Understand Person-Level ID, Intent Data, and GTM Terms

Framework for assigning credit to marketing touchpoints that contribute to conversions, measuring the effectiveness of each channel and campaign in the customer journey.

Common obstacles in B2B selling including long sales cycles, multiple stakeholders, limited personalization, and difficulty identifying actual decision-makers.

Targeting users with ads or content based on their online actions, browsing history, preferences, and past behaviors rather than just demographics.

Strategies and techniques to reduce or eliminate unfair biases in AI models, data, and decision-making processes to ensure equitable outcomes.

Tracking and analyzing competitors' pricing strategies, discount patterns, and packaging to optimize your own pricing and win more deals.

AI technology that automates customer interactions through intelligent chatbots, virtual assistants, and conversational interfaces using natural language processing.

The total revenue a business expects to earn from a customer over the entire duration of their relationship, used to guide acquisition spending and retention priorities.

Predicting which sales opportunities will close, when they'll close, and for how much revenue using historical data, pipeline stage, and predictive analytics.

Predicting future customer demand for products or services using historical data, market trends, and statistical models to optimize inventory and resource planning.

Adjusting product or service prices in real-time based on demand, competition, customer segment, inventory levels, and market conditions.

Ensuring AI systems operate transparently, fairly, and responsibly, without bias or harm, while respecting privacy and human rights.

AI technology that creates new content—text, images, audio, code—using machine learning models trained on large datasets. Examples include ChatGPT and Midjourney.

A methodology for ranking leads by their likelihood to convert, using behavioral data, demographic attributes, and engagement patterns to prioritize sales efforts.

Using data analysis to identify new prospects who share characteristics with your best existing customers, enabling more effective targeting and prospecting.

Analyzing patterns in market data, customer behavior, and industry dynamics to identify emerging trends and inform strategic planning.

Delivering a seamless, consistent customer experience across all channels and touchpoints—website, email, social, ads, events, sales calls.

Using historical and real-time data with statistical models and machine learning to forecast future outcomes, customer behaviors, and business trends.

Prospects identified through immediate behavioral signals showing active research of topics related to your offerings, enabling instant, timely outreach.

Software and resources that provide sales teams with content, training, data, and technology to improve efficiency, shorten sales cycles, and close deals faster.

Using AI and natural language processing to analyze customer emotions and opinions from text data like reviews, social media, surveys, and support tickets.

Identifying and engaging prospects based on behavioral and intent signals on and off the website, using email, LinkedIn, and phone outreach.

Monitoring social media platforms for mentions of your brand, competitors, products, and industry topics to understand customer sentiment and market trends.