Keyword Research for Search Ads: Practical PPC Guide

Keyword research in search advertising is often treated as a technical task: open Keyword Planner, export a list of search terms, filter by volume, add match types, and launch a campaign. That approach is too narrow. A strong keyword strategy is not just a list of words. It is a map of demand, intent, risk, landing pages, and future reporting.

In modern Google Ads and Microsoft Advertising, keywords no longer work in a purely mechanical way. Exact match does not mean a strict character-by-character match. Broad match can reach searches outside the literal keyword wording. Smart Bidding uses many signals to evaluate each auction. The advertiser's job is not to manually guess every possible phrase. The job is to describe the business correctly, separate demand by intent, build a useful structure, protect the budget with negative keywords, and continuously refine campaigns through real search terms.

This guide explains a practical approach to keyword research and campaign structure: starting from the product and the customer's language, grouping keywords by intent, building thematic ad groups, using match types as a risk control, preparing negative keywords before launch, analyzing search terms, and connecting keywords with ads and landing pages.

Start With the Product, Service, and Customer Language

Keyword research should start with the business, not with a tool. Before collecting thousands of keyword ideas, advertisers need to understand what the company sells, who it sells to, what problems it solves, and how customers describe that need in their own words.

This is especially important in B2B and complex categories. A company may call its product an end-to-end marketing analytics platform, while customers search for connect ad spend to CRM, marketing attribution dashboard, revenue reporting software, or how to track marketing ROI. A restaurant equipment supplier may describe itself as a HoReCa equipment distributor, while buyers search for commercial kitchen equipment supplier, restaurant dishwasher machine, walk-in cooler for restaurant, or equipment for opening a cafe.

If the keyword list starts only from the company's internal terminology, it may look correct but still miss real market demand. That is why the first step is to collect several layers of customer language:

• product and service names;
• website categories;
• commercial offers;
• customer questions;
• briefs and form submissions;
• CRM data;
• sales team conversations;
• Google Search Console queries;
• search suggestions;
• customer reviews;
• competitor websites;
• real search terms from existing campaigns.

The goal at this stage is not to collect the largest possible list. The goal is to understand how the market describes the need. The same product can appear in several language layers: technical, commercial, problem-based, comparative, and transactional.

For example, business loans can be described in several different ways:

Strong keyword research starts with understanding these differences.

Divide Keywords by Intent

After collecting the initial keyword list, the next step is to classify keywords by intent. Without intent-based grouping, campaign structure quickly becomes messy. The same ad group may end up mixing users who want to buy, compare, learn a definition, find a job, or download a template.

In search advertising, the following intent types are usually useful:

Transactional Intent

The user is ready to take action: buy, order, request a quote, apply, book a demo, or contact sales.

Examples: buy commercial dishwasher for restaurant, request quote restaurant equipment, apply for business loan, book marketing analytics demo.

Commercial Investigation

The user is comparing solutions, suppliers, products, or providers.

Examples: best CRM analytics platform, top restaurant equipment suppliers, business loan providers for small business, commercial oven brands comparison.

Solution-Aware Intent

The user understands which type of solution they need but has not yet selected a product, vendor, or provider.

Examples: marketing attribution software, freight forwarding company, commercial kitchen equipment supplier, restaurant refrigeration equipment.

Problem-Aware Intent

The user describes a problem but may not know the exact category of solution.

Examples: how to track marketing ROI, equipment needed to open a cafe, how to finance restaurant expansion, reduce shipping delays for imports.

Informational Intent

The user is looking for an explanation, instruction, definition, or educational material.

Examples: what is freight forwarding, business loan requirements, commercial dishwasher maintenance guide, CRM analytics meaning.

Employment Intent

The user is looking for a job, salary information, vacancies, or training.

Examples: restaurant equipment technician jobs, freight forwarding salary, marketing analytics course, business loan officer vacancy.

Not all intent types are equally valuable for PPC. Transactional and commercial intent are usually closer to revenue. Problem-aware searches can work in expensive B2B categories, but they require stronger landing pages and a longer-funnel strategy. Informational searches may be useful in some categories, but they usually need a separate offer, budget, and KPI. Employment intent should be excluded from most commercial campaigns.

The key principle is simple: intent should shape structure. Queries like buy commercial oven, commercial oven repair manual, and commercial oven jobs should not sit in the same ad group. They may contain similar words, but they represent different business meanings.

Group Keywords Into Thematic Ad Groups

Once keywords have been classified by intent, they should be grouped into thematic ad groups. A strong ad group brings together keywords that:

• belong to one clear theme;
• represent one type of intent;
• can use similar ad copy;
• can lead to one relevant landing page;
• have similar commercial value;
• require similar negative keywords.

An ad group should not be a container for words that look similar. It should be a working unit of relevance: keyword, ad copy, landing page, and conversion path.

