Strategies for Mastering Ad Performance Metrics in B2B

Measuring ad performance in B2B is like solving a puzzle. 

A complex puzzle where each piece holds the key to unlocking your next big opportunity. With sales cycles that feel like marathons and a decision-making team that could rival a football squad in size, getting your ad performance metrics right can be challenging.

For starters, B2B ad performance measurement is fundamentally different from the instant gratification world of B2C. In B2C online shopping, someone might see an ad and instantly buy the product, meanwhile, B2B involves lengthy sales cycles.

The decision-making process stretches over time, involving RFPs and often a committee of about 11 people making the call. This means B2B marketers seek more than instant conversions or return on ad spend (ROAS). Their focus spans leads, brand awareness, and engagement with their content.

As a B2B marketer, when you analyze your ad performance data, you can’t just look at conversion metrics—even if that’s what you’re being asked to report. 

Start by understanding your ideal customer profile (ICP) and which businesses are interacting with your ad campaigns. Then, peel back the layers to see who clicked on your ad and what drew them in.

Ask questions like:

• Did they interact because they were interested in your service or were they seeking information on a related topic? 
• Did they engage with the ad only or did they engage also on your website?
• Did they engage with a relevant topic on a website? (hint: contextual targeting)

This deeper insight into engagement tells you where these accounts stand in their buying journey, and what content is steering their interest.

Ultimately, you want to map out how potential clients move through the sales funnel, driven by targeted ads that meet them at every stage.

In this article, we’ll look at how to measure your marketing efforts effectively—going beyond chasing clicks, and focusing on strategizing, understanding, and leveraging data to resonate with your clients.

Metrics and KPIs Across the Customer Journey

Can you switch up your metrics at each stage of the customer journey? Absolutely. 

In B2B, key performance indicators (KPIs) lead the way. 

At the heart of lead generation, you’re distinguishing between marketing qualified leads (MQLs) and sales qualified leads (SQLs), two lead stages that can help to determine buyer readiness. So, it’s about understanding the type and quality of these leads before deciding on the next move.

Then, there’s account scoring, a strategy that segments and ranks potential clients, adding another layer to your strategy. 

Account scoring ranks potential clients based on how likely they are to buy something. The score is based on various factors, such as how often they visit your website, if they open your emails, and their overall engagement with your brand. This method helps you focus your efforts on the accounts with the highest scores, meaning those most interested and likely to make a purchase.

It’s all interconnected, with each element feeding into a larger, more complex picture of engagement.

Best Practices for Interpreting Ad Performance Data

You probably have access to a lot of engagement metrics, but as a dense collection of raw data. 

The key is learning how to interpret this data, segmenting accounts based on their interactions and responses.

For instance, many advertisers using StackAdapt start with a broad account-based marketing (ABM) list and apply a uniform marketing tactic across the board. 

This approach, however, overlooks the differences in readiness and awareness among the accounts. 

Ideally, an advertiser would analyze the engagement data to identify which accounts are top of the funnel and largely unaware of their product, as opposed to those that are more engaged and further along in the decision-making process. 

For example, out of an initial list of 1,000 accounts, 500 might be early in their journey, requiring awareness-focused messaging, while another 100 might be ready for more direct, conversion-oriented approaches. Unfortunately, the tendency to apply a single strategy across the entire list can dilute the effectiveness of the campaign.

To elevate your strategy, you should employ best practices in data interpretation, leveraging the insights gained from engagement metrics. This means moving beyond a one-size-fits-all approach to recognize and act upon the distinct characteristics and needs of different account segments.

That way, you can align your marketing tactics more closely with the stages of the customer journey, ensuring that each account receives the most relevant and impactful messaging. 

Here are some best practices you can use to interpret your ad performance data:

1. Segmentation of data: Segment accounts by engagement level to customize messaging and tactics that are most appropriate for each group.
2. Longitudinal analysis: Look at data over a longer period to identify trends and patterns, to understand how campaigns affect potential clients over time, rather than making decisions based on a snapshot of data.
3. CRM Data Leverage: Upload the 1st-party data from your CRM into your adtech platform for better targeting and insights.
4. Multi-touch attribution: Understand the value of each touchpoint along the customer’s journey.
5. Qualitative insights: Go beyond numerical data and gather qualitative insights, such as customer feedback and engagement context to see why certain behaviours or patterns occur.
6. Actionable reporting: Reports should not just present data, but also suggest clear actions for campaign adjustments, budget reallocation, or strategic shifts.
7. Testing and learning: Set up controlled experiments to compare different tactics, messaging, or audiences to see what works best and refine strategies based on evidence.

This approach maximizes the potential for engagement and conversion and paves the way for more sophisticated and effective marketing strategies in the future, as deeper and more detailed reporting becomes available. 

Ultimately, the goal is to harness the power of data to inform smarter, more dynamic marketing tactics that resonate with each segment of the target audience, driving better outcomes and higher ROI.

The Role of AI and Machine Learning

As you gain access to more data than ever before, the task of analyzing and leveraging it for your campaigns can feel overwhelming—yet this is where the true value of the data lies. With a wealth of data available, you make the smartest decisions when you incorporate machine learning and artificial intelligence.

At StackAdapt, our goal is to provide B2B marketers with actionable insights that lead to a comprehensive funnel strategy, allowing for the precise targeting of accounts with strategies that match their current journey phase.

For instance, here are some of the ways AI is integrated into the StackAdapt platform:

• StackAdapt applies machine learning at the time of the bid request to predict the likelihood of fraud, and to ensure the auction is bidding on a real audience.
• Leveraging StackAdapt Page Context AI and Browsing Audiences allow you to target billions of possible user interests.

Machine learning and artificial intelligence are the foundation upon which the entire demand-side platform (DSP) is built. It is how StackAdapt approaches programmatic.

Learn how a digital agency leveraged StackAdapt to drive leads at a 7.05% conversion rate.

Choosing the Platform With the Best Data

StackAdapt offers detailed engagement metrics on both account and individual levels, empowering clients with valuable insights. Our clients have access to all the necessary data to conduct this analysis. 

This feature sets us apart from many other digital advertising platforms. Unlike general platforms like Google or other DSPs, which might not provide this depth of data, we ensure you can dive deep into how different individuals and accounts interact with your campaigns. Our comprehensive reporting delivers granular details, enabling a thorough understanding of audience engagement and segmentation possibilities.

Interested? Learn more about StackAdapt, by requesting a demo today.