How to Select B2B Data by Industry (and Why It Matters More Than You Think)

If you're looking to buy B2B data, one of the first questions you'll be asked is:

"What industry are you targeting?"

On the face of it, a simple question but not always a simple answer. This is because selecting B2B data by industry (or data by sector) isn't just about ticking a box. It's about making sure the businesses you target accurately reflect the audience you want to reach.

Get it right and your campaigns land with your dream audience. Get it wrong and even if you have the best email content and quality of data lists it won't matter, because the targeting is irrelevant.

At Databroker, we tend to break this down into five key approaches.

(1) Using SIC Codes for B2B Data

For most campaigns, this is the starting point when selecting B2B data by industry. SIC codes (Standard Industrial Classification) are the official way UK businesses are categorised. We typically work with UK SIC 2007, which is the current standard used across most B2B data providers. But there are older UK versions too.

SIC Codes are structured in levels:

Sections - broad sectors like Construction, Manufacturing, Information & Communication
2-digit codes (Divisions) - a bit more specific
5-digit codes (Classes) - where it gets more detailed

This structure makes SIC codes a useful foundation when building B2B data lists. But there are limitations:

Companies self-select their codes, so accuracy can vary
Some codes that contain keywords like "other" or "not elsewhere classified" can be too generic or broad
Some businesses sit across multiple sectors but only list one or two codes
They're nearly 20 years out of date!

So, while SIC codes are essential when working with data by industry, they're rarely the full picture on their own. There are exceptions, for example in Manufacturing, where SIC codes are very detailed and ideal for targeting.

(2) Directory or Sector Codes for More Accurate Targeting

If SIC codes are the backbone, directory or sector data is where things get sharper. These classifications are built around what businesses actually do, not just how they describe themselves. Often directory or sector codes are far more useful than SIC, because the continue to evolve and offer a greater level of detail.

This makes them incredibly useful when building more refined email data lists or targeting specific niches.

Instead of just "Construction", you might target:

Office fit-out specialists
HVAC contractors
Facilities management providers
Commercial refurbishment firms

From a B2B data perspective, this level of detail is far more actionable and it's often the difference between a broad campaign and one that feels properly targeted.

(3) Turning Generic Terms into Usable B2B Data

A lot of briefs don't come in as codes at all - and we are fine with that! Databroker are the UK's B2B data experts, so just send us your brief in whatever language suits you and we'll translate it into the most suitable set of sector/SIC codes. Often briefs come in as:

"Professional services"
"White or Blue collar businesses"
"Organisations likely to supply X or Y"
"Trades and contractors"

These are great from a marketing perspective, but they don't exist neatly in raw B2B data lists. So, we translate them. We take those terms and map them into a combination of:

SIC codes
Directory classifications
Additional filters and exclusions

This is where experience matters. Two interpretations of "data by sector" can look very different depending on how it's built. Our job is to make sure the final B2B data delivery actually reflects what you meant when you briefed it in to us.

(4) International B2B Data by Industry

Once you move beyond the UK, things get a bit more complex. There's no single global standard for data by industry, so you're typically working with a mix of:

US SIC 1987 codes
NACE codes across Europe
Country-specific systems like French NAF codes

Each system structures industries slightly differently. Thus, building international email data lists isn't just about pulling data, it's also about translating industries across different frameworks.

Done properly, you'll get consistency across markets.
Done badly, you end up targeting completely different audiences in each country.

Databroker supply data on 1000s of European, US and fully global data sets every year, our expertise and knowledge for your international marketing campaigns is exceptional. We will make sure you're getting a list that matches and hopefully exceeds your expectations.

(5) Bespoke B2B Data

Increasingly, selecting data by any of the methods above simply isn't enough. You need something super-tailored.

For example:

Businesses actively growing
Companies investing in technology
Organisations with specific operational characteristics
Multi-site businesses with defined structures
Bespoke technographic selections
Complex cleanse and append work

At this point, you're moving beyond standard B2B data lists and into fully bespoke audience builds.

This is where we combine:

Industry selection
Company size and structure
Behavioural indicators
Data cleansing and suppression

To create highly targeted email data lists that don't exist off the shelf.

Final Thought

If a campaign hasn't worked, it's often not the messaging or the channel. It's the audience. That is why Databroker go into so much detail at the briefing stage.

Getting data selected correctly by industry is one of the biggest factors in campaign success, whether you're using direct mail, outbound calling or email data lists. And that's why working with the right B2B data provider makes all the difference.

FAQs: Selecting B2B Data by Industry

What is the best way to select B2B data by industry?

There isn't a single "best" way. The strongest B2B data lists are usually built using a combination of SIC codes, directory data and bespoke filters.

SIC codes give you structure, directory data adds accuracy, and bespoke layering helps refine the audience. Blending these approaches is what turns standard B2B data into something that actually performs.

Are SIC codes accurate enough for building email data lists?

They're a good starting point, but not always enough on their own.

SIC codes are self-selected by businesses, so they can sometimes be outdated or too broad. That's why many B2B data providers combine them with other sources when building email data lists. If accuracy really matters, it's worth going beyond SIC codes.

What's the difference between data by sector and data by industry?

In practice, they're often used interchangeably.

"Data by industry" usually refers to formal classifications like SIC or NACE codes, whereas "data by sector" can be a bit broader and more marketing-led.

How do you target niche industries in B2B data?

This is where directory data and bespoke builds come into play. If you're targeting something quite specific, standard SIC-based B2B data lists might not be detailed enough. Directory classifications and custom filtering allow you to get much closer to real-world activity.

Can you build international email data lists by industry?

Yes, but it's a bit more complex and sometimes more costly than UK data.

Different countries use different classification systems, such as US SIC 1987, NACE in Europe or country-specific codes like NAF in France. A good B2B data provider will map these properly to ensure consistency, so your email data lists align across markets.

What are bespoke B2B data lists?

Bespoke B2B data lists are built around specific criteria that go beyond standard industry selection.

That might include company size, behaviour, growth signals, or operational factors. They're typically created by combining multiple datasets and applying tailored filters. If your brief doesn't fit neatly into "data by industry" or "data by sector", bespoke is usually the way to go.

How do I know if my B2B data is well targeted?

A good sense check is simple: If you looked down the list, would the businesses feel right? But a better approach is to ask Databroker to run a free data audit for you.

If the answer is "not quite", it's usually down to how the B2B data has been selected rather than the data itself. Getting the industry or sector definition right is what makes the biggest difference to performance.