TL;DR
A prospect list is a collection of potential customers for targeted outreach. Essential data points include geography, industry, company size, services/products, funding/revenue, and growth rate. Additional information like decision-makers, tech stack, and past engagement history can enhance personalization.
A well-curated prospect list is vital for efficient sales outreach, serving as the foundation for identifying and engaging potential customers. By incorporating relevant data points, businesses can tailor their messaging and focus on the leads most likely to convert.
AI sales assistants can automate the process of building and refining this list by integrating with CRM tools and providing detailed prompts. Locale.ai's AI sales assistant excels in gathering data from various sources, scoring prospects based on criteria like funding and growth, and automating list generation for effective, personalized outreach.
What is a Prospect List and What Data Should it Include?
A prospect list is a list of potential customers or businesses for targeted outreach to sell your product or service. Essential data points to include in the prospect list are geography, industry, company size, services/products, funding/revenue, and growth rate. Additional useful information includes decision-makers, technology stack, and past engagement history.
Including the right data points in your prospect list allows you to segment and prioritize potential customers effectively. With detailed insights into geography, industry, company size, and more, your sales team can engage prospects with personalized outreach that drives results.
Here are the key data points that should be included in a prospect list:
Geography (Geo): Location of the prospect (country, region, city). Helps in tailoring communication based on local needs, laws, and languages.
Industry: The specific sector the prospect operates in (e.g., SaaS, healthcare, manufacturing). This helps in identifying industry-specific pain points and tailoring messaging.
Company Size: This could include employee count or revenue size (e.g., SMB, mid-market, enterprise). Determines the scale of potential deals and customization needs.
Services/Products: What the prospect offers, which helps assess alignment with your solution. Could also include the current software stack or tech tools used by the prospect.
Funding/Revenue: Information on funding rounds, investors, or revenue figures. Gives an idea of the company's financial health and potential purchasing power.
Growth Rate: Whether the company is growing, shrinking, or stable. High-growth companies are often more likely to invest in new solutions.
Additional useful data points could include:
Decision-Makers & Titles: Info about key decision-makers (e.g., CEO, CTO, VP Sales)
Technology Stack: Information on the technologies or platforms the company uses.
Engagement history: Any past interaction or relationship with your company.
How to Build a Prospect List Using an AI Sales Assistant
AI sales assistants can significantly streamline the process of building a prospect list by automating research, lead generation, and CRM integration. Here’s a step-by-step process to build a prospect list using an AI sales assistant:
1. Define Your Ideal Buyer for the AI assistant
Buyer Persona: Clearly outline who your ideal buyer is, including specific details like role (e.g., CXO), industry (e.g., edtech), company size, and location (e.g., US).
Data Points to Collect: Mention critical data points like funding, revenue, technologies used, and decision-making authority.
Example: We are targeting CXOs in edtech companies located in the US that have raised funding in the past year.
2. Connect AI to Your Tools
CRM and Data Sources: Integrate your AI with platforms such as LinkedIn, Apollo, ZoomInfo, or Crunchbase for gathering contact data. Ensure the AI is also connected to your CRM system (e.g., Salesforce, HubSpot) for seamless data export.
Email and Outreach Tools: Optionally, connect with email marketing or LinkedIn automation tools for immediate outreach.
3. Give Prompts to the AI for List Generation
Prompts: Create specific prompts that define the filters for the AI. These prompts tell the AI what type of prospects to search for, including the exact characteristics of the companies and people you want to target.
Example Prompt: "Find CXOs (CEO, CTO, CMO) at edtech companies in the US that have raised at least $1M in funding in the past year."
You can further refine the prompt by asking for company size, technology stack, or specific pain points they may face.
4. Review & Refine the AI-Generated List
The AI will pull data from multiple sources based on your prompt. Review the list for quality control, ensuring the companies and individuals meet your ideal criteria.
If needed, refine your filters and ask the AI for more specific results.
5. Automatically Populate Your CRM
After reviewing the list, instruct the AI to automatically export the prospect data into your CRM system. This ensures that the information is ready for your sales or marketing teams to take immediate action.
You can further categorize prospects in the CRM based on different stages (cold, warm, hot leads) or create segmented lists for personalized outreach.
