As marketers and creators, we put so much effort into our visual content. But what happens after we hit "publish"? We track likes and clicks, but we often miss the full story of how people are truly interacting with our images. Computer vision changes that. It allows us to finally close the gap between a person seeing something they love and being able to act on that inspiration immediately. It's the technology that makes a photo on a social feed instantly shoppable or turns a magazine ad into an interactive experience. We'll explore the key computer vision marketing applications that are reshaping this journey.
Key Takeaways
- Understand Your Audience Visually: Go beyond simple metrics to see what your customers see. Computer vision helps you analyze the actual content of images they engage with, giving you powerful insights into their aesthetic tastes and real-world needs.
- Make Every Image a Starting Point: Turn passive viewing into active engagement by making your visual content interactive. This creates a direct and seamless path from inspiration to purchase, allowing customers to act the moment they feel interested.
- Use Data to Refine Your Creative Strategy: Replace guesswork with evidence by using computer vision to analyze which visual elements perform best. This allows you to make smarter decisions about everything from color palettes to product placement, ensuring your creative work connects effectively.
What is Computer Vision Marketing?
Think of computer vision as giving computers the ability to "see" and understand images and videos, just like we do. It's a type of artificial intelligence (AI) that processes visual information to identify objects, people, and even context within a scene. When you apply this to marketing, you get a powerful way to connect with your audience on a visual level. Instead of just guessing what your customers are interested in based on clicks or keywords, computer vision marketing helps you understand what they're looking at, how they might be feeling, and what they're likely to want next based on the visual content they engage with.
This technology moves beyond simple analytics. It allows you to create ads that are more relevant and campaigns that are more creative. For example, a brand can analyze user-generated content on social media to see how people are using their products in real life, gathering insights that would be impossible to find otherwise. But the real magic happens when you use it to create new, interactive experiences. Imagine a customer seeing a picture of a product they love in a magazine or on a billboard and being able to scan it with their phone to buy it instantly. That's the kind of direct engagement that computer vision in advertising makes possible, turning any image into a gateway for action. It transforms passive viewing into active participation.
How Does Computer Vision Work?
So, how does a computer learn to see? It all comes down to special programs called machine learning models. These models are trained on millions of images, learning to recognize patterns, shapes, and objects. Think of it like teaching a child to identify a cat by showing them lots of pictures of different cats. The system uses techniques like pattern recognition to find familiar elements within a new image.
For marketers, this means the technology can analyze the photos you share or interact with online to suggest products that are a perfect fit for you. If you post a photo from a hiking trip, you might start seeing ads for outdoor gear. The system identifies the mountains, trees, and hiking boots in your picture and connects them to relevant products, creating a highly personalized ad experience.
The Power of AI and Machine Learning
Computer vision is a key part of the broader field of Artificial Intelligence, and its capabilities are fueled by machine learning. Instead of being programmed with specific instructions for every possible image, machine learning allows computers to learn from data and improve over time. This is why AI computer vision systems are becoming so incredibly accurate at identifying everything from brand logos to specific facial expressions.
As this technology continues to evolve, it will open up even more creative possibilities. Soon, computer vision might be able to understand a person's emotional reaction to an image or video, allowing for truly empathetic marketing. It will also work with other AI tools to generate unique visuals tailored to each individual viewer. This power isn't just for large corporations; it's becoming more accessible, empowering creators and businesses of all sizes to build more meaningful connections with their audiences.
How Marketers Use Computer Vision
Computer vision is changing how brands connect with us. It's not just a complex technology for scientists; it's a practical tool that marketers are using to make their content more engaging and their strategies more effective. At its core, computer vision gives computers the ability to see and interpret the world through images and videos, just like we do. This opens up a whole new playbook for creating marketing that feels intuitive, helpful, and deeply personal.
Instead of just pushing out static images, marketers can now use computer vision to understand what's in a photo, how people react to it, and even turn that image into a direct path to a product. It's about closing the gap between seeing something you love and being able to act on that inspiration immediately. From making a photo on your social feed instantly shoppable to ensuring the product that arrives at your door is perfect, computer vision is working behind the scenes. Let's look at five key ways this technology is reshaping the marketing landscape.
