As a marketer, understanding where your traffic comes from and how your ads perform is vital. But there’s a lot happening behind the scenes that can easily trip up even the most seasoned marketers.
Ever wondered what “gclid” and “fbclid” mean when they show up in your URLs?
These parameters are crucial in tracking ad performance and determining the success of your campaigns. Let’s break down what they are, what they do, why they matter, and how to prevent them from messing up your data.
Let’s start with the basics: “gclid” standards for Google Click Identifier. This UTM parameter is Google’s way of tracking users who click on your ads. A UTM is a snippet of text added to the end of a URL to help track the performance of a campaign. When someone clicks on an ad, this unique identifier is passed along so Google can associate a click with the given campaign, ad group, and/or keyword that brought in the user.
Similarly, “fbclid” is Meta’s Click Identifier. It is used to track user behavior post-click when someone engages with a Meta ad, and to tie that behavior to a particular ad in turn.
These two parameters — gclid and fbclid — tell you where your users are coming from and provide insights into their journey from ad to landing page, ultimately helping you understand which campaigns are driving the best results.
Unfortunately, maintaining these identifiers isn’t always straightforward. If a user is redirected on their way to your chosen landing page, a unique gclid or fbclid parameter could be dropped from their UTM. Basically, redirects can cause certain UTM parameters to drop, messing with your attribution. Stripped-down UTMs can make traffic appear organic or direct when it isn’t.
Here are some reasons your ad or campaign might redirect and lose its unique UTM parameter:
These issues are common, but they can have a significant impact on your understanding of campaign success and how to ultimately allocate your budget.
Picture this: you’re a U.S-based brand and you’ve just launched an expensive, international Google Ad campaign to drive purchases on your website. Visitors from the U.K. get redirected upon click to your U.K.-specific site, losing their unique gclid parameters. Now, these visitors show up as plain old gclid — “Google Organic” — instead of as paid traffic, making it seem like your campaign isn’t driving any results in the region despite the conversions you’re actually achieving.
The good news is that there are several strategies you can use to minimize UTM parameter issues and retain accurate data:
It’s worth investing in your data. The road to perfect attribution is bumpy, but by paying attention to common parameter pitfalls, you can best optimize your campaigns for success. With clean data about your ad performance, you can allocate budget more effectively, clearly understand what is driving conversions, and set more accurate goals for your marketing efforts.
The future may be uncertain, but one thing is not: we have more data at our fingertips than ever before, and this is only going to become more true over time. And in this data-rich environment, how we do marketing has fundamentally changed.
Sorry, Mad Men lovers: the days when marketing decisions were based entirely on intuitive assumptions or creative instincts is fading. While creativity matters more now than ever before due to the mass proliferation of AI-generated campaigns, decisions in today’s competitive marketing environment have to be backed by cold, hard data.
This is reflected by the rise of data-driven marketing. Within this strategy, Creative remains a large portion of the picture, but decisions must be driven first and foremost by data. That being said, not all data is created equally. In this blog post, we’ll delve into what data-driven marketing is, why not all data makes the cut, and the benefits of adopting a data-driven approach to your marketing strategy.
At its core, data-driven marketing is the approach of leveraging data to make marketing decisions and measure success. Sounds simple, right? But data-driven marketing goes beyond spreadsheets and platform data.
What we’re talking about is the distinction between setting a strategy and then using data to measure results, and looking at data at each step of the process. With a data-driven approach, you would:
A data-driven approach might take advantage of tools like customer segmentation, personalized campaigns, predictive analytics, A/B testing, and more.
The maxim that numbers don't lie has never been more true. When marketing strategy is based on data rather than theories, you’re more likely to set yourself and your team up for success with each and every dollar.
And rather than eliminate room for experimentation, having a data-backed strategy lets you experiment within a more controlled environment, giving you a better shot at achieving your goals.
But what happens if you base your data-driven marketing strategy on inaccurate or misleading data? This is so often the case, especially if we’re talking about platform analytics.
Nearly all platforms that sell ads have their own analytics suites that aim to let you see how your ads are performing. While these analytics suites are easy to read and access, they don’t provide the best data. They don’t create space for multi-touch attribution, and have a hard time attributing credit to other platforms or campaigns. In this way, they fail to represent the complicated nature of the buyer’s journey.
TL;DR: Platform data is interesting, but it’s not good enough to inform important decisions.
We need to ask ourselves: how hard is my data working for me versus how hard am I working for it?
Many marketers keep complicated spreadsheets of different data points, collated in one place to support their decision making. But this type of reporting, no matter how skillful, will be subject to very human error and bias issues.
This maxim also holds true: you just don’t know what you don’t know. What important data points are right outside of your scope of view? Are you looking too broadly? Should you be going deep on a campaign level?