Templates for Creating a Prospect List Using AI Sales Assistant
Template 1: Building a Prospect List of CXOs for EdTech Companies in the US
Goal: Find CXOs at US-based edtech companies that have raised funding in the past year.
Step-by-Step Prompt:
Find EdTech companies in the US with recent funding:"Find all edtech companies located in the US that have raised funding within the past 12 months."
Identify CXOs at those companies: "Identify the CXOs (CEO, CTO, CMO) for each of these companies."
Pull additional data points: "Pull details on the funding amount, company size (employee count), and the key technologies they use (e.g., CRM, LMS, cloud infrastructure)."
Export the data: "Export this list into Salesforce/HubSpot as new leads tagged under the 'EdTech' segment, adding all relevant data points for outreach
Template 2: Building a Prospect List of Mid-Sized SaaS Companies in Europe
Goal: Target decision-makers at mid-sized SaaS companies in Europe with revenue between $5M–$50M.
Step-by-Step Prompt:
Find mid-sized SaaS companies in Europe: "Find SaaS companies located in Europe with revenue between $5M and $50M."
Identify key decision-makers: "Identify decision-makers such as the Head of Product, CTO, and VP of Sales at those companies."
Collect additional details: "Pull information like employee size, company location, recent growth trends, and any relevant technology stack they’re using."
Export the data: "Export this list into our CRM and categorize it by country for region-specific outreach, with decision-makers flagged for the European SaaS segment."
Best AI Sales Assistant for Prospect List Building: Locale.ai
Locale's AI sales assistants stand out with their advanced deep-research neural network, designed to understand companies with the depth and nuance of a founder. This AI excels in capturing the full context of every interaction and data point, ensuring it has a comprehensive grasp of each prospect. Leveraging this extensive knowledge, Locale's AI generates highly tailored lists that significantly enhance sales efficiency and effectiveness. Here's a more detailed breakdown of each section for how Locale gathers data from multiple sources, assigns scores, and prioritizes prospects:
1. Gather Data from Multiple Sources
Website & Case Studies:
Website Analysis: Locale’s AI scrapes and analyzes the content on company websites to gain insights into their business model, products, and services offered. The AI looks for patterns in how companies describe their solutions, the markets they serve, and their value propositions.
Business Model Identification: Based on this analysis, Locale's AI can categorize whether the company operates as B2B (business-to-business), B2C (business-to-consumer), SaaS (Software as a Service), or other business models. This is crucial for identifying if the prospect fits Locale’s target market.
Pain Points from Case Studies: Case studies published on company websites provide insights into the challenges their clients face and how they solve them. Locale’s AI extracts these pain points, which can be valuable for crafting targeted messaging during outreach.
Crunchbase for Funding & Revenue:
Funding Rounds & Investors: Locale pulls funding data from Crunchbase, including the latest funding rounds (Seed, Series A, B, etc.) and who the investors are. Knowing the stage of funding helps Locale understand the company’s growth trajectory.
Revenue Estimates: Crunchbase also provides estimates on a company’s annual revenue, which can be a strong indicator of company size, health, and capacity to invest in new solutions.
Funding as a Growth Indicator: Companies that have raised recent funding are actively expanding and likely to adopt new technology or invest in growth solutions. Locale’s AI flags these companies as higher priority due to their readiness to purchase.
LinkedIn for Growth Rate & Employee Size:
Employee Growth & Hiring Velocity: Using data from LinkedIn company pages, Locale tracks the growth in the number of employees. If the employee count is rising rapidly, this indicates expansion and likely growing needs for technology or services. Locale also analyzes the rate at which the company is hiring (i.e., hiring velocity) to gauge urgency.
Company Size Insights: Locale uses employee count data to classify companies as small, mid-sized, or large, which helps in tailoring the sales approach. Large companies may have more complex buying processes, while smaller companies may need fast and scalable solutions.
Growth Trends: By comparing past and current employee data, Locale’s AI identifies trends in growth. Companies with a steep growth trajectory are ideal targets as they often face scaling challenges that Locale can help address.
