Cohort Tracking for B2B Audience Attribution Accuracy

Zafar Jutt


A million-dollar question is: how can we prove paid advertising ROI? Most advertisers realize the complexity of the B2B customer journey: the sales opportunities might come from the organic search or outbound emails, but they’ve likely seen your ads before.

Fair enough, most teams prefer sticking with the last-click conversion to attribute campaign ROI to the corresponding ad channel. However, it doesn’t explain whether the increased ad spend impacted your overall marketing ROI and contributed to final revenue. Everything changes when you leverage an audience-based attribution model known as cohort tracking.

What Is the Ad Audience Cohort Tracking?

The audience-based attribution model called cohort tracking allows you to identify a converted lead as a member of your ad audience segment. Thus, you can conclusively say that the customer has seen your ad, and it has influenced their purchase decision.

Knowing who was in the ad audience segment and how many sign-ups you got during the active paid ad campaign allows you to attribute conversions from organic and direct visits to your advertising efforts. Just like that, it’s crystal clear and spares you from over-complicated attribution systems.

Most importantly, such a transparent multi-channel attribution helps the marketing team justify additional ad budgeting.

How Cohort Tracking Differs from the Last-Click Attribution

The prime benefit of switching to an ad audience cohort tracking system is that it allows you to oversee ad performance holistically and analyze it beyond the last-click conversion. You no longer rely on campaign-specific UTM parameters to measure advertising success.

Advertising based on lookalikes and the platform’s native targeting doesn’t allow you to access the actual identifiers of ad network members, which you can use to match converted leads with your CRM or B2B IP tracking. This means you can’t determine how many inbound prospects converted after seeing your messages, which could be quite valuable for your ABM efforts in the future. The only metric you can gauge in this case is last-click conversion ROI. The typical measurement pattern includes:

  • Tracking UTM link clicks.
  • Counting lead form fill-outs.
  • Attributing lead conversions to the campaign you ran.
  • Calculating customer acquisition costs (sales and marketing spend/customers acquired) and lifetime value.

Conversely, cohort audience tracking allows you to calculate ROI regardless of the traffic source, as you can count the conversion rate for the entire pre-defined audience segment.

How Ad Measurement Changes with Audience-Based Tracking

The point is that you complement the existing last-click tracking with additional data on the audience to which you serve ads. It adds accuracy when attributing newly acquired MQLs/SQLs to the recently run advertising campaigns.

This enhanced attribution approach will bring together tracking data coming from:

  1. Ad platform analytics. You can analyze which part of the audience was reached during the active campaign and how many of them were engaged with the ad message and clicked through.
  2. IP Targeting and Reverse IP lookup. With IP targeting, you can deliver relevant messages to IPs, while the reverse IP lookup helps to identify incoming traffic from an ad platform and match visits with third-party prospecting data provided by B2B data vendors.
  3. UTM links. Clicked-through UTM links will flag platform-specific traffic and show how it is distributed within your multi-channel campaign.
  4. Emails/Names. You can cross-match acquired MQls/SQLs’ contact data with the audience list uploaded to the ad platform.

Eventually, you get the most accurate attribution of converted leads to your PPC campaign. This enables you to effortlessly calculate multi-channel ROI and identify the top revenue-contributing channels.

Leverage Custom List-Based Audiences to Unlock Cohort Tracking

The cohort tracking will work out only if there’s a high enough match rate (>70%) between ad network accounts and your list-based audience. The problem is that, on average, you have a contact name, business email, and work phone number in a targeted list record. With such scarce prospecting data in hand, you can’t expect match rates higher than 10 to 30%.

Enable B2B customer data enrichment, and you’ll ramp up ad platform match rates. By enriching customer records through Primer and similar B2B data orchestration platforms, you can achieve 70-80% matching for custom-built audiences across Facebook, LinkedIn, Instagram, Google Ads, and other PPC networks.

Moreover, Primer allows you to build custom audiences as close as possible to your Ideal Customer Profile and synch them across channels. Start with targeted paid social campaigns and then run an automated email follow-up campaign on the same leads group. Such a combined approach can grow your conversion rate by another 20%+.

Simplified Pursuit of ABM Accounts

Let’s not forget that cohort tracking can greatly boost the efficiency of strategic account-based marketing. Since you’re serving targeted ads to pre-qualified audiences, the overall cost of customer acquisition drops dramatically. 

Additionally, you can effectively identify highly engaged leads, attribute higher scores to them, and pursue them as high-value accounts. Audience-based attribution allows you to double down on these valuable leads by streamlining multi-channel follow-ups.

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