In brief: Your buyer decides this, and price follows from that. LinkedIn publishes where every targeting option gets its data, and the options are not equally reliable. It allows an audience of 300 and suggests 300,000 for Sponsored Content. Meta publishes no equivalent, so its B2B targeting cannot be checked the same way.
Most posts about these two start with price. Price is the least useful place to start. We have covered that ground already, in what LinkedIn ads cost and in what Meta ads cost in India.
The question that decides a B2B campaign is different. Can you name the person you are trying to reach, and can the platform find them?
That is answerable, because LinkedIn publishes where every targeting option gets its data. What you find there is worth more than any price table.
Key Takeaways
- LinkedIn allows an audience of 300 members and suggests 300,000 for Sponsored Content.
- It documents the data behind each targeting option, and the options differ sharply in reliability.
- Job seniority and job function use a taxonomy with no AI inference. Job title uses an AI model.
- Company size targeting rests on what a page admin typed, or on a headcount estimate.
- Meta publishes no equivalent, so its B2B targeting cannot be audited the same way.
What Actually Separates LinkedIn and Meta Ads for B2B?
Whether the platform knows what your buyer does for a living. That is the whole gap. Price is a result of it. A platform that knows job titles can be aimed. A platform that knows only interests has to guess at it.
LinkedIn runs on work data that members type in themselves. People keep their job title current because their career depends on it. No other ad platform can say that.
Meta knows a great deal about a person. Very little of it is what they do at work. For a purchase manager in Vatva, that is the whole problem.
How Reliable Is LinkedIn's B2B Targeting?
Steadier than Meta’s, and less even than the sales pitch claims. LinkedIn documents the data behind each targeting option. Read that page and the options stop looking equal (targeting options). Two of them turn out to be steadier than the one most firms pick.
Job title is the one most firms pick, and it is the most worked on. It is also the one to watch. LinkedIn says the data is “primarily member account input, with some business logic and inference”, and that “no third-party data is used”. Then it explains the inference.
When somebody types a free-text title, LinkedIn says “rules and inference models are used to infer the job title”. In some cases “a MultiLayerPerception (MLP) AI model” classifies that raw string into a standard title.
Two options work differently. Both job function and job seniority are mapped from titles through what LinkedIn calls its “proprietary taxonomy”. For each one the page states plainly: “no AI modeling or inference is used”.
That last row is the one to sit with. LinkedIn says company size targeting “primarily uses Page admin account input data”. If no admin entered a size, “the company size is determined by the number of member accounts associated with the Page”.
So a 400-person firm whose page nobody updates can read as a small one. Filter hard on company size and you can quietly exclude your best prospects.
You can also skip the guessing and upload a list of companies. LinkedIn requires “at least 300 rows for a successful upload”, and recommends “1,000 or more companies, organizations, or schools” (company lists). Most Ahmedabad firms do not have that list yet. That is the honest reason this route stays on the shelf.
How Small Should a B2B Audience Be?
Far larger than instinct says. LinkedIn allows a minimum of 300 member accounts. In the same breath it tells you to stay well clear of that floor (audience size). The number it suggests instead sits a thousand times above that floor.
The guidance is blunt. The minimum for an ad set “is 300 member accounts”, while LinkedIn suggests “a minimum of 50,000 to drive results”. For Sponsored Content it goes further and suggests “a minimum of 300,000”.
This is where most first B2B campaigns die. A firm picks four job titles in one city, lands on 900 people, and cannot work out why nothing spends. LinkedIn even warns against it, advising you to “avoid limiting your audience by targeting only a few job titles” (targeting best practices).
Location is not optional either. LinkedIn states that “location is a required targeting facet”. Every audience is therefore cut down once before you add a thing.
The logic inside an audience trips people up too. Select several job titles and a member needs only one of them, because LinkedIn says they “could have any of the job titles selected”. Add a second facet and it tightens. With seniorities and functions together, members “will need to match one of the selected job seniorities and one of the job functions”.
One more trap sits in matched audiences. LinkedIn warns about them. If you apply such a segment, “it’s important the segment matches more than 300 member accounts as location might decrease your audience size”.
