Paid Social Lead Generation
What it is
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.
Who it's for
Anyone who:
- Is spending >$10k/month on digital ads
- Has an ICP of >50,000 people
Metric
Expect to see improvements in lead volume, reach, and cost-per-lead efficiency.
Relevant channels
- LinkedIn, Facebook, Instagram, Youtube, GDN, Gmail, Twitter, Reddit, Quora
How it’s done today
Marketers typically use one of three options to create audiences in ad platforms:
- Use the platform's native targeting filters (e.g. Interests on Facebook; Job Titles on LinkedIn, etc.)
- Import custom audiences using pixels or uploaded lists
- Build lookalike audiences
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.
What to do instead
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:
- Conversion rate: You’re serving messages to prospects based on filters and attributes that don’t exist natively in ad platforms. Better targeting = better results.
- Efficiency: Many ad clicks and form submits are garbage. With more granular targeting you can pre-qualify your audience members and not waste ad spend.
- Reach: You’ve expanded beyond SEM and LinkedIn to serve ads to your B2B buyer on B2C ad platforms.
- ROI: By knowing exactly who is in your audience and looking at all your conversions, regardless of source, you can assess whether your ads are lifting conversions in other channels, like direct or organic traffic.
How it works
1. Plan
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:
- Funding (Data sources: Crunchbase, Pitchbook, Harmonic)
- Website traffic (SimilarWeb, SEMRush, DataforSEO)
- Tech stack (Builtwith, Aberdeen, HG Insights, PurpleSonar)
- Social following (Harmonic, Charm.io, Phantombuster)
- Open job postings (Rocks & Gold, Sourcestack, Predictleads, Jobspikr)
- Job change (UserGems, Phantombuster)
- Department headcount (Apollo, ZoomInfo, PeopleDataLabs)
- Headcount growth (Harmonic, PeopleDataLabs)
- Advertising spend (Adbeat)
- Ecommerce/DTC attributes (Charm.io, Storeleads, PipeCandy)
- Custom intent sources (G2, Clearbit Reveal, 6sense)
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:
- Facebook: 100 leads to create custom audience but we recommend at least 30,000 leads for reasonable last-click conversion performance
- LinkedIn: 300 leads to create a matched audience
- Google: 1,000 leads to technically create a customer match audience but we recommend at least 50,000 leads for optimal reach
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.
2. Build your campaign
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):
- Set your campaign objective to be traffic. Do not allow the ad platform algorithm to optimize for conversions and instead optimize for reach. Given the limited audience, optimizing for leads will be incredibly expensive. Don’t worry – we’ll explain below how you’ll still measure performance at the lead level.
- Ignore conventions on frequency cap. Conventional wisdom says high frequency burns budget on wasted clicks and fatigues your campaign. But because you’re targeting your exact ICP with this method, you want more frequency not less. The winning strategy is to consistently stay in front of prospects in case an internal buying trigger occurs.
- Don’t worry about budget. Because your audience is limited, there is a natural ceiling on ad inventory which means it’s very hard to overspend. You can even set aggressive ceilings on your daily or weekly budget and see if you can even max those out.
- Consistently rotate creative. Use fresh ads to continuously educate prospects on your product’s value. Consider creating sequential messaging. You can even take audience members on a messaging journey - from an initial click, to a mid-funnel messaging (using pixel-based retargeting) to a nurture/closing message. Consider duplicating campaigns. If you’re noticing a decline in reach, do this to “reset the algorithm.”
If your audience is >50k (FB or Google):
- Test setting your campaign objective to be lead gen. Your audience size is likely large enough where optimizing for lead capture will be cost effective.
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.
3. Launch with custom creative
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.
4. Measure results with audience cohort tracking
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.
Results
Primer customer Air saw the following results after implementing this playbook:
Recap: How using multiple data sources can help you unlock paid social
About us
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