Understanding the return on marketing investments is more critical than ever. We’ve exited a reasonably long stretch of economic stability, and business leaders are adjusting accordingly by asking more detailed questions of marketing—particularly around digital ad spend.
According to a January 2021 Forbes article, several large companies made drastic cuts to their digital marketing budgets without experiencing a decline in sales:
- P&G cut $200 million in digital marketing
- Chase reduced website ad coverage by 99%
- Uber eliminated $120 million of digital marketing
If you Google “return on ad spend,” you’ll get a lot of unhelpful advice about how simple it is to calculate. Their equation will look something like this:
That calculation works if your customer is buying a pair of socks or a book. If your product costs enough to warrant a purchasing committee, the odds that someone sees one advertisement and immediately wants to sign a contract are extremely low. Field marketers, email marketers, content marketers, and salespeople will be unhappy with that simple equation because they (justifiably) want their efforts to count, too.
These examples highlight the importance of accurately measuring and understanding Return on Ad Spend (ROAS). However, calculating ROAS in the B2B world is far more complex than the simplistic formulas often found online.
The Complexity of B2B ROAS
Unlike B2C transactions, where a single ad might lead directly to a purchase, B2B sales cycles are longer and involve multiple touchpoints. A purchasing committee rarely decides based on a single advertisement.
Let’s dig into common reasons marketers stumble when calculating return on ad spend (ROAS) and how to overcome them.
1. Mismatched Reports
As a marketer, we want data captured in our marketing automation platform. This means, at the very least, actions get associated with an identifiable human in our database. Unfortunately, there are a lot of reasons this may not play out as we hoped:
- Disabled cookies
- Browser setting blocking Google Analytics
- Lack of UTM tracking
- Lack of call tracking
- Lack of pixel tracking
These issues can result in anonymous web traffic or misattributed lead sources. While some marketers resort to “directionally accurate” reporting, this approach often fails to satisfy executives when significant budgets are at stake.
Solution:
Implement robust tracking mechanisms, including UTM parameters, call tracking, and pixel tracking. Familiarize yourself with the metrics of your analytics platforms to explain any discrepancies confidently.
In other words, do everything possible to track conversions!
Check out this article on MediaPost and searchengineland.com as starting points.
2. Form Fill Attribution
While Google effectively tracks initial entry points, it struggles to maintain visibility as users navigate your website. This can lead to unclear attribution for form fills and demo requests.
Solution:
Implement comprehensive UTM tracking across your digital properties. Establish clear guidelines for your team and consider the following best practices:
- Define consistent sources and mediums
- Include ad IDs in campaign names for more accurate reporting
- Be mindful of case sensitivity in Google Analytics segments
- Avoid using internal UTM codes between pages on your site
Check out this article from SpyFu for more best practices. Although many companies suggest using URL shorteners, I’ve personally found that people are more likely to click a long link if they can tell where it’s originating from. It’s worth A/B testing.
3. Phone Call Tracking
I prefer to argue online with a technical support representative for thirty minutes rather than make a five-minute phone call to resolve an issue. It’s ridiculous. I know calling is more efficient. And yet, as an introvert, actually talking to someone is not appealing.
There are many people out there who don’t share my view of the world. They’ve learned from their frustrating online experiences. This means you need a method of tracking people who find your number through an advertisement.
Solution:
Implement unique phone numbers for each campaign and train your inbound team to attribute leads properly. Regularly review call data to ensure accurate attribution.
4. Social Media and Retargeting Attribution
While there is some inherent tracking available from social media on Google Analytics, that information doesn’t always transfer to your marketing automation platform. It also won’t specify that the click was from an advertisement on social media unless you use proper UTM parameters and pixel tracking.
Pixel tracking is essential if you want your retargeting ads to fire correctly or social media to record specific actions as conversions. For example, if a target visits CaliberMind, we use pixel tracking to serve up ads on CNN or Forbes.
Solution:
Utilize proper UTM parameters and implement pixel tracking for social media and retargeting campaigns. This allows for more accurate conversion tracking and a better understanding of these channels’ impact on your ROAS.
5. Ignoring Leading Indicators
As marketers, we know it takes time for people to move down the funnel after first engaging with paid search or paid social. However, many leading indicators can help us determine whether or not the ad is resonating with the right audience.
Solution:
Monitor leading indicators such as engagement rates, qualified traffic, and conversion costs. These metrics can provide early insights into campaign effectiveness and allow for timely optimizations. We’ve given a real-world example of how we used analytics and leading indicators to optimize some of our advertising. For more details about which metrics to watch and why they matter, check it out.
6. Anonymous Visitors
Companies relying on IP addresses to calculate the company associated with the visitor had a rude awakening in April of 2020. Those designated IP ranges were useless when people began working from home en masse.
Solution:
Installing web tracking like Analytics.JS can help you retroactively identify people once they complete a form. This allows you to retroactively identify historical interactions and give sales a better picture of what their prospect was engaging with before the opportunity was created.
While we can’t always show anonymous touches as part of ROAS, there is an ability to incorporate some of this data at the account level and incorporate it into scoring. This is another example of how having engagement AND Attribution (or ROAS) in the same platform is so important to gauge how marketing is doing. You can read more of my thoughts on this topic here.
7. Single-Touch Attribution Models
Marketers who use first-touch single-point attribution will be accustomed to seeing a lot of value placed on early engagement activities like paid search. Those who use last-touch single-point attribution must explain to management why their chatbot isn’t the only marketing tactic they should invest in. Neither of these views gives a holistic view of marketing efforts needed to generate a sale.
It’s essential to think of your ad campaigns in the context of your complete marketing story. Likely, this touch is one of many at a given company. Salesforce campaign influence reporting, for example, offers full credit to any campaign that touches an account with an opportunity IF the contact is associated as a “contact role” on the chance. This doesn’t sit well with me because:
- It doesn’t consider the entire buyer journey across the account, incorporating contacts and leads that aren’t called out by the sales team but have interacted with your company.
- It double (triple or quadruple or…) counts revenue instead of looking at the touch as a fraction of the total effort.
- It lists your total ad spend on each campaign touch instead of considering all of the activity across all accounts that was generated, the revenue those touches generated, and then calculating ROAS.
Thinking of ROAS in the context of multi-touch attribution can give you a more realistic “value” picture.
Solution:
Multi-touch attribution only works if you have the data infrastructure necessary to clean your underlying data. If you bolt an attribution tool onto your CRM or MAP, your output will only be as good as the data you’re plugging into. For more information on must-have features for any attribution tool, check out our article.
The Path to Accurate B2B ROAS
To truly understand your Return on Ad Spend in a B2B context, consider the following steps:
- Implement comprehensive tracking across all channels
- Adopt a multi-touch attribution model
- Monitor both leading indicators and long-term results
- Regularly clean and validate your data
- Educate stakeholders on the complexities of B2B ROAS
By addressing these challenges and implementing robust tracking and attribution systems, B2B marketers can better understand their ROAS and make more informed decisions about their marketing investments.
Remember to reach out to CaliberMind if you need help on your data journey!
