Google Ads for the B2B industry: why generic campaigns don't convert

A B2C search tends to signal an immediate or near-immediate decision: someone who types in “men's running trainers 42” could buy today or tomorrow. Google has built its platform around this reality. Match algorithms optimise volume, automatic bids maximise short-term conversions, keyword suggestions expand reach. It makes sense when every euro invested can generate a return in hours.

Industrial research operates on a different time scale. Someone looking for “continuous industrial oven for bakery” may be starting a survey that will only end in an approved quote six months later, after a technical committee, a visit to three suppliers and a round of negotiations. Between the initial research and the decision, time passes, people pass, cost centres pass. The campaign that optimises for immediate conversion is confused in this scenario, because the useful conversion (a qualified contact that becomes a commercial lead) can occur three visits after the first survey.

The reality of the figures reflects this mismatch. Technology and B2B SaaS companies face the highest cost per acquisition of almost any industry, more than double the overall average, although the cost per click remains relatively modest. The disconnect results from low conversion rates and long, complex sales cycles typical of B2B purchases. In heavy industry and professional equipment, the pattern repeats itself with variations: expensive clicks, spaced-out conversions, leads that need lengthy commercial treatment before materialising into a sale.

Ignoring this structural difference is the root cause of the poor results in almost every industrial campaign that has ever been managed without a specific B2B strategy.

Broad match is the first point. By default, Google Ads uses broad match, which allows the algorithm to show the advert to searches that are semantically close to the chosen keyword. In B2C, this is advantageous: it captures variations that the advertiser didn't anticipate. In industrial B2B, it's a disaster. Those who advertise “industrial inspection equipment” end up paying for clicks on searches such as “cleaning equipment”, “technical car inspection”, “cheap equipment”. Each click costs between three and eight euros depending on the niche, and the overwhelming majority don't represent commercial intent.

The second source of waste is the absence of sector-specific negative lists. Terms like “free”, “used”, “DIY”, “cheapest price” are a clear sign of non-industrial intent. Without negative lists that systematically exclude them, the campaign continues to serve adverts to those who will never buy fifty thousand euros worth of professional equipment.

The third is the structure of campaigns designed by product, not by stage of buyer readiness. A single campaign that aggregates all the keywords related to a product mixes searches from those who are learning what the product does (“how a continuous kiln works”), searches from those who are comparing suppliers (“best continuous kiln manufacturer”), and searches from those who are ready to ask for a quote (“quote continuous kiln 500kg”). These three searches deserve different adverts, different landing pages and different forms. When they share structure, the advert loses relevance at all stages and the conversion rate becomes uniformly low.

The fourth is the temptation to let automation decide. Performance Max, Maximise Conversions and Target CPA are legitimate tools, but they assume that there is enough conversion history for the algorithm to learn from. In industrial B2B, where a campaign might generate three qualified conversions a month, the algorithm never gets enough signal. The result is automation that tries to optimise over noise, and therefore optimises badly.

Rebuilding an industrial campaign starts with realising that the B2B buying cycle has three distinct phases, each with its own language on Google. Search changes in a predictable way as the buyer progresses, and the structure of the campaign must mirror this progression.

Recognition phase. Here, the buyer is still understanding the problem. They search for symptoms, causes and generic technical alternatives. The keywords are longer and more educational: “how to reduce production losses on a packaging line”, “humidity problems in an industrial warehouse”. The volume is small, the intent is low, the cost per click is moderate. The aim of the campaign at this stage is not to sell, it's to capture the lead in a simple technical content download form. The advert promises information, it doesn't promise a commercial solution.

Consideration phase. The buyer has realised the problem and starts mapping suppliers. Research comparisons, specifications, technical capabilities. “Comparison of continuous industrial ovens”, “German manufacturer vs Italian equipment X”, “IECEx certification industrial equipment”. The intent is average, the cost per click goes up. The advert must offer detailed technical content: technical brochure, case study, industrial application video. The form accepts more fields, including company name and job title.

Decision phase. The buyer is finalising a short list or asking for quotes. Very specific search: “quote for equipment X model Y”, “sales contact for manufacturer Z”, “representative in Portugal for manufacturer W”. The volume is lower, the intent is maximum, the cost per click is the highest. The advert promises a quick response and direct access to the technical sales assistant. The form is short: name, company, requirements in two lines, contact.

This segmentation by phase changes everything. It allows for different negative lists in each campaign (recognition phase keywords should not appear in the decision campaign and vice versa). It allows budgets to be allocated by phase, according to the relative weight each one has in the company's actual commercial cycle. It allows conversion rates to be measured by phase, which reveals whether the problem lies in initial capture or progression along the funnel. Above all, it allows you to ensure that the advert each person sees matches the question they are asking.

Pre-qualification doesn't end at the advert. It continues in the form. A well-designed B2B form asks three questions that no disqualified buyer answers, and which automatically qualify those who answer.

The first is the company name. People who fill in their first name without a company name are rarely industrial buyers. Making the field compulsory eliminates a significant part of the noise.

The second is the volume or scale of the operation. “How many units do you produce per day”, “how big is the installation”, “what is the current monthly consumption”. These are concrete questions that require operational knowledge. Anyone who can't answer them isn't a business partner.

“I'm mapping suppliers”, “I have an approved budget”, “I have a decision planned for this quarter”. This field allows the sales assistant to prioritise the follow-up and prepare the first conversation with contextual information that the lead has already provided.

A form with these three questions has a lower conversion rate than a form with two fields, it's true. But every lead that goes through it comes back to the sales assistant with enough information to decide whether the meeting is worth travelling for, and with enough context for the first conversation to be substantive. Exchanging lead volume for lead quality is always a positive exchange in industrial B2B.