Revolutionary AI Package Sorting at Amazon Empowers Delivery Station Staff!

This new AI tech will make sorting packages easier for Amazon’s delivery station employees

This technology, which derives from Amazon’s Vision-Assisted Package Retrieval (VAPR) system for delivery vans, uses visual cues to help employees identify the packages during the sorting process.

Amazon is testing new technology that will help employees at delivery stations more efficiently identify and sort packages before they’re loaded onto delivery vans.

It’s called Vision Assisted Sort Station (VASS) and it uses computer vision and projection technology similar to the Vision-Assisted Package Retrieval (VAPR) system in Amazon’s delivery vans.

When packages arrive at Amazon delivery stations from local fulfillment and sortation centers, employees sort and stow them into bags which then get loaded into vans by their delivery route to reach their final destination—customers’ doorsteps. During this process, VASS will create a static buffer area, holding multiple packages, where it spotlights packages with visual cues to help employees quickly identify the right ones without the need to look at a screen or device. In parallel, the destination bags are brought to them, so employees no longer have to walk. This dramatically improves efficiency and simplicity through the sorting process.

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“VASS is a powerful example of how we’re innovating at Amazon to make work easier for our teams,” said Chris Harris, Amazon’s director of logistics engineering. “VASS helps simplify decision-making for our employees and speeds up the process of getting packages where they need to go.”

Amazon's new robot system, Vulcan, picking up a cardboard box.

This innovation builds on VAPR, an Amazon technology embedded into delivery vans that automatically project a green “O” on all packages that need to be delivered once the van arrives at a delivery location, and red shapes on all other packages. Through an audio and visual cue, VAPR prompts the driver to confirm it has found the right packages before the driver even needs to enter the cargo area.

The technology, which can locate and decipher multiple barcodes in real time, was built by training machine learning models to recognize different labels and packages in various lighting conditions and package characteristics. It also removes the need for drivers to use a mobile device throughout the process.

Based on early VAPR tests, Amazon teams saw a 67% reduction in perceived physical and mental effort for drivers and more than 30 minutes saved per route.

Real benefits, real results

The technology’s cameras, being explored for an under the roof application in our delivery stations, scan packages on a conveyor belt so when they arrive at a stow station, employees instantly know their destinations.

VASS shines a green O, indicating to the employee which package needs to be picked (and a red shape on those that shouldn’t be picked) and placed in the corresponding destination bag, which is brought directly to the employee for better ergonomics.

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“It’s sophisticated technology under the hood,” Harris added, “but what our employees experience is something simple, intuitive, and genuinely helpful.”

Early testing of VASS at Amazon’s Innovation Center DNZ3, in Dortmund, Germany, showed promising results:

  • Reduced mental load for employees, who no longer need to memorize destinations or constantly reference their handheld devices or screen.
  • Increased accuracy with a substantial decrease in missorts in pilot stations.
  • Greater efficiency through improved sort time per package: Employees were able to manage a buffer of up to 10 packages simultaneously, versus just two with conventional methods.
  • Enhanced flexibility: The system decouples sorting performance from machine sequencing, allowing employees to work at their own pace.

Amazon fulfillment center showing staff and automated sorting equipment

Looking ahead

Currently in pilot phase, VASS is scheduled for implementation across some of Amazon’s delivery stations in Europe and the U.S. starting in 2027.

Amazon’s last-mile delivery technology team is already working on enhancements that will incorporate more advanced computer vision algorithms. VASS, as an iteration of VAPR, is an example Amazon’s ability to innovate and scale across its operations, and shows our commitment to employees and partners, to keep delivering smiles to customers.

 

How to build a successful online reselling business

Are you sitting on a goldmine of unused items, or dreaming of starting a profitable side hustle? The world of online reselling has exploded in recent years, offering enterprising individuals and businesses the opportunity to turn their keen eye for value into a sustainable income stream.

In this guide, we’ll explore how to start and grow a successful reselling business, from choosing your niche to scaling your operations.

Getting started: Choose your reselling niche

The first step in your reselling journey is deciding what types of items you want to sell. While it might be tempting to try to sell everything under the sun, successful resellers often specialize in specific categories. This focused approach allows you to develop expertise, build reliable supplier relationships, and better understand your market.

Popular reselling categories include:

  • Vintage clothing and accessories
  • Electronics and gadgets
  • Collectibles and antiques
  • Books and media
  • Designer fashion items
  • Sports equipment
  • Home decor

For beginners, it’s often wise to start with items you’re already familiar with. For instance, if you’re an avid reader, you might want to focus on reselling books online. The key is to choose a niche where you can effectively identify valuable items and understand the demands of the market.

Sourcing inventory: Where to find products worth reselling

Successful reselling businesses rely on a steady supply of profitable inventory. Here are several proven sourcing methods:

1. Retail Arbitrage

This involves buying products on clearance or at significant discounts from retail stores and reselling them at a higher price online. Many resellers start here because it requires minimal initial investment.

2. Wholesale purchasing

As your reselling business grows, you might consider working directly with manufacturers or distributors to resell wholesale products. This approach typically requires larger upfront investments but can offer better profit margins and more consistent inventory.

3. Thrift stores and estate sales

These venues are goldmines for unique items, especially in categories like vintage clothing, books, and collectibles. But to be successful, you’ll need knowledge of brands and values, along with a willingness to hunt for treasures.

4. Online sourcing

Various online liquidation platforms offer opportunities to purchase returned or excess inventory from major retailers at significant discounts.

5. Private sellers

Building relationships with individual sellers can provide a steady stream of inventory, especially for specialized items like antiques or collectibles.

Maximizing profits: Pricing and channel strategies

The key to a successful reselling business lies in smart pricing strategies and choosing the right selling channels. Here’s how to optimize both:

Pricing strategies

  • Research current prices for similar items.
  • Consider all costs, including sourcing, shipping, platform fees.
  • Factor in fluctuations in seasonal demand.
  • Build in enough margin to accommodate occasional discounts.
  • Monitor competitor pricing regularly.

Amazon’s Automate Pricing tool can help keep you competitive

Amazon sellers with a Professional selling plan can use our free Automate Pricing tool, which automatically adjusts your prices in real time. You choose the rules and the tool responds 24/7, keeping you competitive while freeing up valuable time. Select your products, customize your parameters, and let Amazon execute your pricing strategy and improve your chances of becoming the Featured Offer.

Popular places to sell

  • Online stores like Amazon.com
  • Social media selling platforms
  • Specialty reselling websites
  • Local selling platforms
  • Category-specific platforms

Each selling channel can have its own fee structure, rules, and audience. Many successful resellers maintain presence on multiple platforms to maximize exposure and sales opportunities.

Scaling your reselling business: From side hustle to full-time income

Once you understand the basics of reselling, you might want to scale your operations. Here’s how to grow sustainably:

Inventory management

  • Implement a robust inventory tracking system.
  • Monitor sales velocity to inform purchasing decisions.
  • Maintain organized storage solutions.
  • Consider warehouse space as you grow.

Business operations

  • Develop efficient shipping and handling processes.
  • Create standard operating procedures for listing items.
  • Invest in quality photography equipment.
  • Consider hiring help for tasks like photography or shipping.

Financial management

  • Track all expenses and revenue meticulously.
  • Maintain separate business banking accounts.
  • Consider professional accounting software.
  • Plan for taxes and maintain proper records.

Marketing and customer service

  • Build a social media presence.
  • Develop an email list of regular buyers.
  • Provide excellent customer service.
  • Consider creating a brand identity.

Seller Central is a one-stop shop for selling with Amazon

After registering as an Amazon seller, you get access to Seller Central, a one-stop shop for listing products, fulfilling customer orders, monitoring payments, and complete other essential selling tasks. That means you can manage and grow your selling business all from one place.

Get ready for reselling success

Starting a reselling business can be an exciting and profitable venture, whether you’re looking to clear out your closet or build a full-time enterprise. Success in reselling requires a combination of market knowledge, sourcing skills, and business acumen. It’s often best to start small, learn continuously, and adapt your strategies based on what works best in your chosen niche.

Remember that the most successful resellers are those who treat their venture as a real business, not just a hobby. This means maintaining professional standards, providing excellent customer service, and continuously learning about their market and products.

Whether you choose to resell books, focus on wholesale products, or specialize in vintage items, the key is to start with what you know and gradually expand your expertise. With dedication, smart strategies, and consistent effort, your reselling business can grow from a side hustle into a thriving enterprise.

