The easiest win is using tech to talk to riders like individuals instead of a crowd. If I were running a transit agency, I would start with a solid mobile app that remembers a rider's usual routes and times, then pushes only the updates that actually matter to them. So instead of generic service alerts, someone who takes the same bus every morning gets a quiet ping when that specific line is delayed, a stop is moved, or there is a faster option nearby. One system I saw tested something similar on a rail network using real time data and basic preferences and it completely changed how riders felt about disruption. People were still delayed, but they were not blind. A simple example would be an app that learns you always go from neighborhood A to downtown between six and eight in the morning and starts showing a tailored home screen with next departures, crowding estimates, and one tap options to reroute if something breaks. That kind of personalization does not require crazy AI, just good data, clean integrations, and a decision that you will stop treating riders as one big anonymous blob.
Transit agencies can really give their riders a more personal touch if they adopt a customer data platform that puts all the customer interactions and preferences together in one place, so they can tailor the way they communicate across all channels in a much more meaningful way. In my previous gig I actually used a similar platform in retail, bringing together purchase history, browsing habits and demographics to create profiles and send out emails, text messages and website content that was directly relevant to each customer at the time. This allowed us to send messages that really matched where each customer was at in terms of their shopping journey. If a transit agency were to do the same thing, they could send real-time updates on the rider's usual routes, share special station updates right on the app, and highlight all the nearest ways to get to and from the station that play to that rider's habits. The end result is that the info feels super relevant and not just some bland generic message.
Transit agencies can personalize the rider experience by using the app like a "smart commute assistant," not just a route finder. If a rider opts in, the app can remember their usual routes, favorite stops, typical travel times, and needs (like step-free access, fewer transfers, or less walking). Then it combines that with real-time data such as delays, cancellations, platform changes, service alerts, and fare rules to show only what matters to that rider, at the exact moment they need it. Example: a rider saves "Home - CBD" and selects "step-free routes." At 7:10am the app sends: "Lift is out at Central. Use Entrance B for ramp access. Next accessible train in 9 minutes. Alternate option: Bus 210 arrives 6 minutes later but avoids stairs." The app can also suggest the right ticket automatically and notify the rider if they're about to hit a daily fare cap.
Transit agencies can get the most out of technology by tailoring their updates to individual riders' habits rather than sending the same message to everyone. For instance, they can use riders' app-based travel history and preferences to send targeted service alerts. If a commuter always takes the same bus and train on weekdays, the system can send alerts that specifically affect their usual route, time, and transfer point. Instead of a citywide disruption notice, they'll get a message saying their usual train is delayed, suggesting an alternative route, and estimating the impact on their arrival time. Personalization can also help with fare optimization. Agencies can notify riders when they're close to their weekly or monthly cap, or suggest a better pass based on their past usage patterns. This builds trust because the system is helping riders save money, not spend more. The key is to use technology thoughtfully. Riders don't want more notifications; they want fewer, more relevant ones that respect their time and context. When technology reduces uncertainty and friction in daily travel, personalization feels like a helpful service, not surveillance.
Chief Marketing Officer / Marketing Consultant at maksymzakharko.com
Answered 4 months ago
Transit agencies can use rider behavior and preferences to tailor communications and app content so riders get information that matters to them. As a customer of a travel and hospitality brand, I received timely, tailored emails and saw dynamic website content based on my past behavior, which made the experience feel personal and relevant. Agencies can mirror this by offering opt-in alerts aligned to a rider’s usual routes and times, and by surfacing dynamic updates like platform changes, crowding levels, or faster transfer options. The app or site can also highlight nearby first‑ and last‑mile choices and service advisories that match a rider’s typical journeys. Done well, this increases relevance, reduces friction, and builds trust while respecting privacy.
