Welcome to the forefront of conversational AI as we explore the fascinating world of AI chatbots in our dedicated blog series. Discover the latest advancements, applications, and strategies that propel the evolution of chatbot technology. From enhancing customer interactions to streamlining business processes, these articles delve into the innovative ways artificial intelligence is shaping the landscape of automated conversational agents. Whether you’re a business owner, developer, or simply intrigued by the future of interactive technology, join us on this journey to unravel the transformative power and endless possibilities of AI chatbots.
Most companies use chatbots wrong. They slap a bot on their website, watch it frustrate customers, then wonder why adoption stays low.
The reality: chatbots work brilliantly for specific tasks and fail miserably at others. A recent survey found 60% of U.S. consumers appreciate 24/7 availability, while 45% just want faster answers1 . Notice what’s missing? Nobody mentioned “delightful conversations” or “human-like interactions.”
We looked at 40 real chatbot applications across industries to see what actually delivers results versus what’s just marketing hype.
Reactive chatbots wait for you to start the conversation. Customer support, product questions, order tracking, you ask, they respond.
Proactive chatbots message you first. Software update reminders, abandoned cart notifications, and shipping alerts reach out without prompting.
Customer support chatbots work well in virtually any industry where you need to keep clients informed and connected.
Support chatbots answer common questions immediately. Password resets, order status, return policies—queries with clear answers get resolved without human involvement.
The more intelligent bots know their limits. When someone asks, “Why hasn’t my refund arrived after 3 weeks?” the bot collects details and routes to a human. When someone asks, “What’s your return policy?” the bot just answers.
Amazon’s support bot processes millions of queries daily. It handles straightforward issues (tracking numbers, delivery dates) and escalates anything involving money or complex problems. The bot also asks “Did this help?” after each interaction, feeding data back to improve responses2 .
Natural language processing lets bots understand questions phrased fifty different ways. “Where’s my order?” “When will it arrive?” “Shipping status?” all trigger the same tracking lookup.
This matters more than it sounds. Humans get tired of answering the same question repeatedly. Bots don’t.
Domino’s Pizza bot lets you order, track delivery, and resolve issues without calling anyone. Sounds simple, but consider: every bot-handled order saves 5-7 minutes of phone time. At scale, that’s hundreds of employee hours weekly3 .
Store hours. Contact info. Product specs. FAQs. Bots excel at sharing information that never changes.
IKEA’s bot tells you store locations, opening times, and whether specific items are in stock. Before the bot, customers called stores directly, tying up phone lines for questions that took 10 seconds to answer.
After the bot launched, call volume dropped 30% for basic inquiries. Staff now spend more time helping customers actually in the store4 .
Figure 1. IKEA’s Chatbot.
Some bots don’t talk to customers; they help the people who do.
Allstate Business Insurance Expert (ABIe) assists 12,000 insurance agents. Agents ask ABIe about policy details, pricing, and coverage options. The bot surfaces information from massive databases faster than agents can search manually.
This flips the usual chatbot model. Instead of replacing humans, ABIe makes humans more effective5 .
Nobody enjoys chasing late payments. Bots send reminders automatically.
AT&T’s billing bot messages customers 3 days before payment is due, then again on the due date if unpaid. Late payments dropped 25% after implementation—not because customers suddenly became more responsible, but because they stopped forgetting6 .
Shopping bots suggest products based on what you’ve viewed, bought, or searched for. The good ones ask clarifying questions instead of just throwing recommendations at you.
Spotify’s bot suggests playlists by asking what you’re doing (working out, studying, relaxing) rather than just analyzing your listening history. Small detail, big impact on relevance7 .
When customers browse then leave without buying, bots can offer discounts to close the sale.
Sephora’s bot analyzes how long you’ve been looking at a product and whether you’ve visited before. First-time browsers get welcomed. Return visitors who added items to cart get a 10% discount code8 .
The trick: offer discounts only when likely to change behavior, not to every visitor.
Keeping existing customers costs less than acquiring new ones. Bots identify warning signs, decreased usage, support complaints, missed payments, and intervene.
Netflix’s retention bot notices when you haven’t watched anything in 2+ weeks. Instead of waiting for you to cancel, it sends personalized show recommendations based on your history 9 .
Does it always work? No. Does it recover enough subscribers to justify the effort? Absolutely.
Car dealerships waste hours on unqualified leads. Someone fills out a form asking about a $60,000 SUV, but actually wants financing info for a used sedan.
Toyota’s bot asks qualifying questions upfront:
Sales staff only get leads that match available inventory and have realistic budgets. Test drive scheduling happens automatically for qualified leads10 .