Unlocking the Power of AI Predictive Analytics: How Shopify is Revolutionizing Business in 2025

Predictive analytics killed Subway’s $5 footlong. While the retirement of the sandwich chain’s famed economical menu item was bad news for sandwich fans, it provided a significant upside for Subway: increased profits.

Predictive analytics gave the sandwich giant an unexpected insight—the increased sales brought about by the promotion weren’t offsetting the discounted price. As a result, Subway raised its sandwich prices and leaned into deals with add-ons, which analytics predicted would improve profits.

With the rise of artificial intelligence (AI), advanced analytics technology has opened up new decision-making avenues for businesses in nearly every sector. Companies across industries can use AI predictive analytics—powered by machine learning—to unlock market and individual customer insights at unparalleled speeds with unprecedented accuracy.

What is AI predictive analytics?

AI predictive analytics leverage machine learning models to seek out patterns in current data and use those patterns to forecast future outcomes and predict trends. Predictive models are trained on historical data gleaned from data mining and various modes of data collection.

For business owners, AI predictive analytics can translate raw data into actionable insights. For example, AI predictive analytics can provide data analysis based on a customer’s buying history, predicting future purchases and providing personalized shopping suggestions.

Drive your business forward with Shopify’s analytics

Shopify’s user-friendly reports and analytics capabilities help you make better decisions, faster. Choose from pre-built dashboards and reports, or build your own to spot trends, capitalize on opportunities, and supercharge your decision-making.

Explore Shopify’s analytics

AI predictive analytics vs. predictive analytics

Traditional predictive analytics is the process of using data to forecast future outcomes and form data-driven insights. Data scientists take care of data collection, prepare it, and then use predictive techniques like decision trees (to map individual decisions) or regression models (to analyze large datasets) to detect clear patterns.

In AI-powered analytics, data scientists automate data collection, train machine learning models using the collected data, validate insights using manual or automated methods, deploy the model, and iterate over time. The primary difference between traditional and AI-powered predictive analytics is automation and intelligence. Both predict future events, but AI-powered analytics unlock insights at a much faster cadence.

While tedious for the data scientists running them, traditional predictive analytics are the cornerstone of AI-powered predictive analytics. It builds on its predecessor using machine learning models to process massive amounts of unstructured data. Backed by powerful algorithms and advanced neural networks (which can identify nonlinear relationships in large datasets), AI predictive analytics can identify trends with minimal human effort. It can also become more accurate over time and create adaptive predictions across complex data environments.

3 components of AI predictive analytics

  • Data
  • Algorithms
  • Predictions

Here’s how data, algorithms, and predictions power predictive analysis:

Data

AI models—including those using predictive analytics—use data to make constant adjustments to become better at simulating human intelligence. For ecommerce businesses, input data might be customer data points like purchase history, demographics, and shopping experience preferences. Whatever your business, you’ll need historical data to fuel your predictive analytics tool.

Algorithms

Predictive AI models use advanced algorithms—which power technologies like deep learning and neural networks—to make sense of complex data and uncover impactful insights. When applied across disciplines like mathematics and computer science, an algorithm can be defined as a chain of steps that complete a task. They are the building blocks of computers, software, and artificial intelligence.

Predictions

Predictions are the ultimate outcome of AI algorithms. Predictive models are used to forecast future outcomes, to predict the likelihood of specific possibilities by detecting patterns. You can use actual outcome data to improve predictions over time.

4 benefits of using predictive analytics

  1. Increased efficiency
  2. Better decision making
  3. Improved risk management
  4. Enhanced customer service

In the face of dynamic market conditions and quickly evolving customer needs, predictive analytics have become foundational to business operations in multiple industries. The key benefits of predictive analytics include:

1. Increased efficiency

AI predictive analytics can increase your operational efficiency by reducing your team’s manual workload, analyzing data, and allocating resources more effectively. Famously, FedEx uses predictive analytics to map the most efficient routes for its drivers. In turn, this reduced travel costs, increased shipment volumes, and optimized its employees’ time.

2. Better decision-making

Predictive analytics help companies across all industries make informed decisions by giving you access to actionable insights that are constantly adjusting to new learnings. It can also simulate outcomes from different decisions—as Subway did when it retired its beloved-but-unprofitable $5 footlong campaign to make way for higher-yield ideas.

3. Improved risk management

In risk reduction, predictive analytics expedites fraud detection, flags suspicious activity in contexts like financial institutions, forecasts risks before they escalate, and streamlines fraud prevention. HSBC, a British bank, claims predictive analytics reduced its false positives in fraud detection by 60%, freeing up resources to focus on urgent instances of fraud.

4. Enhanced customer service

Predictive insights help you understand customer behavior and identify ways to enhance customer service. You can improve customer interactions by responding in real time and offering solutions based on the customer’s preferences and purchasing history before a question turns into a complaint.

Predictive analytics can also help forecast future behaviors and offer relevant products or services to meet the customer’s emerging wants and needs. Netflix’s AI-powered content suggestion is an example of predictive analytics improving customer service—in this case, by serving customers personalized content based on their watch history.

4 ways to use AI-powered predictive analytics

  1. Logistics
  2. Finance
  3. Retail
  4. Health care

AI predictive analytics have become relevant across many industries, including:

1. Logistics

Predictive analytics is a key facet of supply chain optimization—forecasting demands, identifying bottlenecks, and ensuring materials arrive at their destination. Predictive maintenance reduces downtime and improves operations. For example, DHL invested millions of dollars into integrating predictive analytics into its supply chain, which helps its operations adapt to real-time demands.

2. Finance

When it comes to risk management, financial institutions rely on AI predictive analytics to improve fraud detection, create financial projections, and make informed decisions ahead of market shifts. On an individual level, financial institutions use predictive analytics to assess creditworthiness.

3. Retail

Ecommerce and in-person retailers lean on predictive insights to better understand customer behavior, personalize shopping experiences, and improve inventory management. For example, Walmart uses AI predictive analytics to predict demand and maintain relevant stock. By analyzing purchasing patterns you can anticipate trends, improve sustainable practices, and hone your marketing strategies.

4. Health care

In the health care field, predictive analytics are utilized to maximize patient outcomes. Medical data analysis identifies risk factors, personalizes treatments, and predicts disease progression. For example, Mayo Clinic uses predictive analytics to analyze its electronic health record data, predicting the likelihood of chronic diseases like diabetes.

AI predictive analytics FAQ

How is AI used in predictive analytics?

AI enhances predictive analytics by automating data analysis and identifying patterns. It creates accurate forecasts that provide visibility into large datasets, improve decision-making, and reduce the need for human intervention.

Is ChatGPT generative AI or predictive AI?

ChatGPT is a generative AI model—it creates text based on learned patterns, much like language generated from the human brain. Generative AI produces new content, while predictive AI forecasts specific outcomes.

What is the main goal of AI predictive analytics?

Predictive analytics is designed to anticipate trends and future outcomes, offering insights that optimize business processes and improve efficiency.

Introducing Vulcan: Amazon’s first robot with a sense of touch

The next time you drop a coin on the ground, consider how you go about picking it up again. Maybe your hearing tells you which way it bounced. Your vision lets you zero in on its location. And for the final, crucial act of getting it from the ground to your hand, you rely on your sense of touch to know exactly when to clasp your fingers together and how to flip it into your palm or your pocket.

But what many humans do so easily, few robots can tackle. For all their accomplishments—defeating chess masters, driving around city streets, pulling entire kennels’ worth of dog hair out of carpets—most robots are unfeeling, and not just in the emotional sense.

The typical robot is “numb and dumb,” says Aaron Parness, Amazon director, applied science, especially those that work in commercial settings. “In the past, when industrial robots have unexpected contact, they either emergency stop or smash through that contact. They often don’t even know they have hit something because they cannot sense it.”

An Amazon fulfillment center employee wearing an orange safety vest with his arm over the Vulcan robotic systemVulcan’s ability to pick and stow items makes our associates’ jobs easier—and our operations more efficient.

Today at our Delivering the Future event in Dortmund, Germany, we’re introducing a robot that is neither numb nor dumb. Built on key advances in robotics, engineering, and physical AI, Vulcan is our first robot with a sense of touch.

“Vulcan represents a fundamental leap forward in robotics,” Parness says. “It’s not just seeing the world, it’s feeling it, enabling capabilities that were impossible for Amazon robots until now.”

Amazon fulfillment center showing staff and automated sorting equipment

And it’s already changing the way we operate our fulfillment centers, helping make our employees’ jobs safer and easier while moving customers’ orders more efficiently.

