PPC & Pay-Per-Click Advertising: Types, Costs & Platforms 2026

PPC advertising, or pay per click, is the model where advertisers pay a fee each time someone clicks their ad rather than paying for impressions or airtime. That basic definition hasn't changed since Google introduced AdWords in 2000. What has changed is the number of places you can run PPC, how much each platform costs, and how much manual effort it takes to run all of them well. Most explainers stop at "here's how PPC works on Google." This post covers the full landscape — Google, Microsoft/Bing, Meta, LinkedIn, Amazon, TikTok — what each costs, where each fits, and how to manage a multi-platform PPC account without hiring a specialist for every channel.

If you're only running PPC on one platform, you're likely leaving cheaper clicks or better-qualified traffic on another. If you're running PPC on three or four platforms, you already know the real challenge isn't strategy — it's the operational load of managing bids, budgets, and creative refreshes across accounts that don't talk to each other.

What PPC Advertising Actually Means in 2026

PPC has expanded well beyond search ads. The term now covers:

• Search ads — text ads on Google and Bing triggered by keywords
• Shopping ads — product listings with images and prices, mostly on Google Shopping and Amazon
• Social PPC — image/video ads on Meta, LinkedIn, TikTok, Pinterest, X
• Display and programmatic — banner ads across ad networks, paid per click or per thousand impressions
• Retail media — Amazon Sponsored Products, Walmart Connect, Instacart Ads

The common thread is the billing model, not the ad format. Some platforms have shifted a meaningful share of spend to auto-bidding toward conversions rather than clicks, but "PPC" remains the umbrella term because click-based billing is still how most accounts are structured and reported.

The practical implication: "PPC advertising pay per click" today is a portfolio decision, not a single-channel one. The question isn't "should I do PPC" — it's "which combination of PPC platforms matches my funnel and budget."

Types of PPC Advertising: A Practical Breakdown

Here's how the major types break down by intent and use case.

Search ads capture existing demand. Someone types "commercial espresso machine repair" into Google, and your ad appears because they're already looking. This is the highest-intent, typically highest-CPC form of PPC.

Shopping/product ads work similarly but show the product directly — image, price, merchant name — before the click. Conversion rates tend to be higher than text search ads because the buyer sees the price before clicking, which pre-qualifies traffic.

Social PPC creates demand rather than capturing it. You're interrupting someone's feed, not answering a query. CPCs are usually lower, but so is intent — you need stronger creative and more touchpoints before conversion.

Display/programmatic is mostly used for retargeting or top-of-funnel awareness at scale. Clicks are cheap, but so is the traffic quality unless it's tightly retargeted.

Retail media (Amazon, Walmart) sits close to the point of purchase. If someone's already searching Amazon for "wireless earbuds," a Sponsored Products ad is arguably higher-intent than a Google search ad for the same term, because they're on a shopping platform with a cart already in mind.

Type of PPC	Primary Intent	Typical CPC Range	Best For
Google Search	High (active search)	£1–£15+	Lead gen, high-consideration purchases
Google Shopping	High (product research)	£0.30–£3	Ecommerce with catalog
Microsoft/Bing Search	High, smaller pool	£0.50–£8	B2B, older demographics, lower competition
Meta (Facebook/Instagram)	Low-medium (interrupt)	£0.40–£2	Brand awareness, ecommerce, retargeting
LinkedIn	Medium-high (B2B)	£4–£15	B2B lead gen, recruiting
Amazon Sponsored Products	High (transactional)	£0.30–£2.50	Ecommerce sellers on Amazon
TikTok Ads	Low-medium	£0.30–£1.50	Younger demographics, DTC brands

These are directional ranges — actual CPCs vary heavily by industry and competition. A "personal injury lawyer" search click on Google can run £50+; a broad-interest Meta ad in a low-competition niche can cost £0.20.

PPC Advertising Cost by Platform: What Actually Drives the Number

CPC isn't set by the platform — it's set by the auction, which is driven by three things: competition for the audience, your quality/relevance score, and your bid strategy.

Google Ads has the highest average CPCs of the major platforms because it captures the highest-intent traffic and has the most advertiser competition. Legal, insurance, and finance keywords commonly exceed £20–£40 per click. Ecommerce and local service keywords are usually £1–£8.