Make Products Instantly Shoppable with Visual Search
Imagine scrolling through your favorite blog and seeing a picture of a chair you absolutely love. Instead of trying to describe it in a search bar ("vintage-style green velvet armchair"?), you could simply use the picture to find it, or something very similar, online. That's the power of visual search. This technology allows customers to use an image as their search query, creating a seamless path from inspiration to purchase. For marketers, this is a game-changer. It removes friction and helps customers find what they want faster. By making your product images recognizable to visual search engines, you can attract highly motivated buyers who already know what they're looking for.
Understand Customer Behavior
Marketers have always used data to understand their audience, but computer vision offers a much deeper level of insight. It can analyze how customers interact with visual content, tracking things like where their eyes focus first, how long they look at a specific part of an image, and what visual elements trigger an emotional response. This information is gold. It helps you move beyond basic metrics like clicks and impressions to truly understand customer behavior. By knowing which images and videos capture attention most effectively, you can refine your creative strategy, ensuring your campaigns feature visuals that genuinely connect with your audience and encourage them to engage.
Personalize Your Marketing
Generic marketing messages are becoming a thing of the past. Customers now expect experiences that are tailored to their specific interests, and computer vision is a powerful tool for delivering that personalization. By analyzing the images and videos a user interacts with, marketers can get a clear picture of their preferences. For example, if someone frequently likes and shares photos of minimalist home decor, computer vision can help identify them as a great candidate for ads featuring a new line of Scandinavian-inspired furniture. This allows for smarter ad targeting that feels less intrusive and more like a helpful, relevant recommendation.
Adjust Pricing in Real-Time
Staying competitive requires knowing what the market is doing at all times. Computer vision automates this process by allowing businesses to monitor competitor pricing with incredible speed and accuracy. Specialized software can scan competitor websites, promotional emails, and even photos of in-store displays to extract pricing information. This data can then be used to inform a dynamic pricing strategy, where your own prices are adjusted in real-time based on market conditions, demand, and competitor actions. This ensures your pricing remains attractive to customers while protecting your profit margins in a fast-moving market.
Protect Your Brand and Product Quality
Your brand's reputation is one of your most valuable assets, and it's built on the promise of quality. Computer vision plays a crucial role in upholding that promise. On the production line, AI-powered cameras can inspect products for defects with a level of precision that surpasses human ability, ensuring every item meets your standards. But brand protection extends online, too. Computer vision can scan the web for counterfeit products or unauthorized uses of your logo and brand imagery. By quickly identifying these threats, you can take action to protect your brand integrity and ensure that customers always have a positive and authentic experience with your products.
Why Use Computer Vision in Your Marketing?
So, why should you bring computer vision into your marketing strategy? Think of it as gaining a new sense. For years, marketers have relied on clicks, keywords, and demographic data to understand their audience. While useful, this data only tells part of the story. Computer vision lets you see what your customers see, understanding their world through the images and videos they interact with every day. It's about moving beyond abstract numbers and connecting with people on a visual, intuitive level. This technology helps you answer crucial questions: What visual trends are capturing my audience's attention? How do they really feel about my product visuals? Are my ads showing up in the right visual contexts?
By analyzing images and videos, you can gather rich, contextual data that was previously out of reach. This allows you to create marketing that feels less like an interruption and more like a helpful, relevant conversation. It's the difference between showing a generic ad for a couch and showing an ad for the perfect-sized, pet-friendly sectional to someone who just shared a photo of their new apartment and their golden retriever. This level of understanding helps you build stronger relationships with your customers, create more effective campaigns, and ultimately, drive better business results. It's a powerful way to bridge the gap between your brand and your audience in a visually-driven world.
Create a Better Customer Experience
At its core, great marketing is about creating a fantastic customer experience. Computer vision helps you do just that by making every interaction more personal and seamless. Imagine a customer scrolling through their social feed and seeing a photo of an influencer wearing a jacket they love. Instead of having to leave the app, open a browser, and search for it, they can simply scan the image to buy it directly. This is the kind of frictionless experience that turns a passing interest into a sale. It also powers features like AR "try-ons," where customers can see how a shade of lipstick or a pair of glasses looks on them without ever leaving home. These interactive experiences make shopping fun and give customers the confidence to make a purchase.