For example, a restaurant equipment supplier could use the following structure:

This structure makes ad copy more precise. In the commercial dishwashers ad group, headlines can focus on professional dishwashing equipment. In the full kitchen setup ad group, the message can focus on complete restaurant equipment packages, equipment planning, and quote requests. If all keywords are placed into one broad ad group called “Restaurant Equipment,” the ads become generic, the landing page becomes less specific, and search terms analysis becomes less useful.

Modern campaign structure is moving away from overly granular SKAG structures, where every keyword gets its own ad group. Close variants, automation, and Smart Bidding need enough data to work efficiently. But that does not mean everything should be consolidated into one ad group. The practical middle ground is thematic ad groups: focused enough to maintain relevance, but not so fragmented that they split data and complicate management.

Do Not Mix Products, Services, or Goals That Are Too Different

One of the most common mistakes in search campaigns is mixing different products, services, audiences, and business goals within the same structure. This makes it harder to control budgets, bids, ads, landing pages, and reporting.

A HoReCa equipment supplier may sell:

• new equipment;
• refurbished equipment;
• equipment rental;
• repair and service;
• spare parts;
• full restaurant setup packages;
• bar equipment;
• hotel kitchen equipment;
• dark kitchen equipment.

All of these may belong to the broad topic of restaurant equipment, but from an advertising perspective they are different products, different intents, and often different business models.

A query like commercial dishwasher for restaurant should not be mixed with commercial dishwasher repair near me if the company sells new equipment and does not provide repair services. A query like used restaurant equipment auction should not lead to a premium new-equipment landing page if the business does not sell used equipment. A query like equipment for opening a restaurant may need a completely different page than walk-in freezer for restaurant.

The same logic applies to campaign goals. The structure should not evaluate the following actions as if they were the same:

• product purchase;
• consultation request;
• catalog download;
• quote request;
• demo booking;
• service department call;
• job application.

If goals are different, the structure should reflect that difference. In some cases, different ad groups are enough. In other cases, separate campaigns are needed, especially when goals have different budgets, bids, conversion actions, or economics.

A useful test is this: “Can I write one strong ad and choose one logical landing page for this keyword group?” If the answer is no, the keywords should be separated.

Use Match Types as Risk Management

Match types are not just a technical keyword setting. They are a way to control risk and decide how much freedom the algorithm should have.

Exact match gives the highest level of control. It is useful for the most valuable and clearly defined intent: brand queries, high-intent categories, expensive B2B searches, and keywords with proven conversion value.

Phrase match provides a balance between control and expansion. It can cover additional wording within a clear theme without expanding as widely as broad match.

Broad match provides the widest expansion. It can discover relevant searches that the advertiser did not add manually. But it requires high-quality data, Smart Bidding, negative keywords, strong landing pages, and regular search terms reviews.

For example, the keyword commercial dishwasher for restaurant can behave differently depending on match type:

In a new account, it is safer to start with exact and phrase match for the clearest commercial searches. Broad match should usually be tested with limits: a separate campaign, separate budget, strong negative keyword lists, and clear evaluation criteria.

In a mature account, broad match can be more useful. If the system receives qualified leads, revenue, pipeline, or offline conversion data, it can better distinguish valuable demand from weak demand. But if optimization is based only on any form submission, broad match can scale cheap but low-quality leads.

Match types should not be selected based on habit. They should be selected based on the account's data maturity and risk level. The less data the account has and the more expensive the mistake, the more control is needed at launch. The stronger the tracking and economics, the more safely the account can expand.

Prepare Negative Keywords Before Launch

Negative keywords should not be left only for post-launch cleanup. Search terms will show real irrelevant queries, but many obvious exclusions can be predicted before the first click. This is especially important in expensive categories, where a few bad clicks can already cost meaningful money.

Before launch, advertisers should prepare starting negative themes. They depend on the category, but in B2B campaigns several blocks appear again and again:

Negative keywords should be precise. Universal lists should not be copied blindly. The word used may be irrelevant for a premium distributor of new equipment, but it may be a core theme for a refurbished restaurant equipment marketplace. The word repair may be irrelevant for a seller of new ovens and highly valuable for a service company.

A layered approach usually works best:

Account-level negatives block what the business almost never needs: employment searches, irrelevant education, piracy-related queries, or completely unrelated categories.

Campaign-level negatives block what does not fit a specific campaign. For example, used can be excluded from a campaign that sells only new equipment.

Ad group-level negatives help route traffic between related groups. For example, dishwasher can be excluded from a commercial ovens ad group if queries start crossing between themes.

Exact negatives are useful for delicate cases where a specific query should be blocked without cutting off the entire theme.

Negative keywords are not just cleanup. They are a way to describe the business boundaries to the advertising system.

