B2B Data Glossary

Comprehensive data about a target company, including firmographics, technographics, intent signals, and organizational structure.

The process of identifying and visualizing the key stakeholders, decision-makers, and influencers within a target account.

A methodology for ranking target accounts based on their fit and likelihood to buy, used in ABM and enterprise sales.

A B2B marketing strategy that focuses on targeted accounts rather than broad-based lead generation.

Annual Recurring Revenue (ARR) and Monthly Recurring Revenue (MRR) measure the predictable, recurring revenue from subscriptions.

Signals that indicate a prospect is actively researching or considering a purchase in your category.

The process a B2B buyer goes through from initial awareness of a problem to selecting and purchasing a solution.

The group of people within a company who are involved in making a B2B purchase decision.

The percentage of customers who stop using a product or cancel their subscription during a given time period.

A Customer Data Platform architecture that runs on your existing data warehouse instead of copying data into a separate system.

Technology that records, transcribes, and analyzes sales conversations to surface coaching insights and deal intelligence.

The practice of maintaining clean, accurate, and complete data in your CRM through regular audits, deduplication, and data standards.

A platform that unifies customer data from multiple sources into a single, persistent profile.

The buying activity and research that happens outside your trackable marketing channels, invisible to attribution tools.

A secure environment where multiple parties can share and analyze combined datasets without exposing raw data to each other.

The process of identifying and merging or removing duplicate records in a database or CRM.

The process of appending additional data points to existing records in your CRM or database.

The framework of policies, processes, and standards that ensure data is accurate, secure, compliant, and consistently managed across an organization.

The ongoing practice of maintaining clean, accurate, and up-to-date data in your CRM and databases.

A data architecture that combines the low-cost storage of data lakes with the structured querying and performance of data warehouses.

A decentralized data architecture where domain teams own and manage their own data products.

The automated coordination of data flows between multiple systems, tools, and processes.

The process of verifying that data is accurate, complete, and in the correct format.

A centralized repository that stores structured data from multiple sources for analysis and reporting.

A centralized function that manages complex deal approvals, pricing exceptions, and contract negotiations for non-standard sales transactions.

Descriptive attributes about a company, such as industry, revenue, employee count, and location.

The plan a company uses to bring a product to market, including target audience, messaging, pricing, and distribution channels.

A detailed description of the type of company that's the best fit for your product or service.

Behavioral signals that indicate a company or person is actively researching a specific topic or solution.

The automated process of assigning incoming leads to the right sales rep based on predefined rules.

A methodology for ranking leads based on their likelihood to convert to a customer.

Lead qualification stages that define when marketing hands a lead to sales (MQL) and when sales confirms it's worth pursuing (SQL).

The practice of building relationships with multiple stakeholders within a target account, not just a single champion.

The percentage of recurring revenue retained from existing customers over a period, including expansion, contraction, and churn.

A metric that measures how fast revenue moves through your sales pipeline, calculated as (opportunities × win rate × average deal size) / sales cycle length.

A business strategy where the product itself drives user acquisition, activation, and expansion rather than traditional sales teams.

A potential customer who has demonstrated purchase intent through actual product usage, not just marketing engagement.

The process of connecting closed revenue back to the marketing and sales touchpoints that influenced the deal.

A business function that aligns sales, marketing, and customer success operations to drive predictable revenue growth.

The process of syncing data from a data warehouse back into operational business tools like CRMs and marketing platforms.

Technology that automates repetitive sales tasks like follow-up emails, data entry, lead routing, and activity logging.

A structured sequence of outreach touchpoints (emails, calls, social touches) designed to engage a prospect over a defined period.

The process of providing sales teams with the content, tools, training, and data they need to close deals effectively.

Software platforms that help sales teams execute multi-channel outreach cadences at scale.

The process of estimating future sales revenue based on pipeline data, historical performance, and market conditions.

Technology and data that helps sales teams identify, target, and engage the right buyers at the right time.

Sales ops focuses on sales team efficiency. RevOps aligns sales, marketing, and customer success operations under one umbrella.

A visual representation of where prospects are in the sales process, from initial contact to closed deal.

Any data point or event that indicates a prospect or account may be ready to buy.

The process of dividing your total addressable market into defined territories assigned to specific sales reps or teams.

A formula that measures how quickly your sales team generates revenue, combining deal count, win rate, average deal size, and sales cycle length.

A sales approach that uses real-time buying signals to prioritize outreach and personalize messaging based on prospect behavior.

Information about what technology products and platforms a company uses.

A data enrichment strategy that queries multiple data providers in sequence, using the best result from each.

Data that a customer intentionally and proactively shares with a brand, like preferences, survey responses, and purchase intentions.