Get More From Your Marketing Budget
Every marketer wants to make their budget work harder. Computer vision is a key tool for making that happen by ensuring your message reaches the right people in the right context. By analyzing the visual content someone engages with, you can serve ads that are incredibly relevant to their current interests. For example, if someone is watching videos about home renovation projects, computer vision can identify that context and serve them ads for paint or power tools. This precise targeting means you're not wasting money on irrelevant impressions. When your ads are more relevant, they're more effective, leading to higher engagement and a better return on investment for your advertising spend.
Make Smarter Decisions with Data
Guesswork has no place in a modern marketing strategy. Computer vision provides the hard data you need to make smarter creative decisions. It can analyze thousands of images to tell you which visual elements resonate most with your audience. You can learn what colors catch the eye, which product angles get the most engagement, and how long people look at a specific part of an image. This information is gold for your creative team, helping them produce visuals that are practically guaranteed to perform well. This data-driven approach allows you to refine your brand's visual identity and consistently create content that your audience loves.
Gain Real-time Insights
The digital landscape moves fast, and the ability to react quickly is a major advantage. Computer vision can provide instant feedback on how your visual campaigns are performing. You don't have to wait weeks for a campaign report to know if something is working. You can monitor engagement as it happens and make adjustments on the fly. For instance, if you notice a particular ad image isn't getting the attention you expected, you can get immediate insights into why and swap it for a better-performing alternative. This agility allows you to optimize your campaigns for maximum impact and stay one step ahead of the competition by responding to market trends in real time.
Understand Customer Emotion
Beyond clicks and conversions lies a deeper metric: emotion. How does your marketing make people feel? Computer vision is beginning to help us answer that question. By analyzing facial expressions or comments associated with images, this technology can perform a kind of visual sentiment analysis. It can help you gauge whether your creative is sparking joy, curiosity, or inspiration. Understanding the emotional impact of your marketing is crucial for building a strong, lasting brand connection. When you know how your visuals resonate emotionally, you can craft campaigns that don't just sell a product but also build a loyal community around your brand.
Essential Tools for Computer Vision Marketing
So, you're ready to put computer vision to work in your marketing. The next step is finding the right tools to make it happen. Think of these tools as the bridge between a cool concept and a real strategy that gets results. They are what allow you to translate raw visual data—like images and videos—into actionable insights about your customers and campaigns.
The right tech stack can help you do everything from making your product photos instantly shoppable to understanding exactly which visual elements grab your audience's attention. Some tools specialize in one area, like visual search, while others offer a more integrated solution. For example, a platform like IRCODE combines image recognition with analytics and interactive capabilities, turning a single image into a complete marketing experience. As you explore your options, think about which functions will best support your specific goals. Below are the key categories of tools you'll want to consider for your marketing toolkit.
Image Recognition Platforms
At its core, computer vision marketing relies on image recognition. These platforms use Artificial Intelligence (AI) to help computers "see" and understand the content of your images and videos, just like a person would. For marketers, this is incredibly powerful. It allows you to analyze visual trends, understand the context in which your brand appears, and see what your audience is engaging with. Instead of just guessing which images will resonate, you can use these tools to identify patterns and objects that capture interest. This technology is the foundation for turning any visual into a data point you can learn from.
Visual Search Solutions
We've all been there: you see a product you love in a photo but have no idea how to find it. Visual search solutions solve this problem. They let customers search for products using an image instead of text. By uploading a photo, a user can instantly find similar items available for purchase. This makes the path from inspiration to checkout much shorter and more intuitive. For your business, this means a smoother customer experience and, ultimately, more sales. Tools like IRCODE take this a step further by making the original image itself the gateway to shopping, eliminating the search process altogether.
Analytics and Tracking Tools
How do you know if your visual content is actually working? That's where analytics and tracking tools come in. These platforms go beyond simple metrics like likes and shares to show you how people truly interact with your visuals. Computer vision helps you learn how customers react to different images by tracking what catches their eye, how long they look at something, and what visual cues prompt them to buy. This gives you a much deeper understanding of customer behavior, allowing you to refine your creative strategy based on what the data says people want to see.
Tools to Measure Performance
Once you have insights from your analytics, you need tools to act on them. Performance measurement tools help you optimize your visual assets through testing. They allow you to experiment with different creative elements—like colors, layouts, or calls to action—to see which versions perform best. This process, often called A/B testing, replaces guesswork with evidence. By continuously testing and refining your visuals, you can ensure your marketing campaigns are always improving. This data-driven approach helps you get the most out of every image and video you create.