“Working alongside Vulcan, we can pick and stow with greater ease,” says Kari Freitas Hardy, a front-line employee at GEG1, a fulfillment center in Spokane, Washington. “It’s great to see how many of my co-workers have gained new job skills and taken on more technical roles, like I did, once they started working closer with the technology at our sites.”

The power of touch

Vulcan is not our first robot that can pick things up. Our Sparrow, Cardinal, and Robin systems use computer vision and suction cups to move individual products or packages packed by human workers. Proteus, Titan, and Hercules lift and haul carts of goods around our fulfillment centers.

But with its sense of touch—its ability to understand when and how it makes contact with an object—Vulcan unlocks new ways to improve our operations jobs and facilities.

Amazon Vulcan robot picking up Febreze bottle

In our fulfillment centers, we maximize efficiency by storing inventory in fabric-covered pods that are divided into compartments about a foot square, each of which holds up to 10 items on average. Fitting an item into or plucking one out of this crowded space has historically been challenging for robots that lack the natural dexterity of humans.

Vulcan is our first robot with a similar kind of finesse. Vulcan can easily manipulate objects within those compartments to make room for whatever it’s stowing, because it knows when it makes contact and how much force it’s applying and can stop short of doing any damage.

Vulcan does this using an “end of arm tooling” that resembles a ruler stuck onto a hair straightener, plus force feedback sensors that tell it how hard it’s pushing or how firmly it’s holding something, so it can stay below the point at which it risks doing damage.

Amazon's Vulcan robot stowing a book

The ruler bit pushes around the items already in those compartments to make room for whatever it wants to add. The arms of the hair straightener (the “paddles”) hold the item to be added, adjusting their grip strength based on the item’s size and shape, then use built-in conveyor belts to zhoop the item into the bin.

For picking items from those bins, Vulcan uses an arm that carries a camera and a suction cup. The camera looks at the compartment and picks out the item to be grabbed, along with the best spot to hold it by. While the suction cup grabs it, the camera watches to make sure it took the right thing and only the right thing, avoiding what our engineers call the risk of “co-extracting non-target items.”

Amazon's Vulcan robot using a suction cup to pick an item from the lower part of a storage podVulcan uses an arm that carries a camera and a suction cup to pick items from our storage pods.

With the ability to pick and stow approximately 75% of all various types of items we store at our fulfillment centers, and at speeds comparable to that our front-line employees, Vulcan represents a step change in how automation and AI can assist our employees in their everyday tasks. It also has the smarts to identify when it can’t move a specific item, and can ask a human partner to tag in, helping us leveraging the best of what our technology and employees can achieve by working together.

The human-robot connection

We did all this work to improve not just efficiency, but worker safety and ergonomics. At our fulfillment centers in Spokane, Washington, and Hamburg, Germany, Vulcan is focused on picking and stowing inventory in the top rows of those inventory pods. Because those rows are about 8 feet up, they typically require an employee to reach them using a step ladder, a process that’s time-consuming, tiring, and one that is less ergonomic than stowing and picking at their midriff. Vulcan also handles items stowed just above the floor, so our employees can work where they’re most comfortable.

“Vulcan works alongside our employees, and the combination is better than either on their own,” says Parness.

An Amazon fulfillment center employee using a step ladder to place items in the upper part of a storage podVulcan will let our associates spend less time on step ladders and more time working in their power zone.

This application of Vulcan’s capabilities is just the latest example of how we think about and use this kind of technology. Over the past dozen years, we’ve deployed more than 750,000 robots into our fulfillment centers, all of them designed to help our employees work safely and efficiently by taking on physically taxing parts of the fulfillment process.

Meanwhile, these robots—which play a role in completing 75% of customer orders—have created hundreds of new categories of jobs at Amazon, from robotic floor monitors to on-site reliability maintenance engineers. We also offer training programs like Career Choice, which help our employees move into robotics and other high-tech fields.

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Picking problems

Vulcan’s technology isn’t handy by happenstance. Just as it fits in with our approach to robotics, it’s one more example of how we innovate: We pick out important problems and find or develop solutions—we don’t create interesting tech and then look for ways to use it.

Vulcan started with our realization that every time one of our employees has to use a ladder to reach the upper parts of our storage pods, they’re spending time on a less ergonomic and less efficient task. Adding a robot to this process required years of work on all sorts of tech, from force feedback sensors and a “hand” that can carefully handle millions of unique items, to a tool for nudging all kinds of boxes and baggies of all shapes and sizes, to a stereo vision system to estimate where there’s available space in a bin.

Two Amazon employees with Amazon's Vulcan robotVulcan represents “a technology that three years ago seemed impossible but is now set to help transform our operations,” says Aaron Parness, Amazon’s director of robotics AI.

It also required the novel application of physical AI, including algorithms for identifying which items Vulcan can or can’t handle, finding space within bins, identifying tubes of toothpaste and boxes of paper clips, and much more. And we couldn’t just teach Vulcan with computer simulations, but trained its AI on physical data that incorporates touch and force feedback. It tackled thousands of real-world examples, from picking up socks to moving fragile electronics.

Vulcan even learns from its own failures, figuring out how different objects behave when touched and steadily building up an understanding of the physical world, just like kids do. So, you can expect it to become smarter and more capable in the years to come.

The result, Parness says, is “a technology that three years ago seemed impossible but is now set to help transform our operations.”

Touchdown

That transformation is on its way not just because Vulcan’s so capable, but because we implement our best work at Amazon scale. We plan to deploy Vulcan systems over the next couple of years, at sites throughout Europe and the United States.

“Our vision is to scale this technology across our network, enhancing operational efficiency, improving workplace safety, and supporting our employees by reducing physically demanding tasks,” Parness says.

Better operational efficiency translates to getting the right product to the right truck at ever faster speeds, allowing us to continue widening our selection and offer industry-leading prices.

And all it took was teaching a robot to feel.

The Untold Story of Building a Successful Bridal Fashion Empire Without Outside Funding – Insights from Shopify (2025)

At just 18, Gaby Bayona started making dresses out of her apartment with nothing but a sewing machine, some fabric, and the skills she picked up working alongside her mother, a professional seamstress. A decade later, she leads a team of 40 across multiple bridal brands and four retail stores—all while keeping production local in Vancouver.

In this episode of Shopify Masters, Gaby shares how she scaled Truvelle and her other brands organically, bootstrapped with a $15,000 loan, and built a loyal team that’s stayed with her for over a decade. She opens up about her approach to sustainable production, how she structures her team to avoid burnout, and why saying “yes” before you’re ready can pay off in the long run.

Growing organically as a one-woman operation

Gaby’s entrepreneurial journey began with a single dress and no business plan. At age 20, after years of custom sewing with her mom, she took a leap and put her first collection on Etsy. She was soon approached by a retailer in Ottawa asking if she could wholesale dresses. She agreed without hesitation.

“I had no idea how to wholesale dresses…I didn’t even have [standardized] sizes,” Gaby says. “That’s how unprepared I was for this. But I said yes.” That first leap marked the start of Truvelle’s expansion from side hustle to global brand.

Rather than try to scale quickly, Gaby stuck to what she knew. She sewed the dresses herself, fulfilled each order by hand, and used every experience to inform the systems she would eventually teach her team “It made the process of growing my business a lot easier because it all came from firsthand experience.”

She didn’t open her first retail store until she was consistently booked with weekend appointments out of her apartment. “If I can sell four dresses in a month, I’m not losing money. If I’m breaking even with the potential for growth, then that is a good direction.”

Building multiple brands with a shared infrastructure

As Truvelle grew, Gaby didn’t create just one brand—she launched four. Each targets a different bridal aesthetic, but they share a core operational backbone. Laudae, launched in 2016, catered to a bolder, sexier bride. Aesling followed in 2019 with minimalist, modern designs. The motivation wasn’t just creative—it was strategic.

“I started creating these other brands so that I could sell to different stores in the same city—or sell to the same store twice,” says Gaby. Bridal shops often require exclusivity zones, and distinct labels allowed her grow without geographic limitations.

Gaby believes the learning curve shortens with each new venture. “The more you do it, the more used to it you are—and the easier it is to manage.”

Woman is modeling a bridal gown.
Founder Gaby Bayona offers a variety of styles for brides to choose from, including this “Brigitte” gown from her Laudae brand. Gaby Bayona

Scaling slowly and building a loyal team

Hiring was never a sprint for Gaby. Her first hire was a seamstress she knew through her mom. The second was someone who asked to shadow her. Most of her core team started out working alongside her in her apartment—and have stayed ever since.

