# Open — full content Source: https://www.getopen.com This file is a single-file dump of Open's public content for LLMs and AI agents. For a structured map, see /llms.txt. --- ## About Open Open is the AI workforce for restaurants. For the first time, restaurant software can do the work — not just track and organize it. Open replaces a stack of marketing, loyalty, online ordering, and customer engagement tools with a single AI-native platform. Open is built for independent restaurants, multi-location groups, and enterprise restaurant brands. Operators use Open to capture more customers, convert more orders, and retain more regulars — without hiring a marketing team or stitching together five vendors. ## Products ### Marketing Websites AI-built and AI-maintained restaurant websites. The replication agent builds a new site from a restaurant's existing one in minutes; the editor agent makes ongoing changes for the operator in plain English. ### Online Ordering Direct online ordering that the restaurant owns. Lower fees than third-party marketplaces, full customer data, and a checkout experience tuned for conversion. ### Loyalty A loyalty program built into the ordering experience. No separate app, no separate signup — points, rewards, and tiers all live alongside checkout. ### Gift Cards Branded digital gift cards that can be sold and redeemed across web, mobile, and in-store. ### Catering Catering ordering and lead management. Quote, qualify, and convert catering inquiries with a workflow built for restaurants. ### SMS Two-way SMS marketing and customer messaging, with A2P 10DLC compliance handled. ### Email Email marketing and lifecycle campaigns. Segments and templates are generated and tuned by the Marketing Agent. ### Mobile Apps Branded iOS and Android apps for restaurants, with ordering, loyalty, and push notifications built in. ## AI agents ### Ecommerce Agent Runs the online ordering storefront. Handles merchandising, upsells, abandoned-cart recovery, and conversion optimization without manual configuration. ### SEO Agent Continuously audits and improves the restaurant's organic search presence — metadata, structured data, page speed, and local listings. ### Advertising Agent Plans, launches, and optimizes paid ads across Google, Meta, and other channels. Allocates budget to the campaigns that drive real orders. ### Marketing Agent Sends the right message to the right customer at the right time across SMS and email. Builds segments, drafts copy, and runs lifecycle campaigns autonomously. ### Support Agent Handles guest questions and order issues. Knows the restaurant's menu, hours, and policies, and escalates only what needs a human. ### Catering Agent Captures and qualifies catering leads end-to-end. Replies to inquiries, gathers requirements, and hands off ready-to-close opportunities. ## Customer stories ### Eat Fantastic **Eat Fantastic doubles monthly orders in five months on Open** “The results speak for themselves. We doubled our orders in five months, completely revamped our tech stack, and gave customers an incredible online experience. The integration with our POS is smooth as can be. Open feels like having a whole growth and engineering team working in the background.” Read more: https://www.getopen.com/customers/eatfantastic ### LOQUI **LOQUI grows from 3 stores to 6 and lifts same-store online sales 50%+** “Open is the best.” Read more: https://www.getopen.com/customers/loqui ### Pop's Bagels **Pop's Bagels 4x's direct online sales** “Our website is sharp, our app is approachable, and the AI marketing tool is futuristic in all the right ways. No wonder we’re up 400% since our launch.” Read more: https://www.getopen.com/customers/popsbagels ### Hot Tongue Pizza **Hot Tongue grows online sales 83%** “The marketing tools? Unreal. You can feed an AI agent a promo and it builds a fully dialed-in campaign, SMS, and scheduled push notifications, ready to go.” Read more: https://www.getopen.com/customers/hottonguepizza ### dan modern chinese **dan modern chinese doubles online sales and grows its mobile app to $1M/year** “After switching to Open, our online sales and customer retention skyrocketed and our customers love the new mobile app!” Read more: https://www.getopen.com/customers/danmodernchinese ### Schlok's Bagels & Lox **Schlok's doubles online sales in four months** “Working with Open has been one of the best decisions we’ve ever made. Open’s tech is great and their team is awesome. We can’t recommend them enough.” Read more: https://www.getopen.com/customers/schloksbagelsandlox ### Poached Neighborhood Kitchen **Poached Neighborhood Kitchen grows digital sales 57% and 5×'s app adoption** “I wanted a partner to help give customers a better ordering experience, grow sales, and reduce my vendor costs. Open delivered across the board!” Read more: https://www.getopen.com/customers/poachedneighborhoodkitchen ### LaSorted's **LaSorted's grows online sales 500% after switching to Open** “Switching to Open wasn’t just about getting a better app—it was about unlocking the full potential of LaSorted’s. And that’s exactly what happened.” Read more: https://www.getopen.com/customers/lasorteds ### Flour Pizzeria **Flour Pizzeria moves from disconnected systems to a seamless AI-powered experience with Open** “The seamless POS integration is incredible and truly unique to Open. We’re happy we made the switch and even happier to see sales growing.” Read more: https://www.getopen.com/customers/flourpizzeria ### Square Pie Guys **Square Pie Guys grows app sales from $0 to $2m/year** “Open allows us to compete with third-parties and own our data. It's the best decision I've made this year without a doubt.” Read more: https://www.getopen.com/customers/squarepieguys ## Blog ### The Payment Processing Lie: Your 'Rate' Isn't Your Real Cost Published: Dec 9 · Author: Open Category: Payments > Most restaurants think payment processing is just a rate. Approval rates, tokenization, fraud systems, and AI-driven optimization matter far more. Most restaurants compare payment processors by one thing: the rate. 2.9% + $0.30 vs. 2.5% + $0.10 vs. whatever someone else promises. But a lower rate does not mean lower cost — and a higher rate does not mean higher cost. What actually determines your true payment cost is something almost no one talks about: your approval rate. Approval rate is the percentage of customer card payments that succeed on the first attempt. Even a tiny change (1–3%) can mean tens of thousands of dollars gained or lost per year. Behind the scenes, modern processors use a completely different infrastructure to maximize approvals and protect revenue. Older processors don’t — and restaurants pay the price in silent, invisible revenue loss. Below are the four technologies that determine whether your payments actually go through, your guests reorder, and your revenue grows. ## 1. Auto-Retries: Recovering Revenue You Didn’t Know You Were Losing Most payment declines aren’t real problems with the customer’s card. They’re transient issues like: - Bank network timeouts - Temporary fraud checks - Momentary insufficient funds - Processor routing errors Legacy processors fail once and stop — meaning the order is dead. Modern payment processors run intelligent auto-retries , which automatically reattempt payments using bank-specific timing logic. These retries can recover 3–8% of otherwise lost transactions . ### Why this matters for restaurants When a Friday night guest’s order fails due to a temporary glitch, you don’t just lose the order. You lose: - Revenue - A potential lifetime customer - Conversion in your direct ordering funnel - Trust in your brand Auto-retries silently fix all of this in the background. ## 2. Card Account Updating: Keeping Stored Cards Fresh Automatically Every year, 30–35% of stored cards expire or change due to: - Expiration dates rolling over - Lost or stolen cards - Banks issuing new cards after fraud alerts - Card upgrades or replacements Without Card Account Updating (CAU) , these cards begin failing — and your guests don’t proactively update them. This creates payment failures for loyalty reloads, frequent guests, corporate accounts, catering clients, and anyone who relies on stored cards. ### What Card Account Updating does - Updates expiration dates automatically - Retrieves new card numbers securely from Visa and Mastercard - Prevents failed payments before they happen - Preserves frictionless checkout for loyal guests This dramatically improves repeat order conversion and reduces support load. ## 3. Network Tokenization: The Future of Higher Approval Rates A network token is a secure, continuously updated card credential issued directly by Visa or Mastercard. It replaces a raw 16-digit card number (PAN) and has major advantages: - Automatically updates when the customer gets a new card - Is cryptographically tied to your domain or app - Carries additional trust and fraud-reduction signals - Banks approve tokenized transactions at a materially higher rate Across major merchants, network tokens have been shown to improve approval rates by 1.5–3.2% , and sometimes up to 6% for mobile wallets. ### Why this matters A raw card number gets worse over time. A network token gets better over time. It’s the single most powerful modern payments upgrade — and many processors still don’t support it. ## 4. Approval Rates: The Real Cost of Payment Processing A processor offering 2.5% + $0.10 isn't cheaper if they have a worse approval rate. Example: - Processor A: 2.5% + $0.10 with 92% approvals - Processor B: 2.9% + $0.30 with 99% approvals Processor B will generate dramatically more revenue — often tens of thousands of dollars per year — despite the “higher” rate. For a restaurant doing $2M/year online with a $35 average basket size, a 5–7% approval lift can mean $100,000–$140,000+ in recovered revenue . If you compare that to the $19.5K saved in fees, you're still netting out $80,000–$120,000 better despite the higher processing cost. ### What approval rates impact - Revenue - Cart abandonment - Guest satisfaction - Tip volume - Loyalty participation - Paid marketing efficiency - Repeat ordering behavior Approval rate is the single biggest lever in your payments stack. ## 5. Fraud Intelligence & Radar-Style Systems: Improving Trust and Approval Rates Fraud tools aren’t just for stopping bad transactions — they’re critical for getting good transactions approved. Modern fraud systems analyze hundreds of signals per payment, including: - Device fingerprint - Past order behavior - IP address reputation - Velocity checks (how often the card was used recently) - Whether the card has been trusted before - Geolocation mismatch patterns These systems aren't simply protecting against fraud — they are sending trust signals to issuing banks. Issuing banks are far more likely to approve a payment when: - The processor has an established fraud model - Behavioral scoring suggests the user is legitimate - Risk signals are low or well-managed - 3D Secure is intelligently triggered only when needed ### Why this matters Strong fraud models improve approval rates by 1–4% , especially for: - First-time guests - High-volume repeat customers - Mobile ordering - Loyalty + stored payment flows Without intelligent fraud handling, processors either: - Decline too many legitimate payments, or - Approve too many fraud attempts and get punished by the networks (which lowers future approvals) Modern fraud modeling is one of the biggest hidden differentiators between payment processors. ## The Bottom Line Payment processing is not a commodity. The infrastructure beneath the rate matters far more than the rate itself. Modern processors provide: - Auto-retries - Network tokenization - Card Account Updating - Smarter routing and fraud detection - Higher approval rates - More reliable checkout experiences - Increased lifetime value - Fewer payment failures - Less customer support overhead The real question isn’t “Who has the lowest rate?” It’s: “Who helps me keep the most revenue?” Restaurants that optimize their payment infrastructure — not just their fees — consistently grow faster, retain more customers, and generate more predictable revenue. Source: https://www.getopen.com/blog/real-cost-of-restaurant-payment-processing --- ### A2P 10DLC vs. Toll-Free Numbers: Why Local A2P Numbers Are Becoming the Standard in Restaurant SMS Marketing Published: Dec 3 · Author: Open Category: SMS > A practical breakdown of deliverability, trust, and compliance differences between A2P 10DLC and toll-free messaging. SMS has become one of the highest-ROI channels for restaurants. Whether it’s promoting weekly specials, re-engaging lapsed customers, announcing new menu items, or sending out loyalty rewards, text messaging consistently outperforms email and push notifications. But there’s a hidden variable that dramatically impacts SMS performance: the type of phone number your messages come from. Until recently, many businesses relied on toll-free numbers for SMS. In 2025, however, A2P 10DLC (Application-to-Person 10-Digit Long Code) numbers have become the superior and carrier-recommended option for marketing, growth, and deliverability—especially for restaurants. This guide breaks down why , without bias toward any specific provider. - Deliverability: A2P 10DLC Has Become the "Preferred Lane" for Marketing Traffic Mobile carriers now aggressively filter toll-free numbers for promotional messaging. Restaurants often see: Increased filtering - Slower throughput - Delays in time-sensitive campaigns - Unpredictable approval processes for toll-free verification A2P 10DLC was created specifically to address these issues. Because it requires brand and campaign registration, carriers pre-approve the sender and purpose of each campaign. The result: - Higher deliverability for marketing content - More consistent throughput - Far fewer false spam blocks - More predictable performance as message volume scales For restaurants where a 15-minute delay can tank a promotion, this reliability matters. Imagine sending a limited-time lunch special at 11:00 a.m. and the customer not receiving the message until 7:00 p.m. SMS is only effective when it arrives exactly when you intend it to. - Local Trust: Consumers Respond Better to Local Numbers Than Toll-Free In study after study, consumers rank communications from local phone numbers as more trustworthy than messages from: Toll-free numbers - Short codes - Shared numbers A2P 10DLC numbers look and feel like a normal local business line, which creates a psychological advantage: - People are more likely to open texts from local area codes - Customers feel the business is nearby and relevant - Reply rates and engagement are meaningfully higher - The sender becomes part of a customer’s contact list over time This matters for small businesses and multi-location restaurants alike. A local sender identity builds familiarity that toll-free numbers simply can’t replicate. - Fewer Interruptions and Compliance Surprises Toll-free traffic is subject to periodic review waves by carriers. Restaurants often experience: Temporary suspension while carriers “re-review” the use case - Multi-day response times - Sudden blocks after promotions - Manual escalations required to restore service A2P 10DLC avoids most of this because: - Brand registration verifies the identity of the sender - Campaign registration outlines the exact messaging purpose - Carriers pre-approve the category (e.g., marketing, loyalty, order updates) This framework dramatically reduces the risk of sudden interruptions or service downtime. - Better Identity + Better Data Toll-free numbers tend to blend together — most customers don’t recognize or save them. A2P 10DLC gives restaurants: A consistent, dedicated identity for all messaging - Clearer conversational threads - Higher attribution accuracy - More reliable unsubscribe and opt-in tracking - Clean separation between marketing, ordering, and support flows Across a full guest lifecycle—lead capture, re-engagement, loyalty, and support—having a stable sender identity improves the data quality behind every campaign. - A2P Is Designed for AI-Driven Messaging and Two-Way Conversations Restaurants are increasingly using SMS for: Automated follow-ups - Intelligent segmentation - Two-way replies - Post-visit questions - Loyalty nudges - Real-time recovery messages Toll-free numbers were built for call centers, not conversational messaging. AI-driven SMS behaves differently: - It sends more messages per guest (micro-segments) - It depends on real-time back-and-forth - It triggers based on behavior and timing - It needs fast throughput and near-100% deliverability A2P 10DLC is optimized for exactly this type of messaging. Toll-free is not. - Cost: A2P Often Provides Better ROI at Lower or Equal Cost Toll-free numbers seem inexpensive on paper, but the hidden costs show up in: Lower deliverability - Slower campaign velocity - Reduced conversion rates - Time spent resolving carrier issues A2P 10DLC registration fees are small and predictable, and the performance benefits tend to outweigh any cost difference. Restaurants ultimately pay less for every effective message sent. ## Should Restaurants Still Use Toll-Free Numbers for Anything? Toll-free numbers still have useful roles: - Customer support hotlines for national chains - Corporate offices - National multi-brand communication - Non-promotional messaging in low-volume contexts But for marketing , loyalty activation , AI-driven messaging , and revenue-generating campaigns , A2P 10DLC is now the industry standard. ## Summary: Why A2P 10DLC Is Becoming the Norm Category A2P 10DLC Toll-Free Deliverability High, consistent Moderate, variable Throughput Fast, optimized for marketing Often slower Trust Local and familiar Corporate, impersonal Spam Filtering Lower risk Higher filtering for promos AI + Conversational Messaging Strong fit Limited Stability Few interruptions Subject to periodic re-reviews Cost Efficiency Higher ROI per message Lower ROI due to filtering ## Final Thoughts A2P 10DLC isn’t “new”—but it has quietly become the best-practice standard for restaurants that rely on SMS to drive measurable revenue. It provides: - A verified, trusted identity - High deliverability - Predictable compliance - Better engagement - Better performance for AI-driven personalization Whether you’re sending SMS through a POS, a marketing automation platform, or a CRM, choosing A2P 10DLC over toll-free is one of the simplest ways to upgrade your communication infrastructure. Source: https://www.getopen.com/blog/a2p-10dlc-for-restaurant-sms --- ### Restaurant SEO 101: How to Rank #1 for “Best [Food] Near Me” Published: Dec 4 · Author: Open Category: SEO > Modern SEO, AI-driven optimization, local content, and structured data — the 2025 guide to ranking #1 on Google for local restaurant searches. ## Introduction: Most Restaurants Don’t Realize How Easy It Is to Win Local SEO - “best tacos near me” - “best pizza in [city]” - “sandwiches near me” - “coffee shop near me” Google decides which restaurant makes money . Most restaurants think SEO is complicated. It’s not. It’s simple, structured, predictable , and incredibly lucrative when done correctly — especially with AI doing most of the work. This guide breaks down exactly how restaurants can rank #1 for local food searches in 2025. ## Why Local SEO Matters for Restaurants Local SEO is now more valuable than: - social media - paid ads - influencer marketing - traditional PR Because when someone searches “best [food] near me,” they already have intent . They’re ready to order right now . Winning this search unlocks: - more online orders - more walk-ins - more catering inquiries - more discovery - higher average check Local SEO is the difference between being an option… and being the answer . - You Must Own Your Google Business Profile (GBP) Your Google Business Profile is your #1 SEO asset — not your website, not your social media, not Yelp. The top-ranking restaurants for “near me” almost always have: Fully completed GBP fields: Categories - Description - Hours - Menu - Attributes (e.g., “Offers pickup,” “Outdoor seating”) - Photos - Website link - Ordering link - Reservations link (if relevant) ### Fresh content: - New photos weekly - Menu updates - Updates/posts - Accurate holiday hours ### Real reviews coming in consistently ### Accurate NAP: Name, Address, Phone — identical everywhere online. GBP is 50–60% of local ranking. If you don’t optimize it, nothing else matters. - Use “Search Intent First” Menu Language Restaurants often name dishes creatively, which is great for branding but terrible for SEO. Google ranks based on what people search for , not what your chef calls it. Examples: ❌ “The Dragonfire” ✔️ “Spicy Chicken Sandwich (Dragonfire)” ❌ “The Classic” ✔️ “Cheeseburger (The Classic)” ❌ “The Downtown” ✔️ “Turkey Club (The Downtown)” If Google doesn’t understand what you serve, it will not rank you. Use customer-friendly, search-friendly dish names — and your SEO immediately improves. - Optimize Your Website Like Google Actually Uses It People misunderstand restaurant SEO. Google does not scan your homepage and magically rank you. It ranks you based on: Location pages Every restaurant must have: a dedicated location page per store - address, map, hours - nearby city references - neighborhood names - service areas - pickup/delivery availability - Menu structured data Mark up your menu with schema so Google can read it like a database. - Fast load times Restaurants lose 30–40% of traffic to slow websites. - Clear ordering buttons Google loves websites that lead to strong customer satisfaction signals. - AI-generated local content (this is the big unlock) Instead of a generic homepage, the site should include sections like: “Best sandwiches in Costa Mesa” - “Healthy lunch options in Newport Beach” - “Top-rated breakfast in Studio City” This is where your CMS + AI approach crushes every competing platform . - Build Hyper-Local Pages That Target Nearby Searches For every location, you should generate: Neighborhood pages e.g. “Best Tacos Near Playa Vista” City pages e.g. “Top Sandwiches in Orange County” Food-specific pages e.g. “Healthy Bowls Near Hermosa Beach” Long-tail pages e.g. “Best gluten-free pizza in Pasadena” Each page targets a different keyword group and leads people directly to an Order Now CTA. This strategy is how you create: hundreds of ranking opportunities - massive internal linking authority - hyper-relevant local content - Collect Reviews Consistently (Steady, Not Spiky) Google monitors: review quantity - review frequency - review velocity - review recency - review diversity - photo reviews A restaurant with 50 reviews per year, every year, will outrank one with 500 reviews dumped in a single month. Your strategy: - ask consistently - reply quickly - respond with valuable info - encourage photo uploads - push text-message review requests Reviews are a ranking signal , not just social proof. - Local Backlinks (The Most Underrated SEO Signal) Google uses local backlinks as a “credibility test.” Your restaurant should have links from: local magazines - food blogs - city directories - community sites - chamber of commerce - sponsor mentions - local event pages Even 10–15 solid local links can push you to the top. AI tools can now automate outreach and track new mentions. - Your Online Ordering Flow Impacts SEO Most people don’t realize this: Google rewards restaurants whose websites lead to strong customer satisfaction. That means: short checkout flow - clear menu structure - fast ordering - mobile-optimized - minimal friction When your ordering experience delights customers… Google boosts your visibility. This is another reason Open beats Owner.com and Popmenu — your ordering UX is superior. - AI Gives Restaurants an Unfair SEO Advantage Most SEO is repetitive: generating local pages - writing descriptions - optimizing keywords - updating metadata - monitoring rankings - generating schema - tracking changes - updating hour changes - swapping location-specific content AI automates all of this at scale. Instead of editing dozens of pages manually… Your AI engine can generate, optimize, and publish hundreds of pages that all rank well. ## Conclusion: Ranking #1 for “Near Me” Is Not Luck — It’s Structure The restaurants dominating “best [food] near me” aren’t lucky, trendy, or algorithmically blessed. They follow a simple formula: - great Google Business Profile - fast, clean website - AI-driven local pages - consistent reviews - structured data - strong ordering experience - local backlinks - predictable content cadence If you get these right, ranking #1 becomes inevitable. Source: https://www.getopen.com/blog/restaurant-seo-best-food-near-me --- ### How Restaurant AI Decides What to Send — Inside the Decision Engine Published: Dec 2 · Author: Open Category: AI > A deep dive into how AI determines what to message restaurant customers, when to message them, and why — using real-time behavior and adaptive personalization. ## Introduction: The Future of Restaurant Marketing Isn’t Campaigns — It’s Decisions Traditional restaurant marketing works like this: - Create a promo - Choose a segment - Choose a send time - Blast everyone - Hope something works This is human logic applied to a channel that demands machine precision . In 2025, restaurants don’t need campaign calendars. They need decision engines — AI systems that observe, think, predict, and take action autonomously. This post explains how a restaurant AI actually decides what to send, who to send it to, and when to send it — without a single human creating a campaign. ## The AI Decision Loop: Observe → Predict → Act → Learn Modern restaurant AI doesn’t run a schedule. It runs an infinite-loop decision cycle , triggered thousands of times per day. Here’s the architecture. - OBSERVE — AI Takes in Continuous Real-Time Signals The system constantly monitors: Customer Behavior Signals browsing patterns - shopping cart behavior - order cadence - daypart preferences - frequency trends - item affinities - discount sensitivity - device type - location signals (if enabled) ### Business Signals - current order volume - kitchen load - backlog warnings - prep-time shifts - menu changes - stock availability ### Environmental Signals - weather - temperature - local events - holidays AI doesn’t guess. It listens — to every signal flowing through the business. - PREDICT — AI Computes Probability of Outcomes Every time the AI sees new data, it instantly re-evaluates probabilities. It predicts: How likely a customer is to order right now - How likely a customer is to churn - What incentive increases conversion - What message style resonates most - Whether sending a message will be profitable - Whether now is the wrong moment to interrupt Traditional marketing segments customers. AI predicts propensities — likelihoods. This is the difference between: “Send to all customers who haven’t ordered in 14 days.” vs “This person has a 72% probability of ordering in the next 3 hours if nudged.” This is the leap forward. - ACT — AI Executes the Optimal Action at the Optimal Moment Once the AI has its probabilities, it decides: Should I send a message? - What message should I send? - Should it include an incentive? - What type of incentive? - Should it wait instead? - Should it combine a message with an upsell? - Should it only notify certain customers? This is where the “agentic” layer lives. Instead of waiting for operator instructions, the AI takes action autonomously — like a digital marketing employee with perfect memory and zero fatigue. AI doesn’t send campaigns. AI creates outcomes. - LEARN — AI Improves Every Message, Every Week Every single interaction becomes training data: Did the customer open? - Did they click? - Did they order? - Did they ignore? - Did they unsubscribe? - What message did they react to? - What timing worked best? - What offer lifted conversion the most? The AI adjusts its entire strategy accordingly. Humans A/B test twice a month. AI runs thousands of micro-tests per week. This is why results compound. ## Inside the AI Brain: Decision Variables the System Weighs ### Here’s what Open’s AI actually evaluates when making a choice: - Are we close to the customer’s typical ordering window? - Is this a hunger-trigger time for them? - Is today a day they normally order? - What did they browse recently? - Are they trending upward or downward in activity? - Do they buy new items or repeat orders? - Are they price-sensitive? - Will weather influence cravings? - Is today a payday? - Are there local events? - Can the kitchen handle a surge right now? - Is there a lull that needs demand? - Are we out of popular items? Only when everything aligns does the AI decide to message. This eliminates unnecessary messages — which means lower unsubscribes, more profit, more orders. ## Why AI-Determined Messaging Outperforms Human Campaigns - Humans operate on calendars. AI operates on probability curves. AI isn’t deciding “what to send this week.” It’s deciding “what this customer needs right now.” - Humans segment. AI personalizes. Two customers in the same “segment” might behave completely differently — AI accounts for that. - Humans rely on gut. AI relies on 10,000 data points per day. Emotion, guessing, inconsistencies vanish. - Humans schedule. AI sequences. AI knows what message to send next based on each customer’s personal journey. - Humans get tired. AI improves every week. Performance compounds. ## Example: A Real Decision Tree (Simplified) A restaurant operator sees a “customer list.” The AI sees this: Customer #42814 - 82% probability of ordering today - 66% chance they’ll order during late lunch - 12% discount sensitivity - 3-item affinity: Fried Chicken, Chicken Bowl, Mac - responds strongly to weather messages - always orders on mobile - last week’s message was ignored — tone should change - kitchen load is low → good moment to nudge - predicted LTV: high - best time to send: 1:12–1:25pm → Recommended action: send personalized nudge, no discount This is not “email marketing.” This is decision intelligence . ## Conclusion: Restaurants Don’t Need More Campaigns — They Need Smarter Decisions The restaurants that thrive in 2025 won’t be the ones sending more promotions. They’ll be the ones using AI to make: - smarter timing - smarter incentives - smarter personalization - smarter engagement - smarter retention - smarter demand shaping The decision engine is the new marketing team. Source: https://www.getopen.com/blog/restaurant-ai-decision-engine --- ### How Restaurants Are Using AI to Increase Sales in 2025 Published: Nov 27 · Author: Open Category: AI > How restaurants are using AI to increase online orders, reduce operational costs, improve customer retention, and drive growth in 2025. ## Introduction: AI Is Becoming the New Growth Engine for Restaurants 2025 is the year AI stops being a “future idea” and becomes a day-to-day revenue driver for restaurants. AI is now helping restaurants: - Increase online orders - Reduce labor burden - Improve order accuracy - Boost retention - Personalize marketing - Automate low-value tasks - Grow revenue without growing headcount And the restaurants adopting AI early are outperforming those that don’t — by a wide margin. This guide breaks down exactly how modern restaurants are using AI today to drive growth, with real examples and practical applications you can start using immediately. - AI Increases Online Orders Through Personalization The biggest revenue lift from AI today comes from predictive, personalized engagement . Modern AI looks at: ordering patterns - browsing behavior - daypart preferences - weather - frequency trends - basket size - what customers almost ordered Then it sends perfectly-timed, personalized nudges that increase the chance of an order. Example: A customer usually orders on Thursdays at 6pm. The AI identifies the pattern and sends them a message at 5:45pm: > “Your usual? One tap away.” This small moment consistently drives 8–15% incremental orders per week. No human could time, personalize, and optimize every message like this — but AI can. - AI Turns One-Time Guests Into Repeat Regulars Restaurants normally lose 60–70% of first-time customers. AI flips this dynamic by: detecting the exact moment a customer is becoming “at-risk” - sending dynamic, personalized incentives - adjusting messaging style to match past behavior - creating frictionless pathways back to re-order Instead of “blast campaigns,” AI does pattern-level retention work. Example: If a guest normally orders weekly but skips one week, the AI nudges them early — before they’re truly lost. > “Quick dinner tonight? We saved your favorite.” This gentle, behavior-matched intervention increases retention by 15–30% . - AI Optimizes Incentives to Increase Profitability Most restaurants discount too much — or to the wrong people. AI identifies: which guests never need a discount - who converts with free items instead of money off - who responds to scarcity vs. value - the exact discount needed to convert (without overpaying) - high-value guests you shouldn’t discount The result: Less discounting → more orders → higher margins. AI eliminates the guesswork. - AI Reduces Labor Load by Automating Routine Tasks Restaurants are understaffed, overworked, and constrained by rising labor costs. AI helps by automating the low-value tasks that normally eat time. AI now handles: answering common customer questions - updating website information - generating promotional messaging - pulling performance reports - identifying unhappy customers - creating social content - analyzing sales trends - schedule optimization - inventory insights You don’t need a marketing coordinator, social media manager, and data analyst — AI executes these functions in seconds. This lets teams focus on what matters: - hospitality - food quality - speed - execution - AI Improves Order Accuracy & Kitchen Efficiency Operational AI is becoming a competitive advantage. Restaurants are using AI to: predict rushes - adjust prep timing - identify bottlenecks - reduce wait times - optimize load balancing - flag inaccurate or suspicious orders - guide new staff during peak hours Imagine your kitchen knowing: - “You’re about to get hit with 40 online orders.” - or “Prep time is spiking — redistribute items.” AI gives restaurants “operational foresight.” The result: fewer mistakes, happier customers, and higher throughput. - AI Helps Restaurants Expand Without Adding Overhead A single-location restaurant using AI can suddenly operate like a sophisticated multi-unit brand. AI makes it possible to scale: marketing - ordering - loyalty - customer comms - data analysis - reputation management …without increasing headcount or hiring specialists. AI is the modern growth multiplier. - AI Improves Menu Strategy & Pricing AI sees patterns no human can track manually. It can identify: which items drive repeat visits - which items drive highest-margin orders - which menu items are “decoys” - which items should be highlighted in upsells - who responds to bundles vs single items - what price increases won’t hurt conversion Restaurants using AI for menu intelligence typically see: - 4–8% margin lift - 10–25% AOV increases through smarter upsells - higher repeat frequency from item personalization - AI Streamlines Customer Support and Saves Time AI agents now handle: refund requests - order status questions - menu inquiries - allergen questions - hours & location details - loyalty points questions - catering requests - high-volume holiday support Instead of your staff spending hours answering the same questions: AI handles 80–90% automatically — instantly and accurately. This reduces labor costs and improves customer satisfaction at the same time. - AI Gives Owners a True “Command Center” for Their Business Most restaurant owners rely on gut instinct and spreadsheet exports. AI gives owners: real-time insights - sales forecasts - labor forecasts - cost trends - channel performance - customer segmentation - retention curves - growth opportunities Owners no longer guess or check 10 dashboards. AI summarizes everything and recommends actions. This is the future of restaurant leadership. - AI Powers Fully Autonomous Marketing The most powerful use case of all: AI becomes your always-on marketing team. It: learns your customers - messages them at the right time - personalizes incentives - adapts tone - drives retention - experiments with offers - automates local SEO - localizes menu content - creates social content - amplifies ordering This is not “AI-assisted marketing.” This is autonomous revenue generation . This is Open’s thesis — and why it will change the industry. ## Conclusion: AI Is No Longer Optional for Restaurants AI is not replacing hospitality. It’s removing everything that gets in the way of hospitality. Restaurants using AI in 2025 are: - more profitable - more efficient - more repeat-driven - more scalable - more predictable - more stable And they grow faster. Those who adopt early will win. Those who wait will fall behind. Source: https://www.getopen.com/blog/ai-for-restaurants-2025 --- ### The Complete Guide to SMS Marketing for Restaurants (2025 Edition) Published: Nov 25 · Author: Open Category: SMS > Use SMS marketing to boost online orders, increase repeat visits, and grow customer loyalty — the definitive 2025 guide for restaurant SMS. ## Introduction: SMS Is the Most Profitable Channel Most Restaurants Aren’t Using If you’re a restaurant owner or marketer, you’re sitting on the most powerful revenue channel in your business — and you might not even be using it. SMS marketing consistently outperforms: - Email - Social media - Push notifications - Ads With 98% open rates , 15–35% click-through rates , and 8–15% order conversion , text message marketing isn’t just “another channel.” It’s the highest-ROI growth engine in restaurants today . This guide breaks down exactly how restaurants can use SMS to increase orders, improve retention, and build a direct relationship with every guest. ## Why SMS Works So Well for Restaurants Most marketing channels are noisy. SMS isn’t. Here’s why it dominates: - Instant visibility (98% open rate) People check text messages within 3 minutes . Emails? Hours or days — if they ever get opened. - Direct ownership of your customers DoorDash and Uber Eats own your repeat customers through their apps. SMS gives you a direct line to them — no middlemen. - High conversion into orders Restaurant SMS campaigns regularly drive: 15–35% click through rates - 8–15% conversion rate - $6–$12 in sales for every $1 spent It’s why national brands like Chipotle and Starbucks invest millions into SMS programs. - Perfect channel for “moment-of-need” cravings Text messages hit people when they’re hungry: - Lunchtime - Dinner - Weekends - Paydays - Holidays Restaurants win by reaching customers at the exact moment they’re likely to order . ## How Modern Restaurants Should Use SMS: Dynamic, Personalized, AI-Driven Most restaurant platforms still treat SMS like it’s 2014: - weekly blasts - time-based winbacks - generic promotions - “Send to all customers” But this approach is dead. In 2025, the highest-performing restaurants don’t send campaigns . They use AI to create adaptive, personalized messaging that adjusts in real-time based on customer behavior. ## AI Changes the Entire Paradigm of Restaurant SMS With AI, your SMS system doesn’t wait for you to tell it what to do. It actively thinks , chooses , personalizes , and executes . Here’s what that looks like. - Predictive Messaging (Who Needs a Nudge Today?) Instead of blasting everyone, the AI analyzes: order frequency - time-of-day patterns - preferred days - eating habits - historical conversions Then it messages only the people most likely to order right now . No guesswork. Just probability-based outreach. - Behavior-Adaptive Personalization Every customer is different — and AI adapts messages in real-time based on: last order - favorite menu items - typical spend - preferred ordering channel - last website visit - abandoned carts - time since last activity Two guests might get two completely different messages at the same time — because the AI tailors each message to maximize conversion. Personalization becomes automatic , not manual. - Incentive Optimization Instead of using one blanket offer, AI tests and learns: Does this guest respond better to percentage-off or dollars-off? - Do they convert without