How to Measure Your Success
Launching a new marketing campaign is exciting, but the real magic happens when you can prove it works. Measuring your success is how you move from guessing to knowing, turning your creative ideas into predictable business growth. With computer vision, you're not just looking at surface-level metrics like likes or shares. You're getting a clear view of how people interact with your visuals and what drives them to act. This data is your roadmap to refining your strategy, making smarter investments, and creating experiences your audience truly loves. Let's walk through the key areas to focus on so you can measure what matters.
Key Metrics to Track
At its core, measuring success comes down to a simple question: Is the value you're getting greater than the cost? To figure this out, you don't need a complicated spreadsheet. Just think about it in three parts. First, consider your savings—how much time or money did this new approach save your team? Second, look at your gains—what new revenue did you generate from sales or leads? Finally, tally up your costs, including any software or setup fees. A successful campaign is one where your savings and gains far outweigh what you spent. This simple framework helps you calculate your return on investment and justify your marketing efforts with clear, compelling numbers.
Conversion and Engagement Metrics
When your images become interactive, you can track engagement on a whole new level. Instead of just wondering if people saw your ad, you can measure how many scanned it, what they clicked on, and how long they spent with your content. These are powerful conversion and engagement metrics. For example, with a scannable IRCODE on a product image, you can see exactly how many users went from viewing the image to visiting the product page. Computer vision tools can also help you understand what catches the eye in your visuals, giving you insights to create more effective designs that guide customers toward making a purchase.
How to Track ROI
Tracking your return on investment (ROI) becomes much more straightforward with computer vision marketing. Because you can link actions directly to specific visuals, attribution is no longer a mystery. If a customer scans a code on a poster and makes a purchase, you know exactly which asset drove that sale. This allows you to get more from your advertising budget by investing in the campaigns that deliver real results. By using computer vision in advertising, you can precisely target your audience and track performance, ensuring every dollar you spend is working as hard as it can for your brand.
Analyze Customer Retention
Understanding why customers stick around is key to long-term growth, and computer vision can offer valuable insights here, too. By analyzing how customers interact with your brand both online and in physical spaces, you can identify friction points and opportunities for improvement. For instance, a scannable code in a retail store can link to a feedback survey or a loyalty program sign-up, giving you direct data on customer satisfaction. This information helps you refine and improve the customer journey, creating a seamless experience that encourages people to come back again and again.
Using Computer Vision Responsibly
As exciting as computer vision is, it comes with a responsibility to use it ethically. When you collect and analyze visual data from your audience, you're handling personal information. Building a marketing strategy on this technology means you also need to build a foundation of trust. This isn't just about following rules; it's about respecting your customers and creating a brand they feel good about supporting.
Responsible use of computer vision boils down to a few core ideas: being a good steward of customer data, being transparent about how you use it, working to eliminate bias in your systems, and always putting the customer's experience first. When people feel safe and respected, they're more likely to engage with your brand and become loyal advocates. Think of these practices not as limitations, but as guidelines that lead to stronger, more meaningful customer relationships. It's how you turn a cool piece of tech into a genuinely positive experience for everyone. By embedding these principles into your strategy from the start, you show your audience that you see them as people, not just data points. This approach will set you apart and is essential for long-term success in a world where consumers are increasingly aware of their digital privacy.
Protect Customer Data
When you use computer vision, you're often collecting sensitive information, even if it's just images of how people interact with a product. Your top priority must be to protect customer data with strong security measures. This means using encrypted systems, controlling who has access to the data, and choosing technology partners who take privacy as seriously as you do. Think of it as the digital equivalent of locking the doors to your store at night. You wouldn't leave your customers' information exposed on the street, and the same principle applies online. Proactively securing data is a fundamental part of earning and keeping your audience's trust.
Be Transparent and Get Consent
No one likes feeling like they're being watched without their permission. That's why transparency and consent are non-negotiable. You need to be crystal clear with your audience about what data you are collecting, why you're collecting it, and how you plan to use it. This information should be easy to find and understand—no hiding behind complicated legal jargon. Before you collect any data, you must get explicit consent. This approach respects your customers' privacy privileges and shows them that you value their choice to engage with your brand. Being upfront builds a much stronger relationship than any data point ever could.