“I’ve always taken the approach of making things work for people,” she explains. “You can’t grow a business to any substantial size without having a really strong team.”

Now managing 40 employees, Gaby leans on a structured leadership team. She meets monthly with four core managers who each lead their own teams. “If I were to be hands-on with every single person, I just wouldn’t be able to do a good job managing that many people,” she says.

That said, she learned the hard way about maintaining boundaries. “I was very buddy-buddy with a lot of the people that I worked with…it made it so that I wasn’t able to properly manage people.” The experience taught her how to balance trust with clear expectations.

Staying local and sustainable

Many fashion brands outsource production to keep costs down. Gaby doubled down on Vancouver. Every dress is still made locally, which helps her team pivot fast, customize designs, and eliminate inventory waste.

“Local manufacturing has been a huge core part of my growth,” she says. Early on, fabric was expensive, so she learned to puzzle piece patterns to reduce waste—a practice she maintains to this day. “Yes, that does mean things take a little longer for us, but at least we’re not being as wasteful as some of the other fashion companies out there.”

Today, all Truvelle linings are made from recycled fabrics, and every dress is made-to-order. Scraps are donated to design schools or sold at a discount to local designers. “We just try to create in a way that is maximizing our fabric.”

Still, she’s realistic about the challenges of local production. “It is getting harder and harder to manufacture, and not just in Vancouver. The sewing trade is a bit of a dying art.” To future-proof, her team is exploring new ways to support and sustain the talent pipeline—including sponsorships for international sewers.

Creating unforgettable in-store and online experiences

Gaby knows that bridal gowns are typically a once-in-a-lifetime purchase—but one bride can influence a dozen others. The goal is to create unforgettable experiences. Appointments are relaxed, the lighting is soft, and stylists never pressure a sale.

“You want to make sure people just feel really confident and good in their decision,” she says. That mindset extends to social media, too. Instead of outsourcing to agencies, Gaby ran her own TikTok account at first to understand the platform. “When I first started TikTok, I found it really difficult to be able to manage and give insight in the way I’ve always been able to.”

Now, each brand has its own viral account, and online sales have never been higher. Gaby takes a hands-off approach with her team’s content. “If it’s something I don’t like and it’s working, I don’t interfere.”

Gaby Bayona turned a single sewing machine and a passion for dresses into four bridal brands, four stores, and a 40-person team—all without external investors or compromising her values. Her advice to entrepreneurs?

“Start it. Pivot. Be flexible. The quicker you start, the faster those early mistakes happen—and the faster you’re able to move on.”

To learn more about how Gaby is scaling her sustainable bridal fashion brands, catch her full interview on Shopify Masters.

Revamp Your Product Listings with Amazon’s Gen AI Technology: The Game-Changing Upgrade to Boost Sales!

Today marks another exciting milestone in our Generative AI journey with the launch of Enhance My Listing (EML), a powerful new capability that puts control in sellers’ hands to effortlessly maintain and optimize their existing product listings. Selling partners update their listings from time to time to ensure they are relevant, reflective seasonal trends, and appeal best to buyers. They’ve told us these updates can sometimes require substantial effort, so we wanted to simplify this process for them. Building on what we’ve learned from our listing-creation capabilities and from direct seller feedback, we’re introducing Enhance My Listing to save selling partners time, ensure the highest-quality-listings, and make it seamless for sellers to keep their product content current and compelling.

The path to Enhance My Listing began at the end of 2023 when we introduced Gen AI-powered capabilities to sellers who were creating product listings in Amazon’s store. Sellers can now simply describe their products in just a few words, upload a single image, or even provide a URL from their existing websites, and we generate Amazon-style titles and comprehensive product-listing attributes using customer insights and shopping data to ensure listings resonate with customers. Soon after, we rolled out these capabilities for bulk listing creation, enabling sellers to create multiple enriched listings by uploading a spreadsheet. Along the way, we’ve learned that sellers find these tools really useful and appreciate the added value that our Gen AI listings creation tools provide. Now, more than 900,000 Amazon selling partners have embraced these tools, with sellers accepting AI-generated content with little to no edits approximately 90% of the time. When sellers use our Gen AI tools to create listings, they see a 40% increase in overall listing quality, helping them create content that enhances customer engagement and boosts sales potential.

“We’re absolutely blown away by Amazon’s Gen AI listings tools,” says Michael and Cynthia Gore, who founded C&M Personal Gifts. Their small business specializes in personalized glassware and has been selling in Amazon for more than a decade. “The AI is wonderful, and it’s getting better with time. Now it creates detailed bullet points and descriptions and makes our 800+ listings more uniform. So far, we’ve created about 300 listings with the tool, and they’re more discoverable and shoppable than ever.”

We’ve seen great results and received positive feedback, but we also learned that sellers want to use these capabilities for more than just creating listings; they also want to leverage these tools for their existing listings. Our selling partners told us that keeping listings unique and relevant requires adaptation to customer preferences, for example, by adding new attributes, adjusting to retail trends, or updating listings to attract holiday shoppers.

“Amazon’s Gen AI tools pretty much rock,” says Jason Hunt of Campcraft Outdoors, a family-owned business in Kentucky that specializes in waxed canvas bags and outdoor gear for survival, bushcraft, and camping enthusiasts. “Listings used to take me an hour, but with Gen AI, I just upload photos and have content generated in under 15 minutes. I have listings I haven’t touched in years, so updating those without the manual hassle would be just what I need.”

To address this need, we created Enhance My Listing, which integrates seamlessly with the product listings tools that sellers already use today. The service is powered by Amazon Bedrock, allowing us to quickly evolve our Gen AI models based on the most current customer activity and engagement. We put these invaluable insights to work by generating timely, relevant recommendations for product titles, attributes, descriptions, and missing details, saving sellers from having to take on that research themselves. Maintaining discretion, sellers can review, customize, or decline these suggestions with a click, ensuring that listings reflect their expertise while benefiting from Amazon’s detailed knowledge.

“Optimizing our existing listings with Amazon’s AI tools would be incredibly helpful,” says Ryan Cramer, Gen-Y Hitch’s Amazon Channel Manager, whose company offers over 300 automotive hitch products. “Since I handle all our Amazon business myself, I could use this valuable time-saving tool to transform our technical product descriptions into more engaging, relevant content that draws in customers. This could be a game-changer—helping us reach even more buyers looking for great products—not just those who already know the complex automotive terminology.”

Enhance My Listing has begun rolling out to select U.S. sellers, with expanded availability planned in the U.S. in the coming weeks. We look forward to seeing how this tool helps our selling partners and to continue learning and innovating on their behalf.

Enhance My Listing is just the newest AI-powered tool we’ve created to help sellers streamline their businesses and improve their experiences selling in Amazon’s store. Read on to learn about what else we offer.

Project Amelia adds a personalized Amazon selling expert for every seller

Amazon released a generative AI assistant codenamed Project Amelia in beta to an initial set of U.S.-based sellers. Project Amelia delivers a personal Amazon selling expert that understands a seller’s unique business and provides personalized recommendations, insights, and information to help sellers thrive. As Project Amelia evolves, it will soon be able to recognize business opportunities and diagnose problems, developing key insights on how to grow revenue, optimize inventory, and resolve key issues, and in some cases will even offer to take actions on a seller’s behalf. Sellers can simply ask questions like, “How is my business doing?” and Project Amelia will provide instant and secure access to sales and business metrics, compare trends, and provide guidance. Always available from any page on Seller Central, Project Amelia stands at the ready to tackle strategy questions and provide unique insights tailored to each seller’s business needs.

Expanding generative AI product-listing capabilities to get more products in front of customers faster

In 2023, Amazon began dramatically reducing the time and effort required from sellers to create and manage high-quality product listings by leveraging the latest advances in generative AI. Sellers simply need to input a brief description, a URL from their own brand website, or just provide a product image and generative AI will create high-quality, comprehensive product listings that engage customers and help drive sales. More than 400K sellers globally have already used Amazon’s generative AI product listing tools, and later this year, we will expand on these capabilities by leveraging AI to help sellers create multiple listings at the same time. In the new bulk listing workflow, sellers can upload a spreadsheet containing a sparse set of listing details and let Amazon’s generative AI create rich titles, bullet points, and descriptions for multiple listings at once. These capabilities will help sellers create highly optimized detail pages and get more of their products in front of customers faster than ever before.

