-Jul-31-2026-04-53-31-9714-AM.png?width=252&height=45&name=image%20(7)-Jul-31-2026-04-53-31-9714-AM.png){kind=small}
The Background
When a plant manager at a pharmaceutical company needs to modernize their production line, or a controls engineer at an automotive plant is evaluating new SCADA software, they no longer start with a trade publication or a vendor list from procurement. They open ChatGPT or Perplexity and ask which industrial automation platform to use. The answer they receive in the next thirty seconds shapes which vendors make their shortlist.
-Jul-31-2026-05-02-26-3395-AM.png?width=664&height=354&name=image%20(16)-Jul-31-2026-05-02-26-3395-AM.png)
COPA-DATA is an independent industrial automation software company headquartered in Salzburg, Austria, and their product, the zenon Software Platform, is trusted by more than 5,000 organizations globally, including BMW, Toyota, Pfizer, Merck, Coca-Cola, and Saudi Aramco. Across industries as demanding as pharmaceutical manufacturing, energy infrastructure, and automotive production, engineers rely on zenon to connect machines, plants, and buildings, and to control and monitor processes in real time. COPA-DATA’s mission is simple and serious: make industrial automation accessible, reliable, and future-ready for teams of every size and background.
That mission depends on something that sounds simple but is increasingly complex: being found at the exact moment the right engineer is asking the right question. As AI-powered search started reshaping how industrial professionals discover software, the way COPA-DATA showed up for those engineers began to matter in an entirely new way.
The Challenge
When the Engineer Asks AI, Will They Find You?
The engineers, plant managers, and OT specialists who depend on industrial automation software are not passive buyers. They are problem-solvers under pressure, managing production environments where downtime costs real money and the wrong platform choice cascades across an entire facility. When they ask an answer engine for a recommendation, they trust what comes back. That trust, extended or withheld in the span of a single AI response, is now one of the most consequential moments in COPA-DATA’s marketing funnel.
Constantin von Pander, Senior Digital Project Manager on COPA-DATA’s Digital Tools and Touchpoints team, had been watching this shift unfold. His team manages the company’s corporate website in nine languages, its online shop, and a global marketing technology ecosystem built almost entirely on HubSpot. For nearly seven years, Constantin has been the internal expert on how COPA-DATA’s digital infrastructure performs. When organic search traffic began declining and the team started hearing more about LLMs from subsidiaries around the world, it became clear that a new challenge was forming.
The Problem With Five Different Answers
The team understood the stakes. If an engineer at a prospective client typed a query into ChatGPT about the best SCADA or HMI platform and COPA-DATA did not appear, or appeared poorly, that moment of discovery would happen without them. The opportunity to become the trusted recommendation inside AI-powered research was real, and so was the risk of being left out.
The harder problem was infrastructure. COPA-DATA’s global marketing teams, operating across ten subsidiaries and multiple regions, needed a consistent, measurable approach to AI search visibility. What they had instead was the beginning of a fragmentation problem. Different tools producing different data, different regional teams potentially pulling in different directions, and no reliable way to track how COPA-DATA appeared across the LLMs and answer engines their prospects were using.
Constantin put it plainly: he did not want five data sources with five different measurements behind them. For a team already running its global marketing operations through HubSpot, the solution needed to live inside the system they already trusted, not alongside it.
The Solution
One Platform, One Source of Truth
The engineers who ask AI which automation platform to trust deserve a confident, accurate answer. COPA-DATA made it their job to ensure that answer includes zenon. The tool that made that possible was HubSpot AEO.
COPA-DATA first encountered AEO through the HubSpot AEO Grader, which gave them an early read on how their brand appeared across large language models. When the beta program for the new AEO tool for ongoing visibility tracking opened, they joined early. Constantin’s team integrated AEO directly into their existing HubSpot environment, so brand visibility across AI search platforms, citation insights, and content recommendations could be monitored and acted on from the same place where their global marketing already lived.