How to Prevent Bias
Computer vision models are only as good as the data they're trained on. If the training data is skewed, the model's outputs will be, too. This can lead to algorithmic bias, where your technology might perform poorly for certain demographics or misinterpret images from underrepresented groups. To prevent this, it's crucial to use diverse and representative datasets when training your models. Regularly audit your systems to check for unfair patterns and be prepared to make adjustments. The goal is to create an experience that feels inclusive and works well for everyone in your audience, not just a select few.
Guidelines for Ethical Use
Beyond the technical details, it's important to have a clear set of ethical guidelines for how your team uses computer vision. The technology should always be used to add value to the customer experience, not to exploit or manipulate. For example, using computer vision to offer personalized product recommendations is helpful; using it to track people without their knowledge is not. Establish principles that put the user first, ensuring that your marketing efforts are helpful and respectful. These guidelines will help you innovate responsibly and enhance security and customer experience in a way that aligns with your brand's values.
What's Next for Computer Vision in Marketing?
Computer vision is evolving at a rapid pace, and its role in marketing is set to become even more integrated and intuitive. We're moving beyond simple image tagging and product identification into a future where this technology understands context, predicts intent, and even responds to human emotion. For marketers and creators, this opens up a new world of possibilities for building deeper connections with audiences. The next wave of computer vision applications is all about creating experiences that are not just personalized, but truly responsive and seamlessly woven into our daily lives.
Imagine a world where the line between the physical and digital blurs completely. You could point your phone at a friend's jacket to buy it instantly, or your favorite brand could serve you an ad that changes based on your reaction. These aren't scenes from a sci-fi movie; they're the tangible outcomes of advancements in computer vision. The focus is shifting from simply "seeing" to "understanding." This deeper comprehension will allow for more meaningful interactions, turning passive visual content into active, engaging experiences. It's about making technology feel less like a tool and more like a helpful, intuitive partner in how we discover, shop, and connect.
Integrating with Augmented Reality
One of the most exciting frontiers for computer vision is its partnership with augmented reality (AR). Computer vision acts as the eyes for AR, identifying surfaces, objects, and spaces in the real world so that digital elements can be placed accurately. This is what powers those "try before you buy" features that are changing ecommerce. You can see how a new sofa would look in your living room or virtually try on a pair of sunglasses without ever leaving your home. This creates a more confident and interactive shopping experience, reducing returns and building a stronger connection between the customer and the product.
Taking Personalization to the Next Level
We're all used to getting recommendations based on our browsing history, but computer vision is taking personalization much further. By analyzing the visual content people share and interact with, brands can gain a deeper understanding of their customers' aesthetic tastes and lifestyles. For example, if you frequently post photos of minimalist interior design, a home decor brand could show you ads featuring clean lines and neutral palettes. This moves beyond simple demographics to offer suggestions based on your unique visual identity, making marketing feel less like an interruption and more like a genuinely helpful style consultation.
The Future of Real-time Analytics
The ability of computer vision to provide valuable insights is becoming faster and more dynamic. In the near future, marketers will be able to get real-time feedback on how audiences are visually engaging with their campaigns. Think of a digital billboard in a shopping mall that can analyze foot traffic and gauge which parts of the ad are drawing the most attention. This allows for immediate A/B testing and optimization, so you can adjust creative elements on the fly to better capture your audience's interest. It's about making data-driven decisions in the moment, not weeks after a campaign has ended.
Innovations in Visual Search
Visual search is getting smarter every day. Soon, it won't just be about finding an exact match for a photo you upload. The technology is evolving to understand context and relationships between objects. You could snap a picture of a shirt you like, and the search engine will not only find that shirt but also suggest a complete outfit to go with it. This makes the path from inspiration to purchase incredibly short and intuitive. Instead of trying to describe something with words, you can simply show what you want, turning any image into a starting point for discovery and shopping.
Marketing Based on Emotion
Perhaps the most forward-thinking application is emotion-based marketing. Using computer vision to analyze facial expressions, brands could one day gauge a user's emotional response to an ad or piece of content in real time (always with user consent, of course). If a viewer seems confused by a product demo, the system could trigger a pop-up with more information. If they smile at a particular scene in an ad, the brand gets instant positive feedback. This technology could lead to truly empathetic and responsive advertising that adapts to the viewer's feelings, creating a more positive and effective brand interaction.