A+ Content automatically creates brand storylines that attract customers

Brands on Amazon are able to develop custom content like rich image carousels and comparison charts on their product detail pages. Called A+ Content, it allows them to better communicate their unique value proposition and brand story to customers. A+ Content can drive a sales lift of up to 20% for sellers, but historically, creating this type of high-quality content could require a lot of time and resources: photo shoots, drafting, design, testing, iterating, and so on. Now, brands can streamline the production of their A+ Content by using new generative AI capabilities to easily enhance their product detail pages, create more engaging and informative listings, and generate captivating and authentic lifestyle imagery that highlights their products.

With these powerful new AI capabilities, Amazon is enabling brands to capture the essence of their brand by inputting a few descriptive product terms they want to highlight, like “quality leather” or “versatile for any occasion,” and the tool will generate rich narrative content that highlights the product’s unique qualities. By uploading an image of their product, sellers can also generate captivating background imagery and scenes that bring their products to life and more effectively showcase their brand identity. With these new content creation solutions, even smaller brands that don’t have the in-house capabilities or agency support to create high-quality brand-themed imagery and messaging, can now easily develop impactful content that resonates with customers and increases brand awareness.

Personalizing product recommendations and descriptions for customers

Amazon is innovating with generative AI to personalize product recommendations categories and product descriptions on our website and in our shopping app. Based on a customer’s shopping activity, Amazon reviews the customers’ preferences to create personalized recommendations categories on our homepage and throughout the shopping journey, as well as provide personalized product descriptions that are more relevant to individual customers. For example, instead of offering customers “More like this,” we’re providing more specific recommendations, such as “Gift boxes in time for Mother’s Day” or “Cool deals to improve your curling game” based on a customer’s shopping activity. Or, if a customer regularly searches for gluten-free products, the term “gluten-free” may be added to a relevant product description to help the customer find the best product to meet their needs. This improvement is particularly useful for shoppers on mobile devices with limited screen space, helping sellers get their products in front of the right customers more effectively.

Sellers can leverage generative AI to create highly engaging video ads

If a picture’s worth a thousand words, then how much is a video? Creating video advertisements is an impactful way to connect and engage with customers. Amazon offers Video Generator, a new generative AI-powered tool that enables sellers using our advertising tools to create visually rich video content in a matter of minutes and at no additional cost. Using a single product image, Video generator instantly creates custom, AI-generated videos that showcase a product’s features. These videos leverage Amazon’s unique retail insights to vividly bring a product story to life in ways that are relevant to customers. Now sellers will be able to reimagine the limits of their creativity, while bringing shoppers a more engaging and informative advertising experience.

Leveraging best-in-class AI infrastructure to build long-term seller success

None of these advancements would be possible without Amazon Web Services’ (AWS) generative AI capabilities, including Amazon Bedrock. Foundational Models (FMs) are the building blocks of generative AI, and Bedrock’s fully managed service makes it easy to leverage leading FMs as part of building these amazing generative AI-based solutions.

These impactful new tools are the latest examples of how Amazon is leveraging generative AI to transform nearly every experience we know—including how we support independent sellers in creating thriving businesses by selling in our store. We’re super excited about the innovation and value that these new offerings provide for sellers, and we will continue to develop additional, innovative AI tools to further enhance the success of Amazon’s selling partners.

Unlock the Power of Multimodal AI: Your Ultimate Guide to 2025 – from Shopify

A humanoid robot hands its operator a lush red apple after he asks for something to eat. This isn’t science fiction—it’s a scene from a demonstration by Figure AI, flexing one of the latest capabilities of artificial intelligence (AI): multimodal AI.

When the robot handed its operator the apple, its multimodal models were interpreting multiple inputs: the voice command, the apple’s visual presence, and the operator’s visual presence. Humanoid robots are the flashiest use case for this technology, but multimodal AI also powers autonomous vehicles, interactive virtual characters, AI assistants, and search tools like Google Lens.

In ecommerce, multimodal AI enables visual search, augmented reality try-ons, and advanced customer support. Here’s what you need to know to unlock its potential for your business.

What is multimodal AI?

Multimodal AI refers to machine learning models built to intake, interpret, and process multiple forms of data simultaneously. These models can receive input and create output in different modalities—rather than being limited to just one type—including text, images, audio, video, numerical data, and sensor data like GPS or accelerometers.

For instance, given a text prompt and a source image, multimodal AI can generate a video, setting the image in motion or reinterpreting it (depending on the prompt).

Three defining characteristics of multimodal AI are:

  • Heterogeneity. This term describes diverse data types. For example, an AI-generated video output is different from the text input that prompted it.

  • Connections. Multimodal models create connections between different modalities. For example, Figure AI’s humanoid linked multiple pieces of sensor data: visual data (an apple), language (“apple”), and auditory cues (a verbal request) to form a coherent understanding.

  • Interactions. This refers to how different modalities respond to one another when brought together. In a self-driving car, the visual input of a stop sign interacts with the presence of an approaching intersection in its GPS input, reinforcing the decision to stop.

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Multimodal vs. unimodal vs. generative AI

Multimodal AI systems are capable of integrating multiple types of data simultaneously and creating multiple types of output. When given text prompts, audio, video, and images, a multimodal model can interpret, analyze, and respond to multiple inputs at once (provided the model is designed to handle those modalities)—much like how the human brain synthesizes what it sees, hears, and feels in real time. This versatility makes multimodal AI more accurate, agile, and intelligent than unimodal AI.

Unimodal AI is limited to understanding a single type of data, usually textual data or visuals. While still powerful—natural language processing and unimodal neural networks used in chatbots are strong examples—it lacks the holistic comprehension that multimodal systems offer.

Generative AI learns patterns from a vast dataset and uses them to generate new content. It can be either unimodal (like MusicLM, which generates music from text) or multimodal (like Chat GPT-4o). Multimodal generative AI models can generate visual content, translate between modalities, and respond creatively to real-world scenarios.

How does multimodal AI work?

Multimodal AI relies on three primary components to process multiple types of data simultaneously: the input module, fusion module, and output module.

Input module

The process starts with the input module, where raw data from various data types—textual data, customer service audio data, product images, and videos—are ingested and processed by unimodal neural networks. These networks are often built on large-scale transformer architectures, which are proficient at spotting patterns and relationships within sequences and specialized for their respective modalities. Collectively, they allow the AI system to interpret multimodal data, making it possible to interact across diverse inputs from multiple sources.

For example, a text model might predict missing words in a sentence, while a vision model can perform tasks like image inpainting to infer missing parts of an image.

Fusion module

The fusion module combines and aligns relevant data. The data is transformed into numerical representations—called embeddings—so that different modalities can communicate using the same language. This process involves translating words into tokens, images into visual embeddings, and audio into frequency-based features.

The fusion module aligns diverse data types either through early fusion, where embeddings from each modality are combined at the start, or late fusion, where they’re integrated after being processed independently. In early fusion, a model might learn what an apple looks like and how the word sounds—all paired with text, “apple.” Early fusion helps models develop a richer, more holistic understanding of the concept at hand.

Output module

After integrating the data, the output model uses the system’s underlying neural network—often a transformer decoder—to synthesize insights and produce responses. Responses vary widely but include generative content, predictions, or decisions.

To refine performance and reduce harmful outputs, models go through fine-tuning using methods like reinforcement learning with human feedback and red teaming (an adversarial testing exercise). This helps ensure the system performs well in real-world scenarios and responds with more accuracy, safety, and contextual awareness across all supported data modalities.

Examples of multimodal AI

  • Gemini
  • GPT-4o
  • Amazon StyleSnap
  • PathAI
  • Waymo

If you’re online in any capacity, you’re likely interacting with large multimodal models more often than you realize. Examples include:

Gemini

Google’s multimodal generative AI platform, Gemini, combines vision, audio, and text to complete complex tasks. It can, for example, describe a sales funnel diagram and accompanying video out loud—interpreting multiple visual inputs at once.

GPT-4o

OpenAI’s large multimodal model can perform tasks based on textual and visual prompts. For example, GPT-4o can generate an image of an action figure in your likeness by ingesting a text prompt describing your accessories and qualities (text modality) along with an attached photo (visual modality).

Amazon StyleSnap

StyleSnap is an AI tool that uses computer vision technologies—which can analyze and interpret user-uploaded images—and NLP to suggest fashion items. The intuitive ecommerce tool makes connections between uploaded photos and its exhaustive inventory of clothing items.

