AI-Driven Upselling Techniques

Successful companies deploy AI to help their people create more value. Companies that fail deploy AI to avoid paying people to create value. Clients expect AI’s ROI to come from cost reductions, but bigger wins come from turning cost centers into revenue generators. A large airline client expected AI to reduce its customer service costs. We implemented AI to detect customer intent and deliver outcomes faster. Productivity improved, but instead of laying people off, we deployed a sales coach into select agents’ workflow. One model gives every customer a rating based on how likely they are to buy an upgrade and predicts the top upgrades to recommend. A second model generates a personalized pitch for the customer service agent to use. We ran a 3-sided experiment: 1️⃣ One group of customer service agents kept working on the AI intent-outcome augmented workflow. 2️⃣ A second group was given a generic script and discretion to pitch upgrades without the AI coach. 3️⃣ A third group was given the AI sales coach and discretion to decide when to accept its recommendations and which upgrade to pitch. After 3 months, the second group had an 8% upgrade pitch success rate, and the third group had a 31% success rate. In the first month, the second group pitched more upgrades than the third, but that switched in months 2 and 3. People do not immediately trust AI. They need to see it function reliably before they truly integrate it into their workflows and trust its output. Giving customer service agents discretion was critical for adoption. As the initiative scales to the entire customer service team, the airline expects to make significantly more money from upsells than it would have saved with layoffs. We reclaimed time with the AI intent-outcome agent and used the opportunity to create a new revenue stream for customer service. We found that when customers quickly go from “I have a serious problem,” to “Hello, thanks for calling support, how can I help?” to “Wow, that was an easy fix,” they’re more receptive to upsells. Businesses that win with AI are reorchestrating workflows and finding new ways to create value. Others don’t see these opportunities, so their only option is cost-cutting.

“We just proved something controversial: This AI Agent sells better than humans.” The proof is right here in this video !! We partnered with CPG Wholesalers and Distributors selling multiple brands from top CPG companies (ITC, HUL, Nestle, Coca-Cola, Britannia), and put SCAI to the test, to achieve the following: 1. Call all the Stores for orders 2. Talk to like an expert salesperson 3. Create a Hyper-personalised catalogue for each store 4. Do promo upsell intelligently, specific to the store 5. Cross-Sell with the most relevant SKU, for each store 6. Take the order and push to the DMS/OMS 7. Summarise each call and the conversation sentiment 8. Learn from the calls and improve The result surprised us !! - None of the retailers realised that they were talking to AI !! - 76% of those who picked up engaged in full conversations - 100% believed it was a human calling - 22% placed orders - 8% bought SKUs, never bought before - Most others asked SCAI to call back next time And during these calls, SCAI handled objections, questions, clarifications, calculations, promotions, and even responded well to several unexpected queries it had no prior data for. SCAI outperformed a human seller on all the benchmarks: AI Seller Benchmark vs Human Sellers: 1. Learning time ⟶ Perfect sales calls from Day 1 (score > 92%) 2. Knowledge ⟶ Full Mastery of products, pricing and promotions (> 100%) 3. Expertise ⟶ Cross-sell, promo up-sell, new products (> 96%) 4. Error rate ⟶ Transaction error 0%, conversation accuracy >98% 5. Response time ⟶ <2 sec for replies, <3 sec complex calculations 6. Consistency ⟶ For all the trained scenarios, >95% 7. Objection handling & Reasoning ⟶ Score : >97% for trained scenarios, >90% for unexpected 8. Patience and empathy ⟶ Score : 100% for trained and unexpected scenarios Plus… - Zero Attrition - Zero Absenteeism - Zero Vacant positions - Zero Missed visits/Calls - 24×7 Availability - Scale from 100 → 100,000 outlets instantly But here’s the real point: Why should AI compete with humans? SCAI doesn’t compete with sales teams; ⟶ it gives them superpowers. "AI handles the calls and orders. Humans handle the customers.” It ensures every store gets the perfect call, every day, while humans double down on what they’re best at: building trust and executing at the store. AI isn’t here to replace humans. AI is here to remove the inefficiencies that hold humans back. SCAI executes flawlessly at scale, and humans step in where empathy, judgment, and relationships matter most. ** The Future is Not Human vs AI ⟶ It's Humans with AI, outperforming anything we’ve seen before.** #SCAI is available in all the major languages (50+ languages, including Hindi, English, Spanish, Portuguese, Arabic and others) For early access to talk to #SCAI yourself, comment “SCAI” or request via this Link >> https://lnkd.in/gAkFvAWw #SCAI #SellsBetterThanHumans #AgenticAI

How To Create An "Amazon" Experience For Each of Your Customers No one does it better, and now you can provide that same experience today for your B2B customers using AI. 1. Predictive Analytics: The Mind-Reader of B2B Buying Behavior Example: AI detects when a prospect repeatedly visits case study pages but ignores pricing, signaling an interest in success stories but potential concerns with cost. With this insight, sales teams can tailor their outreach with ROI-driven messaging rather than generic sales pitches. 2. Real-Time Personalization: Turning Engagement into Action Example: A VP of Marketing visits a SaaS company’s blog on “ABM Strategies.” Instead of a generic website experience, AI reconfigures the homepage to showcase ABM case studies, demo invitations, and ABM-specific pricing models—creating a frictionless, hyper-relevant journey. 3. Intent Detection & Lead Scoring: Stop Guessing, Start Knowing Example: A prospect downloads a whitepaper but doesn’t respond to follow-ups. AI cross-references their LinkedIn activity and detects that they recently engaged with a competitor’s post on the same topic. This triggers an automated, high-touch follow-up addressing competitor comparisons. 4. AI-Driven Conversational Sales: Guiding Buyers in Real-Time Example: A chatbot engages a first-time website visitor, identifies their industry, and instantly suggests relevant case studies and a tailored demo video. Meanwhile, AI flags this visitor as a high-value lead and notifies the sales team for real-time engagement and relationship building. 5. Automated Multi-Channel Engagement: Right Message, Right Time Example: A decision-maker engages with an email but doesn’t click. AI automatically retargets them with a LinkedIn ad showcasing a customer success video, increasing the likelihood of further engagement. 6. AI-Driven Churn Prediction: Preventing Drop-Off Before It Happens Example: AI flags an enterprise client who suddenly reduces platform logins and stops engaging with support tickets. Instead of waiting for churn, AI triggers a proactive outreach campaign, offering personalized support or exclusive features to reignite engagement. This is your opportunity to create a personalized customer journey for each one of your top Ideal Customer Profiles and DOUBLE YOUR SUCCESS almost immediately. #customerexperience #customerjourney #digitalmarketing #marketing