Job Descriptions (JDs) for Tech Stack & Metrics:
Tech Stack Identification: Locale’s AI scans job descriptions for specific keywords related to the technologies a company uses or is planning to implement. For example, if a company is hiring for roles requiring experience with AWS, Salesforce, or AI technologies, Locale can deduce that these technologies are part of the company’s infrastructure.
Tech Stack Relevance: By identifying a company’s tech stack, Locale’s AI determines whether its product or service aligns with the company’s existing technologies, ensuring a more relevant outreach approach.
Metrics & KPIs: Job descriptions often include metrics that indicate company priorities or challenges. For example, a JD might mention a need to "scale cloud infrastructure to support 100,000 users" or "optimize conversion rates." These metrics give Locale’s AI valuable insight into the company’s current focus areas and pain points, which can be used to personalize messaging.
Job Listings for Hiring Trends:
Hiring Role Insights: Locale analyzes active job listings to understand the roles a company is actively hiring for, such as VP of Engineering, Data Scientist, or Head of Product. These roles can indicate specific business goals, such as scaling the product, improving data infrastructure, or building new tech solutions.
Roles Indicating Growth: Companies hiring for key leadership or technical roles are often in growth phases. Locale flags these companies as prospects since they are likely expanding teams and may need products or services to support this growth.
2. Score & Prioritize Prospects
After gathering data, Locale’s AI assigns a qualification score to each prospect based on the following criteria:
Recent Funding:
Companies with recent funding (especially in Series A or B) get a higher score because they are in expansion mode and likely looking to invest in new technology or services. This increases the chances of them being ready to engage with Locale.
Growth Rate:
Prospects showing significant employee growth or high hiring velocity are prioritized because rapid growth often correlates with scaling challenges. These companies are more likely to need new solutions that support growth, which Locale can offer.
Tech Stack Alignment:
Companies using technologies that Locale’s product integrates with or complements are assigned higher scores. If the company’s tech stack matches Locale’s product capabilities (e.g., they are using cloud-based solutions like AWS or AI-based platforms), it makes the sales conversation easier.
Revenue Size:
Companies with revenue falling within a target range (e.g., mid-sized companies with $5M–$50M in revenue) are scored higher as they are more likely to afford Locale’s solutions and be at the right stage for investing in growth tools.
Hiring Roles:
Companies hiring for key roles, such as engineering leadership or product management, are scored higher. These roles often signal a focus on scaling products, improving infrastructure, or expanding tech capabilities, making them ideal prospects.
Once You Have a Prospect List, Here's What Comes Next:
Once you've built a solid prospect list, the next crucial step is turning those leads into meaningful conversations. With a well-curated list in hand, you can now focus on reaching decision-makers, crafting personalized messages, and initiating targeted outreach.
1. Get All the Prospects and Decision Makers
Use the list you’ve built to extract key decision-makers (CXOs, VPs, etc.) for each prospect.
Ensure that you have the most relevant contact information, including emails, LinkedIn profiles, phone numbers, or physical addresses if applicable.
2. Craft Tailored Messaging for Each Prospect
Personalization: Tailor your messaging based on the data points you’ve collected, such as company size, recent funding, or challenges they may be facing.
Value Proposition: Highlight how your product or service addresses their specific pain points.
Tone & Style: Keep the tone in line with their industry and role (formal for CXOs, more casual for startup teams, etc.).
Example Template:
Subject: Congrats on your recent funding, [Name]! Let’s talk scaling.
Message: Hi [Prospect's Name], I noticed that [Company Name] recently raised funding—exciting times! Scaling a business can come with its own set of challenges, and I believe our solution can help [specific benefit]. Let’s schedule a time to discuss how we can support your growth.
3. Reach Out Through Multiple Channels
Email Campaigns: Set up personalized email sequences for your list. Make sure to follow up consistently while offering value in every interaction.
Social Media: Use LinkedIn to connect with prospects and engage with their content. Share insights or articles related to their industry. Consider using LinkedIn InMails or sending a connection request with a personalized note.
Face-to-Face or Events: Attend industry-specific conferences or events where you know your prospects might be present. You can also organize meetups or networking events specifically tailored for your target audience to interact with them in person.
This level of personalization streamlines the sales process, empowering teams to engage prospects with precision and confidence, driving better results and more successful outcomes. Book a demo to learn more about Locale’s AI sales assistants.
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