I've spent 18 years optimizing digital experiences, and the #1 mistake I see is over-personalizing too early. Transit agencies do this when they hit riders with account creation prompts or notification requests before proving any value. That's like the aggressive salesperson following you around the store--it kills trust instantly. Here's what actually works: IP-based location detection for automatic station defaults, combined with one simple question at first use--"Commuter or Visitor?" That single data point changes everything. Commuters get saved routes and delay alerts for their regular lines. Visitors get tourist-friendly maps with landmarks, not just station codes. No login required until they want to save preferences. I helped BBQGuys increase revenue by 30% using this exact approach--we showed location-specific content without asking for anything first. A transit app could do the same: detect you're near the airport station at 6am on a Tuesday, automatically surface express routes downtown with arrival times. If you open the app at that same station on Saturday at 2pm, show weekend service schedules and connecting lines to entertainment districts instead. The secret is transparent personalization. Tell riders *why* you're showing them specific information: "Based on your location, here are the fastest routes to downtown" builds trust. Silently changing what they see without explanation feels creepy. Make the personalization feel like helpful service, not surveillance.
I built real-time tracking systems for bourbon pricing at BRBNFNDR--400 subscribers relied on instant alerts when bottles dropped below their target price. Transit agencies can do the same: let riders set a "comfort threshold" (crowding level, temperature, delay tolerance) and push notifications only when those conditions are met on their saved routes. The trick is starting with one high-friction moment and automating the answer. At Penn Medicine, we saw 38% higher email opens by sending appointment reminders timed to when patients actually checked their phone--morning for early shifts, evening for night workers. Transit apps should do this: if someone always boards the 7:12 AM bus, surface that specific departure with live capacity and weather-adjusted walking time at 6:50 AM, not a generic "plan your trip" homepage. We saved $85k/year by deploying AI agents that monitor server performance and answer repetitive support questions. Transit agencies could use similar agents to auto-respond to "Where's my bus?" texts with real-time ETAs and reroute suggestions based on the rider's location and destination--no app download required, just SMS. The riders who need help most (older adults, low-income commuters without smartphones) get served first, not last.
Transit agencies can use AI to read rider behavior signals and tailor messages, alerts, and offers. At Aitherapy, I used AI to analyze exploration time and feature revisits, then redesigned offers around those engagement signals to increase relevance for each user. A similar model in transit can track how often a rider checks a specific route, the times they plan trips, and which alerts they reopen. The system can then prioritize service notifications for those routes, surface the best transfer options for their usual time window, and present fare choices that fit their usage. This keeps information timely and reduces noise, which helps build trust and satisfaction.
I spent 40 years managing two practices--a law firm and a CPA firm--and learned that personalization isn't about fancy tech, it's about anticipating what someone needs before they ask. Transit agencies should look at payment history and route patterns to automatically flag when a rider's monthly pass is about to expire, then send a renewal reminder with a one-tap purchase option. We did this with client retainers--automated reminders three days before they'd need to renew saved hundreds of hours in back-and-forth. Here's what actually works: segment riders by behavior, not demographics. Someone who always boards the 7:15am bus Monday-Friday doesn't need weekend route promotions clogging their notifications. They need to know if *that specific bus* is running late tomorrow. In my CPA practice, we tracked client interaction patterns and only sent tax reminders relevant to their filing type--S-corps got different alerts than sole proprietors. Engagement jumped 40% when we stopped spraying general updates. The biggest miss I see is agencies asking riders to manually input preferences. Nobody does that. Instead, use passive data--if someone's GPS shows they're standing at a bus stop in the rain at 6:45am, push an alert showing exactly when their bus arrives, not the system-wide status. When clients logged into our portal during tax season, we auto-displayed their most urgent deadlines first, nothing else. Simple behavioral triggers beat complex preference menus every time.
