Every B2B marketer has experienced the law of diminishing returns on paid social: That point at which efficiency starts dropping no matter what you try. The reason? Unqualified traffic. You’ve already picked off ready-to-buy prospects, and now you’re reaching an increasingly wider audience with poor results.
You’re officially at the point where native targeting isn’t enough. You need more data to more accurately construct your audience, unlock higher match rates on B2C channels, and track non-last click, view-through conversions.
This guide shows you how to unlock B2C social channels to reach your B2B buyers by layering on multiple data sources.
Anyone who:
Expect to see improvements in lead volume, reach, and cost-per-lead efficiency.
Marketers typically use one of three options to create audiences in ad platforms:
Eventually, they run into at least one of the following problems:
The underlying problem is that ad platforms are not built to give you transparency into your audience composition or all the filters you need to accurately represent your ICP.
Layering multiple data sources on top of each other can help you drill down into a tight audience of pre-qualified prospects. Enhancing this audience can help you boost match rates on B2C platforms, allowing you to reach your pre-qualified prospects beyond LinkedIn (aka everywhere). When you target these prospects cross-channel, and quantify the impact of your spend beyond last-click conversions, you’ll see dramatic increases in growth and efficiency. You’ll have unlocked:
Ad platforms like Linkedin have very limited filters, which means you end up targeting a broad swathe of potential prospects instead of a highly qualified list. When you access data from multiple providers, you can use much more specific filters and attributes.
Most B2B performance/demand gen marketers are familiar with uploading CSVs to create custom audiences on LinkedIn, Facebook, and Google. Oftentimes, they’re exporting data from their CRM, a third-party data provider like ZoomInfo or Crunchbase, vlookuping it together, reformatting it, and then, finally, uploading it. While annoying and manual, this works for LinkedIn because LinkedIn can create high matches with a work email or company domain.
However, B2C platforms like Meta, Google, Twitter require different data. You need to take a person’s business identifiers (e.g. company, role, email address) and connect it to their personal profile on social platforms. It’s like using translation software to translate one language into another.
So if you're going to build an audience using multiple data providers, the first step is to think through the most important filters you’d use to identify your audience. Here are some example identifiers and data sources that could provide them:
The next step is to identify the data sources that can translate your B2B attributes into B2C data to generate a high match rate. Each ad platform has different requirements. For example, hashed personal email drives 70% of the match rate in Meta, but there are 10 other fields that Facebook uses to say Kevin Delanowitz on LinkedIn is @kevin_d on Instagram. Meanwhile, Tiktok requires a MAID (Mobile Ad ID). This data is considered PII (personally identifiable information) so make sure if you get it, you get it from compliant sources like Fullcontact, PeopleDataLabs, Pipl, etc.
However, there’s an inherent tension between audience size and audience quality. If your audience is too small, you won’t get enough results and if it’s too big, your ad spend will be inefficient. Here’s a quick guide to audience minimums by channel:
Audience minimums by channel:
Once you’ve stitched together all your data (or built it in an easy-to-use platform like Primer), you’re ready to sync your audience into your ad platforms.
To sync your audience into your ad platforms, you can either upload a CSV or leverage existing CRM tools like Hubspot and Marketo. However, these tools don’t easily allow you to store PII like personal emails inside them, so they’re less effective for B2C platforms.
Next, you need to define the goal of your campaign in individual ad platforms. This, in turn, will be dependent on the size of your audience. With LinkedIn, smaller audiences (<10K) can generate leads, but we find that with consumer social media platforms picking the right campaign objective is key for a B2B conversion.
Here’s our guide to picking the right goal based on the size of your audience:
If your audience is <50k (FB or Google):
If your audience is >50k (FB or Google):
TIP! Explore lookalike audiences. Because of the high match rates of your custom audience, they tend to make good seed lists for lookalike audiences. Just make sure to watch lead quality and CPL.
When you build highly targeted audiences, you have the ability to make your creatives as specific as possible. For example, at Primer, we defined our initial ICP as early-stage startups from Seed to Series B. Then, we built a more specific audience of just decision makers of startups that have been through YCombinator and designed creatives to be as tailored to them as possible - and the results speak for themselves.
Another example – for an HR software solution, we could build a list of all HR leaders at companies with employees 100+ who were hired in the last 30 days and serve them this bespoke creative.
When you target your audience natively on ad platforms, the common way to measure results is via last-click conversion via UTM params.
But very few B2B purchases are made from one click to an ad.
When you build a custom audience using multiple data sources, attribution becomes dead simple because you know upfront who will be receiving your ads. This means you can measure the percent of leads who converted after being served an ad – whether they clicked on the ad or just viewed it – we call this audience cohort tracking. To calculate your conversion rate, simply look at the number of leads who were served your ad and the number of leads who signed up, regardless of last source.
Below you’ll see real results. We always see a spike in direct signups when we turn the dial up on our Facebook audience spend. There is a proven correlation and with audience cohort tracking you can measure it on an individual level.
Primer customer Air saw the following results after implementing this playbook:
Primer unlocks hyper-precise targeting for B2B marketers. Get better leads and spend less. Sign up.