Lookalike ICP Targeting
Generate and warm net-new demand
Sales Stage
Pre-Sales
Difficulty
Intermediate
Impact
Medium
Channels
Overview
Setting up scoring models to target the best-fit, highest priority accounts is essential for optimizing outbound prospecting performance. Many scoring models rely on CRM data to seed and train the model to return an ideal customer profile—but that data is often inaccurate or incomplete. You can analyze account profiles for deals won and lost, customer attributes, firmographics, technologies, and other relevant data points to create ideal customer profiles. You can further prioritize your ICPs with buyer intent and other actionable insights.
Key Features
Data Types
Triggers
- Identify ZoomInfo Companies which now meet your Saved Search company filter criteria
Actions
- Discover a set number of ZoomInfo contacts which meet your contact filters
- Export
- Send records to your business system (CRM, MAT, SEP, CSV)
- Assign to a User
- Then enroll in a Campaign (optional)
Default Natural Language Configuration
When new companies are added to select saved search then discover up to 20 ZoomInfo contacts which select criteria then export to select system as record type and select campaign and assign to select user
Standard Operating Procedure
1. Define Ideal Customer Profile (ICP)
- Analyze closed-won and closed-lost accounts
- Import account list to generate automatic ICP
- Identify key attributes for lookalike targeting
2. Set Up Saved Search
- Configure saved search with ICP attributes
- Establish company filter criteria
3. Configure Contact Filters
- Set management level and department criteria
- Determine number of contacts to discover per company
4. Automated Lead Discovery
- Monitor for new companies meeting saved search criteria
- Trigger contact discovery process in ZoomInfo
5. Data Export and Enrichment
- Export discovered contacts to CRM/MAT/SEP
- Enrich company and contact data as needed
6. Lead Assignment
- Automatically assign leads to appropriate sales team members
7. Campaign Enrollment
- Create targeted email campaign for lookalike prospects
- Enroll discovered contacts into the campaign
8. Multi-Channel Engagement
- Implement outreach across various channels (email, phone, ads, etc.)
9. Performance Monitoring
- Track engagement and conversion metrics
- Compare performance against non-lookalike prospects
10. Continuous Optimization
- Regularly review and refine ICP criteria
- Update lookalike targeting based on new closed-won data
Yield Model
Yield in $ Formula
Potential Yield = (VO * ADMER * CR / 10,000) * ADSKey Drivers
Driver Definitions
Accuracy of ICP (AICP) This metric reflects how accurately the Ideal Customer Profile has been defined. It's a critical factor because a more accurate ICP leads to better targeting of potential customers.
Conversion Rate (CR) This metric indicates the proportion of leads that convert into customers. A higher conversion rate suggests a more effective engagement and follow-up strategy.
Average Deal Size (ADS) This refers to the average revenue generated from each successful deal. Maximizing the average deal size is essential for increasing overall revenue, especially when the number of conversions is limited.
Target Account Volume (TAV) This is the total number of target accounts that are identified for this strategy.
AI Agent Prompt Template
I. Prompt Instructions - Overview
This email targets contacts at companies that match the Ideal Customer Profile (ICP) of our best accounts. The goal is to engage with these high-priority prospects through relevant content or a direct invitation, encouraging further interaction.
II. Information Included
The email will include personalized information between <context></context> for proper dynamic insertion:
- ICP Matching Information: Context about why the company matches the ICP of our best accounts.
- Company Information: Insight into the prospect's company, including identified pain points and behavior from engagement history.
- Signals & Behavior: Details on the account's engagement history and recent intent signals.
- Account History: Includes documented CRM account history along with a complete history of conversation data recorded via Chorus Conversational Intelligence.
- Contact Information: A group of five contacts across the buying committee, including the contact's role, persona information, and other details to personalize the email.
- Content Library: Relevant content, such as upcoming webinars, whitepapers, or downloadable content that can be included as part of the follow-up.
- Messaging: Tailored messaging addressing the account's segment and the contact's persona to make the outreach more relevant.
- Copilot AI Account Summary: A summary that merges ZoomInfo data, customer CRM data, email communications, and call recordings, offering a clear overview of the account's pain points and strategic goals, along with actionable next steps.
III. Email Structure
Format Instructions: Return the email in a valid XML format. The template will look like this:
<email> <subject>{{Personalized Subject Line}}</subject> <body> <p>Hi {{Contact.FirstName}},</p> <p>I wanted to reach out because we've identified <strong>{{CompanyName}}</strong> as a company that aligns with the profile of some of our most successful customers. We specialize in helping companies like yours achieve <insert outcome, e.g., "greater efficiency in outbound sales">.<p> <p>To help you get started, I'd love to share <strong>{{ContentLibrary.Whitepaper}} / {{ContentLibrary.CaseStudy}}</strong> that details how companies similar to yours have leveraged our solution to achieve <insert benefit>.<p> <p>If you're interested in learning more about how we can help <insert pain point or business challenge>, I'm happy to discuss your needs further.<p> <p>Looking forward to hearing from you!</p> <p>Best regards,</p> <p>{{Sender.Name}}</p> <p>{{Sender.Title}}, {{Sender.Company}}</p> <p>{{Sender.ContactDetails}}</p> </body> </email>IV. Context
<context> <ICP-Matching-Information> **`{{ICP Matching Information}}`** </ICP-Matching-Information> --- <Company Information> **`{{Company Information}}`** </Company Information> --- <Signals & Behavior> **`{{Signals & Behavior}}`** </Signals & Behavior> --- <Account History> **`{{Account History}}`** </Account History> --- <Contact Information> **`{{Contact Information}}`** </Contact Information> --- <Content Library> **`{{Content Library}}`** </Content Library> --- <Messaging> `{{Messaging}}` </Messaging> --- <Copilot AI Account Summary> **`{{Copilot AI Account Summary}}`** </Copilot AI Account Summary> </context>V. Optimizations
- Subject Line Personalization: E.g., "Companies Like Yours Achieve <Outcome>—Here's How We Can Too."
