On Oct 22, LinkedIn made its professional targeting available for connected TV through Google's Display & Video 360. Advertisers can now aim streaming ads at people by job title, industry and seniority, among other attributes. It is a reasonable move. LinkedIn knows where people work better than almost anyone, and B2B marketers have long wanted a credible way onto the TV screen. But a television belongs to a household, not to a job title. Whether a CTV ad reaches a procurement director or her teenager depends on how the platform connected her profile to that living room, and LinkedIn hasn't said how it does that.
LinkedIn has sold CTV ads in its own Campaign Manager since 2024. This year it started offering its audiences to outside DSPs. The Trade Desk and Amazon DSP came first, and DV360 is the latest. The audiences are packaged with streaming inventory sold through Microsoft's supply-side platform and delivered as private marketplace deals that buyers activate in their DSP.
A few details matter for planning:
LinkedIn hasn't disclosed what determines whether the product works: how a LinkedIn member connects to a TV, what share of a target audience it can reach, and how often the person who sees the ad is the person who was targeted.
The average US household has about 2.5 people. Whoever is home watches a streaming TV in the living room. In practice, a CTV ad aimed at a CFO targets the CFO's household, and the CFO may or may not be on the couch.
That isn't a reason to avoid B2B CTV. Plenty of consumer brands accept household-level delivery because the household is the buying unit. B2B is different because the buyer is one person in that household, and often one person in a company buying group. The useful questions are what share of impressions land in households that actually contain a target, and whether the plan accounts for the ones that don't.
There are three broad ways to connect a person known for their job to a television. Each has strengths and each fails in its own way.
1. Platform login. A platform knows a member's profile and uses its own identity graph to connect that member to devices, including TVs. This is likely the closest to LinkedIn's approach, though LinkedIn hasn't described it. The strength is the quality of the professional data: people keep their profiles current because it matters to their careers. The weakness is the jump from profile to TV, which happens inside a graph buyers can't inspect, and which is only as good as the signals that tie a person to a household's devices.
2. Deterministic person-to-address records. A known professional is matched to a residential address from compiled records, and the address is connected to the household's internet connection and the devices on it. The strength is that each step can be checked against a record rather than inferred. The weaknesses are freshness (people move and change jobs) and coverage, since not every professional can be tied to a home address with confidence.
3. IP and device inference. Devices are grouped by the networks they use, and networks are classified as business or residential. This works well for reaching people at large offices with dedicated networks. It works less well for everyone else: small businesses on residential internet plans, coworking spaces, and employees on mobile networks. It's also the method most exposed to browser and operating system privacy changes.
Most products combine these. The point for buyers isn't to pick a winner. It's to know which method is doing the work in the product you're buying, because that tells you where it will be wrong.
Remote and hybrid work. About a quarter of paid workdays in the US are worked from home, according to WFH Research's July 2026 survey, and about 38% of full-time employees are fully remote or hybrid. That cuts both ways for B2B CTV. More decision-makers are home during the day, near a TV, but office-based targeting reaches fewer of them, and the household they're in on Tuesday afternoon is the same one they watch from on Saturday night.
Small offices on residential networks. Many small businesses run on the same internet plans as households. IP-based business targeting often misses them or classifies them as homes. For advertisers selling to small businesses, like VistaPrint, that's most of the market.
Frequency spread across a household. A frequency cap of three per household may mean the target saw the ad once and their partner saw it twice. Household caps are the right tool for controlling waste. They don't show how often the decision-maker saw the ad.
Stale job data. Every method depends on knowing who works where. Job changes break the link between a person and a company, and in B2B that link is the whole point.
Brand lift studies are a reasonable start, but they measure recall among a surveyed sample, not whether the right accounts moved. For B2B, these measures are more useful:
None of these is perfect. Together they say more than impressions and lift alone.
Ask for the answers in writing, and ask every provider, including the ones you already use.
This section reflects Semcasting's perspective.
Semcasting matches business and consumer records to households and IP addresses, and we run B2B audiences on CTV. So we compete in this market, and you should read this article with that in mind. LinkedIn has professional data that nobody else has, and its move into DSPs is good for buyers who want more options. We think the match between a job title and a TV should be something a buyer can inspect and measure, regardless of who provides it.
Ask us the same six questions.