What are Buying Signals?
Buying signals are indicators that help identify potential buyers.
Examples of Buying Signals
Buying signals can be grouped into two broad categories: Fit Signals and Interest Signals.
Fit Signals
Fit signals reveal whether organizations and individuals are likely to be able to acquire and use a solution. Common company-level fit signals include firmographic and demographic signals, such as company size, industry, financial performance, and installed technologies. On an person-level, fit signals include demographics signals such as job title, department, and prior employers.
Interest Signals
Interest Signals reveal what a potential customer is showing interest in and, therefore, is likely to buy soon. Intent data, which is a record of what people from potential customer organizations are researching online, is a popular form of Interest Signal.
The most important interest signals for most B2B organizations are website traffic and form-fill leads. These signals are important because they are evidence that prospects have discovered their solutions and are already reviewing them.
Where Do Buying Signals Come From?
Fit and Interest Signals can each be acquired from third parties and found within internal systems. Examples of signals acquired from third parties include:
- Interest Signal: Intent Data
- Fit Signal: Company annual reports
- Fit Signal: Installed technology
Most B2B companies also have records in internal systems that contain important signals, typically in marketing automation, customer relationship management, and website management systems among others. Examples of signals that are typically sourced internally:
- Interest Signal: Website visits
- Interest Signal: Form fills (leads)
- Fit Signal: Customer Status
- Fit Signal: Job Function
Using B2B Buying Signals
The meaning of some buying signals is clear, like when individuals fill out forms to request contact from sales. More often, the meaning of any given signal is less clear. For instance, one person who downloads a whitepaper from a vendor’s website may be doing so out of personal curiosity, while another is part of an active buying team.
In most cases, it takes many specific signals to produce insights to fuel more effective revenue production. Signals from a variety of sources must be combined and analyzed to identify meaningful patterns that identify prospects that are likely to become customers. The pattern-matching capabilities of AI are key to capitalizing on the breadth of buying signals available.