PathAI

PathAI supports diagnostics using multimodal AI models to interpret medical images, electronic medical records, and clinical data. For example, its PathAssist Derm tool helps doctors quickly identify skin malignancies, addressing a pressing dermatologist shortage and improving patient outcomes.

Waymo

Waymo’s self-driving cars integrate multiple sensors like cameras and radar for real-time driving decisions. Its end-to-end multimodal model reacts to sensor data like the visual cues of lane markers, radar-detected distances, and contextual map data to safely navigate dynamic environments.

Benefits and challenges of multimodal AI

One of the most compelling advantages of multimodal AI is its ability to generate rich, context-aware content across formats. These systems can craft videos from text prompts, narrate images, and deliver insights that blend language with visuals or sound.

Multimodal AI models interpret multiple data types simultaneously, enabling more human-like interactions and more accurate outcomes. In fields like health care, education, and autonomous systems, combining data from diverse sources enhances decision making and problem solving.

However, building robust multimodal systems poses significant challenges. Aligning data from disparate modalities—like matching a voice clip with a facial expression—can be technically complex. Ensuring the model fully grasps the semantics of each data type and how they connect is equally difficult. Reasoning across diverse data sources, especially when interpreting things like intent or emotion, remains an evolving capability.

And then there’s the issue of data: Training these models requires high-quality, representative, and ethically sourced multimodal data—something not always readily available. Missing data, biased samples, or poor data quality can all weaken performance and trust in the system.

What is multimodal AI FAQ

What does multimodal in AI mean?

Multimodal AI refers to systems that simultaneously process and understand information from multiple data types, such as text, images, audio, and video.

Is ChatGPT a multimodal model?

Yes, the latest versions of ChatGPT, like GPT-4o, are multimodal AI models capable of interpreting both text and images.

What is multimodal conversational AI?

Multimodal conversational AI combines text, voice, visuals, or other inputs to enable richer, more human-like interactions with users.

What is a multimodal example?

An example of multimodal AI is a virtual assistant that analyzes spoken language and facial expressions to understand and respond to a user.

Revolutionizing AI in Saudi Arabia: Amazon and Humain’s Unstoppable $5B Team-Up

Amazon Web Services (AWS) and HUMAIN, Saudi Arabia’s newly created company responsible for driving AI innovation across the Kingdom and globally, today announced plans to invest $5 billion-plus in a strategic partnership to build a groundbreaking “AI Zone” in the Kingdom. This first-of-a-kind AI Zone will bring together multiple innovative capabilities, including dedicated AWS AI infrastructure and servers with world-class semiconductors, UltraCluster networks for faster AI training and inference, AWS services like SageMaker and Bedrock, and AI application services such as Amazon Q to advance Saudi Arabia’s mission to be a world leader in AI.

AWS previously announced and is currently building an AWS infrastructure region in Saudi Arabia that will become available in 2026. Amazon is investing US$5.3 billion (approx. 19.88 billion Saudi riyal) in Saudi Arabia to develop this new region for AWS. The new AI Zone announced today is an additional investment to grow global and local demand for advanced AI services in the Kingdom, and is part of AWS’s long-term commitment to bring its world-class infrastructure and services to Saudi Arabia.

This collaboration aligns with Saudi Arabia’s Vision 2030 and builds upon the Kingdom’s pledge in 2024 to invest in building an AI-powered economy, representing a significant step towards realizing Saudi Arabia’s ambitions to become a global AI leader. AWS will bring to Saudi Arabia its advanced server and network infrastructure capabilities, as well as its artificial intelligence and machine learning services—including Amazon SageMaker AI, Amazon Bedrock and Amazon Q, fully managed services for building and scaling generative AI (genAI) applications. With Amazon Bedrock in Saudi Arabia, businesses and government organizations can access high-performing models from leading AI companies to develop genAI applications with security, privacy, and responsible AI. Amazon Q is the world’s most capable coding assistant, and also enables organizations to build genAI-powered assistants to answer questions, provide summaries, generate content, and complete tasks based on enterprise data.

Through this collaboration, HUMAIN plans to develop AI solutions using AWS technologies for its end customers. Further, HUMAIN will work with AWS on the development of a unified AI agent marketplace, simplifying the discovery, deployment, and management of AI software for the Saudi Arabia government. The collaboration also intends to spur the growth of Large Language Models (LLMs), including Arabic Large Language Models (ALLaM), while spearheading wide adoption of AI in organizations and industries across the Gulf Region and beyond.

Key sectors, such as government, energy, healthcare, and education, will be able to accelerate their transformation, envisioning AI-powered tools that can personalize learning experiences for students, help provide early disease diagnoses for patients, and unleash productivity across core upstream and downstream processes for government administration. Use cases such as these will be accelerated via the AWS Generative AI Innovation Center, in partnership with HUMAIN, enabling customers—from the fastest-growing startups and largest enterprises, to government agencies—to amplify genAI roadmaps and workloads, leading to equitable and efficient delivery of vital services for greater societal impact.

“We thank AWS for doubling down on their long-term partnership with the Kingdom. This new collaboration with HUMAIN lays the foundation for the intelligent era, accelerates our innovation momentum, grows our talent, and reinforces Saudi Arabia’s position as a global partner of choice in the age of AI,” said His Excellency Eng. Abdullah Alswaha, Minister of Communications and Information Technology.

Fueling Saudi Arabia’s vibrant startup sector with AI-powered innovation

AWS and HUMAIN will also work together to advance an AI-powered startup sector in the Kingdom, providing access to the broadest and deepest set of cloud technology tools and programs, including AWS Activate, and helping Saudi Arabia’s most ambitious founders and entrepreneurs scale their businesses.

AWS has helped more than 330,000 startups globally bring their business ideas to life. Its scalable, secure, low-cost cloud solutions and AI-powered services, combined with HUMAIN’s deep support network, will help supercharge Saudi’s startup scene. According to MAGNiTT, Saudi Arabia startups secured US$750 million venture capital funding in 2024, the highest share of capital deployed across the Middle East and North Africa last year.

“This collaboration to build an AI Zone in Saudi Arabia will enable innovations across all industries using AWS’s advanced AI offerings, and reflects our commitment to support Saudi Arabia’s Vision 2030,” said Matt Garman, CEO, Amazon Web Services. “Together, we will empower customers with cost-effective and secure cloud technologies, fuel innovation and economic growth across the nation, and enable HUMAIN to appeal to customers globally.”

Accelerating talent development for a vibrant Saudi tech industry

As part of its long-term commitment to fast-track cloud adoption in Saudi Arabia, AWS is scaling its training and certification programs focused on genAI skills-building in line with the Kingdom’s Vision 2030 digital transformation goals. Working with Saudi Arabia’s Public Investment Fund (PIF), AWS has committed to train 100,000 citizens from the Kingdom in cloud computing and genAI, focusing on the two newest AWS genAI certifications: AWS AI Practitioner and AWS Machine Learning Engineer Associate Certifications. Training will be delivered by the Amazon Academy. Launched in 2023, the Amazon Academy is the largest talent development program of its kind in the Middle East. It provides transformative training and certifications, free of cost to participants, to elevate in-demand competencies and equip Saudi talent for jobs of the future. The program is designed to empower the next generation of Saudi youth, entrepreneurs, and professionals at any stage of their career to achieve success across in-demand skills, such as cloud computing, logistics, and leadership.

In addition, to help accelerate Saudi Arabia’s goal of empowering women to increase participation in the workforce, AWS in 2024 also launched an upskilling program, “AWS Saudi Arabia Women’s Skills Initiative,” in partnership with Skillsoft Global Knowledge. AWS has committed to train 10,000 women on AWS Cloud Practitioner Essentials, at no charge, through classroom trainings with AWS-certified professionals.

Supercharging HUMAIN’s AI ambitions

Saudi Arabia is forecast to hold the lion’s share of AI’s estimated economic impact across the Middle East in the coming years. According to PwC, AI will contribute $130 billion to Saudi’s economy by 2030, comprising more than 40 percent of the estimated $320 billion of AI value for the entire Middle East.

The Kingdom is also at the forefront of a regional drive to transform both public sector services and enterprises with AI-powered innovation built in the cloud. PwC estimates that nearly 70 percent of Middle East companies plan to migrate most of their operations to the cloud within the next year, while a 2023 report by Telecom Advisory Services predicts public cloud adoption to unlock US$733 billion in economic value by 2033 across the Middle East and North Africa.

