Attribution Modeling: How Server-Side Tracking Can Improve Accuracy

There are many ways people can find you and become customers. Think ads, your website, emails, social media, among many others. But determining which specific channel brought you the desired conversions shouldn’t feel like trying to find a needle in a haystack, right?

We get it, running multi-channel marketing campaigns isn’t easy. You pour resources into various touchpoints and have to know for good which ones perform better and are worth the effort. Ideally, you shouldn’t be scratching your head and guessing if you manage to measure campaign success accurately.

Marketing attribution modeling is like the sniffer hound that helps you pinpoint what’s really working. It shows you which of these efforts are worth your time and money. On this page, we’ll take a deeper dive into attribution modeling and how applying server-side tracking may revolutionize attribution accuracy to help your ad campaigns thrive.

What Is Attribution Modeling?

Today, we have more tools and platforms than ever to reach our target audiences, and every interaction is a chance to connect. Yet, not all our efforts are equal. Since money is at stake (especially with paid ads), understanding which ones truly drive results is twice as important if you don’t want to waste resources.

Basically, attribution modeling is a way to learn which of your marketing efforts are actually moving the needle and identify what’s making the most impact. It lets you see how much each marketing thing you do helps get you a customer. It looks at all the different places people might “touch” your brand and figures out which ones are most important for getting them to buy something or take action.

When people are thinking about buying something from you, they might see your stuff in a lot of different places. Maybe they click on an ad, read a blog post on your website, or see something on social media. These are all “touchpoints”.

Attribution modeling is like a detective who investigates the user’s steps, retracing the path of how they converted or took the action you expected. Different types of marketing attribution models are like formulas that let you assign and distribute credit across numerous touchpoints.

The thing is that some models just look at the last thing someone clicked before buying, but last-click analysis lacks the depth that would allow you to understand how much each touchpoint influenced the person’s decision to become a customer. Other models, like multi touch attribution, try to get to the bottom of the whole journey. They analyze the given touchpoints, somewhat mapping the user’s major stops on the route from their first interaction with the brand or service to the moment they click “buy”. This helps you see how all those different interactions work together to affect someone’s decision over time.

Why Is Accurate Attribution Modeling Important?

Tracking conversions or data just for the sake of it is pointless. You have to understand the why and how behind those conversions and turn raw data into actionable insights.

Attribution modeling is a way to give credit where it’s due. It helps you see which marketing things are working at each step of the process, from when someone first searches for something online to when they finally purchase it, sign up, book a demo, or take some other kind of action that you consider as a conversion.

Using these models can help you get a better idea of what’s driving people to become leads and move through your sales process. This means you can be sure about what’s resonating with your audience and how to fine-tune your strategy, reconsider your channels, refocus efforts, and allocate your budget more reasonably to where it really matters.

Types of Attribution Models

Since everyone’s path to becoming a customer is different, with lots of possible interactions along the way, there’s no single “right” way to measure how well your marketing is working. There are actually lots of different attribution models.

For starters, it’s worth noting that attribution models could be deterministic, that is, they operate on a set of predefined rules and assign credit to a single touchpoint, assuming there’s a direct cause-effect relationship between conversions and touchpoints (like if a user clicks on a Google ad and makes a purchase, this advertisement will get all the credit).

The probabilistic approach is thought of as more accurate, as customers rapidly switch between channels. It distributes credit to all touchpoints in a user’s journey based on statistical analysis according to the probability or likelihood of their conversion influence.

Attribution models could also be categorized by the number of touchpoints they consider, like single- or multi-touch. Let’s take a closer look at the commonly applied ones.

Single Touch Attribution Models

What’s the difference between single-source attribution and multi-touch attribution models? As the name says, single touch attribution is a deterministic model that only gives credit to one interaction. Usually, it’s either the very first time someone heard about you or the last thing they clicked before buying. These models are easy to apply, however, they fail to see the entire customer journey scope.

• First-touch attribution — This model says that the very first thing someone sees or clicks on is the most important. It gives all the credit to that initial interaction with the brand.
• Last-touch attribution — Sometimes called the qualified lead model, it is the opposite of the first touch. It says that the last thing someone clicks on before buying is the only thing that matters, so that gets all the credit.
• Attributing other points — Other touchpoints could also be given credit, such as the last non-direct click, the last paid click, or the last “most important touch” model that emphasizes a specific channel or platform.

