send a ready technical task to a programmer directly by email. Now I’ll show you a universal option that will suit almost everyone: no Tag Manager, you don’t work with codes, but you have a developer capable of making changes to the site code.
Select the “Install the tag yourself” option. The system will offer two scripts:
Global Site Tag — installed on all pages of the site. If you’ve previously set up the Google Ads remarketing tag, this code is likely already there. If this is the first setup — take the script and insert it in an available place between <head> and </head> on every page. Without exception — put it everywhere.
The second will be the script responsible for passing purchase data. Before installation, you need to select the transaction recording method: by page load or by button click. For example, on some sites, order data is passed when the “Thank you for your order” page loads. On others — at the moment of clicking the “Place order” button. Choose the option that matches your site’s logic.
Important point: this script is placed only on that page (or on that element) where the purchase is recorded. It’s placed between <head> and </head>, immediately after the first script.
The script tells the Google Ads ad account about the fact of a “Purchase” type conversion and indicates which specific account to pass data to. But simply copying and pasting it “as is” won’t work. Here’s why:
How many calls and sales will I get by ordering contextual advertising from you?
The value parameter must be dynamically replaced depending on the specific order amount. If a user bought a product for 1,200 UAH — 1,200 is passed. If for 4,500 UAH — 4,500 is passed. A static value is useless here.
The transaction_id parameter is also highly desirable to set up. It prevents conversion duplication, and this directly affects Smart campaign operation. I’ll tell you a real case from practice: on one project, transaction_id was not set.
The system showed profitability of 400–500% with a break-even threshold of 200%. It seemed — everything was great. But when checked against real orders, it turned out we were barely reaching those same 200%. The reason — conversions were duplicated due to page loading features, and the algorithm optimized based on distorted data.
Therefore, for setting up the second script, you need a programmer who understands how to pull the required values (value, transaction_id) from the site’s data array and correctly substitute them into the code.
After installing the scripts, the purchase tag conversion setup is essentially complete. Next, you launch a shopping or search campaign and make the first test order from it. Why? Until someone visits the page with the tag, the conversion will hang in “Unverified” status. To avoid waiting for a real customer — simply place an order yourself.
After this, one conversion will be displayed in the account, and next to it — its value (the amount of your test order). Pay attention to the “Repeat rate” indicator — normally it should be around 1.0. If you see values like 1.19, 1.40, or 1.50 — this is a signal of duplication, and you need to deal with transaction_id. At this point, the setup of purchase with dynamic value is complete.
Setting up e-commerce in Google Analytics looks very similar. You also need the Global Site Tag (only for recording data in Analytics) and a similar script passing transaction information. You can find it in Google Analytics help — the structure is practically identical.
In both cases, I recommend involving a programmer, especially if you’re not familiar with Google Tag Manager. And here’s why: sometimes when updating the site or making code edits, the script passing data to Data Layer can “fall off.” Moreover, sometimes this happens not on the entire site, but only on part of the product positions — and you may notice the problem too late. When a specific developer is responsible for this task, they implement the code so that with further changes to the site, nothing breaks or gets lost.
Assigning conversion value
Now let’s break down the situation when there’s no technical possibility to pass dynamic conversion value. It doesn’t matter whether we’re talking about the purchase tag or another type of conversion — call, feedback form, one-click order. The main thing — pay attention to details. If there’s an opportunity to involve a programmer for setting up dynamic passing — better do it. But if you’re working on a platform where the purchase tag can’t be technically set up — you can temporarily get by with fixed value.
In this case, we set the same value for all conversions. And here’s a serious nuance: this value can’t be pulled out of thin air — it needs to be calculated.
What exactly do we calculate? Average check — the average price of selling one product position over the last 14–30 days (period depends on order volume). When calculating, I recommend removing minimum and maximum values from the sample so they don’t distort the picture. Suppose you have 50 orders per month. The smallest — 120 UAH, the largest — 18,000 UAH. Discard both extreme values and calculate the average from the remaining 48 orders.
Why does so much depend on the correctness of this number? Because Smart Shopping and any other automation oriented on conversion value builds its decisions specifically on it. Undervalue the value — the system will “save” and under-collect revenue, thinking that each conversion is worth little. Overvalue — the algorithm will start spending more than you actually earn, and go into the negative.
Summary: if there’s an opportunity to set up different conversion value via purchase tag — set it up. Doesn’t work out — calculate average check for 14–30 days, remove extreme values, and enter the result. Whether it’s 2 dollars, 100 zlotys, or 634.5 UAH — enter exactly what you got.
We’ve dealt with the purchase tag. But what if you’re tracking other types of conversions — calls, feedback forms, one-click orders? They also need to be assigned value, but the approach will be different.
First — choose the correct conversion category in Google Ads. The system offers several options: “Contact” (suitable for calls), “Form submission” (for callbacks and feedback forms), “Request quote,” “Outbound click,” and others. Choose the category that most accurately describes the user’s action.