- Engaging Opening: Highlight the alignment with the ICP and why this makes the company a high-priority target.
- Value-Driven Content: Offer resources such as case studies or whitepapers that resonate with the ICP's interests and needs.
- Call to Action: Invite the recipient to a call or a meeting to discuss how the solution can help their company specifically.
- Polished Close: Maintain a friendly tone and provide an open invitation to continue the conversation.
Merge Tokens Used
{{Personalized.SubjectLine}}{{Contact.FirstName}}{{CompanyName}}{{ContentLibrary.Whitepaper}}{{ContentLibrary.CaseStudy}}{{Sender.Name}}{{Sender.Title}}{{Sender.Company}}{{Sender.ContactDetails}}Play Description for LLM
<play> **PLAY NAME** Lookalike ICP Targeting --- **🔁 Triggers** - Identify ZoomInfo Companies which now meet your Saved Search company filter criteria --- **⚡️ Actions** - Discover a set number of ZoomInfo contacts which meet your contact filters - Export - Send records to your business system (CRM, MAT, SEP, CSV) - Assign to a User - Then enroll in a Campaign (optional) --- **✅ Goal / Problem to Solve** ✅ Cold / New Leads --- **➡️ Channels** ✉️ Email, 💬 Text, 📪 Mail, 📅 Events, 📢 Ads, 🖥 Chat, 📞 Phone --- **✏️ Summary** Setting up scoring models to target the best-fit, highest priority accounts is essential for optimizing outbound prospecting performance. Many scoring models rely on CRM data to seed and train the model to return an ideal customer profile—but that data is often inaccurate or incomplete. You can analyze account profiles for deals won and lost, customer attributes, firmographics, technologies, and other relevant data points to create ideal customer profiles. You can further prioritize your ICPs with buyer intent and other actionable insights. --- **✏️ Default Natural Language** When new companies are added to **select saved search** then discover **up to 20** ZoomInfo contacts which **select criteria** then export to **select system** as **record type** and **select campaign** and assign to **select user** --- **Explainer-Video-Script** Want to automatically target best-fit prospects you don’t yet know about? Try the lookalike ICP targeting play! Use data from your closed won and lost opportunities, to set up a lookalike ICP that automatically finds new prospects based on this historical data. Enroll these accounts in all your core campaigns. Now you’re prospecting smarter, not harder. --- **🏷Features)** ABM Audiences, Lookalike Targeting, Account Fit Score --- **🏷️ZoomInfo Data Types)** Contact Data, Company Data --- **📁 Sales Stage** Pre-Sales --- **🚦 Difficulty** 🟦 - Intermediate --- **🧪Standard Operating Procedure (SOP)** ## 1. Define Ideal Customer Profile (ICP) - Analyze closed-won and closed-lost accounts - Import account list to generate automatic ICP - Identify key attributes for lookalike targeting ## 2. Set Up Saved Search - Configure saved search with ICP attributes - Establish company filter criteria ## 3. Configure Contact Filters - Set management level and department criteria - Determine number of contacts to discover per company ## 4. Automated Lead Discovery - Monitor for new companies meeting saved search criteria - Trigger contact discovery process in ZoomInfo ## 5. Data Export and Enrichment - Export discovered contacts to CRM/MAT/SEP - Enrich company and contact data as needed ## 6. Lead Assignment - Automatically assign leads to appropriate sales team members ## 7. Campaign Enrollment - Create targeted email campaign for lookalike prospects - Enroll discovered contacts into the campaign ## 8. Multi-Channel Engagement - Implement outreach across various channels (email, phone, ads, etc.) ## 9. Performance Monitoring - Track engagement and conversion metrics - Compare performance against non-lookalike prospects ## 10. Continuous Optimization - Regularly review and refine ICP criteria - Update lookalike targeting based on new closed-won data --- **🪙 RAG Inputs Used (Broad)** ICP Matching Information, Company Information, Signals & Behavior, Account Data, Contact Information, Content Library, Messaging, Copilot AI Account Summary --- **🪙 Email tokens Used** Personalized.SubjectLine, Contact.FirstName, CompanyName, ContentLibrary.Whitepaper, ContentLibrary.CaseStudy, Sender.Name, Sender.Title, Sender.Company, Sender.ContactDetails --- **🟨 Yield in $ Formula** Potential Yield = (VO * ADMER * CR / 10,000) * ADS --- **🟨 Yield Key Drivers** Accuracy of ICP (AICP), Conversion Rate (CR), Average Deal Size (ADS), Target Account Volume (TAV) --- **🟨 Yield Driver Definitions** Accuracy of ICP (AICP) This metric reflects how accurately the Ideal Customer Profile has been defined. It's a critical factor because a more accurate ICP leads to better targeting of potential customers. Conversion Rate (CR) This metric indicates the proportion of leads that convert into customers. A higher conversion rate suggests a more effective engagement and follow-up strategy. Average Deal Size (ADS) This refers to the average revenue generated from each successful deal. Maximizing the average deal size is essential for increasing overall revenue, especially when the number of conversions is limited. Target Account Volume (TAV) This is the total number of target accounts that are identified for this strategy. --- </play>