a discount? - Does a free item outperform a coupon? - How deep does the discount need to be? - At what times do they respond best? Open’s AI constantly adjusts to deliver the lowest-cost incentive with the highest conversion . - Moment-Based Messaging Traditional SMS waits for a scheduled time. AI-driven SMS reacts to moments. Examples: the weather changes - your kitchen is slow and needs a boost - a customer walks near your location - a customer buys from a competitor - a holiday or game day surge - lunchtime or dinner-time spikes - a customer’s birthday or anniversary Instead of static messaging, restaurants get real-time demand activation . - Intelligent Reactivation (Goodbye, 14/30/60 Day Windows) Instead of waiting arbitrary amounts of time (“send a winback at 14, 30, 45 days”), AI identifies: the exact moment a customer becomes “at-risk” - their likelihood to return - the best incentive to bring them back No more rigid time windows. Reactivation becomes precise and fully automated . ## What Kinds of Messages AI Might Send (Without You Lifting a Finger) Instead of pre-planned “campaign templates,” AI should generates messages intelligently based on what’s actually happening inside your business and in the life of each customer. Here are examples of real AI-driven moments . - When your guest is most likely to order The AI predicts ordering likelihood based on: time-of-day - day-of-week - historical patterns - weather - paydays - cravings - neighborhood trends Example: > “Hungry for your usual? We’ve got it ready. Tap to order.” - When someone browses your menu but doesn’t order The AI waits the optimal amount of time (different per guest), then follows up. Example: “Still in the mood for that Chicken Bowl? We saved you a spot.” - When the kitchen has extra capacity If your kitchen is in a lull between rushes, the AI gently boosts demand. Example: “Short wait times right now — perfect moment for takeout.” - When a customer is on the brink of becoming “at-risk” Instead of time-based winbacks like 14, 30, 45 days, the AI identifies subtle behavioral shifts. Example: “It’s been a minute — get $5 off your usual tonight?” - When a regular customer’s ordering pattern changes AI detects micro-trends: slower ordering frequency, smaller basket size, changing dayparts. Example: “Trying something new? Here’s something you might love.” - When someone responds well to scarcity or new items The AI identifies customers who love new drops and uses that to drive excitement. Example: “New item just dropped — early access for you.” - When someone reacts strongly to non-discount messaging The AI learns who doesn’t need promos and stops sending them. Example: “Your favorites are hot right now. Tap to order.” Messaging becomes continuous, adaptive, and personal , not a marketing calendar. Your restaurant doesn't send “campaigns.” Your AI grows revenue autonomously. ## How to Grow Your SMS List (Fast) SMS is only powerful if your list grows quickly. Here are the top-performing tactics: - Online Ordering Popups Offer $10 off first order → 10–20% opt-in. - QR Codes Everywhere Tables, bags, boxes, receipts. - Website CTAs Persistent footer or slide-up. - WiFi Splash Pages Connect → join SMS for perks. - In-Store Staff Scripts Train staff to say: > “Want VIP text-only deals?” Restaurants can grow from 0 → 5,000 subscribers in 60–90 days using these methods. ## How Often Should Restaurants Send SMS? With AI personalization, frequency no longer equals fatigue. The optimal cadence becomes: - AI-driven personalized messages anytime a guest is likely to order - 1–2 weekly promotional messages - Moment-based or behavior-based texts when relevant Because messages are personalized, unsubscribes drop , not rise. ## Compliance (Simple & Fully Handled by AI) SMS compliance worries operators — but modern systems make it straightforward: - Every subscriber explicitly opts in - Easy one-tap unsubscribe - Quiet hours automatically enforced - AI respects messaging limits per subscriber With Open, compliance is built-in. ## The ROI Restaurants See From AI-Powered SMS Here’s what restaurants typically experience after enabling SMS: Metric Typical Result Open rate 98% Click rate 15–35% Conversion 8–15% Return on spend 6–12× Lapsed guest recovery 10–20% Loyalty frequency lift +22–38% This is why SMS becomes the #1 revenue channel for most restaurants within 60 days. ## Why AI Makes SMS 10× More Effective Most SMS tools offer standard SMS blasts. They should deliver personalized, adaptive, agentic AI messaging that improves every week. AI makes SMS: - smarter - more relevant - more predictive - more profitable - fully automated Your restaurant doesn’t need a marketing team. Just an AI system that learns and executes. ## Conclusion: SMS Is the Underrated Engine of Restaurant Growth SMS is the most efficient way to increase online ordering, retention, and loyalty in 2025. But the future isn’t manual campaigns. It’s AI-powered, behavior-aware, autonomously optimized messaging that treats every customer differently. Restaurants that adopt SMS + AI today will dominate their markets tomorrow. Source: https://www.getopen.com/blog/sms-marketing-for-restaurants --- ### How to Increase Online Orders for Your Restaurant in 2025 (The Complete Playbook) Published: Nov 21 · Author: Open Category: Ordering > A practical, modern guide for restaurants that want more direct orders, higher margins, and repeat customers — without relying on marketplaces. - Make Your Website Your #1 Ordering Channel Your website is the highest-margin place a customer can order. The goal is simple: funnel guests away from marketplaces and into your first-party ordering channel. A high-converting website in 2025 includes: → A giant “Order Now” button above the fold Center it. Bright color. Visible instantly on mobile. → Speed + simplicity Fast load times = more orders. Clean layout = less friction. → Mobile-first design 70–80% of restaurant traffic is mobile. Your site must be built for mobile. → Direct ordering you own First-party ordering = higher margin, more data, more repeat customers. - Optimize Your Online Menu for Maximum Conversion Your menu is your online salesperson — design it that way. Quick optimization wins: Put best sellers first - Add photos to every item - Short, punchy descriptions - Streamline categories - Add “Popular” or “Recommended” sections - Add modifiers (upgrades, extras, combos) - Run limited-time drops Just cleaning up your menu can increase AOV by 10–25% . - Remove Friction from Your Ordering Experience Every unnecessary tap is a lost order. Customers should be able to: checkout on one page - pay with Apple Pay or Google Pay - reorder in one tap - verify via SMS (not email) The fewer steps, the higher your conversion rate. - Launch a Loyalty Program That Actually Drives Repeat Orders Most loyalty programs fail because they’re confusing and slow. The best loyalty programs today are: simple - instant - SMS-based - automatic - personalized ## Why we recommend cash-back over points Points introduce friction: customers don’t know what they’re worth. Cash-back feels real, immediate, and universal. We explain the full strategy here . - Turn One-Time Customers Into Loyal, High-Frequency Regulars Segmentation is outdated. The new model is: Every customer is a segment of one. AI lets you treat each person differently based on: their order frequency - their favorite items - their typical reorder window - their price sensitivity - whether they respond better to SMS or email - their individual lifetime value trajectory ### 1:1 personalization looks like this: - If someone normally orders every 10 days → win them back on day 11. - If someone always buys the same item → recommend the perfect upsell. - If someone is approaching churn → send the highest likelihood offer to reactivate them. - If someone is high value → give them VIP treatment automatically. No segments. No buckets. No generalized messaging. Just a personalized, adaptive system for every diner. This is the future of restaurant CRM. - Capture Every Visitor Who Doesn’t Order 80–90% of website visitors do not place an order. Most restaurants never see them again. High-growth restaurants capture: phone numbers - emails - SMS opt-ins Once captured, you can turn anonymous traffic into predictable revenue — through 1:1 outreach, not broad segments. This is the philosophy behind Open Capture : every visitor is a potential relationship you can personalize. - Use Google Reviews to Increase Ranking & Orders Google reviews directly influence how many customers choose you. Weekly checklist: ask for reviews after positive experiences - respond to every review - refresh your photos - update your Google Business Profile - upload your menu More reviews → higher ranking → more online orders. - Run Targeted Ads on Meta & Google Paid acquisition works best when your entire ordering engine is optimized. Meta campaigns that work: local radius ads - food photos with simple CTAs - weekly specials - UGC posts - Lead forms to capture SMS opt-ins ### Google campaigns that convert: - “order [restaurant name]” - “[food] near me” - competitor conquesting - branded keyword protection The goal is simple: bring demand directly to your site — not the marketplaces. - Run Limited-Time Items & Seasonal Drops Drops create urgency, excitement, and habit. Examples: weekend-only specials - seasonal dishes - LTO sandwiches - loyalty-exclusive items - “only available for 72 hours” Restaurants who run drops grow faster — because customers start checking in regularly. - Track What Works (Then Multiply It) You don’t need complicated dashboards — just track: website → order conversion rate - AOV - reorder frequency - loyalty participation - SMS click-through rate - online order GMV - monthly customer retention The moment you begin measuring, you start improving. ## Final Takeaway Increasing online orders in 2025 isn’t about discounts or gimmicks. It’s about: - removing friction - improving your online menu - driving traffic to your site - capturing every visitor - and then treating every customer as a segment of one through AI Do this, and online orders grow consistently — month after month. Source: https://www.getopen.com/blog/increase-online-orders-for-your-restaurant-in-2025 --- ### The Big Brands Are Already Doing It: How Chains Bake Delivery Into Menu Prices Published: Jul 29 · Author: George Jacobs Category: Ordering > A follow-up on including delivery in your prices — turns out Chipotle, Chick-fil-A, McDonald’s, and others have quietly been doing exactly this for years. A little while back, I wrote about why restaurants should [include delivery costs in their menu prices instead of tacking on a fee at checkout](/blog/include-delivery-costs-in-your-menu-prices-not-at-checkout). The gist: people hate delivery fees, and a surprise fee at checkout is one of the fastest ways to lose an order. The most common pushback I heard was some version of: *“That feels sneaky. No serious brand actually does that.”