Imagine unwrapping a set of Russian dolls, each nesting within a bigger one. Or, if you’re gastronomically inclined—imagine peeling back an onion, layer by layer.
The innermost doll (or the center of the onion) represents your highest-value customers—the ones that you target, convert, and retain. The attributes and interactions of these highest-value customers form the crux of your high-quality B2B marketing data. This data acts as your guide to prospecting the “outer-layer” customers and converting them into high-value accounts.
Without high-quality B2B marketing data, you can’t effectively develop your ideal customer profile (ICP), generate leads, engage in outbound sales, or harness your analytics. In other words, you can’t develop a data-driven marketing strategy to grow your business because you don’t know who to target and interact with.
Especially in an uncertain economy with tight budgets, you either waste resources testing and filtering out low-quality leads or are left shooting in the dark, hoping to land customers.
What is B2B marketing data and why does it matter?
B2B marketing data refers to the information available about companies and their employees across online and offline sources. This includes everything from basic attributes like company and employee names, job titles and tenures, business emails, and phone numbers to more complex information like headcount, social media followers, and job postings.
It also includes quantitative and qualitative data like website clicks and form completions as well as sales conversations and product feedback.
The use of B2B marketing data has evolved over the years from telemarketing and event marketing. Back in the day, sales and marketing teams would go to conferences and trade shows and collect details of people who’d be interested in their product or service. Or, they’d cold call businesses that fit their ICP and try to build a relationship. The Internet rapidly transformed these methods to make data available from a variety of online and offline sources.
Today, B2B marketing data can be collected from public sources like websites and social media profiles and private sources like paywalled websites, paid platforms, and B2B data providers.
But the truth is that data is scattered everywhere and siloed in different places. And that makes acting on it really hard. In fact, the American Marketing Association reported that 90% of marketers don’t have the data they need, and don’t even know that they need it.
The best marketers understand the breadth of data available and use it to their competitive advantage. After all, B2B marketing data is hardest to copy—your competitors can imitate your product and advertising but it’s hard to figure out who you’re targeting and leverage the same data set. As a result, your high-quality data can become the secret to your success.
Types of B2B marketing data
Simply put, B2B data falls into three broad categories—data on people, companies, and events or actions. In business terms, there are five types of structured B2B data:
- Demographic data: Names, titles, contact information of employees, employment history, and skills.
- Firmographic data: Company name, location, industry, size, and revenue.
- Technographic data: Technology used by a company and employees, when the tools were acquired, and the features and integrations of the tech stack.
- Chronographic data: Company funding, acquisition, IPO, or hiring and departing movements of decision-makers.
- Intent data: The ‘intentions’ of your prospects, and whether they’re ready to buy based on their online behavior and the content they are consuming. This includes pageviews, downloads, and subscriptions.
B2B data also includes unstructured, microdata, that isn’t pulled into a spreadsheet. For instance, if you’re selling in the insurance industry, you want to know how strict a customer’s terms of service are and if there are certain keywords that indicate a lower risk score. This data then shows you that they fit your ICP and you can nurture the lead.
Sources of B2B marketing data
There are several sources of B2B marketing data but they can be broadly categorized into in-house or internal and external sources.
Internal and private sources of data comprise all the information you get about potential customers interacting with your website and outreach efforts. This includes the prospects who consume your content, download your assets, fill out forms, and engage with your social media posts.
Sales and marketing teams can also scour websites, social profiles, and business news to pull data. But, aggregating all this data together manually is time-consuming and laborious, and not sustainable in the long run.
The optimal way to source data is to partner with a reputed B2B data provider who will do the work for you. Today, B2B data providers don’t just hand you a list of contacts — they offer a range of services from data cleaning and maintenance to data validation and normalization (which we explain later in this article). Plus, businesses often choose a ‘base’ data provider and, with continued growth, more niche providers to expand their coverage.
The key is to compare the data providers that meet your needs and compare them using the features that serve your business goals. Create a shortlist and choose the one that offers the best data quality in terms of accuracy and coverage, and integrates with your existing workflow and tech stack.