The way out is the combination LinkedIn itself recommends. Pair job function with job seniority, and stop listing titles. That widens the pool and keeps the seniority you care about.
When Does Meta Make More Sense for B2B?
When your buyer cannot be named by job title. Plenty of real B2B buyers cannot. The owner of a 12-person workshop in Odhav keeps no LinkedIn profile. No seniority filter will find him there, because he is not on the platform.
That comes from our own work across 100+ brand accounts. No platform puts a figure on it. It is still the best reason to put B2B money into Meta. If the buyer runs the place himself, Meta reaches him and LinkedIn will not.
Cost matters at that point too, and the comparison is set out in our guide to Google Ads against Meta ads.
Can You Audit Meta Targeting the Same Way?
No, and the gap is worth naming. Everything above comes from pages LinkedIn puts out about its own data. We looked for Meta’s equivalent and could not read one. Its help pages do not render without JavaScript, so there is no primary text to quote.
We are not claiming Meta hides it. We are saying you can check LinkedIn’s working. You cannot check Meta’s, and for a B2B budget that is a real difference.
That changes how you test. On LinkedIn you can work out why an audience is wrong. On Meta you change a thing and watch the number.
How Do You Test LinkedIn and Meta Ads for B2B?
One at a time, and LinkedIn first if your buyer has a job title. Give it four to six weeks and an audience large enough to spend. Then judge it on cost per qualified lead, which is the only number that pays a salary.
Build the audience by function and seniority, add your city, and check the size before anything else. If it reads under 50,000, widen it before you add budget.
Attach a form so the mobile half of your audience can reply in two taps. Our note on LinkedIn Lead Gen Forms covers that in full.
Only then run the Meta test. Use the same offer and the same landing page, so the two numbers mean something side by side.
What We Do for Ahmedabad Clients
The audience gets built before the creative, because the audience decides whether the creative ever gets seen. That order is the opposite of how most agencies work, and it is why our first tests rarely stall. It costs one extra afternoon up front.
- Write down the buyer in one sentence, including their job title and their company size.
- Build the LinkedIn audience by job function and seniority, never by a short list of titles.
- Check the audience size against LinkedIn’s own 50,000 suggestion before any money moves.
- Run Meta only for the buyers LinkedIn cannot name, which is often the owner.
Step 1 is the one clients skip. A buyer you cannot describe in a sentence is a buyer no platform can find. That is a problem with the offer, and no ad account will solve it.
Start Here
Write your buyer down first, in one sentence. Job title, seniority, company size, city. If you can fill all four, LinkedIn can probably find them and deserves the first test. If you cannot, the problem is upstream of any ad platform.
Owners who run the place are the usual case, and Meta with a strong offer is the better use of the money. A job title field will never show them to you.
Then check one number before you spend anything: the audience size. Under 50,000 and you are about to fund a campaign that cannot deliver. If you would rather hand it over, that is what our LinkedIn marketing team does.
Frequently Asked Questions
Are LinkedIn ads always better than Meta ads for B2B?
No. The deciding thing is your buyer, and the platform follows from that. If the buyer holds a job title inside a company, LinkedIn can aim at them. If the buyer owns the firm and barely uses LinkedIn, Meta reaches them and LinkedIn will not, whatever you spend.
What is the smallest LinkedIn audience worth running?
LinkedIn allows 300 member accounts, and suggests 50,000 as a minimum to drive results, rising to 300,000 for Sponsored Content. Treat anything under 50,000 as a warning sign. A narrow audience feels sharp and often just starves the campaign.
Why is company size targeting unreliable?
Because it rests on what a page admin typed. LinkedIn says company size targeting primarily uses page admin input. Where no admin entered a size, it falls back to the number of members associated with that page. A large firm with a neglected page can therefore read as small.
Should I target job titles or job functions?
Functions paired with seniority, in most cases. LinkedIn advises against limiting an audience to a few job titles. Job function and seniority are mapped by taxonomy with no AI inference, while job title passes through an AI model. The pairing is both wider and steadier.
Can I run both platforms at once?
You can, though not on a first test. Run both together and you cannot say which audience worked. B2B numbers are often too small to read two tests at once. Run LinkedIn, then Meta, with the same offer on both.
