How to Use an AI Sales Tool to Improve Your Funnel

Everyday a new AI app is launched in the market, overwhelming sales leaders on which one is real and which are hype.

This post will teach you how to cut through the noise and identify the right AI sales tool for your needs. 

What is AI sales automation?

Conduct a ‘Sales Funnel’ audit before buying

The first step is to understand what is broken in your sales process before jumping to solutions. 

Ask yourself:

• Do we struggle to find leads? (Top of Funnel problem)
• Do we struggle to get replies? (Middle of Funnel problem)
• Do we struggle to close deals? (Bottom of Funnel problem)

Identify the problem, then move on to find an AI sales automation tool to fix it.

How does AI sales automation optimize the sales funnel?

Top of Funnel (Lead Generation + Outreach)

This is the awareness stage where people know they have a problem but don’t have a solution. This is where outbound outreach becomes essential. You don’t wait for them to contact you; you hunt them.

AI helps with:

• Prospecting: Find companies that match your ICP.
• Finding verified emails: Uses predictive match pattern to guess email format and pings the servers to verify existence.
• Personalized outreach: LLMs scrape prospect info (recent news, linkedin post) and fuses them into the email content.
• Outbound automation: Manages the sequence at which emails/calls are scheduled. 
• Ad targeting optimization: AI sales tools handle real-time bidding and pops the most creative ad to a specific user to grab their attention, all based on their browser history.

Mid Funnel (Lead Qualification + Nurturing)

In this stage, the buyer is considering solutions and the salesperson is qualifying the buyer to see if they are a wasted effort or a real opportunity.

AI helps with:

• Lead scoring: Uses predictive scoring to analyze thousands of historical closed-won deals to identify hidden patterns (e.g., "leads who visit the pricing page twice in one week are 80% likely to close").
• Automated follow-ups: Sends nurture emails to those that have gone cold in a sequenced manner so no lead is left unattended.
• Predicting likelihood of closing: In CRMs, this is called win probability. AI sales tools predict the likelihood of deal closure based on lead behaviour (opening/replying to emails).‍
• Chatbots that pre-qualify leads: Acts as a 24/7 SDR. Conversational AI qualifies leads by asking BANT questions, and directly blocks a meeting in the rep’s calendar if they match all criteria.

Bottom Funnel (Deal Closing + Forecasting)

In this stage, the buyer is in decision mode, while the salesperson handles negotiations to close the deal, all the while upholding business credibility. 

AI helps with:

• Sales call analysis: AI records calls, transcribes them, and analyzes sentiment (did the customer sound convinced/happy/angry) and talk-to-listen ratio (did the rep speak too much?)
• Deal insights: AI flags deal risks. For example, it might alert a manager: "This deal is set to close Friday, but the decision-maker hasn't emailed back in 12 days."
• Pipeline health: AI sales tools update lead info on the CRM and flag stalled deals (no stage update for 20+ days), for managers to intervene and nurture that contact.‍
• Forecasting: Analyzes data by combining deal score, win probability and historical patterns to predict accurate revenue.

Post-Sale (Retention + Upsell)

AI helps with:

• Churn prediction: AI sales tools analyze product usage telemetry. If a user stops logging or the usage of a key feature drops significantly, they are flagged as ‘at-risk’ months before contract expiry. 
• Behaviour-based triggers: Identifies moments to upsell. For example, if a customer hits 90% of their data limit, AI can auto-trigger an email suggesting an upgrade to the next tier.‍
• Automated renewal reminders: AI tracks contract end dates about 90, 60, 30 days before renewal and drafts an email to the account manager for review.

An AI sales tool integration checklist

• Does it integrate with your existing CRM?
• Is it scalable with your business growth?
• Does the tool comply with necessary guidelines?
• Does it require a heavy set-up or is it easy to implement?
• Will it help improve pipeline and forecast revenue better?

Rippling increasing win rates and LTV using Gong

Challenge

Rippling needed to streamline performance across a rapidly expanding Go-to-Market (GTM) operation that included over 45 products and thousands of accounts. They were facing:

• Missed signals during discovery and implementation.
• Slower-than-necessary deal cycles.
• Inconsistent customer onboarding processes.

Solution

Rippling implemented the Gong Revenue AI Platform across its sales and account management teams to enable smarter sales enablement and proactive retention. They used Gong for:

• Scaling best practices and improving deal execution by sharing top-performing calls and snippets.
• Identifying churn signals proactively using sentiment analysis.
• Creating playbooks based on call data to eliminate unnecessary questions during onboarding.

Result

By leveraging Gong's AI-powered insights, Rippling achieved significant improvements:

• Win Rates increased by 13%.
• Customer Lifetime Value (LTV) climbed 15%.
• Customer onboarding time was reduced by over 20%.
• Deal cycles were shortened by 10%.

AI will not replace salespeople, it is here to help them work faster, smarter and make data-driven decisions. The earlier you adopt, you gain a competitive advantage in the market. 

Identify the issue, pick your tool list, book a demo, run CRM trials, and see the difference for yourself.