Multi Touch Attribution Models

What is multi touch attribution? Multi channel attribution modeling is a probabilistic method that looks at everything a customer did before they converted. This data driven attribution model figures out which ads, emails, or social media posts had the biggest impact and how they all worked together. It then allocates a portion of the credit to each interaction.

• Linear attribution — This is a simple one! Linear attribution gives equal credit to every single interaction a customer has along the way. So, if they click on five different things before buying, each one gets an even 20% of the credit.
• Time-decay attribution — This model gives credit to all the interactions, but it gives more credit to the ones that happened closer to the time the conversion took place. As such, four touchpoints could be split 5%, 10%, 35%, and 50%. The closer they got to buying, the more important those interactions.
• U-shaped attribution — Also called position-based, this model says that the first and last interactions are the most important. It splits most of the credit between those two.
• W-shaped attribution models — This model gives the most credit to three things: the first interaction, the last interaction, and one interaction somewhere in the middle of the process. Then, any other interactions get a smaller piece of the credit.
• Data-driven attribution — Also referred to as Z-shaped, it credits all touchpoints, falling back on analyzed data from multiple channels to determine the weight and impact of each.

The Role of Server-Side Tracking in Attribution Modeling

Nonetheless, there are a few obstacles to marketing attribution models. For instance, it may be difficult to fully capture customer journeys due to new privacy measures and stricter regulations. Plus, other tracking limitations can make collecting meaningful and reliable data tough. And if you count only on assumptions, this can lead to misguided conclusions. But there’s a way to solve that.

Campaign attribution can be tracked through either client-side or server-side methods. Let’s take a closer look at both options.

How S2S Tracking Is Different from Traditional Client-Side Tracking

Client-side tracking methods are widely used due to their simplicity. They monitor user activity, are often pixel-based, and rely on data collected from the person’s web browser. However, this approach often falls short, leaving you with inaccurate or incomplete data. Here are several reasons why:

1. Browsers are getting smarter about privacy. They’re making it harder for these little bits of code to track people for very long. This means you might not get a complete picture of what’s going on.
2. Browser extensions and ad blockers can stop these tracking codes and block client-side tracking entirely. If someone uses this kind of solution, it can prevent the tracking code from working at all, so you lose that data.
3. Traditional client-side tracking codes can sometimes grab sensitive information, like where someone is located or what kind of device they’re using, without you even knowing it. This can create legal problems with data privacy laws if you violate regulations such as CCPA, GDPR, and others.
4. Cookies collected by client-side tracking methods have a short lifespan, with the expiration time often being around one week. If you need a more permanent view of data to compare and analyze it, then this is not the way out.
5. Topping all of that, client-side tracking can even slow down website performance. This can potentially frustrate users and have a negative impact on their experience.

Server-side tracking (SST) is a different way of collecting information, a more precise approach that doesn’t let any data fragments slip away. Instead of relying on things that run inside someone’s web browser, it gets the data directly from the server, centralizing data collection and remaining privacy-conscious.

For example, when someone visits your site, they do things like look at pages, click on buttons, or buy stuff. These actions are called “events”. With server-side attribution marketing tracking, these events are recorded directly on your server. The data is gathered from different places, like your server’s logs, special connections called APIs, and your databases. Then, it’s sent off to the tools you use to analyze your website’s performance.

S2S gets data in real-time, without delays, and from multiple domains and devices. It’s a more technically complex method that requires tools like RedTrack, yet it can visibly change the data collection and analysis game.

How Server-Side Tracking Can Benefit Marketing Attribution

Why is server-side tracking better? Well, it lets you see through the noise of marketing data. Below are the reasons why server-side tracking is more reliable and accurate than client-side methods:

• More Accurate Data: Because it doesn’t rely on things running in the browser, server-side tracking can get more complete and accurate data.
• Ad Blocker Bypassing: It’s not affected by ad blockers or browser privacy settings, so S2S lets you track people who use such software. You thus bypass adblock detection and make the tracking codes invisible to ad blockers.
• Makes Cookies Last Longer: Almost all web browsers have ways to limit how long cookies can track people on various pages, including your own website. When someone clicks on an ad, special codes called “click IDs” keep track of where the click came from. If the cookies disappear too quickly, you can’t connect the sale back to the original ad. S2S changes that expiration date.
• More Privacy and Control: You get to decide exactly what data is collected and shared, which makes it easier to follow privacy rules.
• Faster Websites: By using less JavaScript code on the website itself, the pages can load faster, which makes for a smoother experience for your visitors.
• Improved Personalization: With more accurate data, you can do a better job of showing people the right content and ads, which can lead to more sales.

