How does server-side tracking improve data accuracy?

Marketing data accuracy is one of the main components of effective analytics and marketing strategies. Errors in the collected data can lead to incorrect conclusions and ineffective decisions. Since traditional tracking usually depends on the user's browser, it can be subject to restrictions such as ad blockers or changes in privacy policies.

What is data accuracy?

Data accuracy refers to the degree to which data is correct, precise, and error-free. It measures the closeness of a piece of data to its true value. In the realm of data quality, data accuracy is paramount as it ensures that the information you rely on is a true reflection of reality. Accurate data forms the bedrock of reliable analytics, enabling businesses to make informed decisions and devise effective strategies. When data accuracy is high, the insights drawn from it are trustworthy, leading to better outcomes and more confident decision-making.

Data accuracy example

Marketing campaign and conversion tracking

Situation

A company that sells electronics through an online store is conducting an extensive advertising campaign through Google Ads. They use Google Analytics to track traffic to the site and Google Tag Manager to set up events such as clicking the buy button and completing a purchase.

Problem

Some users cannot be tracked correctly through Google Analytics due to the use of ad blockers. Ad blockers not only prohibit the download of advertising elements but can also block scripts that collect data about the user's interaction with the site. This means some users who purchased it will not be included in the report.

Impact on data accuracy

As a result, the system can show that 1000 users visited the site, and 50 made a purchase, giving a conversion rate of 5%. However, due to the blocking of certain users, the actual number of visitors was 1200, and the number of purchases was 60. This means that the real conversion is 5%, but based on inaccurate data, the company may draw the wrong conclusions about the effectiveness of advertising. They may decide to increase the campaign budget, although the actual situation does not require such a step.

Solution

Switching to server tracking will help avoid the influence of ad blockers since data is collected directly on the server and not through the user's browser. It also allows you to process data without browser privacy policies' restrictions, giving a more accurate idea of visitors and their interaction with the site.

How to measure data accuracy?

Data accuracy measurement can be done using different methods, depending on the specific task. Here are some essential approaches:

1. Synchronization with other sources. Compare data from multiple sources, such as analytics systems and internal databases. For example, check the number of purchases made on the site, in Google Analytics, and in the CRM system.
2. Check with real transactions to see if the number of sales or other important events in tracking systems matches the actual transactions.
3. Analysis of missing or unreliable data. If tracking does not consider all events or gives false values, you can identify these shortcomings by checking the reports on the collected data.
4. Comparison with control groups. If you are doing A/B testing, check to see if the test results match the real changes and are not the result of tracking errors.

How to improve data accuracy with server-side tracking?

Server-side tracking collects and processes data not on the client side (browser or mobile device) but on the server. This avoids some of the drawbacks of traditional client tracking.

Here's how server tracking can improve data accuracy:

• Bypasses the influence of ad blockers. One of the main disadvantages of client tracking is ad blockers, which may not allow you to track events correctly. Since server tracking runs on a server, it is independent of browser extensions such as AdBlock, which provides more accurate data about visits and interactions with content.
• Reduces the impact of browser mechanism reliability. Traditional tracking may be limited to browser privacy policies such as Intelligent Tracking Prevention (ITP) in Safari. These restrictions can lead to data loss or false monitoring of users. In server tracking, these restrictions do not affect data collection.
• Validates data before sending it. You can add additional layers of filtering and data processing on the server, which allows you to clear data of errors even before they get into analytics systems. For example, this makes it possible to modify or enrich information about users before transferring to the analytics platform, increasing the results' accuracy.
• Collects data from several platforms. Server tracking allows you to directly integrate data from different sources on the server, creating a more complete picture of user behavior. For example, you can combine data from other advertising platforms (Google Ads, Facebook, TikTok) in one place.

Conclusion

Server tracking is a tool for improving data accuracy. It fixes many problems that arise from ad blockers, browser policies, or errors in client tracking. Since server tracking allows you to process data on the server, you get more accurate and reliable results. This is essential for effective marketing campaigns, process optimization, and informed decisions. Data accuracy is becoming critical for businesses looking to improve the effectiveness of their advertising and analytics strategies. With platforms like Stape, improving data accuracy becomes much easier and more accessible to a wide range of users.