The Leadspace B2B Audience Management Platform is designed to help users discover their Total Available Market (TAM). The platform aims to increase customer and prospect engagement with data users need on both accounts and individuals. Leadspace uses artificial intelligence (AI) to recommend which prospects and customers to prioritize, and help enable users to align sales and marketing with a single data source.
The B2B Audience Management Platform has three modules:
- Audience Discovery, which provides visibility into the Total Available Market, using AI to identify who a company’s most profitable buyers are, and discover new accounts and decision makers.
- Audience Data Management, a single source for comprehensive marketing and sales data, drawing from over 40 sources to provide more than 80 fields of data on leads and accounts verified in real-time.
- Audience Modeling, which uses AI to score leads and accounts by propensity to buy, and almost any other criteria, so that marketing and sales can be more efficient and increase conversion rates by prioritizing the best prospects.
As an end-to-end audience management platform, Leadspace’s target audience spans sales and marketing throughout the B2B sales funnel — from demand gen marketers and sales ops to sales reps.
The Platform is fully integrated with leading CRMs and Marketing Automation Platforms, including Salesforce, Microsoft Dynamics, Marketo and HubSpot. Customers can also integrate Leadspace AMP with any solution via the Leadspace API.
The Leadspace Audience Management Platform is a SaaS offering with pricing based upon annual subscription license and data volume usage. The most popular edition is priced at $30,000 for an annual subscription.
More than 130 B2B brands currently use Leadspace, including Microsoft, HP Enterprise, Marketo and RingCentral.
Leadspace B2B Audience Management Platform combines B2B data and predictive intelligence in a single solution. Data is both comprehensive and consistently relevant. Predictive scores are transparent — customers can access the data behind the scores to learn from it and add human input into the model.