“HUMAIN’s partnership with AWS is a pivotal moment in Saudi Arabia’s journey to become a global leader in AI,” said Tareq Amin, CEO of HUMAIN. “By leveraging AWS’s world-class cloud infrastructure and AI expertise and HUMAIN’s full-stack AI capabilities, we are creating an offering that will attract global investment and talent, thereby driving our digital transformation agenda forward.”

Unlock the Power of Small Business Rewards: Types + Tips to Launch in 2025 – From Shopify Experts!

In today’s competitive corporate landscape, strong customer loyalty can mean the difference between a surviving business and a thriving one. What’s one way to bring customers in and have them come back for more? An enticing rewards program.

Small business rewards programs can be a cost-effective way to build trust with customers and encourage repeat business. Read on for a breakdown of how small business rewards programs work, and a step-by-step guide to designing your own.

What is a small business rewards program?

A small business reward program is a type of loyalty program that incentivizes specific customer actions with redeemable discounts, cash back, or free products. For example, a business might reward customers for making purchases, referring new customers, or publishing content about the brand. After taking enough of these actions and accumulating a certain number of points, the customer can redeem the corresponding reward. The primary goal of a rewards program is to increase purchases and/or engagement with the brand.

Reward loyalty everywhere customers shop

Only Shopify’s integrated loyalty apps let customers collect and redeem loyalty rewards when shopping with you both online and in store—no complicated workarounds required.

Types of small business rewards programs

  • Punch card programs
  • Referral programs
  • Points programs
  • Subscription programs

Small business rewards programs are flexible—you can reward customers for anything you want them to do, using anything they value enough to do it. Here are four popular options to get you started:

Punch card programs

Punch cards are a classic way to encourage repeat business. They typically look like business cards and display several icons, like 10 tiny coffee cups or 25 hot dogs. Customers earn a punch or a stamp for each purchase, and when the card is full, their next purchase is free.

Consider punch cards if your business model relies on repeat purchases of relatively inexpensive products or services. Bakeries, ice cream parlors, and oil change shops are good candidates, while mattress stores are not. Punch cards are particularly popular with brick-and-mortar shops, but you can also use an ecommerce app to add one to your online store.

Referral programs

Referral programs reward existing customers for recommending your business to others. When a potential customer makes a purchase, the referring party earns a reward, like store credit, a free item, a discount, or a specific number of loyalty points.

Referral programs help small business owners quickly build a customer base. They also improve relationships with current customers and keep your company top of mind, encouraging repeat business. Consider thanking referring customers through email or social media shoutouts, or even in person if you run a services business, to maximize program benefits. Personal acknowledgments make customers feel appreciated and encourage future referrals.

Points programs

Points programs are a versatile and flexible choice for small businesses. You decide how customers earn points, what they’re worth, and how they’re redeemed. You can also adjust incentive structures as your needs change, shifting focus without introducing customers to an entirely new program.

Here are example activities you might reward:

  • Referring a customer
  • Making a purchase
  • Purchasing a specific product or product type
  • Subscribing to a service
  • Tagging your company on social media channels
  • Reviewing your company on a review site
  • Signing up for email marketing newsletters
  • Completing surveys
  • Providing testimonials or product photos
  • Signing up for a free trial

Design your redemption system to meet your needs. You might allow customers to trade in points for store credit, exclusive discounts, or free items, or provide VIP rewards like free samples, instant access to sales, or special deals to customers who reach a certain number of points. If you choose a non-redemption strategy, customers continue to accrue points to access more personalized experiences and increasingly exclusive perks.

Points programs allow business owners to adjust terms as business needs and available resources change. If you received an over-shipment of a certain product type, you can add it to your rewards shop or distribute it as a VIP gift. If a product recall issue generates a batch of negative online reviews, you can add review points to your incentive structure or increase the point value assigned to that action to counteract your negative reviews.

Subscription programs

Subscription ecommerce businesses use rewards programs to encourage sign-ups and boost brand loyalty. They may also discourage customers from cancellation: It’s one thing to stop paying for something, but another to give up free perks.

Claudia Snoh, the founder and CEO of the subscription coffee concentrate company Kloo, shared the details of her company’s program on an episode of the Shopify Masters podcast. Kloo automatically enrolls all subscription customers in its program, The Cupper Club. The club offers members the following benefits:

  • Free shipping
  • Seasonal gifts every few months, including free samples of new product launches
  • First invitations to exclusive Kloo events like coffee cuppings
  • Access to member-only products and merchandise
  • Guaranteed best pricing on all Kloo products
  • Early access to new product drops
  • Priority concierge support

“The program is designed to reward our most loyal customers and create a community of coffee enthusiasts who appreciate the sommelier experience we provide,” Claudia says, noting the program’s effectiveness as a relationship-building tool. “The Cupper Club has created strong brand affinity and loyalty. When we send out seasonal gifts and exclusive offers, we regularly receive personal thank you emails from members,” she says, adding, “These moments of connection have transformed many customers from casual buyers into genuine brand advocates.”

The Cupper Club has also helped Kloo build its subscriber base. “The program has become an effective conversion tool, helping us transition one-time purchasers into long-term subscribers who experience the full value of our brand,” says Claudia.

How to create a small business rewards program

  1. Set goals
  2. Identify actions
  3. Build an incentive structure
  4. Launch your program and monitor performance
  5. Adjust strategy and plan for the future

Small business rewards programs are infinitely customizable, so where do you start? Kloo took inspiration from competitor programs. “As we developed the concept, we studied successful loyalty programs from other brands, drawing particular inspiration from Flamingo Estate’s Estate Membership,” she says. This strategy supports the brainstorming process and provides helpful inspiration—so long as you don’t copy your competitor’s approach exactly, Claudia says.

Here’s a five-step framework to help you design and run a small business rewards program that works and feels unique to you:

1. Set goals

Loyalty program goals are typically a subset of a business’s overall marketing and sales goals, so review yours to identify your areas of greatest need. Common rewards program goals include boosting revenue, improving brand reputation, and attracting new customers.

Kloo designed The Cupper Club’s program to build relationships with its subscription customers. “We began our rewards program journey by focusing on a core question: How could we meaningfully show appreciation to the loyal customers who supported us during our soft launch phase?”

This customer-first thinking guided their entire approach because it came from a genuine desire to show appreciation to early customers who believed in Kloo before the brand was fully established.

2. Identify actions

Next, identify customer actions that support your goals. Dig into sales data, target audience demographics, and market research to get specific. If your goal is to boost profits, you might ask yourself the following questions:

  • Do you need to increase sales volumes across the board, or are you only struggling to move your higher-margin products or services?
  • How’s your market penetration? How does it compare to your competitors’?
  • Do you earn repeat visits from existing customers? How much do they spend, and are those figures consistent with industry benchmarks?
  • What actions or behaviors indicate a high-value customer for your business? Do you earn more from customers coming from specific sources?
  • What are your biggest sales and marketing expenses? Could a rewards program be a cost-effective alternative to pricey campaigns?

Use these questions to figure out what you want your customers to do. A company with strong retention rates might reward referrals, for example, and a company with a content shortage might reward customers for participating in user-generated content (UGC) campaigns.

Kloo focused on habituating customers to use its product based on data showing that customers in its market form long-term brand attachments. “We recognized that coffee is a product with high lifetime value potential,” says Claudia. “Once customers connect with a coffee they love, they tend to remain loyal over time.”

3. Build an incentive structure

Create an incentive structure that encourages the actions you choose, aligning the value of the reward with the value of the action for your business. Ratings and reviews tend to earn small discounts or free samples, for example, but successful referrals can earn customers hundreds of dollars from some business types.

Consider offering rewards that serve your business goals. If you’re struggling to generate interest in a new product line, offer a product-specific discount to VIPs or allow customers to redeem points for a free trial of the product type.

Kloo focuses on perks its members actually want. “We created The Cupper Club to reward subscribers and create additional incentives for customers to engage with our brand long term,” says Claudia. “The structure was designed to offer meaningful benefits that coffee enthusiasts would genuinely value, like seasonal gifts, first look access to new products, and exclusive events.”

4. Launch your program and monitor performance

Launch your program and promote it to customers. Encourage signups or automatically enroll customers, depending on your goals. Elective signup lets you educate new members on program terms and allows you to position your program as exclusive. Automatic enrollment maximizes participation and creates an opportunity to surprise customers with benefits they’ve already earned.

Once you’re up and running, monitor performance by tracking targeted metrics with your analytics software. Look for outcomes beyond your targeted metrics, too. Although The Cupper Club was designed to reward current subscribers, it ended up attracting new customers to the brand.

