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Cracking the B2B Marketing Attribution Code for Quantifying Marketing Impact in the Privacy Era
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Cracking the B2B Marketing Attribution Code for Quantifying Marketing Impact in the Privacy Era

Marketers must get creative and use both old and new B2B marketing attribution techniques.
Author
Primer team
Updated on
January 23, 2024
Published on
November 21, 2023

Table of Contents

Attribution has become crazy for B2B marketers. With all the new privacy stuff, third-party cookie restrictions, and walled gardens, getting clear visibility into the customer journey is tougher than ever. But attribution still matters big time for understanding marketing ROI and optimizing programs. In this new environment, marketers must get creative and use both old and new B2B marketing attribution techniques to keep driving growth. 

Why Attribution Matters for B2B Marketers

For B2B marketers, attribution is key for figuring out the impact of campaigns, channels, and tactics. With good attribution, marketers can:

  • See the most effective marketing channels for getting new leads and deals
  • Understand the typical buyer journey and what touchpoints influence deals
  • Optimize budgets and double down on high-performing strategies  
  • Calculate return on investment (ROI) for campaigns and programs

Ways Primer can help

Without solid attribution, there's lots of guesswork and inefficiency in marketing. B2B marketing attribution provides the visibility needed to make smart decisions. It provides context for lead gen and helps drive higher conversion rates. Especially in B2B with long sales cycles, attribution is critical for both short-term and long-term approaches.  

The Data Crisis of B2B Marketing Attribution

Over the last few years, B2B attribution has become unreliable. Privacy changes have restricted data, and problems have popped up in major analytics platforms:

  • iOS updates like iOS 14.5 have hurt advertiser access to IDFA, impacting mobile attribution.
  • Browsers like Safari, Firefox, and Chrome are tightening up on third-party cookies.  
  • Walled gardens like TikTok and Facebook provide limited visibility into customer journeys.
  • Unidentified/untracked traffic and leads are everywhere in tools like Google Analytics.

This “dark data” provides an incomplete view of the real customer journey. Marketers are seeing inflated numbers for some channels based on bad categorization. Meanwhile, other marketing efforts may not even show up in reports due to tracking limits. The data crisis in B2B marketing attribution seems to only be getting worse over time as privacy evolves.

Walled Gardens Amplify the Attribution Headache 

Walled gardens like Apple, Google, and Facebook bring unique attribution challenges. On these platforms, brands have limited control and visibility. They rely on each platform’s proprietary reporting and targeting.

Because data is siloed and measurement methodologies differ, attribution numbers can vary widely across gardens. These discrepancies make it hard to create a unified view of the customer journey. Since gardens only provide insight into their own channels, marketers are left guessing about cross-channel effects and true ROI.

However, you can activate the same custom audiences across multiple channels thanks to Primer. It will ensure a single baseline for your ROI calculations.

Lack of transparency into gardens can also lead to poor budget decisions. Marketers may double down on platforms that inflate performance due to bad categorization or flawed methodology. Without the full picture, they don’t know how to properly spread budgets across different channels.

The Limits of Multi-Touch Attribution Models

To provide more visibility into the buyer journey, many B2B marketers use multi-touch attribution models like time decay or algorithmic models. However, these B2B attribution models have limits, especially as data quality declines.

Time decay models overweight early and recent touchpoints, which may not reflect deal cycles. Algorithmic models rely heavily on machine learning, so their accuracy depends on input data quality. Models are only as good as the data that feeds them. With so much unknown traffic and engagement, these models remain directional at best.

Because these B2B marketing attribution models use cookie data, they also miss important offline interactions throughout the buyer’s journey. This provides an incomplete view of each deal’s sales progression. As a result, marketers may underestimate the influence of field sales and customer success on converting and expanding accounts. 

Getting Back to Marketing Basics with Lift Analysis

With the perfect storm-hitting attribution, B2B marketers need to get back to classic marketing tactics like lift analysis to assess program impact. 