In-depth analytics takes precious time, and granularity is crucial today in an age where marketing is ever-present on infinite platforms and in every area of a person’s life. Each touch matters, and it’s hard to account for that in a manually-updated spreadsheet.
When it comes to big data, machine learning has changed the game. Marketing intelligence platforms that use machine learning to turn billions of data points into digestible and actionable insights will help you wield data-driven marketing strategies in a way that really moves the needle and takes as much guesswork out of the equation as possible.
Embracing a data-driven marketing approach can bring numerous benefits to your organization. Here are some of the most compelling reasons to adopt this approach:
Data-driven marketing is a fundamental shift that allows today and tomorrow’s top marketers to make smarter decisions, create more effective campaigns, and achieve better results with the resources at hand. While marketers have always used data, the difference at play is akin to a paradigm shift: we have access to more data than ever before, and powerful AI tools to help us really take advantage of it to drive informed action. Marketers who don’t use this data to its fullest potential risk falling behind the competition — or just a lot of wasted spend.
By adopting sophisticated data-driven marketing platforms that leverage powerful artificial intelligence, marketers can overcome the challenges associated with data quality, availability, and reliability to make better decisions that inform better outcomes.
In a world where every click, interaction, and transaction generates data, the ability to analyze and act on this information in a seamless and immediate way will be the real differentiator that sets marketers apart.
Today’s top marketers aren’t just marketers: they’re data analysts, product insiders, customer champions, growth strategists, and more. Marketers have to hold an overview of the entire organization in their mind in order to best position their company’s products and services for success. They have to be savvy with numbers and comfortable getting down with accounting principles to make the best of their budget.
Understanding the different accounting modes — the different ways that ROI can be calculated and accounted for — makes a significant difference in how you assess the performance of your marketing campaigns.
In this guide, we’ll cover basic accounting modes and discuss the two most common ones on the Northbeam platform and beyond: Cash Snapshot and Accrual Performance.
In this context, accounting modes refer to the different ways in which conversions and revenue can be credited within an analytics platform. Northbeam uses the Cash Snapshot and Accrual Performance modes to mirror traditional accounting methods used in corporate finance: cash basis and accrual accounting.
At a high level, accounting modes can shape how you interpret key metrics like revenue, return on ad spend (ROAS), and media efficiency ratio (MER).
Cash Snapshot mode credits all revenue and conversions to the date when a given transaction actually takes place. This mode is particularly useful for measuring immediate cash flow. It helps you keep track of what is coming in on a daily basis. For example, if a customer makes a purchase on your website tomorrow, all the associated revenue would be attributed to that date.
Accrual Performance mode, on the other hand, credits revenue and conversions to the dates when relevant marketing touchpoints occur. This allows marketers to see a more accurate reflection of how different channels and campaigns contribute to conversions over time. If a customer interacted with your Meta ad yesterday, clicked on your email today, and made a purchase tomorrow, revenue would be distributed across all of these individual dates and touchpoints.
Read More: What Makes Northbeam’s Data Different?
Cash Snapshot mode is more commonly used because it aligns with the way that businesses typically track their finances — based on when cash is received. For example, if you’re reporting on MER, Cash Snapshot mode can provide a clear view of the ratio between total revenue and total spend on a daily basis. This method is straightforward and easy to understand, making it a go-to for many marketers.
However, the simplicity of Cash Snapshot mode can sometimes lead to oversimplified or misleading interpretations of marketing performance. For example, if you launch an ad campaign that leads to significant engagement but no immediate purchases, Cash Snapshot mode might make the campaign seem like a failure, even if it leads to more purchases down the line.
Accrual Performance mode offers a more nuanced understanding of how your marketing efforts are contributing to conversions. By attributing revenue to the individual dates when marketing touchpoints occur, this mode gives you a clearer picture of which channels and campaigns are truly effective and generating ROI. This can be particularly valuable for marketers focused on scaling paid media and calculating ROAS. It can also be useful for products or services with long sales cycles where individual touchpoints need to be accounted for to get the full picture.
On the other hand, Accrual Performance mode could be over-complicated for straightforward sales cycles or simple marketing strategies. If you don’t have a lot of resources, or aren’t running a lot of campaigns, you may choose to keep things as simple as possible.
Take the time to think through your options and choose the right accounting mode so you can make the best decisions for your business. If you’re in doubt, try running both and looking at how the results compare. Northbeam lets users choose their preferred accounting mode, or toggle between the two for comparison.
Choosing the right accounting mode helps you:
When in doubt, chat with an expert. Northbeam’s dedicated advisors are happy to talk you through which accounting mode is best for your unique situation.