“Potential customers frequently reach out specifically to learn more about our rewards program, and these inquiries have directly contributed to increased subscription sign-ups,” Claudia says. “The program has become an effective conversion tool, helping us transition one-time purchasers into long-term subscribers who experience the full value of our brand.”

5. Adjust strategy and plan for the future

Use your metrics to evaluate performance and identify any issues. If you’re not seeing results, ask yourself the following questions:

  • Are our customers aware of our program?
  • Have we selected the appropriate actions for our business and marketing goals?
  • Are we offering rewards that people want?
  • Are reward values sufficient for the effort the action requires?
  • Are customers attempting to use our program? If so, what barriers to entry do they face?

Survey or interview your customers for more accurate insights, and adjust your strategy based on what you learn.

Once you’ve ironed out the kinks, give yourself permission to think bigger. “Looking ahead, our vision is to evolve The Cupper Club into a more sophisticated points-based rewards system similar to airline miles programs,” Claudia says. “We’re excited about the potential to gamify the experience, creating even more engagement opportunities while giving our most loyal customers increasing value as they continue their journey with us.”

Claudia also cautions business owners against scaling their programs too quickly. “Just because fast growth is celebrated and appears sexy doesn’t mean it’s the right approach for your specific situation,” she says. “Sometimes, the patient, deliberate path leads to more sustainable success and greater fulfillment.”

Small business rewards program FAQ

How do I create a rewards program for my small business?

To design your small business rewards program, start by setting goals, identifying customer actions, building an incentive structure, launching your program, and adjusting your strategy to optimize results as you go.

Do loyalty programs work for small businesses?

Yes. Loyalty programs are a cost-effective way to promote your business. Use them to quickly build your client base, increase brand awareness, and boost revenue.

What is the difference between a loyalty program and a rewards program?

A rewards program is a type of loyalty program that encourages specific customer actions. While loyalty programs focus on long-term customer loyalty, rewards programs focus on actions that benefit the business in the near term.

Crush Your Team Goals: A Guide to Setting Powerhouse Goals for Success in 2025 with Shopify!

It takes more than 14 different instruments to play Beethoven’s Symphony No. 9. Performing this complex piece of music requires a lot of behind-the-scenes teamwork. Groups of musicians start working together long before the conductor assembles the entire orchestra. If even one of the instrument sections doesn’t prepare and ultimately play their part, the entire performance will suffer.

Like an orchestra, a business is the sum of its parts. Businesses thrive when each employee, team, and department completes their work to the best of their abilities. Just as musicians all work toward the same performance, teams work toward the same overall business goals. While smaller goals and key performance indicators may differ across teams, in general, team goals create structure, alignment, and a shared vision. Explore why team goals matter and learn how to set them.

What are team goals?

Team goals are a set of clear, defined objectives applied to a specific group within a company. Strong goals provide structure and motivation—they tell employees what they need to accomplish and provide clear benchmarks for success. Strong goals also encourage accountability by making a clear statement about team performance and expectations. Team leaders typically set goals after reviewing company objectives and collecting input from team members.

Companies need high-functioning teams to achieve success. Many common, high-level organizational goals—such as increasing sales revenue or improving customer satisfaction ratings—require work from multiple departments. Improving customer satisfaction ratings, for example, might involve customer service, marketing, and product teams. Setting team-specific goals helps ensure that every part of the organization is aligned and working toward the same larger targets.

Types of team goals

  • Performance goals
  • Collaborative goals
  • Project-specific goals

Team goals can serve a variety of purposes, from establishing performance benchmarks to improving processes. Here’s how different types of team goals can help your employees achieve success:

Performance goals

Performance goals are measurable objectives tied to team or company initiatives. These typically have a quantitative component, so establishing a clear target makes it easier for team members to track progress against performance goals.

For example, an ecommerce marketing team could set a performance-based goal to increase email subscribers by 5% by the end of Q1. Team members can track progress by periodically checking subscriber growth during the quarter. If a mid-February check-in shows 1% growth up to that point, the team might decide to try a new approach or adjust the goal.

Collaborative goals

Collaboration goals are process-based goals designed to improve communication and teamwork. These goals help you establish efficient workflows that make it easier for team members to reach their other targets.

An ecommerce engineering team, for example, could set a goal to develop a clear reporting process that provides regular updates on project statuses. Sharing this information might help team leaders spot projects that are falling behind so they can step in to remove roadblocks or provide additional resources, which in turn will help the whole team stay on track. Collaborating on this goal allows multiple viewpoints to fully capture all necessary elements for a functional reporting process while sharing the actual workload of building out the process.

Project-specific goals

Project-specific goals are tied to initiatives. They’re designed to keep projects on track and can be either collaborative or performance-based. While overarching team goals are often developed at the beginning of the year or quarter, project-specific goal-setting may occur on a rolling basis as initiatives launch.

A performance-based project-specific goal could be: “Drive 1,000 visitors to a specific landing page.” A collaborative project-specific goal, on the other hand, could look like: “Partner with engineering to curate products and develop shoppable landing pages.”

How to set team goals

  1. Align with company goals
  2. Identify objectives
  3. Work with your team
  4. Use SMART team goals
  5. Share goals
  6. Monitor progress
  7. Make adjustments

1. Align with company goals

Start by reviewing your business goals and considering the role your team can play in reaching them. Organizational objectives are often very broad; an example might sound like “increase average order value by 5% by the end of Q2.” An overarching target like this can serve as a guiding light for incremental team goals.

2. Identify objectives

Businesses often work with OKRs—objectives and key results—to structure team targets that build up to larger company goals. OKRs are a two-part tool. The first portion—the objective—clarifies what your team will do. The second half—key results—addresses how you will approach and measure the objective.

Here are two examples of OKR structure:

  • Team objective 1: Increase brand awareness.

  • Key results 1: Increase social media engagement by 5%.

  • Team objective 2: Improve customer loyalty.

  • Key results 2: Increase repeat purchasing behavior by 10%.

OKRs lay the groundwork for strong goal creation. Once they are established, team leaders can develop specific, relevant goals to support a business’s primary objectives.

3. Work with your team

Goals will have a direct impact on your team members; they determine what your employees spend their time on. Team participation can help generate ideas and drive employee buy-in. Consider hosting a brainstorming session to get your team involved in the goal-setting process. Start by sharing OKRs and requesting feedback. Ask employees to reflect on how your team can contribute to broader company goals.

Remember that certain goals may not apply to your team—a goal of increasing employee job satisfaction, for example, might not require work from the product development team.

4. Use SMART team goals

Setting achievable, measurable goals is crucial for team success. Overly ambiguous or vague goals can harm morale; if employees feel that their goals are unreachable, they may become disengaged. The SMART framework can help you create high-quality goals. SMART is an acronym that stands for specific, measurable, attainable, relevant, and time-bound. Each one of your goals should satisfy all of these criteria.

5. Share goals

Once you’ve developed a strong set of goals, share them with your team. Communicate expectations and make space for feedback. Confirm that each team member understands the team goals and how they connect to their personal goals. Ask your team what they need to achieve these goals. Creating shared resources to help team members keep track of progress and deadlines can help keep team goals top of mind.

6. Monitor progress

Keeping track of your progress can help your team accomplish its goals. Teams typically have multiple objectives—they may have several types of goals with different KPIs and deadlines. It can be easy to lose track of deadlines without regular check-ins, especially when it comes to long-term goals.

You might use a project management tool to track goals or dedicate a portion of team meetings to progress updates to keep everyone on track. Take time to celebrate achievements and show appreciation for your team as they make progress on your goals.

7. Make adjustments

Team goals aren’t set in stone. You may need to tweak your goals in response to current events, shifting corporate priorities, or team turnover. Leaders may also make adjustments if it’s clear that initial goals were unrealistic or if the team exceeds a target far before the deadline.

Team goals FAQ

What are team goals?

Team goals are a set of defined objectives or targets for a specific set of employees. Team goals are more focused than broad business objectives. While company goals define expectations and corporate direction, team goals describe the work that a certain team will do to help the company achieve success.

What are SMART goals?

SMART stands for specific, measurable, attainable, relevant, and time-bound. Using the SMART goals structure helps leaders develop reasonable, effective team goals that can be evaluated objectively.

What’s an example of a team goal?

Team goals can be performance-based or process-based. A performance-based team goal could be “Increase page load time by three seconds by the end of Q1” or “Increase March sales revenue by 3% month over month.” A process-based or collaborative goal might look like, “Reduce project turnaround time by 5% by next quarter” or “Hold regular team-building activities to support employee satisfaction.”

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