Microsoft Ads (Bing) typically runs 20–40% cheaper than Google for the same keywords, because there's less advertiser competition. Search volume is lower (Bing handles roughly 5-6% of global search vs Google's ~90%), but for B2B and desktop-heavy audiences, the cost-per-lead is often better than Google.

Meta Ads costs are driven by audience size and competition for that audience, not query intent. CPCs are cheap, but cost-per-lead or cost-per-purchase can still be high if your funnel and creative aren't converting — cheap clicks that don't convert are still expensive customers.

LinkedIn Ads is the most expensive per click of the mainstream platforms, often £5–£15+, because you're paying for job-title and company-size targeting that no other platform offers. It's only cost-effective when the deal value justifies it — B2B SaaS, recruiting, enterprise services.

Amazon Ads costs are ACOS-driven (advertising cost of sale) rather than pure CPC, but the underlying bid mechanics are still pay-per-click. Costs are highly category-dependent — a saturated category like phone cases can have brutal CPCs, while a niche category can be under £0.50.

If you want a concrete estimate for your own account rather than these industry ranges, run your numbers through the free Google Ads forecast tool — it projects clicks, cost, and conversions based on your actual budget and keywords rather than blended averages.

Choosing PPC Platforms: A Framework, Not a Popularity Contest

The most common mistake in multi-platform PPC is choosing channels based on where competitors advertise rather than where your buyer actually is at the point of decision.

Ask three questions for each platform you're considering:

1. Is my buyer actively searching, or do I need to interrupt them? Search platforms (Google, Bing) win for active searchers. Social platforms (Meta, TikTok, LinkedIn) win for creating demand among people not yet looking.
2. What's my average order value or deal size? Low AOV ecommerce (£20-£80) rarely justifies LinkedIn's CPCs. High-ticket B2B (£10k+ deals) can absorb them easily.
3. Do I have a product catalog or a service? Catalogs perform well on Shopping ads and Amazon. Services perform better on search and social lead gen.

A local HVAC company with £3k/month budget should probably be 80% Google Search, 20% local service ads — not spreading thin across five platforms. A DTC skincare brand with £3k/month is better served by Meta and TikTok than Google Search, where CPCs for "anti-aging serum" are brutal and competitive.

The businesses that genuinely benefit from running 3+ PPC platforms simultaneously are usually spending £15k+/month, have distinct funnel stages that map to distinct platforms (LinkedIn for top-of-funnel B2B awareness, Google Search for bottom-of-funnel intent capture), or sell a product that fits multiple channels (ecommerce brands running Google Shopping, Meta, and Amazon simultaneously).

The Operational Problem With Multi-Platform PPC

Here's the part most PPC guides skip: running PPC well on one platform is a part-time job. Running it well on four platforms is a full-time job for a small team, not one person.

Each platform has its own bid strategy logic, its own audience/targeting system, its own creative specs, its own reporting dashboard, and its own optimization cadence. Google Ads' Target ROAS bidding doesn't behave like Meta's Advantage+ campaigns, which doesn't behave like Amazon's dynamic bidding. A media buyer competent in Google Search often isn't equally sharp on LinkedIn Campaign Manager, because the skill sets don't fully transfer.

This is why most agencies specialize by platform, and why in-house teams running true multi-platform PPC tend to be 3-5 people minimum: one search specialist, one paid social specialist, someone owning Amazon/retail media, and someone tying it all together in reporting.

If your account spends £8k/month across Google and Meta, you're likely paying either an agency retainer of £1,500-£2,500/month for that coverage, or absorbing 15-20 hours/week of internal time keeping both accounts optimized — checking search term reports, adjusting bids, refreshing ad creative, reallocating budget between platforms based on which is performing.

Where AI Management Changes the Multi-Platform Math

The reason AI agent management is relevant to multi-platform PPC specifically — not just single-account optimization — is that the bottleneck in running multiple platforms is monitoring cadence, not strategic insight. A human managing four accounts checks each one every few days at best. An agent can check daily, across all connected accounts, without the coverage degrading as you add channels.

AgentikAds runs as an AI agent connected to your Google Ads account via MCP, with Claude as the primary interface. It monitors campaign performance continuously, proposes specific optimizations — bid adjustments, budget reallocation, search term exclusions, ad copy tests — and you review and approve them through a web UI before anything changes live. It's not a black-box autopilot; every recommendation comes with the reasoning behind it, and nothing executes without your sign-off unless you configure specific auto-approval rules.

