The first concern of any B2B marketing leader is showing the impact of advertising investments and actions on revenue.  

But accurate, useful reporting that connects the dots between advertising investments, leads and opportunities, and revenue is easy to imagine, but notoriously hard to do. Even though creating the data infrastructure and processes to do this is a challenge, it’s worth the time and effort.    

Executed and monitored well, the power of this reporting will allow you to answer some of the toughest questions from the C-suite: Everything from the granularity of which campaigns, ad groups, keywords, or regions drive the most pipeline and revenue to identifying macro trends in advertising’s performance month-over-month.    

‍We call this benchmark a full funnel report—essentially, a report that combines ad platform and customer relationship management (CRM) data to bring full visibility into the actions driving revenue. Full funnel reporting ensures that the correct optimizations are being made to maximize your key performance indicators (KPIs). Without seeing the down funnel data, the advertising efforts driving the best customers are unknown—digital advertisers can’t fully see the impact of their efforts, or understand what is working and what isn’t.    

In this post, we’re going to walk through exactly what you need to create a full funnel report and share some examples that help demonstrate just how flexible they can be for your business.  

The three things you’ll need for a full funnel report are:

1. Centralized, accurate data extracted from relevant sources

2. Modelled data to present a polished, trusted dataset to the end user

3. Visualized data to present the right insights in the right way

The first step of full funnel reporting is to bring multiple data sources together. Though these vary dramatically between companies, sources can be categorized into three different groups:
‍
Ad platform data containing spend and in-platform metrics
Event data that tracks conversions like content downloads, demo requests, etc.
CRM data like leads, MQLs, opportunities, and associated pipeline

Extract, transform, load (ETL) tools pipe data from almost any data source into your data warehouse, setting the foundation for building your full funnel report and ensuring a single source of truth. At Outshine, we use Stitch but others include Fivetran, Matillion, or built-in integrations or data connectors offered by many business intelligence (BI) tools.

Most tools are simple to set up, integrate with most ad platforms and CRMs, and authenticate directly to these platforms, eliminating the need for manual uploads and building data pipelines with ad-hoc scripts. The end result is a reliable, automated, real-time stream of data.

However, an in-platform hack to see Performance Maxconversion data is to select the asset group, select “locations”, and customize columns to include conversions to see more granular reporting:

Think of data modelling as the opportunity to present a polished, trusted dataset to the end user. A modelling tool (we use Dataform but other solutions such as DBT, Airflow and Looker also have varying degrees of data modelling capabilities) sits on top of your data warehouse, with read and write permissions enabling you to both create reporting-ready tables from the raw data, as well as collaborate on SQL queries with branching and merging features.

Data modelling is key to usability, interpretability, and accuracy, so a well thought out schema that considers the end user and medium of reporting is critical. For example, if the end user wants to pivot the data in Google Sheets, create fields such as week or month so week-over-week or month-over-month analysis is easy.

For the funnel report to work properly, it’s also important to follow consistent campaign naming and UTM parameters. When combining the data, the campaign and ad group name from both sources (ad platform and CRM) must be exactly the same. If there are discrepancies between these parameters, reporting cost per any KPI at the campaign and ad group level is much more challenging and complex. Consistency means you can easily analyze campaign or ad group performance in more detail, for example by country, industry vertical, or campaign type (brand, generic, competitor).

Now that the heavy lifting is finished—the data has been selected, cleaned, and modelled into a functional and robust table—it’s time to show it off. Reporting can be visualized in many different ways, and depends on your audience and the BI products at your disposal.

Higher-level executives typically want a dashboard clearly outlining progression against KPI targets, giving enough context to understand performance without too much detail. An advertising practitioner, on the other hand, requires more reporting granularity to make optimization decisions. They might look for week-over-week performance at the channel, platform, campaign, and ad group level to understand where their budget is the most effective and where inefficiencies lie.

When choosing where the reporting lives, the main factor in making this decision will be what BI tools you currently have access to. One great—and free— choice is to use Google Sheets and Google Data Studio.

Let’s get to the results—what kinds of insights can you be generating from a full funnel report? Here are some of our favourite examples.

Our go-to chart for demonstrating performance efficiency is Cost Per MQL against Spend.

Next, we typically create two separate tables that look at top performing campaigns and ad groups, to strategically optimize advertising initiatives. For example, looking at Campaign C in the chart below, if the threshold for cost per MQL is $300, this campaign may need to be adjusted and monitored or paused. Or, if ad groups have a high spend but aren’t converting down funnel, these should be either eliminated or refined.

Another chart we like to monitor is the conversion rate between the funnel stages, both to assess success of marketing efforts and to alert the team to any internal processes or changes that may have impacted performance. Due to the complex nature of the data schemas of CRMs, it can be difficult to view the conversion rate of each lead stage for different marketing streams. With a full funnel report this insight is possible.

Today, most companies have a large quantity of data at their fingertips. But it’s a significant challenge to turn that data into high-quality reporting—to build the well-constructed infrastructure that delivers accurate, trusted insights. So truly applying data to business growth goals remains a pipe dream.  

‍The full funnel report makes data-driven advertising decision-making a reality.

‍The beauty of a full funnel report is in its simplicity. It’s not trying to do everything—it’s laser-focused on providing continuous visibility into performance for both advertisers who need insights to optimize campaigns and CMOs looking for long-term, meaningful trends.  

That’s why we think creating a full funnel report should be at the top of every marketing team’s priority list.

Is it on yours?