* It turns out the opposite is true. Some of the largest restaurant brands in the country have been quietly baking delivery costs into their menu prices for years. Let’s walk through the receipts. ## Chipotle Chipotle prices delivery orders placed through its own app and website higher than pickup orders — roughly 12–15% more — rather than piling the full cost of delivery onto a single fee at checkout. Pickup pricing stays the same as in-store. The strategy is exactly what I described in the first article: the cost of delivery lives quietly in the menu prices, not as a big scary number at the end. Customers see one price as they build their order, and the checkout stays clean. ## Chick-fil-A Chick-fil-A takes the same approach, with delivery menu prices running meaningfully higher than in-store prices even as the brand promotes low or free delivery. The delivery cost is built into the food, not tacked on at the end. The most useful part for our purposes: Chick-fil-A now puts a clear note on its app and website letting customers know delivery prices may be higher than in-store. That’s the whole lesson in one move — build delivery into the price, and be transparent that you’re doing it. ## McDonald’s McDonald’s doesn’t hide it at all. Its own McDelivery page states plainly that “McDelivery prices may be higher than at restaurants” and that delivery or other fees may apply. That’s a national brand telling customers, in writing, that the delivery menu is priced differently. McDonald’s also uses its app as the carrot: ordering McDelivery through the McDonald’s app earns MyMcDonald’s Rewards points, which orders placed elsewhere don’t. Higher delivery pricing, offset by loyalty value for ordering direct — that’s the exact playbook. ## Cava Cava is a newer, fast-growing example in the same fast-casual lane as Chipotle — and it says the quiet part right out loud. When you choose delivery on Cava’s own site, it tells you directly: “Menu pricing for delivery is higher and a $1.99 Delivery Fee and $2.99 Service Fee apply … to help offset delivery and online ordering costs.” https://storage.googleapis.com/open-merchant-app-assets/media/31de2a0b-d3dc-436a-b9fa-a3b7ff852ae8/4ef08917-fdd2-4785-ab75-9081d84d9b0e/cava%20screenshot.png|Cava’s delivery flow states that menu pricing for delivery is higher, with a $1.99 delivery fee and $2.99 service fee to offset delivery and online ordering costs. That’s the model in a single sentence: higher menu prices for delivery, a clear explanation of why, and full transparency up front. The direction of travel across the whole category is clearly toward pricing delivery into the experience rather than pretending it’s free. ## Starbucks — the exception that proves the rule Starbucks is the interesting counter-example. It doesn’t run its own first-party delivery — its delivery page routes you out to DoorDash, Uber Eats, or Grubhub, you can’t pay with the Starbucks app, and delivery orders don’t earn Rewards stars. Starbucks even notes that prices through those third parties “may be higher than posted in stores.” In other words, because Starbucks handed delivery to the marketplaces, it also handed over the markup, the customer relationship, and the loyalty hook. That’s precisely the outcome the rest of these brands are working to avoid by owning delivery pricing on their own channels. ## What this means for your restaurant The pattern across all of these brands is consistent: the real cost of delivery gets built into the menu, and the loud, separate “delivery fee” at checkout gets minimized or eliminated. The brands that own this on their own app also own the customer and the loyalty relationship. The one that outsourced delivery gave all of that away. The lesson from the big chains isn’t “hide your fees.” The Chick-fil-A, McDonald’s, and Cava notices all point to the winning version of this: price delivery into your menu, and be transparent that delivery pricing is a little different. You get a clean, surprise-free checkout, a direct channel that can actually compete with the marketplaces on perceived price, and a loyalty program that rewards ordering direct. If billion-dollar brands with entire pricing teams have all landed in the same place, it’s worth asking whether your own delivery pricing is set up to compete — or set up to quietly push your best customers back onto third-party apps. For the full framework on how to set your markup, [read the original article here](/blog/include-delivery-costs-in-your-menu-prices-not-at-checkout). Sources Chipotle: higher menu pricing on delivery orders placed through Chipotle’s own app and website. Chick-fil-A: higher delivery menu pricing and its app/website notice that delivery prices may be higher than in-store. McDonald’s: McDelivery pricing and fees disclosure on mcdonalds.com; MyMcDonald’s Rewards earned on in-app McDelivery orders. Starbucks: Starbucks Delivery information page (DoorDash/Uber Eats/Grubhub routing; third-party pricing notice; no Rewards stars on delivery). Source: https://www.getopen.com/blog/big-brands-already-bake-delivery-into-menu-prices --- ### Include Delivery Costs in Your Menu Prices — Not at Checkout Published: Oct 16 · Author: George Jacobs Category: Ordering > People hate delivery fees, and having them is killing your ability to convert third-party customers into direct customers. If you take anything away from this article, let it be this: 1) increase direct delivery menu prices so that you can eliminate or drastically reduce your delivery fees and 2) remember the following statistic: 90% of consumers are likely to abandon shopping carts that feature high shipping costs. [1] Ok, now on to the article … Back in 2016, when I was launching new markets for DoorDash, we had a large company initiative to eliminate menu inflation in favor of displaying delivery fees at checkout. Up until that point, we made money by increasing most restaurant’s menu prices by 10-30% instead of monetizing via a higher per-order delivery fee. As an example, we’d mark up a $20 item to $25 and have a $1.99 delivery fee instead of leaving the item at its $20 in-store price and tacking on a $6.99 delivery fee at checkout. Wanting to give customers more transparency on what they were paying for delivery, we planned to make all DoorDash menu prices match in-store prices and instead include the full delivery cost at checkout. At the time, we thought splitting out the cost of delivery from the menu item price was a great, customer-centric idea. However, it was a massive flop soon to be forgotten. To emphasize how short-lived it was, I was only able to find two articles about it online (one from TechCrunch and one from Eater ). Below is a snippet from the TechCrunch article: The reason why it was so short lived is because customers didn’t like it and it badly hurt conversion metrics. People would spend time building their cart only to get to checkout to see delivery fees they weren’t willing to pay. If they understood most of the costs up front, they would’ve either started the order with a clearer understanding of the final price they’d pay, or not have built the cart in the first place. I vaguely remember us reverting the change after only a matter of days. We quickly realized the Amazon effect and how consumers have a repulsive response to delivery fees. ## The Amazon effect and our conditioning to hate delivery fees Think about the last time you saw a delivery fee on Amazon or while buying something online. How did you feel when you saw it? Did you decide to enthusiastically checkout? If you knew of an alternative with free delivery, would you have used that alternative? The truth is we hate delivery fees , and have been conditioned to. The conditioning started in 2002 when Amazon introduced Free Super Saver Shipping – a product that gave free shipping on orders over $99, then $49, and eventually $25. This started our love for free and fast shipping. A few years later, in 2005, Amazon launched Prime where customers could pay $79/year for unlimited two-day shipping on over a million items with no per-order delivery fee. Over 40% of US households were subscribed just 10 years later and shipping cost was now the #1 cause of cart abandonment online. Most of retail followed suit, eventually paving the way for last mile delivery services like DoorDash and UberEats, capitalizing on our love for free delivery. ## Food delivery gets primed As food delivery services looked to find ways to make consumers more loyal to their platform and increase conversion rates, they each launched their own version of Amazon Prime –Postmates Unlimited was released in 2018 with free deliveries over $15 for $9.99/mo [2], DoorDash quickly followed up with DashPass that same year [3], and Uber tested Eats Pass in 2019 [4] which eventually evolved to Uber One in 2021 [5]. DashPass and Uber One have both seen incredible growth. DashPass now has more than 22 million active members [6] and Uber One recently hit more than 30 million subscribers [7]. All of this means that free delivery is becoming the default experience for more customers ordering food. Unsurprisingly, Uber states that Uber One members spend three times more than nonmembers. If you’re a restaurant looking to get customers to order direct, these are