Challenges in B2B marketing data
Marketing is hard in 2023. Since data is scattered across the internet, it’s important to identify and aggregate it, and then act on it. Often, marketers skip to the identification part.
If you don’t pull data together in one place, you won’t get the full picture and it’s hard to say which data matters. In other words, marketers miss out on high-value accounts because they don’t have:
- Data breadth: the number of columns or attributes
- Data depth: the coverage of a certain attribute
- Data quality: the freshness and accuracy of the attributes
Instead, focus on aggregating your data from all your tools and platforms into one place, analyze the patterns and attributes of your most valuable customers, and leverage it across different channels like sales, targeted advertising, and direct mail to get the biggest deals.
Once you aggregate the data, you need to perform identity resolution—linking a customer’s online behavior with their unique profile — to deliver relevant and personalized messaging throughout the customer journey.
Keep your B2B data up-to-date with these processes
High-quality B2B data is like fine silver; it needs constant polishing to sparkle and stay fresh. On average, 2.1% of B2B data decays every month. In addition, company addresses and phone numbers change, C-suite leaders rotate, and new startups are launched within a span of minutes.
This means you need to maintain your B2B marketing data, especially in an era of rapid business transformation. Here’s how:
B2B data sourcing
It seems obvious that the quality of your data depends on the quality of your vendors, so businesses must be doing their due diligence. And yet, Garter reports that poor data quality costs businesses $12.9 million on average, impacting revenue, infiltrating data ecosystems, and leading to flawed decision-making.
Evaluate your providers based on your specific needs and the accuracy, pricing, coverage as well as consistency of their data. A few questions you can ask to assess the quality of your data provider:
- How do you collect and verify data?
- How do you measure the accuracy of your data?
- How often is the data updated and enhanced?
- How can our company ingest your data?
- Do you provide data samples?
- What are your privacy practices?
In addition, assess the quality of your second and third-party data sources and vet them before they are entered into your systems.
B2B data cleaning
Poor data quality includes missing contact fields, duplicate entries, outdated information, misspellings and typos. All of this ‘dirty’ data needs to be cleaned periodically to make sure it doesn’t negatively impact your sales and marketing campaigns. After all, you don’t want to call wrong numbers, send emails that bounce back, and be stuck with a list of unfit leads.
Include these best practices in your data cleaning process:
- Get executive buy-in to maintain data hygiene by highlighting the cost of dirty data to your organization
- Delete outdated records and reduce your database size to keep it manageable
- Use technology that integrates and shares data
- Clean your data with automatic processes and in real-time
B2B data validation
Data validation simply means checking the accuracy of your data. But it isn’t a one-and-done exercise since data is constantly changing. Plus, 35% of data submitted through forms is incorrect. For fresh and relevant data, you need to verify that the details you have on prospects are accurate.
Data validation includes both verifying and enriching your data to fill empty fields and get a more complete profile. This is either done through manual research or with the help of sales intelligence tools like UserGems and Zoominfo.
B2B data storing
B2B data contains the details of your highest-value customers, and you want to store it in a secure space. Besides, any B2B data contains people’s identities, and therefore needs to be compliant with rules and regulations of your country. Data sets from reputable B2B data providers tend to be legally compliant, and are safer to use.
Data normalization is the process of grouping and formatting values to give your database a clean and standardized look. For instance, hyphenate all phone numbers or capitalize first names and last names. Data normalization is best done with the information you collect through web forms, event registrations, and outbound prospecting.
Data normalization helps reduce duplicate entries, makes segmenting leads easier, and mitigates the risk of mistakes when you analyze performance and metrics.
Use technology to keep a laser focus on your highest-value customers
Your B2B marketing datasets are the wheels on which your go-to-market strategies run. From cross-channel insights to testing and learn which data attributes are most effective, a precision targeting tool can help you identify and stay focused on your ideal buyers.
There’s two ways to do this—the roundabout way and the smart way. With the roundabout way, you hire a team of data engineers and buy multiple sources of data but you can cut to the chase with a tool like Primer that lets you access 12 data sources in one platform.