Update Contact Fields

1. Peferred Communication Style

📌 Why? Some customers prefer text, others calls, and some only want emails at specific times. 💬 AI Example: “Just so we communicate the way you like, do you prefer updates via text, email, or phone calls?” * 📊 Stored As:* Preferred contact method (Text, Email, Phone), Preferred Contact Time

1. Intent Strength Score (How Ready They Are to Buy/Act)

📌 Why? Knowing if a lead is ready to buy helps businesses prioritize follow-ups. 💬 AI Example: “On a scale of 1-10, how urgent is your need for this service?” * 📊 Stored As:* Lead Priority Level (1-10 Scale)

1. Emotional Sentiment of the Call

📌 Why? AI detects customer sentiment (excited, frustrated, hesitant) to predict churn or conversion likelihood. 💬 AI Example: “I can tell this is really important to you—I'll make sure we get it right.” (Analyzed for tone and word choice) 📊 Stored As: Sentiment Score (Positive, Neutral, Negative)

1. Purchase or Booking Barriers (Why They Haven’t Acted Yet)

📌 Why? Identifies objections so the business can adjust its sales pitch. 💬 AI Example: “Is there anything holding you back from making a decision today?” * 📊 Stored As:* Common Objections (Price, Timing, Uncertainty, Need More Info)

1. Customer's Industry or Use Case

📌 Why? Helps personalize future offers and segment customers better. 💬 AI Example: “Are you using this for personal use or for your business? If for business, what kind of work do you do?” * 📊 Stored As:* Industry Type, Personal vs. Business Use

1. Hidden Upsell Opportunities

📌 Why? Helps identify additional products or services the customer might need. 💬 AI Example: “Most people who buy this also get [related service]. Would that be helpful for you?” * 📊 Stored As:* Interest in Upsell Products/Services

1. Preferred Appointment Days & Times

📌 Why? Reduces scheduling friction by knowing when they are most available. 💬 AI Example: “Do you usually prefer morning, afternoon, or evening appointments?” * 📊 Stored As:* Best Appointment Time

1. Customer’s Budget Range (For Pricing Adjustments)

📌 Why? Knowing budget constraints helps with tiered pricing or special offers. 💬 AI Example: “To make sure I recommend the best option, do you have a budget range in mind?” * 📊 Stored As:* Budget Range

1. How They Found the Business (Marketing Attribution)

📌 Why? Helps measure which marketing channels are working best. 💬 AI Example: “Just curious—how did you hear about us?” * 📊 Stored As:* Marketing Source (Google, Social Media, Referral, Ad, Other)

1. Customer’s Urgency Window (Short-Term vs. Long-Term Buyer)

📌 Why? Helps businesses prioritize follow-ups. 💬 AI Example: “Are you looking to get this done ASAP, or is this something you’re planning for later?” * 📊 Stored As:* Purchase Timeline (Immediate, 30 Days, 60+ Days)

1. Competitor Comparison (What Other Companies They’re Considering)

📌 Why? Helps businesses adjust pricing, messaging, and offerings. 💬 AI Example: “Have you looked at any other options, or are we the first company you’re speaking with?” * 📊 Stored As:* Competitor Name, Decision Factors

1. Customer’s Pain Point or “Why” They Need the Service

📌 Why? Knowing the core reason helps businesses craft more compelling messaging. 💬 AI Example: “What made you start looking for this service today?” * 📊 Stored As:* Core Pain Point

1. Lifetime Value Potential (Are They a One-Time or Recurring Customer?)

📌 Why? Helps businesses identify VIP customers early. 💬 AI Example: “Do you see this as a one-time purchase, or will you need ongoing support?” * 📊 Stored As:* Customer Type (One-Time, Recurring, Subscription Potential)

1. Preferred Product or Service Features

📌 Why? Helps businesses prioritize which features to focus on in marketing. 💬 AI Example: “What’s most important to you when choosing a [product/service]?” * 📊 Stored As:* Feature Priority (Speed, Price, Quality, Customer Service)

1. Referral Potential (Who Else Might Need This?)

📌 Why? Turns customers into referral sources immediately. 💬 AI Example: “Do you know anyone else who might benefit from this? We have a referral program.” * 📊 Stored As:* Referral Lead Collected (Yes/No)

1. Customer's Tech Comfort Level (For Digital Services)

📌 Why? Helps businesses tailor their support approach. 💬 AI Example: “Do you prefer digital self-service tools, or do you like speaking with someone directly?” * 📊 Stored As:* Tech Comfort Level (Self-Service, Hybrid, Full Assistance)

1. Location Data (For Hyper-Local Targeting & Service Areas)

📌 Why? Helps businesses refine local marketing efforts. 💬 AI Example: “Are you based in [city name], or are you looking for services in a different area?” * 📊 Stored As:* Customer’s Location

1. Business Size & Employee Count (For B2B Sales)

📌 Why? Helps segment leads for tailored sales strategies. 💬 AI Example: “Just to personalize this better—how big is your team?” * 📊 Stored As:* Business Size (1-10, 11-50, 50+)

1. Social Media Preferences (For Future Retargeting)

📌 Why? Allows businesses to retarget customers where they spend time. 💬 AI Example: “Are you active on social media? We share updates and special deals there.” * 📊 Stored As:* Social Media Platform Preference (Facebook, Instagram, LinkedIn, None)

1. Customer’s Risk Tolerance for Price vs. Quality

📌 Why? Helps businesses tailor pricing strategies. 💬 AI Example: “Are you looking for the most affordable option, or are you more focused on getting the best quality?” * 📊 Stored As:* Price Sensitivity Level (Budget, Balanced, Premium)