the customers you should be seeking to acquire. Many restaurants are hesitant of including delivery costs up front, not wanting to increase menu prices for direct customers. However, I think there’s a way to reframe how we think about this, and some proof that this might ironically be what customers want. ## Reframing “menu inflation” and giving customers what they want I recently discussed increasing menu prices and having no checkout delivery fee with Lucas, one of my colleagues at Open. I mentioned to him that we might be fighting an uphill battle because restaurants have a negative perception of menu inflation for their owned channels. He responded saying, “Well, menu inflation isn’t the right way to think about this. The right way to think of it is that we include the total price, including delivery fees, up front to the customer. This is actually the best experience because there are no big surprises at checkout. Airbnb recently did this, and it’s clearly what customers prefer.” I decided to look into the Airbnb example more, and ran the thoughts by a few restaurant customers. In late 2022 [8], Airbnb started testing a feature to ease customer complaints from users who were frustrated by seeing a low base nightly fee only to get to checkout and notice they were paying 30%+ more when factoring in fees like cleaning. Airbnb decided to give customers the ability to toggle a setting to instead see the nightly cost inclusive of all fees. There were so many customers that opted for seeing the full cost up front (more than 17 million) that Airbnb made a permanent and standard change to do this for all customers in 2025 [9]. About a month ago, I was thinking of productizing the menu price includes delivery idea. I chatted with one of our most popular restaurants who initially wasn’t a fan. Ironically, his opinion changed without my convincing. His friend texted him a couple weeks later saying he was going to place an order directly with a restaurant but ended up using DoorDash to avoid the $5 delivery fee. The restaurateur told his friend that the DoorDash prices were 25% more and that it would’ve actually been less expensive to order directly from the restaurant. The customer said “Well, the restaurant’s website felt more expensive when I saw the $5 delivery fee compared to free with DashPass.” ## Adding delivery fees in the menu prices is the only way to engineer “lowest cost, order direct” Most of the restaurants I speak with promote cost savings by ordering direct, but that’s not always the case. The challenge lies in the fact that most restaurant’s direct ordering channel has a fixed delivery cost (i.e. $6) and most restaurant’s third-party delivery channels have a relative delivery cost (i.e. 20% mark up). Here’s the simple math: if the customer’s order size is less than your fixed delivery cost divided by the markup %, it will be more expensive to order direct. Conversely, if the customer’s order size is more than your fixed delivery cost divided by the markup %, it will be less expensive to order direct. Here’s an illustration highlighting the difference: Unfortunately, in both cases, the perceived lowest cost option is likely the third-party marketplace. If you made your direct experience delivery cost relative (through a <20% markup for delivery), you could guarantee that your direct channel is always both the actual and perceived best option. For example, if you mark up 20% on third-party marketplaces but mark up 18% direct and both have $0 delivery fees, you know that your direct channel is always a better delivery option (barring any promotions). Couple this with loyalty (ideally a cash based loyalty system ) and it’s a no brainer to order direct. The hidden costs of not doing this are massive. You’ll train and incentivize your customers to continue ordering from third-party marketplaces up until the point where 50-75%+ of your sales are third-party, if that hasn’t already happened. ## Concluding thoughts The other day I saw a $170 shipping fee at checkout (granted the items were 100+ lbs). $170 for shipping seemed ridiculous so I ordered an alternative on Amazon Prime. Because I had been thinking about delivery fees and item prices recently, I decided to look back and compare the total price of the two orders. Ironically, they weren’t that different. But the ones with the $170 delivery fee seemed significantly more expensive. I opened up a support ticket asking if they ever offered free delivery. They told me that they didn’t and sent me this response: Maybe they stay true to that promise, but at the expense of keeping their delivery fees as high as possible and they lost me as a customer. We’re addicted to free delivery. Instead of trying to fight consumer behavior, let’s learn from it and implement the customer-preferred solution of including most (or all) delivery fees up front. ## Appendix: How to determine the markup and answers to common questions Question: How much should I increase my menu prices on my direct channels? Answer: Here are a couple of good options: - You can simply mark up direct slightly less than your third-party marketplace markup. If you mark up 15% on third-parties, you can mark up 14% direct. - You can look at your current customer delivery cost (i.e. $5) and figure out what you’d need to increase delivery prices by to make $5 on average based on your average order size (yes, sometimes you’ll make less than $5 and sometimes you’ll make more than $5). For example, if your average order size is $25, you’d need to increase that by 20% to make $5 on average, assuming the average basket size doesn’t go down. Question: Will my average basket size go down for delivery orders? Answer: Most likely. Customers will be more willing to order delivery for smaller order sizes. This trade off is worth it, but you might end up adjusting the mark up % after you see the adjusted average order size. Question: If I pay a system like DoorDash Drive and Uber Direct $8 per delivery, won’t I lose a bunch of money on small orders? Answer: Yes, but you can institute a small order minimum (matching DashPass and Uber One) and also should be willing to make less margin on some smaller orders because you will offset them with greater margin on larger orders. I’d encourage you to think not solely of your per-order profitability but rather the total lifetime value of that customer as an owned customer vs a rented customer. Question: What should the order minimum be for free delivery? Answer: This can vary by customer and market, but I’d recommend looking at what threshold DashPass and/or Uber One (based on which marketplaces you partner with) members need to meet and setting it at that price (typically $12 or $15). Question: Should I be worried about customers thinking I’m expensive? Answer: This is a valid concern. I still believe that you should be more worried about your customers leaving for third-party marketplaces and not truly being your customers anymore. Sources [1] McKinsey: What do US consumers want from e-commerce deliveries? [2] Postmates Unlimited Grows 300% — Drops Minimum Order Amount [3] DoorDash Launches DashPass Subscription and Free Customer Pickup [4] Leak reveals Uber’s $9.99 unlimited delivery Eats Pass [5] Uber Introduces Uber One: A New Membership Program Bringing Together the Best of Uber [6] DoorDash Revenue and Usage Statistics (2025) [7] Uber One Hits 30 Million Subscribers, Drives Delivery Revenues 22% Higher [8] Airbnb is introducing total price display and updating guest checkout [9] Total price display is now standard for guests worldwide Source: https://www.getopen.com/blog/include-delivery-costs-in-your-menu-prices-not-at-checkout --- ### Loyalty Points Kind of Suck: The Case for Cash Back and Making Rewards Simple Again Published: Oct 7 · Author: George Jacobs Category: Loyalty > In order for restaurant loyalty to really work, we need to simplify and reframe how we think about rewards. Over the past decade, restaurant loyalty has become ubiquitous – the majority of restaurants I order from have some sort of points system, and third-party marketplaces like DoorDash are driving further adoption through restaurant-funded rewards programs. However, ask 100 restaurants if their loyalty program drives meaningful results, and it’s unlikely you’ll hear a resounding yes from any of them. After spending years evaluating different loyalty programs and providers, talking to hundreds of restaurateurs, and surveying tens of thousands of customers, here’s why I feel like today’s restaurant loyalty systems are broken, and how we can fix it. ## We’re overcomplicating it… I was first exposed to different loyalty programs during an RFP for Applebee’s and IHOP in 2019 as we were looking to onboard our first loyalty provider. I sat through hours of meetings evaluating platforms like Punchh and Paytronix, learning about all of the different ways you could give customers rewards for purchasing, from points and birthday offers to sign up bonuses and tiered-based systems. Everything felt unnecessarily complicated, but it was the status-quo so there wasn’t much questioning. Now, 6 years later, after launching a points-based loyalty system myself at Open , I started questioning why we use points as the default loyalty currency, how it got started, and where things are trending. The further I dug, the more I realized there didn’t seem to be a definitive reason for points (everyone was just copying everyone else). I started meeting with public company restaurant CEOs who made the mistake of following the pack, complicating loyalty structures only later to revert them back to something simpler (after significant resources were already wasted). Later, I started looking at where the “thought leaders” in restaurant loyalty were headed. The more I read, the more I thought I was being pranked. One of the most popular loyalty solutions for restaurants, Thanx, was promoting NFT-like access passes for non-discount rewards. Their site allowed you to download a 47 page book of ideas on how to use these access passes. Here’s a snippet of use-cases from their site below: If you’re a restaurant owner