The centralization was not incidental. It was the strategy. By keeping AEO inside HubSpot rather than layering in a separate tool, COPA-DATA ensured that all marketing teams across every subsidiary and region were working from the same data. No parallel reporting. No competing interpretations. One view of how they appeared in the AI search results that mattered most to their customers.
Content That Required Almost No Fixing
AEO Recommendations changed how the team worked. First, the dashboard surfaced what needed to be done, showing exactly which prompts and citations were driving visibility in their category and where gaps existed. Then, with a single click, the Content Agent drafted content directly from those recommendations. The tool generated content based on the prompts and citations that mattered, and the quality surprised the team. Internal reviewers found that very little editing was needed before it could be published. What had previously been a slow, resource-intensive process became faster and more strategic.
-Jun-15-2026-02-50-45-2164-PM.png?width=636&height=477&name=image%20(7)-Jun-15-2026-02-50-45-2164-PM.png)
The recommendations also opened a planning question the team was glad to have: with so many high-quality suggestions available, they now needed to decide which to prioritize, whether to integrate them into existing pages or build new ones around specific topics, and how to sequence that work for maximum impact. It was the kind of problem that signals momentum.
Breeze Assistant Joins the Picture
AEO was not the only HubSpot AI capability reshaping how the team worked. Constantin’s team adopted Breeze Assistant across their marketing workflows and encouraged every member to spend at least an hour each month testing new AI features. One colleague reduced a recurring workflow from three hours to fifty minutes. That result spread through the team and beyond it, as colleagues in sales and other departments began discovering how the assistant could simplify their own daily work. Adoption spread not because it was mandated, but because the results were visible and real.
The Transformation
When AI Answers, COPA-DATA Is There
The engineers, plant operators, and OT specialists at companies like BMW, Pfizer, and Toyota who rely on industrial automation software now encounter COPA-DATA in the places where they are forming their decisions. That presence did not happen by chance. It was built through a structured, centralized strategy, grounded in data, and executed through HubSpot AEO.
Where the team once faced the possibility of fragmentation, with different regional teams using different tools and producing incompatible insights, they now operate from a single source of truth. AEO data feeds directly into company-wide OKRs that the marketing leadership tracks across HQ and subsidiaries alike. Visibility in LLMs is no longer an aspiration or a concern discussed in hallway conversations. It is a measured objective with accountable owners and a consistent methodology behind it. In one early example, a net-new page built directly from AEO recommendations reached a 50%+ citation rate on Gemini in under two months — up from zero.
Speed, Quality, and a Team That Believes in What They Are Building
The qualitative shift inside the team has been just as significant as the strategic one. The speed at which AEO-optimized content can be produced, reviewed, and published has changed what the team believes is possible. The relief of having a tool that generates content their reviewers actually trust, without extensive rework, has freed up capacity for higher-order decisions about strategy and targeting.
Breeze Assistant deepened that confidence. When a teammate saves two hours on a task they had previously dreaded, and that story travels through the team, something changes in the culture around AI adoption. COPA-DATA is not a company experimenting cautiously with artificial intelligence. They are a company building AI into how they operate, with HubSpot as the platform holding it together.
-Jul-31-2026-04-33-45-3054-PM.png?width=1420&height=757&name=image%20(8)-Jul-31-2026-04-33-45-3054-PM.png)
A Foundation for What Comes Next
COPA-DATA has always been a company that runs toward new technology. They joined the AEO beta early. They are already testing Breeze Agents for social media, video, and other workflows. They expanded their HubSpot credits at renewal specifically because AI had become central to their strategy, not peripheral to it.
The future they are building is one where every global marketing team operates from the same visibility data, content recommendations reach the right channels with minimal friction, and the industrial engineers who need COPA-DATA can always find them, in every language, on every platform, in every AI-powered answer that shapes their next decision.
-Jul-31-2026-04-53-31-9714-AM.png?width=269&height=48&name=image%20(7)-Jul-31-2026-04-53-31-9714-AM.png){kind=small}
.png?width=215&height=50&name=lucanet-logo-rgb%20(1).png){kind=logo}
-1.png?width=215&height=50&name=New%20Charter%20Logo_full%20color%20(2)-1.png)