Transit agencies can use technology to personalize the rider experience by leveraging real-time data, mobile apps, and predictive analytics to deliver information and services tailored to individual needs. Instead of treating all riders the same, these tools allow agencies to anticipate preferences, alert riders about relevant changes, and make journeys smoother. For example, a commuter who typically takes a specific bus route could receive push notifications on their phone if that route is delayed, suggest an alternative route, or even offer estimated arrival times based on current traffic conditions. Over time, apps can learn patterns—like preferred departure times or transfer choices—and provide proactive recommendations, such as suggesting a less crowded train car or alerting them when their usual route is faster via a different mode of transport. Some agencies are also using mobile apps to allow riders to customize their experience, like setting accessibility needs, preferred modes, or alerts for nearby stations. When combined with real-time data on delays, service changes, or local events, the system can provide highly relevant, actionable guidance that makes the daily commute less stressful and more efficient. One example comes from several European cities where transit apps integrate multiple modes of transport—bus, metro, bike-share, and ride-hailing—into a single interface. Riders can plan trips based on personal priorities, whether that's speed, cost, or comfort. The result is a more seamless, personalized experience that encourages public transit use and builds trust between riders and agencies.
I run a network of fitness clubs across Florida, and we've spent years figuring out how to give members exactly what they need without bombarding them. The breakthrough for us was using the Medallia feedback platform to capture what people actually care about in real-time--then shaping their experience around those signals. Transit agencies could do something similar: track which routes people search for repeatedly in the app, then surface live updates for *those specific lines* on the home screen before riders even ask. The game-changer is predictive personalization based on behavior patterns. At Just Move, our Fit3D body scanners automatically suggest the next scan date based on each member's workout frequency--someone training 5 days a week gets pinged at 4 weeks, casual members at 8 weeks. Transit apps could watch your travel history and proactively alert you when your Monday commute route has construction coming up *next* Monday, not the day of. That's the difference between helpful and annoying. We also learned that personalization dies if the baseline service sucks. Our meal delivery service only works because members trust the food will actually show up--no amount of customized menus matters if delivery is unreliable. Transit agencies need rock-solid real-time tracking first, then layer on personalization. Fix the buses arriving on time before you build an AI that suggests alternate routes.
I run a roofing company in New Jersey, and we've been testing SMS personalization for six months now--it's taught me a lot about giving people exactly what they need without overload. The biggest lesson: let customers control the flow of information from day one. We set up our SMS system so customers opt in and immediately tell us what they want to hear about--quote updates, scheduling changes, or just final completion notices. Transit agencies could do the same thing: when someone downloads the app, ask them to flag their top 3 concerns (wheelchair access, bike rack availability, or express routes) and filter everything else out by default. That one choice shapes every notification they get. Here's what actually works: we don't share customer phone numbers with third parties, and we make opting out dead simple--just text "STOP." That built trust fast. Transit riders would use an app way more if they knew their route preferences weren't being sold and they could kill notifications instantly without digging through settings. Privacy + control = people actually engage. The other thing we learned is timing matters more than volume. We only text when there's a real update that changes someone's day--roof crew delayed by weather, materials arrived early. Transit agencies should do the same: if your usual 8:15 bus is running 10+ minutes late, ping that rider at 8:00 so they can grab coffee or take an alternate route. No one needs 47 notifications--they need the one that saves them from standing in the cold.
Honestly, I'm not in transit--I run operations for a sewer and drain company in North Carolina. But we face the exact same challenge: getting the right info to people at the moment it matters, without burying them in noise. Here's what actually works for us. When someone calls about a backup, we don't start with a 20-minute explanation of CIPP lining technology. We ask two questions: "Can you use your plumbing right now?" and "Is water coming up anywhere?" Those answers tell us if it's a same-day emergency or scheduled repair. Then we send a follow-up text with their exact arrival window--not a four-hour range, an actual "Tech arriving 2:15-2:45pm" update. Our show rate went up and our phone volume dropped because people aren't calling back asking "where are you?" Transit could do the same thing. If I'm standing on a platform at 7:43am on a Tuesday, I don't need the full system map. I need to know if my usual train is on time, and if not, whether the next one gets me to work before 8:30. That's it. We learned this the hard way coordinating 10-15 jobs during peak season--too much information creates more confusion than no information. The open up isn't fancy AI. It's just asking: what decision is this person trying to make *right now*, and what's the single piece of information that helps them make it? Everything else can wait.