or marketer, please don’t be swayed to think that prime parking spots or invites to “influence mixers” (not quite sure what that is) is going to meaningfully generate loyalty and drive frequency. Here’s a good heuristic to use: if your loyalty program can’t be easily explained in a single sentence (like get 10% in cash towards your next order when you order direct) then it’s probably too complicated. Some restaurants have told me they’re building dedicated pages and blog posts to explain their loyalty program and tiers — this is also not the answer. Just simplify. I’ll walk through a proposed system later in this article that will 1) be much more effective at driving the business outcomes you want and 2) be much simpler for you to communicate and execute. But first, let’s quickly review how we got here. ## The history of restaurant loyalty Before we dive into our broken loyalty system and how we fix it, it’s helpful to think through the history of restaurant loyalty, which started out as refreshingly simple and somehow evolved to overly complex. ### Punch cards (mid 1900s - early 2000s) The earliest restaurant loyalty programs were incredibly simple, executed with physical punch or stamp cards. Customers received a card, which was either stamped or hole punched at every visit. After acquiring a certain number of stamps, customers got a free item (like Subway’s Sub Club where you buy 8 subs and get the 9th free). In the early 2000s, Subway and many other restaurants shut down their stamp programs because of advancements in high quality printers that enabled customers to create counterfeit stamps (hole punching was even easier for fraudsters). ### Airlines introduce miles (1970s - 1980s), hotels introduce points (1980s - 1990s), credit cards institutionalize points (1990s - 2000s) In the 1970s and 1980s airlines started to launch miles programs to reward frequent flyers. Major carriers looked to gain loyalty in exchange for giving the customer something with no marginal cost (an empty seat on an existing flight). As airlines drove more and more adoption, they eventually announced different membership tiers to further reward their most loyal guests and incentivize more flying with a single airline. Hotels quickly followed suit trying to solve for the same problems, realizing the marginal cost of filling an empty room was negligible. Miles didn’t make sense for hotels, so they invented points as a substitute – an abstraction that later spread to credit cards, which cemented points as the default loyalty currency across industries. ### Starbucks and the restaurant points era While restaurants didn’t quite have negligible cost of supply, they did face the same frequency and loyalty challenges as airlines, hotels, and credit cards. In 2008, Starbucks launched its rewards program and its stars/points-based system has served as the gold standard of restaurant loyalty programs ever since. Many other restaurant chains and loyalty providers mirrored their offerings after the Starbucks program, which is part of how we got here today. To be clear, this post isn’t to advocate for eliminating loyalty programs altogether, so let’s dive into why I’m bullish on restaurant loyalty (if done right). ## Why loyalty programs are important In today’s digital-first landscape, loyalty programs are more important than ever. Yelp, Google, and food delivery marketplaces have given consumers access to vast selection. This vast selection creates more competition, and loyalty is a clear benefit when choosing where to dine. Perhaps more importantly, loyalty can serve as a primary driver for customers to order direct instead of from a third-party marketplace. Here are some stats from National Restaurant Association’s (NRA) State of the Restaurant Industry Report highlighting loyalty’s importance for acquisition and retention: - 48% of loyalty program members say that they’re less likely to try new competitive restaurants because they prefer to go where they can earn loyalty - 78% of respondents say they’re more likely to visit a restaurant that offers loyalty Despite customer excitement about loyalty, most rewards programs aren’t driving the definitive results that restaurants are hoping for. ## Why today’s loyalty point programs fall short Most loyalty providers obsess over vanity metrics (things like total members enrolled or monthly loyalty sign ups). This gives restaurants a false sense of program performance, which further fuels restaurant’s adoption and retention of these loyalty providers. These vanity metrics are easy for companies to obsess over and report on because they look good — total members enrolled always goes up. However, the goal for loyalty is simple (drive new visits and increase customer lifetime value) and so they key metric measured for loyalty efficacy should also be simple (new visits and increased customer lifetime value). Unfortunately, most providers aren’t able to confidently report on how their loyalty program drives new visits and increases lifetime value. Most of this lies in how these programs are executed and communicated. ### The problem with the current structure (points and, sometimes, tiers) The problem with loyalty points today is that points aren’t a form of currency, and so they’re definitionally ambiguous. Some restaurants offer 1 point per dollar, others 5 points per dollar, some 10. Points can be worth $0.01, $0.05, $0.10, or whatever the restaurant defines as the exchange rate. Because there is no universal definition of the value of a point, a point is somewhat meaningless. If I have 50 loyalty points in my account, what does that mean? The problem with different loyalty tiers — like silver, gold, platinum — is that they further overcomplicate your loyalty system. When tiers are introduced, you now have to educate your customers on the benefits of each tier and requirements to get there. This makes communicating (and therefore, understanding) the program much more challenging. If you don’t believe me that points and tiered systems are challenging, just take a look at The Points Guy , an online blog solely dedicated to explaining airline and hotel points with more than 10 million monthly viewers. It’s unlikely anyone will be educating your customers with this much content about how your loyalty points and tiers work. Fortunately, there’s a better option that makes both explaining and executing your rewards program a whole lot easier… ## The case for cash back loyalty programs There is a simple and much more effective path forward for loyalty, and we’re already starting to see this work well in other industries: give people cash back towards their next purchase. Paradoxically, this is essentially what loyalty points systems already do — converting the points to cash just does the math for the customer so they can better understand, and perceive, the value of your loyalty program. Recently, I was watching a video on Ramp (a credit card startup that has scaled to more than $1B in revenue in just 5 years), where their CEO said that he interviewed tons of CFOs when starting the company and heard the same thing from all of them “We just want cash back, we don’t care about these complicated points structures and non-cash rewards.” Even Shopify — one of the world’s largest e-commerce platforms — launched a cash-back system with Shop Cash when they introduced loyalty two years ago. The clarity beats complexity playbook is clearly working (and working very well) across other industries. It’s time we bring it to restaurants. The other nice thing about cash back systems is they provide great opportunities to introduce branding to the loyalty experience. Instead of simply framing this as “cash” you can brand your program like “LOQUI Cash” or “Poached Bucks” which reinforces the brand name throughout your communications and marketing. Imagine if, instead of saying “you’ll earn 35 points on this order,” you instead say “you’ll get $3.50 LOQUI Cash on this order.” The $3.50 has immediate and understandable value to the customer whereas 35 points does not. One of the key benefits of a cash based program is not needing to communicate the value of a point to your customers. If I have $25 in my loyalty account, I clearly know that I can redeem that for something that’s $25 or less. However, if I have 100 points, I need to know how those points are converted in value and if all items redeem for the same amount of points to know what I can use the points for. This complicates the digital and in-store experience because, in order to maximize the program’s effectiveness, the restaurant must convey what can be purchased for what amount of points. In addition to the benefits of communicating and understanding cash back loyalty systems, it also instantly gives you a digital currency that can be used across support, operations, growth, and marketing. Imagine if a customer complains online about long wait times — you can apologize and send them $10 loyalty cash for the inconvenience instead of 100 loyalty points. Or if you want to use loyalty as a marketing mechanism, sending a text saying “Get double cash back today only” feels a lot more tangible and exciting than “Get double loyalty points today.” The downstream effects on the brand, loyalty adoption, and engagement are large. ## Concluding thoughts It appears we’ve ended up following a simple copy-paste format for loyalty that might not apply to the restaurant industry, and today’s loyalty providers seem to be wanting to complicate things further. I’m advocating that we all get back to simplifying, and am confident this will drive more meaningful results for businesses and happier, more loyal customers. I put my money where my mouth is and spent significant engineering resources to make it extremely easy for restaurants to launch cash back programs, even though I had previously built a points system at Open. It feels like the right thing to do for both restaurants and customers. If you’re interested in learning more or implementing this at your restaurant, send me a message or set up time to talk here . Source: https://www.getopen.com/blog/cash-back-loyalty ---