Speculating about b2b data quality typically revolves around the idea that match rate is the core metric for targeted ads. Fair enough, you’ve seen tons of guides and case studies representing high ad campaign match rates as the definition of success.
However, that’s not all you need to consider. In short, the match rate characterizes how many profiles of paid ad platforms suit your ICP marketing goals. To gauge the actual coverage of the target audience, you should also pay attention to what we call the “reach rate”.
Why Doesn’t the Match Rate Reflect B2B Data Quality?
Naturally, the match rate of the campaign indicates the number of records corresponding to b2b audience data that you input into a particular ad platform. For example, you’ve run a sponsored ad campaign through Facebook and got a 40% match rate. It means that the system found 40 profiles out of the 100 you’ve been targeting.
The trick is that your ads haven’t necessarily been displayed to these 40 people. It might stem from three reasons:
- Those people weren’t interested in your product. The match rate doesn’t take into account audience relevance. So if you saw a high match rate but fewer conversions, the audience list likely contained mostly irrelevant profiles.
- The match rate doesn’t correlate with audience size. If you get a high match rate for a small audience, the campaign won’t pay off with a sufficient ROI. Conversely, a larger audience with a low match rate can yield a significant ROI.
- Paid audience list might be irrelevant. Lists providers might manipulate marketers by offering them lists with high match rates. Nonetheless, those lists won’t guarantee a good ROI because they don’t suit your business goals.
Finally, match rates can’t tell you whether the audience visits the platform regularly.
Identity Resolution as a Comprehensive Data Quality Marker
Whereas you can still use match rate when evaluating b2b audience data quality, we’d recommend you look into more metrics. You should primarily focus on the following:
- Data relevance
- Audience size
- Targeting precision.
To make your custom audience dataset actionable and profitable, try to nurture the identity resolution. It requires appending non-obvious behavioral signals to customer profiles that help to identify their needs.
Targeting platforms like Primer can source and link missing data points to audiences based on business details. Therefore, you can build a hyper-targeted audience list that will most likely hit the right prospects.
Such a strategy allows you to rely on a reach rate that measures your true addressable audience.
How Reach Rate Helps With Ad Campaigns Optimization
Reach rate is the ratio of your campaign’s actual reach and the total size of the list-based audience. This metric provides you with a better understanding of audience size and measures the impact of your campaigns.
The reach rate is worth considering due to two main reasons:
- Budget optimization. Paid campaigns are all about being competitive in auctions for ad placement. Reach rate visualizes the addressable audience. Therefore, you can predict the size of potential profit and allocate a proper budget to meet a good ROI.
- Reassessment of campaign goals. Marketers often give too much credit to conversions when running Facebook or LinkedIn campaigns. But that’s a sure way to make your audience too narrow. If you aim for a higher reach rate, set ‘awareness’ or ‘traffic’ as your KPIs. It would greatly benefit campaigns focused on top or mid-funnel audiences.
Opt for Hyper Precise Targeting for Impressive Paid Ad Performance
Utilizing an ad targeting platform like Primer allows you to fetch valuable data points from 12+ data providers. Alongside higher match rates, it will enable you to effectively orchestrate audience data and apply tried-and-true strategies to win outstanding reach rates.
same comment as in the previous guest post 1) not sure illustrations are accepted at all 2) not sure we want to provide illustrations that are identical to what we have on our website