Lessons from inside the research process

Corpdata was founded in 1992. In the 34 years since, we have been doing essentially the same thing: telephoning UK businesses to find out who works there, what they do, and how they prefer to be contacted. The method has not changed. Almost everything around it has.

Data quality is not a product feature. It is a process.

The most important thing we have learned is that data quality cannot be achieved once and maintained passively. It is the output of a continuous process — a permanent research team making calls, every working day, to verify and update records that are constantly changing.

Companies move. People change roles. Switchboard numbers are replaced. Preferences shift. A record that was accurate three months ago may not be accurate today. Quality is not a state. It is a rate of maintenance.

The market has changed. The need has not.

In 1992, direct marketing was a primary channel for most B2B companies. Over the following two decades, digital channels — search, email marketing, social media, content marketing — became dominant. Many companies stopped using direct marketing entirely.

Now, in 2026, the landscape is shifting again. AI-generated search results are reducing organic website traffic. Paid digital acquisition costs are rising. The algorithmic channels that replaced direct marketing are themselves becoming less reliable and less controllable.

Through all of this, the underlying commercial need has not changed: every B2B company needs to find and reach the people who buy what they sell. The channels shift. The need is permanent.

Expertise cannot be scraped

One of the less obvious advantages of 34 years of continuous research is the consultative knowledge it produces. When you have spent decades helping companies across every sector target their campaigns, you develop an understanding of what works — which targeting criteria produce results, which combinations are too broad or too narrow, and how to design a selection that matches a genuine commercial objective.

That expertise sits in people, not in databases. It is the reason a conversation with an experienced data consultant produces better targeting than a self-service platform, no matter how sophisticated the filtering tools. And it is the one asset that cannot be replicated by scraping, compiling, or automating.

What we would tell a first-time buyer

If we could distil 34 years into advice for someone using direct marketing data for the first time, it would be this: start with your commercial question, not with the data. Describe who you want to reach and why. Let someone who understands the data help you design the targeting. Test at a manageable scale. Measure what matters — conversations, not impressions. And judge the data by what it produces, not by what it costs per record.