How to Improve Marketing Attribution Accuracy with Server-Side Tracking in 6 Steps

If you want to get started with server-side tracking for your paid ad campaigns, here’s what you need to do.

1. Select the Right Tracking Tool

There are lots of different server-side tracking tools out there. When choosing between them, think about these things:

• Is the company trustworthy? Do some research and see what other people say about them.
• How much does it cost? Make sure it fits your budget.
• Can you get help if you need it? Good customer support is important.
• What can it actually do? Does it have the features you need?
• Can it grow with you? As your business gets bigger, will the tool still work well?

2. Check How the Tool Handles Your Data

Make sure the tool you choose follows all the rules and regulations on data privacy. You want to be certain that your customers’ information is safe. Plus, find out about data ownership.

3. Set a Budget

Decide how much you’re willing to spend on tracking. Some tools offer a free trial or have a free plan available that you can use. RedTrack pricing options, for example, let you try out the tool for free for a limited time to see if you like it. You don’t need to be a tech expert to get started, it only takes a few minutes to set up, and guidance is also available.

4. Plan What You Want to Track and Be Consistent

Think about all the different places people might see your ads or interact with your business. Which channels do you want to track (like Google Ads, Facebook, etc.)? What actions do you want to record (like clicks, views, or purchases)?

Make sure you’re tracking things the same way across all your different channels. If you’re not consistent, your data will be messy and hard to understand.

5. Put All Your Data in One Place and Visualize It

Connect all your tracking tools to a single analytics platform. This will give you a complete picture of how people are interacting with your business.

Turn your data into charts and graphs that are easy to understand. Looking at raw numbers can be overwhelming. Visualizations can help you spot trends, see which channels are working best, and identify problems quickly. For instance, tools like RedTrack have intuitive reports and dashboards available to automate your data analysis.

6. Keep an Eye on Things

Use your tracking tool to monitor your campaigns. If something isn’t working, don’t be afraid to make adjustments or change your strategy when needed. As such, RedTrack makes it simple to monitor your campaign’s progress and make tweaks to reach your goals more effectively.

5 Best Practices for Implementing Server-Side Tracking

Here’s how to ensure your server-side tracking is set up the right way:

1. Match your data — Make sure the way you’re organizing your data on the server matches what your analytics tools expect. You might need to change things around a bit before sending the data.
2. Use server-side tagging — If you’re using something like Google Tag Manager, use its server-side features to manage your tracking code, it’s more efficient.
3. Create your own data — Server-side tracking lets you create custom data points that give you more specific insights into how people are using your website.
4. Keep things consistent — If you’re still using some regular tracking, make sure it’s in-tune with your server-side tracking. This is especially important when you’re switching over.
5. Use real-time data — Many analytics tools like RedTrack allow for tracking insights faster and in real time, so you see data right as it’s happening. Set up your server-side tracking to take advantage of this.

Concluding Thoughts on Attribution Tracking

If you’re serious about maximizing the performance of your paid ad campaigns, server-side attribution tracking is a big deal. It helps you get around ad blockers and other obstacles, giving you a clear picture of what’s really going on and what impact your campaign has.

The bottom line is that server-side tracking lets you gather a wealth of meaningful data, revealing insights regular tracking typically misses. It gives you more control over your data and ensures you follow all the privacy rules. This means you can improve your campaigns, better understand your customers, and get enhanced results for your business.

If you need ad tracking software to take your paid ad campaign tracking to new heights, RedTrack might be just what you need. It’s easy to get started thanks to the tool’s wide range of integrations. Once it’s linked up, the tool does lots of heavy lifting. It offers numerous advanced automation features that handle real-time monitoring across multiple channels, along with complex data collection and processing. It delivers accurate and actionable insights that close reporting gaps, let you optimize campaigns, fine-tune your ad spend, and boost campaign efficiency. If you have questions or need a hand getting started, feel free to reach out to us or book a demo to see how it works!