Figure 2. Toyota’s chatbot
Students need quick answers about courses, deadlines, financial aid. University websites bury this information across dozens of pages.
Custom education bots (built on GPT models) answer questions using the school’s specific policies and catalog. The bot cites sources, so students verify information if needed.
Realtors spend hours qualifying leads who “just want to look” versus serious buyers.
Zillow’s bot pre-screens by asking:
Realtors prioritize leads marked “pre-approved, buying within 90 days” over those marked “exploring options, no timeline.”efn_note]https://github.com/zillow/compliant-real-estate-chatbot[/efn_note]
Subscription and repeat-purchase businesses use bots to trigger reorders.
Chewy (pet supplies) messages customers when purchase history suggests they’re running low on food or medication. “Your usual order of X is due for reorder. Want to schedule delivery?”
This works because timing is predictable. A 30-pound bag of dog food lasts roughly 6 weeks. The bot messages at week 5.11
Customers stop using your service. Maybe they forgot about it. Maybe they found a competitor. Maybe they just got busy.
Uber Eats identifies users who haven’t ordered in 30+ days and offers a discount. The bot personalizes based on past orders: “We miss you! Here’s 20% off your favorite Thai restaurant.”12
Win-back campaigns have low success rates (typically 10-20%), but they’re cheap to run. A bot can message thousands of inactive users for negligible cost.
Healthcare insurance confuses everyone. Copays, deductibles, in-network vs out-of-network, coverage limits, it’s intentionally complicated.
HealthJoy’s bot answers coverage questions in plain language:
The bot pulls from your specific plan, so answers are personalized. Beats spending 45 minutes on hold with insurance companies13 .
Diagnostic bots don’t replace doctors—they triage symptoms before you decide whether to seek care.
Ada Health asks about symptoms, duration, and severity. Based on responses, it suggests:
COVID accelerated adoption dramatically. People wanted symptom screening without exposing themselves or others at clinics14 .
Therapy is expensive and waitlists run months long. Chatbots fill the gap for people needing immediate support.
Fitness apps generate data. Chatbots make that data actionable.
MyFitnessPal’s bot messages you:
The bot turns passive tracking into active engagement15 .
Instead of browsing product pages, you tell a bot what you want. It asks clarifying questions and suggests options.
H&M’s shopping bot asks:
Then shows 5-10 options that match. You can buy directly in chat without visiting the website.
This works better for specific needs (“I need a dress for a wedding”) than general browsing (“I want to see what’s new”).
You want to buy something but not at current price. Traditional solution: check manually every day. Better solution: let a bot watch for you.
CamelCamelCamel (for Amazon) tracks price history and alerts when items hit your target price. Set it at “notify me when this drops below $50” and forget about it16 .
“Where’s my package?” is the most common customer service question for e-commerce. Bots answer instantly by pulling tracking numbers from shipping carriers.
Tars and similar platforms integrate with Shopify, WooCommerce, and other e-commerce systems. Customers ask “where’s order #12345?” and get real-time tracking without human involvement17 .
Selling through Instagram and Facebook requires different mechanics than traditional e-commerce. You can’t send people to a website they want to buy without leaving the app.
Nike’s Facebook Messenger bot lets you browse, ask questions, and purchase entirely within Messenger product photos, sizing info, and checkout all in chat18 .
Canceling subscriptions shouldn’t require calling customer service and getting transferred three times. Yet many companies make it deliberately difficult (hoping you’ll give up).
Travel booking involves coordinating flights, hotels, rental cars, and activities. Bots handle the coordination.
Expedia’s virtual assistant books flights and hotels in one conversation. You specify:
The bot presents options and handles booking once you decide.
Planning trips takes hours of research. Where to stay? What to do? How to get around?
Booking.com’s AI builds itineraries based on your interests. Tell it “5 days in Barcelona, interested in architecture and food” and it suggests:
OpenTable’s bot checks real-time availability and confirms reservations. You can modify or cancel through the same interface.
Before bots, you called restaurants during business hours (often getting busy signals) or used clunky websites. The bot works 24/7 and handles confirmations automatically.
Conferences, festivals, and large events generate repetitive questions: Where’s parking? What time does X start? Where’s the bathroom?
Eventbrite’s bot answers these automatically, reducing the burden on event staff. It also sends personalized schedules based on which sessions attendees registered for.
Google Assistant suggests restaurants, attractions, and activities based on your location and preferences. It learns from past trips—if you always skip museums, it stops suggesting them.
Investment bots assess your risk tolerance, goals, and timeline, then build a portfolio.