For example, you want to track calls, and for the system to account for them when optimizing conversion value? Select the “Contact” category, rename the conversion to “Calls” — and proceed to the most responsible step.
Calculating conversion value
The calculation of value for calls and forms needs to be approached even more carefully than for the purchase tag. The reason is simple: not every call ends in a sale. I’ve practically never encountered 100% conversion from call to payment in practice.
How to calculate correctly? In Google Ads help there’s an excellent example (I’ll leave the link under the video: https://support.google.com/google-ads/answer/2796446). I’ll break it down with specific numbers.
Suppose your average check is 90,000 hryvnias. Margin is 45%. Of 100 contacting customers, 20 close the deal (conversion to sale — 20%). Calculate conversion value: 90,000 × 0.45 × 0.20 = 8,100 hryvnias. Notice how much lower this number is than the initial average check. If you entered 90,000 in the value instead of 8,100, the algorithm would work with completely distorted data.
Apply this same calculation principle to all intermediate conversions: add to cart, calls, feedback forms, “Buy in 1 click.” If you indicate the same value for these goals as for transactions, Smart campaign effectiveness will turn into a lottery. Imagine: you blindfold yourself and get behind the wheel. The car drives on automatic, but not on autopilot. You might get lucky — you’ll arrive without accidents. Or you might not — and the damage will be quite real, primarily monetary, and sometimes moral.
One more point. If you use goals like “Time on site,” “Number of pages viewed,” “Hovering over phone number,” or “Visiting Contacts page” — don’t add conversion value for them. These goals carry no practical meaning for advertising campaign optimization and will only clutter the data.
And the last question that is often asked: “Can I set the purchase goal value at 1 dollar if each order amount is different?” You can — if this is an averaged value and we’re talking only about transactions (orders through the cart). For all other types of conversions, the calculation is different — through margin and real closing percentage to sale. I gave the formula and example above — take it and adapt to your numbers.
How do Google Analytics and Google Ads conversion sets differ?
Moving to the second question: how do conversion sets in Google Analytics and Google Ads differ, and is it worth importing conversions from Analytics into the ad account if similar goals are already set up there?
To answer, I’ll divide all ad accounts into two large blocks. First — accounts with volume up to 200–300 conversions per month. Second — accounts where 300–400 conversions are stably accumulated and more.
Why is this division important? When about 300 conversions accumulate on a separate goal (for example, on transactions) and there’s a sufficient number of clicks, the possibility appears to connect the “Data-driven” attribution model. You can check availability in Google help. This model allows automation to work significantly more effectively than on any other attribution options.
Besides data transfer speed (which we talked about above), there’s one more fundamental difference between conversions from Analytics and from Google Ads. In Google Analytics, the “Last non-direct click” attribution model is used by default — it excludes direct visits as a conversion source and attributes it to the previous channel. In the Google Ads ad account, the “Last click” option corresponds to this model.
What does this mean in practice? If you have both types of conversions set up (transactions from Analytics and purchase tag in Google Ads) and both have the “Last click” model, the number of conversions will roughly match. But if you selected a different attribution model on the purchase tag, while transactions in Analytics are still counted by last click — the numbers will diverge. And this is normal, you just need to understand the reason for the discrepancy.
Changing the attribution model can very noticeably affect Smart Shopping operation. Depends on product specifics, purchase cycle length, and other factors. But from my practice — it’s specifically on the purchase tag that changing attribution gives the most tangible result. When you manage to ramp up the purchase tag to the “Data-driven” model, it’s like updating the firmware on a Tesla to the latest version — the system starts working on a completely different level, without delays and lags.
Do you need to duplicate conversions?
If attribution models are the same — no, you don’t. Track transactions in Google Analytics for general analytics, and for advertising campaign optimization, focus on the purchase tag. If attribution models differ — you can try parallel tracking, but be careful.
The fact is that when duplicating conversions, Smart Shopping will start perceiving one sale as two. The system will decide that it brought twice as many orders, and will start overestimating profitability indicators. You’ll see beautiful numbers in reports, but in reality the results will be twice as modest. For example, the account will show ROAS of 600%, but in fact barely reaching 300%.
Getting out of duplication is a separate headache. When you remove the extra conversion, the data volume for the system is effectively halved. Smart goes into a lengthy relearning period, and restoring results will be harder than if you had immediately started working with one type of conversion and methodically ramped it up.
My advice is simple: decide in advance what you’ll work with — transactions from Analytics or the purchase tag in Google Ads. Choose one type of conversion and record only it. Don’t duplicate.
This concludes the breakdown. I hope conversion value has become clearer — what it is, how to correctly calculate and assign it. And with the types of conversions that need to be recorded for optimization, we’ve also figured out.