I saw this play out when a city transit app quietly started learning rider patterns instead of blasting generic alerts. Commuters who always took the same bus began getting personalized notifications about delays, alternate routes, and crowd levels before they even left home. It felt odd at first. Riders trusted the system more because it spoke directly to their routine. One agency even paired fare data with event schedules so people heading to games got different guidance than daily commuters. Funny thing is complaints dropped without adding new service. Personalization worked because it reduced uncertainty, not clicks. Technology did not change the buses. It changed how prepared people felt before stepping outside.
Transit agencies can leverage technology to create a more personalized and seamless experience for riders, moving beyond the traditional one-size-fits-all approach. At its core, personalization relies on collecting and analyzing data to understand individual rider behavior, preferences, and travel patterns, and then using that insight to deliver timely, relevant information or services. Technology makes this possible through mobile apps, smart cards, real-time tracking, AI, and predictive analytics. For example, consider a transit app that integrates a rider's travel history, preferred routes, and even departure and arrival times. By analyzing this data, the app can provide notifications tailored to each individual. If a rider's usual train is delayed, the system can alert them immediately and suggest the fastest alternative route. Similarly, if a rider typically travels at certain times, the app can provide proactive information on service changes, peak-hour congestion, or even offer personalized route recommendations that minimize waiting time. This level of personalization not only improves convenience but also builds trust, because riders feel that the system understands their specific needs. Another way technology can personalize the experience is through loyalty or incentive programs. Transit agencies could use data to identify frequent riders or commuters who rely on certain routes and reward them with discounts, early notifications about service changes, or access to premium features like real-time seat availability. AI can also help predict rider demand in advance and dynamically adjust services, such as adding buses or trains on routes with high predicted usage, ensuring riders experience fewer delays and overcrowding.
I run a painting company in Lombard, and honestly, this question made me think about how we personalize service for property managers and realtors--transit agencies could steal our playbook. We keep a simple spreadsheet of every client's preferences: the apartment owner who only wants light grays and off-whites because they rent faster, the realtor who needs 48-hour turnarounds between tenants, the restaurant that can only shut down Mondays. Transit agencies should do this--let regular commuters save their "profile" (wheelchair user, travels with stroller, needs AC in summer) and the app automatically filters which buses/trains actually work for them before showing arrival times. The game-changer for us was texting photo updates to clients who can't visit job sites. We send before/after shots of cabinet resurfacing at 2pm and 5pm--exactly when they're on lunch and heading home. Transit could text riders a photo of actual current crowding on their usual train 10 minutes before it arrives, not just a yellow/red dot. People trust their eyes, not abstract "capacity: 76%" numbers. One realtor told us she closes rentals 6 days faster when we paint in those specific light colors that make small apartments look bigger--that's real money saved on empty units. Transit agencies have the same opportunity: the rider who always connects between two lines could get automatic alerts only about *both* of those lines, not every route in the city. Personalization is just remembering what people actually told you they need.
Transit agencies can create individualized experiences for their riders through the implementation of dynamic data delivery systems that utilize rider-specific information instead of traditional fixed schedules. The most effective method involves presenting riders with their most crucial information through the combination of current data and their unique travel habits. The agency should employ automated systems to alert commuters about route delays, enabling them to select alternative travel options based on real-time capacity and arrival times rather than relying on scheduled timetables. This system significantly decreases mental effort and user frustration. Personalization becomes truly effective when technology systems learn to predict what customers will do next. Riders don't want more information; they require access to accurate information whenever it becomes necessary. Albert Richer, Founder WhatAreTheBest.com