Marketing is one of those careers that everyone suspects they could do well. It almost seems intuitive. All you have to do is get the right message in front of the right people at the right time. Right?
Developing and executing a solid strategy takes a lot more than intuition. The best marketers keep up to date on the latest trends, network with one another to figure out how the last Google or LinkedIn update impacted our ads (and pivot accordingly), and stay on top of their data so they can make the best decisions possible.
Staying current on best practices eats up a lot of time when we’re not on the clock, but I would argue that keeping a grasp on the data and then convincing the broader company that your results are real are the two most challenging aspects of marketing.
Leveraging a marketing attribution tool makes sense to marketers. We know a great deal of the activity we generate will never show up on regular opportunity source reports, and we need to justify continuing early and late funnel tactics to the rest of the company. The trick is leveraging the data in a way the rest of the company will buy into.
Let’s look at a few successful use cases we’ve seen in action.
Measuring the Impact of Awareness
The Problem They Wanted to Solve
Since Customer A brought in a new CMO six months ago, their strategy has been primarily focused on top of funnel activities. They updated their brand narrative, overhauled the website, invested in competitive advertising, developed a steady stream of content, and doubled down on social media.
The rest of the C-Suite has been patient, but they’re starting to demand results tied to revenue dollars. They want to understand exactly how much marketing budget they need to invest to hit their target numbers next year.
The Deeper Issue
Like many B2B businesses in the COVID-19 era, Company A had decided to move away from in-person events and focus exclusively on digital tactics. They did face some budget reductions, but they repurposed a decent share of their trade show budget. While paid search advertising increased web activity, those visitors rarely filled out the form on the initial landing page. They tended to click around the page, leave, and come back in days to follow. As a result, their conversion rates were much lower than people using organic search to find Company A.
The Solution
There were a few ways we could have solved Company A’s issue. We could have broken up the chat campaign into several different campaigns based on how the person initially landed on the page. Instead, we used something known as “virtual campaigns” to record web touches. These interactions usually aren’t registered as a standard Salesforce campaign member because we don’t necessarily know who the person is until they fill out a form. That’s not an issue with CaliberMind. With our robust data engine, we can retroactively tag a person’s actions as we gather more information about them.
A campaign hierarchy helps us organize the data by channel, associate ad spend, and segment campaigns by other identifiers:
Because CaliberMind can parse or segment touches based on funnel stages, we can hone in on which campaigns are generating activity at each stage of the funnel. This means we can inspect whether or not digital content has an impact on awareness.
Examples
Let’s look at some campaign stats using hypothetical data to determine which content is working when.
In the example above, the Everything Analytics Guide is the number one driver to this company’s website the first time. In fact, even their older guides still perform well. The data is also telling us they should focus more on Social Media activity.
Stepping up a level, let’s look at how campaign channels influence revenue across the funnel over an undisclosed time period using Chain-Based Attribution:
Using Marketing Attribution to Prove Late Funnel Value
The Problem They Wanted to Solve
At Company B, the marketing operations manager was tired of having the same conversation over and over. It sounded something like this:
“I need you to change the primary campaign on some opportunities.”
“Why?”
“All of them had meetings at the major trade show.”
“Okay, but these look like they came in from demo requests and content downloads.”
“…. They had meetings. The trade show should be the primary campaign source.”
“But that’s not where we created the opportunity.”
“Look. They had meetings, and if you talk to the salesperson, they’ll probably agree that the trade show was essential in getting the sale.”
The marketing operations manager knew that when executives buy into attribution models, it’s a great way to show the value of campaigns that don’t necessarily precede an opportunity. The problem was, the marketing operations manager also knew that the VP of sales was very opposed to attribution and called it “a way to make marketing look better than it should.”
The Deeper Issue
Some tools only consider marketing campaign data when calculating opportunity influence, which creates a very one-sided view of the world. In this case, sales leadership had experienced marketing attribution in the past and didn’t like the math–because nearly everything was “credited” to marketing.
In this example, we exclude non-marketing touches from our attribution scoring to replicate what the sales VP hated:
If you have an attribution tool that only takes marketing activities into account, you shouldn’t use your reports to state department pipeline influence. Sales leadership will protest loudly, dig up data to prove differently, and cast doubt on all of your numbers–not just marketing attribution data. If you’re only incorporating marketing data, your reports should be used as a way to gauge whether or not campaigns are influencing deal closure, not calculating marketing’s contribution to revenue.
The Solution
Company B incorporated sales generated activity and partner data (deal registrations, etc.) into their attribution model. They understood that the volume of sales emails would skew the data in the direction of sales, but that was acceptable. Particularly after we met with sales leadership to click through specific opportunity examples and show them the math.
Muting Campaigns
The Problem They Wanted to Solve
Customer C had a dilemma. Their website chat sessions converted so well into opportunities that their CFO wanted to reduce spend on paid search and paid social campaigns. The VP of marketing knew that paid advertising was one of the key tactics getting people to the website in the first place, and without them, they wouldn’t generate enough pipeline for sales to hit their number.
The marketing team wanted to know if there was a way to mute their chat campaign so the rest of the business could see the value in the rest of the department’s activities.
The Deeper Issue
Customer C’s chat tool wasn’t passing along UTM parameters to their CRM, so they lost insight into how people found themselves requesting a demo.
The Solution
To solve Company C’s visibility issue, we set up virtual campaigns to track web activity and set up some code to pass the UTM parameters in the chat integration call as well. Once web activity began streaming into our data engine, we could give the full activity picture of all contacts at a given account and stop relying on the action that happened immediately before the opportunity.
There are cases when we do suppress campaigns. It’s common for organizations to have parent campaigns for organization purposes or campaigns that all accounts run through by default. We help them develop a clear strategy for flagging which campaigns are relevant and which are not.
Using buyer journey mapping, Customer C provided a visual that demonstrated how people commonly progressed to a chat request. Here is how our demos usually come about as an example:
We’ve found that transparency is just as crucial to executive leadership as a strong data foundation is to stellar attribution reporting. Make sure you only commit to as much as your tools are capable of, and don’t be afraid to dig into a few key opportunities to illustrate how your models work.
Need help? Don’t hesitate to contact us for more information on attribution best practices.
