Prime your AI agents for personalized conversations.

Differentiate your business in an ecosystem filled with generic, uninformed AI agents.

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ai agent priming

Benefits of priming your AI agent.

Priming your AI agent with a unique conversational context enhances its ability to interact with your prospect or customer, improving satisfaction and business outcomes.

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Personalized Interactions
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Increased Customer Satisfaction
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Improved Conversion Rates
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Supported Business Goals
how it works

Examples of  
Primed
Agents.

A prospect or customer is interacting with your company's AI agent in the following common scenarios.

scenario: inquisitive prospect

Prospect is interested in offers and looking around.

The AI agent knows the likely prospect lives in an urban area and has:

  • Browsed the company site several times looking at high-end pricing plans.
  • Has an iOS smartphone on the latest version.
  • Expressed interest in international plan offerings.
Acquisition Model

The AI agent also knows that customers with similar traits have a high likelihood of accepting offers for premium plans.

Offer Taker Model
scenario: likely to churn account

Customer has a single line with an old phone.

The AI agent knows the customer has a high propensity to churn and that their unique contributing churn factors are:

  • An old smartphone with a small screen.
  • They are running out of data, and have purchased additional high speed data allowance at extra cost.
  • They have visited the store several times, and are likely shopping around for other carriers.
Churn Model

The AI agent knows they are a price-sensitive, persuadable customer and likely to accept a discount offer.

Persuadable Customer Model
scenario: high-value customer

Customer with family plan and multiple lines.

The AI agent knows the customer has a high-propensity to upgrade with three lines and a family data plan, along with:

  • The customer has called in about adding Disney+ and ESPN streaming to their plan.
  • They have an associated tablet that is very old with minimal usage.
  • Accounts similar to theirs have purchased accessories.
Premium Upgrade Model

The AI agent also knows the customer is a high-value, high-tenured customer with the potential to further grow their account.

Customer Lifetime Value Model

How it works.

The AI Agent Priming process builds on GlorifAI's traditional modeling process. After model training, unique customer profiles are constructed and supplied to the AI Agent for priming and customization.

Train Predictive Models
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(Step 1)
Identify, acquire and connect data sources
Train, test and select the best models
Identify driving features for each customer or prospect
GlorifAI Task
Build Customer Profile
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(Step 2)
Determine the semantic meaning for each driving feature
Build a model-level profile for each scored individual
Condense an individual's profiles into text context for the AI agent
GlorifAI Task
Supply Context to AI Agent
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(Step 3)
Provide individual text context at the beginning of each conversation
GlorifAI does not supply the AI agent
Selection and deployment of the AI agent is determined by the client
Client Task