According to our recent research, advanced analytics appears to be an underserved niche for marketing teams – presenting a huge opportunity for agencies looking to win and retain more accounts. In fact, just 12% of in-house marketing teams said they have at least one advanced analytics expert on staff.
That means that agencies who can provide this expertise have a distinct competitive advantage over other shops. But simply winning the business is not enough. Agencies must ensure they can access large amounts of clean and accurate data to run these analyses.
So, how do they ensure their clients provide all the required credentials and materials? Glad you asked. We’ll spell it all out for you below.
Why advanced analytics matter
Advanced analytics techniques like marketing mix modeling (MMM), multi-touch attribution (MTA) and incrementality testing enable agencies to make data-driven decisions that optimize marketing campaigns and drive better business outcomes. They go beyond basic metrics like clicks and conversions, helping marketers understand the true impact of their efforts across various channels, touchpoints and customer journeys.
For instance, MMM is a non-linear statistical analysis technique that helps brands understand how different marketing channels (both online and offline) contribute to overall sales. It is beneficial for measuring long-term brand-building activities and balancing investments across channels.
Meanwhile, MTA allows marketers to track which tactics drive conversions and sales. By analyzing every interaction with MTA, marketers can determine which touchpoints drive the most value, making it ideal for optimizing digital campaigns.
Yet, MMM and MTA aren’t as strong when used jointly or independently. The real magic happens when you combine them with a third methodology: incrementality testing. This third corner of what we call “triangulation” measures the true impact of a marketing activity by comparing the performance of a treated group (who saw the marketing) against a control group (who did not). Incrementality testing is a powerful way to assess whether campaigns are genuinely driving additional sales or if the outcomes would have occurred without the campaign.
While these three methods become exponentially more powerful when combined in triangulation, they still need to be fed large volumes of high-quality data to generate meaningful results.
The challenge of accessing large data sets
One of the biggest hurdles marketing agencies face is the need to access large volumes of clean and accurate data. This data often comes from multiple sources, including CRM systems, ad platforms, social media, website analytics tools, etc.
That means agencies need to go beyond their usual client contacts in the marketing team. Instead, they often need to proactively build bridges with IT, business intelligence and legal departments to gain access credentials and more. However, accessing that data in a usable format is not always easy.
If they cannot gain proper access, they may be set up to face failure in several ways, including data fragmentation, privacy and compliance concerns, integration complexity and more.
This leads to an outcome that any agency would want to avoid: wasting money to provide inaccuracy. See, without quality data, advanced analysis simply can’t be trusted. Certain datasets may not represent the actual marketplace, and some data may be repeated (skewing results) or have too many errors to return a result. And advanced analytics work often doesn't come cheap.
The last thing you want, as an agency, is to lead your client toward a bad decision via analysis on which they spent a lot of their budget.
The power of clean, accurate data
On the contrary, when agency teams can access large volumes of high-quality, clean data, the possibilities start to present themselves.
And when data is collected, consolidated and cleaned well ahead of the advanced analysis stage (say, through a tool like Funnel), the entire project timeline can be sped up. Plus, if clients can provide high levels of detail in their data, the analysis can dig down to a much more granular level. This can help agencies understand how nuances between touchpoints contribute to overall revenue.
Just think, you can even help your clients see that a small shift in media spend could result in an outsized increase in sales. That ability to make the full use of advanced analytics builds trust with your clients, leading to longer and more profitable relationships.
But it all starts with data.
Practical examples of advanced analytics
Employing advanced analytics isn’t just about improving the efficiency of a client’s marketing spend. In fact it can be used for a whole host of things.
Tracking customer journeys
Imagine a tech company hiring your agency to promote its new B2B SaaS product. As you unpack their typical customer journey, you identify that prospects typically interact with a Facebook ad, then read a blog post, sign up for the newsletter and (finally) click on a Google ad to make a purchase.
The client wants to know which of these tactics along the journey had the most impact on converting the customer. With the right data, MTA can help your agency team assign a value to each touchpoint, showing that the blog article significantly strengthened their purchasing consideration, while the Google ad sealed the deal. The Facebook ad also played a role, though only to build some very general awareness of the product.
“Is my ad doing anything?”
Sometimes, marketing teams approach an agency with multiple campaigns already running across various tactics. They may be curious if their Facebook ads, for instance, are actually driving as many sales as Meta’s built-in analytics tools really claim. They wonder what would happen if they turned off the Facebook ads tomorrow.
Your agency can determine that by running incrementality testing. To do this, you’ll need to split the audience into two groups: one sees the ads and the other does not. After running the test for a few weeks, you compare the sales from both groups and find that the group exposed to the ads generated 20% more sales than the control group.
That means the Facebook ad is indeed driving a significant amount of conversions.
Personalizing campaigns and experiences
Your agency is working with an online fitness company that targets customers across various demographics. By using advanced analytics, your team can segment the audience into three main groups: college students, young professionals and retirees. What a diverse group!
During your analysis, you identify that college students are most responsive to Instagram ads, while retirees prefer email marketing. This insight helps you create personalized campaigns for each group, ensuring your client’s messaging resonates with each segment.
It all starts with data
Advanced analytics are the clear pathway toward future profitability for many agencies these days. After all, the methodologies can serve up powerful insights that can increase your clients’ profit margins, boost revenues and improve marketing spend efficiency.
However, none of this is possible without access to clean and accurate data at scale. That’s why it behooves agencies to request access to this sort of client data as early as the onboarding or pitching stage. Without it, you risk wasting your client’s budget on inaccurate results, which is not a winning formula for success. But in a world where data is king, agencies that prioritize clean, accurate data collection will deliver better results that foster stronger, longer-lasting relationships with their clients.