Betterment asks:
Then allocates your money across index funds, automatically rebalancing as markets shift.
Minimum investment: $10. Compare to traditional financial advisors requiring $100K+ minimums.
Applying for credit cards or loans involves repetitive form-filling. Bots streamline by asking questions conversationally.
Kasisto’s KAI checks pre-qualification, explains loan terms, and tracks application status. Instead of filling out 30 form fields, you answer questions one at a time19 .
Figure 3. Kasisto KAI chatbot advertisement
Cryptocurrency trading intimidates newcomers. Bots simplify by handling basics.
Coinbase’s bot helps you:
The bot explains concepts in simple terms, “gas fees are transaction costs on the Ethereum network,” rather than assuming knowledge.
Google’s Gemini (partnered with Associated Press) delivers news based on topics you follow. It learns preferences over time—if you skip sports stories, it shows fewer.
Netflix and Spotify use bots to survey users about preferences. Instead of email surveys (low response rates), they ask questions in-app through chat.
“What did you think of Season 2?” “Rate these new releases” “Which genre should we add next?”
Higher response rates because friction is lower.
Disney’s Facebook Messenger bot quizzes fans on movie trivia, offers behind-the-scenes content, and previews upcoming releases. It’s marketing disguised as entertainment.
IBM Watson Assistant handles initial candidate screening:
Qualified candidates get scheduled for interviews. Others receive polite rejections. Recruiters avoid spending hours on unqualified applicants.
New employees have dozens of questions: Where’s IT support? How do I request PTO? What’s the dress code?
Onboarding bots answer these automatically, available 24/7 during those first confusing weeks.
Calendly’s bot finds meeting times across multiple calendars, sends invites, and reschedules when conflicts arise.
No more email chains: “Does Thursday at 2pm work?” “No, how about Friday at 10am?” “I have a conflict then…”
Slack and Microsoft Teams use bots to track project tasks:
The bot pulls from project management tools like Asana or Trello, so information stays centralized.
Figure 4. Slack’s chatbot interface
Hilton Hotels uses AI in staff training for customer service scenarios. The bot plays difficult customer, staff practice responses, and the system evaluates how they handled it.
Better than role-playing with coworkers (who go easy on you) but safer than learning on actual customers.
Asana’s AI assistant sorts your task list by:
It suggests “Start with these 3 tasks today” instead of overwhelming you with a 40-item list.
AI chatbots help companies better understand employee experiences by conducting conversational surveys directly within collaboration platforms, making feedback collection simple and painless.
Example: Slack’s AI-powered Polly bot enables frequent, frictionless employee feedback, resulting in higher participation rates and improved workplace satisfaction.20
Figure 5. Slack’s Polly chatbot advertisemen
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Love these use cases of chatbots in industries and businesses! I would like to add more. Hope your audience will find it useful and interesting: Real estate. The AI assistant was built for simplification property search without additional emailing, calls, or visiting buro. In a few clicks, the client gets the latest offers and books appointments. Take a look at https://chatbots.studio/ai-chatbot-for-real-estate-industry/ Insurance. Chatbots for insurance are the tool for automation administrative tasks and customer journeys. Chatbot acts like live agent and holds all processes from the start and up to the accident where a client needs quick help. Take a look at https://chatbots.studio/chatbot-for-insurance-services-company/ Beauty. Chatbots in this business are widely-used. But only some of them are really useful and make interesting engagement like Sephora, Belle or Yves Rocher. The last one is created not only for selling but also for diagnostics skin and hair. Take a look at the example of successful chatbot in beauty and cosmetology https://chatbots.studio/chatbot-for-online-diagnostics-and-sales-in-messenger/
Thank you!
A very interesting article that coincides with our experiences at inteliwise.com. Every day we introduce similar solutions for clients from various industries. Thanks to the use of natural language processing technology (NLP), we have significantly improved the effectiveness of AI-Chatbot InteliWISE. The client, using his natural everyday language, asks a question, and the Virtual Advisor immediately gives a ready solution to his problem. We describe some of our examples in InteliWISE, from around the world, at InteliWISE.com
Hi there! You guys left a comment that begins almost exactly like this at https://research.aimultiple.com/chatbot-success/. Looks like bots are writing comments. I would expect your bot to be more creative or at least to have filters such that it did not leave the same comments via different users on the same website.
Hi Cem, You have listed some interesting use cases of chatbot.Loved it! I like to add up a few more for your readers. https://www.ideas2it.com/blog/50-chatbot-use-cases/
We follow ethical norms & our process for objectivity. This research is not funded by any sponsors.