Currently this focuses on Google Ads, which is deliberate — doing one platform's optimization logic properly (search term mining, bid strategy tuning, budget pacing, quality score diagnostics) beats doing four platforms shallowly. For teams running Google as the primary spend channel with other platforms as secondary, this means the highest-CPC, most complex platform gets daily monitoring without needing a dedicated in-house Google Ads manager. That frees up your team's time to handle Meta, LinkedIn, or Amazon manually or with platform-native automation, rather than spreading thin trying to manually optimize all four.

Common PPC Advertising Mistakes Across Platforms

A few mistakes show up regardless of which platform you're running:

Set-and-forget bidding. Automated bid strategies (Target CPA, Target ROAS, Meta's Advantage+) need 2-4 weeks of stable data to learn properly, but they also need ongoing sanity checks. Left unmonitored for months, they drift — especially when seasonality or competitor activity shifts the auction.

No negative keyword or audience exclusion hygiene. On Google, this means irrelevant search terms burning budget. On Meta, it means overlapping audiences competing against each other in the auction. Both waste spend the same way: budget going to non-converting impressions.

Ignoring platform-specific quality signals. Google's Quality Score, Meta's relevance ranking, LinkedIn's relevance score — all directly affect your CPC. Ads with poor relevance pay more for the same placement. This is often the single biggest lever ignored by advertisers focused only on bids.

Comparing CPC across platforms without normalizing for intent. A £0.50 Meta click and a £4 Google click aren't directly comparable — they represent different points in the buying journey. Judge platforms on cost-per-acquisition or ROAS, not raw CPC.

Building a Realistic Multi-Platform PPC Budget

For a business starting to diversify beyond a single platform, a reasonable allocation model:

• 60-70% to your primary, highest-intent platform (usually Google Search for most industries)
• 15-25% to a secondary platform that matches your funnel stage (Meta for awareness/retargeting, LinkedIn for B2B, Amazon for ecommerce)
• 10-15% held for testing a third platform before committing meaningful budget

This isn't a rigid formula — a DTC ecommerce brand might flip it, putting 50% into Meta/TikTok and 30% into Google Shopping. The point is to avoid splitting budget evenly across platforms by default; each dollar should go where the marginal return is highest, which requires actually measuring performance by platform rather than assuming parity.

Getting Started Without Overextending

If you're currently running PPC on one platform and considering expansion, the sequence that works best in practice:

1. Get your primary platform's cost-per-acquisition to a stable, known number first. You can't judge a second platform's performance if you don't have a clean baseline to compare it against.
2. Pick the secondary platform based on funnel logic, not competitor mimicry — use the framework above.
3. Budget for a genuine 60-90 day test before judging the new platform. Most platforms' algorithms need volume and time to optimize.
4. Decide your operational model before you launch: are you managing this platform manually, via agency, or with AI-assisted monitoring? Don't decide this reactively after you're already three platforms deep and drowning in dashboards.

If Google Ads is your primary channel and you want a clearer picture of what your budget should actually produce before you commit spend, the free Google Ads forecast tool gives you projected clicks, costs, and conversions based on real auction data for your keywords — a useful baseline before you decide how much budget to hold back for other platforms.

The Bottom Line on Multi-Platform PPC

PPC advertising, pay per click at its core, isn't a single-channel decision anymore. The platforms that make sense for your business depend on buyer intent, deal size, and whether you're capturing demand or creating it. Google and Bing win for active search intent. Meta, TikTok, and LinkedIn win for audience targeting and demand generation. Amazon wins at the point of purchase.

The strategic side of choosing platforms is genuinely not that complicated once you apply the intent/AOV/catalog framework above. The hard part is operational: keeping each platform properly optimized without needing a specialist headcount for each one. That's the problem worth solving before you add a fourth platform to your stack, not after.

If Google Ads is eating a disproportionate amount of your team's time relative to its share of spend, see how AgentikAds' AI agent works — it's built specifically to take the daily monitoring and optimization workload off your team's plate for that channel, so you can focus your limited hours on the platforms that need more hands-on creative and audience work.