Analyze Search Terms Regularly

Search terms show the real queries users typed before triggering ads. This report is not only for adding negative keywords. It is one of the main sources for improving campaign structure.

Search terms can help advertisers understand:

• which real phrases customers use;
• which keywords attract irrelevant traffic;
• where broad or phrase match expands too far;
• which queries should be added as exact or phrase keywords;
• which new landing pages are needed;
• which ads should be rewritten;
• where ad group structure is too broad;
• which negative keywords should be added;
• which unexpected demand segments convert.

For example, a restaurant equipment campaign may reveal that users search not only for restaurant equipment supplier, but also for equipment for opening a cafe, commercial kitchen package, restaurant kitchen setup cost, professional dishwasher for small cafe, and walk in cooler installation. These are not just keyword ideas. They are signals for website structure, content, offers, ad copy, and sales scripts.

Search terms should be reviewed especially often during the first weeks after launch. The campaign is still learning, and match types may collect unexpected queries. For expensive lead generation, daily checks during the first days can be justified. Later, the workflow can move to weekly and monthly cycles.

Search terms should not be treated as a complete raw log of every query. Platforms may hide some low-volume or sensitive data. Still, the visible search terms usually provide enough insight to improve structure and reduce risk.

Connect Keywords With Landing Pages and Ads

A keyword does not sell by itself. It works only when connected with the ad and the landing page. If the keyword, ad copy, and landing page talk about different things, the campaign loses relevance, clicks become weaker, and conversion rates suffer.

A strong connection looks like this:

A weak connection looks like this:

In the second case, the user has to search for the relevant product again. The ad does not reinforce the user's intent. The landing page does not continue the search query. As a result, even a good keyword can perform poorly.

For B2B lead generation, the landing page should not only sell but also qualify. If the company sells equipment only to businesses, that should be clear before and after the click. Headlines, body copy, forms, and calls to action can mention:

• restaurants, cafes, hotels, and dark kitchens;
• commercial-grade equipment;
• request a quote;
• professional installation;
• warranty and service options;
• delivery geography;
• product categories;
• minimum order or project type, when relevant;
• business buyer focus.

The same rule applies to SaaS, finance, logistics, and other B2B categories. If a keyword promises a specific problem or product, the landing page should continue that exact line. A query like CRM analytics platform should not lead to a generic “Marketing Solutions” page. A query like business loans for restaurants should not lead to a generic “Financing” page if a more specific landing page is available. A query like freight forwarding from China to US should not lead to a vague “Logistics Services” page when a route-specific or service-specific page can be created.

The keyword, ad, and landing page connection is the foundation of relevance. The more precise it is, the easier it is for the user to understand the offer and for the advertising system to interpret intent.

How to Turn Keywords Into a System

A good keyword structure is not a one-time list. It is a system where each element has a role.

First, the business defines the product and customer language. Then keywords are divided by intent. After that, they are grouped into thematic ad groups. Products, services, and goals that are too different are separated. Match types are used to regulate risk. Negative keywords are prepared before launch. Search terms are analyzed after launch. Ads and landing pages are connected with each important keyword cluster.

The process can be summarized as a sequence of questions:

1. What do we sell?
2. Who is searching for it?
3. What words do they use to describe it?
4. What intent stands behind the query?
5. Which landing page should the user visit?
6. Which ad continues the search query?
7. Which match type is safe for this level of risk?
8. Which negative keywords are needed before launch?
9. What do real search terms show after launch?
10. How should the structure change based on data?

This approach protects campaigns from two extremes.

The first extreme is an outdated mechanical structure with hundreds of almost identical keywords and ad groups that ignore automation, close variants, and Smart Bidding.

The second extreme is an overly broad AI-friendly structure where all keywords are placed into a few broad match groups without control over intent, negative keywords, landing pages, or lead quality.

A practical strategy sits in the middle. The structure should be simple enough to avoid unnecessary data fragmentation. But it should also be precise enough to manage intent, budget, risk, and relevance.

Summary

Keyword research in search advertising is not just keyword collection. It is the design of how a business will buy demand. A strong keyword strategy starts with the product, service, and customer language. Keywords should then be divided by intent, grouped into thematic ad groups, separated when products or goals are too different, controlled through match types, protected with negative keywords before launch, refined through regular search terms analysis, and connected with relevant ads and landing pages.

New accounts should usually start carefully: exact and phrase match for the clearest commercial intent, limited broad match tests, strong pre-launch negative lists, and frequent search terms reviews. Mature accounts can use broad match and consolidated structures more actively, but only when tracking is clean, qualified leads or revenue are imported, economics are clear, and real search queries are reviewed regularly.

The main principle is simple: keywords should reflect business intent, not just words. When structure is built around intent, offer, and landing page relevance, search advertising becomes a controlled demand acquisition system instead of a random list of keywords.