How to Get Started with Computer Vision
Bringing computer vision into your marketing strategy might sound complex, but it's more about smart planning than technical expertise. By breaking it down into a few manageable steps, you can start using this powerful technology to connect with your audience in new and exciting ways. Think of it as adding a new, highly effective tool to your marketing kit. It's about working smarter, not harder, to create visual experiences that resonate with your customers. Here's a straightforward path to get you started.
Plan Your Approach
Jumping into any new technology without a clear goal is like starting a road trip without a destination. Before you explore any tools, take a moment to map out what you want to achieve. Are you hoping to make your social media posts instantly shoppable? Do you want to understand which product images get the most attention on your website? Simply using image processing won't magically grow your business unless you have a smart plan. Define one or two key objectives first. This focus will guide every other decision you make, from the software you choose to how you measure success.
Select the Right Tools
Once you have your plan, it's time to find the right tools for the job. Computer vision uses Artificial Intelligence to teach computers how to interpret images and videos, but you don't need to build an AI from scratch. Many platforms, like IRCODE, are designed to make this technology accessible. Look for solutions that align with your goals. If you want to create interactive experiences, find a tool that turns your images into scannable codes. If your goal is analytics, look for a platform that specializes in tracking visual engagement. The key is to choose software that feels intuitive and solves your specific problem without a steep learning curve.
Train Your Team
A new tool is only effective if your team knows how to use it. You don't need to turn your marketing department into a group of data scientists, but a little training goes a long way. Walk your team through the new software and explain how it fits into your marketing goals. Make sure they understand the basics of how computer vision works in the context of your new tool and what the data means for their day-to-day work. When everyone is on the same page and feels confident using the platform, you'll start seeing results much faster. Empowering your team with knowledge is just as important as the technology itself.
Optimize Your Performance
Computer vision isn't a one-and-done solution; it's a powerful feedback loop for your visual content. Use the insights you gather to continuously refine your strategy. This technology can show you exactly how people react to different images, revealing what captures their attention and what visuals lead to a purchase. Pay attention to these patterns. If you notice that lifestyle photos outperform product-only shots, create more of them. If a certain color palette gets more engagement, lean into it. This process of testing, learning, and optimizing is how you turn data into a real competitive advantage and create content that truly connects with your audience.
Integrate with Your Current Marketing Tools
To get the most out of computer vision, it needs to play nicely with the marketing tools you already use. Look for platforms that can integrate with your email service provider, CRM, or analytics dashboard. A seamless integration means less manual work and a more holistic view of your marketing efforts. For example, the right tool can help automate tasks like tagging product images in your content management system or tracking visual performance alongside your other campaign metrics. This creates a more efficient workflow and allows your team to spend less time on repetitive tasks and more time on creative strategy.
Frequently Asked Questions
Do I need to be a tech expert to use computer vision in my marketing?
Absolutely not. While the technology itself is advanced, the tools available today are designed for creators and marketers, not engineers. Platforms like IRCODE handle all the complex work behind the scenes. If you can upload a photo and add a link, you have all the technical skills you need to turn your images into interactive experiences.
Is this just a more complicated version of a QR code?
That's a great question, but they are fundamentally different. A QR code is a separate, functional box that you have to place on top of your creative work. With computer vision marketing, the image itself becomes the code. This allows you to maintain your brand's aesthetic and create a much cleaner, more integrated experience for your audience, keeping your beautiful visuals front and center.
What's the simplest way to start experimenting with this technology?
The best approach is to start small with a clear goal. Pick one of your most popular images on social media and make it interactive. For example, you could use a tool to link that single image directly to a product page, a relevant blog post, or a video tutorial. This simple test will give you valuable insight into how your audience engages and provide the confidence to use it in bigger campaigns.
How can I use this technology without making my customers feel like they're being watched?
This all comes down to transparency and providing genuine value. The goal is to use computer vision to make your customer's life easier or more interesting, not just to gather data. When you turn an image into a direct path to buy a product they admire or access a recipe they want, you're offering a helpful shortcut. As long as the experience clearly benefits them, it will feel like a useful service, not an intrusion.
Is computer vision marketing only for businesses that sell physical products?
Not at all. While it's a powerful tool for e-commerce, it's incredibly versatile. A musician could link a concert photo to a ticket-buying site. A consultant could link their headshot on a presentation slide to their LinkedIn profile. A nonprofit could link an image from a community event directly to their donation page. If you use visuals to tell your story, you can use this technology to make them more engaging.