Lift analysis turns campaigns on and off to quantify the incremental impact on key metrics like site traffic, form fills, and SQLs. This allows for head-to-head testing to see how metrics trend for each effort. One can isolate the unique impact of specific activities by using control groups. Learn how to make the most of experimenting with your ads from part 3 of our guide on B2B ad campaigns.

Marketers can do lift analysis across channels, including traditional tactics like field events and digital marketing. While a bit more manual than traditional B2B marketing attribution, this approach accounts for program nuances and provides clear insight into incremental value. Lift analysis works even with bad data tracking.

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Getting Closer to the Customer with Marketing Mix Modeling 

Marketing mix modeling (MMM) is another increasingly important old-school technique. MMM can model how all marketing activities together impact the sales pipeline and revenue. It provides visibility into marketing’s overall contribution and the ROI of different activities.

Since MMM analyzes aggregate marketing data over long time periods, it is far more resilient to one-off data anomalies and tracking errors. The approach relies more on core marketing statistics rather than individual user paths and complex attribution logic. So, it handles reporting turbulence better.

Like lift analysis, MMM provides a big-picture analysis of marketing's impact across online and offline channels. In contrast to common B2B marketing attribution models, it accounts for real-world dynamics like seasonality, market trends, and lag effects based on average deal cycles. This contextualization is key for long-term optimization. 

Using Leading Indicators to Guide Strategy

Given B2B marketing attribution challenges, B2B marketers should check out leading indicators that tie back to pipeline and revenue. Leading indicators may not prove attribution, but they can point strategy in the right direction. 

Some examples of leading indicators include:

  • Reverse IP tracking of target account visits  
  • Form fills and SQLs from target accounts
  • Email engagement like clickthrough rates for key accounts 
  • Brand lift surveys with target accounts to gauge awareness and sentiment

Marketers can also run focus groups with customers to get insights into what influences their decisions. They can use this feedback to double down on impactful areas. Though not perfect, direct customer perspectives provide helpful guidance. 

Getting Creative: New Approaches to B2B Marketing Attribution 

With murky attribution, B2B marketers need to find creative ways to better connect engagement to revenue. Some ideas:

  • Feed analytics directly into the CRM to link sessions with deals
  • Incentivize event and gated content registrations to capture more known contacts 
  • Build custom algorithms that incorporate CRM data like deal stage to attribute credit precisely  
  • Leverage intent data to ID contacts researching products which can signal opportunities
  • Conduct more surveys with customers to get their take on influential content and activities

Marketers should also increase collaboration with sales teams. Reps close to deals can share insights into what marketing activities influence target accounts. This can guide budget decisions.

The Road Ahead: Doubling Down on Testing and Agility 

The turbulence around data and B2B marketing attribution doesn’t seem to be getting better as privacy and walled gardens continue. So marketers need to take a test-and-learn approach to drive optimization. 

They should develop clear hypotheses on campaign impact and design initiatives to test those hypotheses directly. By taking a first principles, scientific approach, they can draw solid conclusions on tactics that work based on real results. Testing also allows for greater agility to pivot what’s not working. 

With ambiguity around reporting, just following the data isn't enough. B2B marketing leaders need to stay up on privacy developments and get creative in demonstrating impact. Though the road ahead has challenges, a focus on fundamentals and cross-team collaboration can overcome them.

Use Primer to Attribute Ad Audiences with Confidence

Primer ensures audience-based B2B marketing attribution so you can gauge the impact of your targeted campaign without a problem:

  1. Build a custom targeted list by pulling together CRM and third-party data.
  2. Push it to any ad network you choose: Google Ads, Facebook, Instagram, or LinkedIn.
  3. Track generated leads, calculate channel-specific ROI, and manage your budgets correspondingly.

With Primer, you can oversee your campaigns as a whole and assess the impact of your ABM efforts at every funnel waypoint. Contact our team to book a live Primer demo and see how it works.

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