Let’s start with a simple truth. The way people find information online has changed alot.

In 2026, many people don’t start with a search engine. They open tools like ChatGPT, Google Gemini, Perplexity AI, or Claude and ask a question.

“What’s the best CRM for a small team?”
“What’s the difference between assisted living and skilled nursing?”
“What running shoes are best for wide feet?”

Instead of sending users to ten different websites, these tools read across the internet and generate a direct answer. For brands, that shift changes the rules.

If your company, expertise, or products are not showing up in those AI responses, you are missing a growing share of the conversation. That’s what we call AI visibility. And right now, it matters more than ever.

What Is AI Visibility?

AI visibility is how often your brand appears in answers generated by AI assistants.

That appearance can take a few forms:

• Your company is mentioned as a recommended option
• Your website is cited as a source
• Your content helps inform or shape the answer
• Your product or service appears in comparisons or lists

In other words, AI visibility determines whether your brand shows up when people ask AI tools about your category. And increasingly, that is where research begins.

Why AI Visibility Is Becoming Critical for Brands

The rise of AI assistants is changing how people discover and evaluate businesses. Here are three reasons brands are paying attention:

1. More research starts with AI

Instead of clicking through pages of results, users are asking AI tools for explanations, recommendations, and comparisons. These tools summarize information and provide a clear response. For many users, that answer is enough to move forward with a decision.

2. AI answers shape early trust

When an AI assistant consistently mentions certain companies, those brands gain credibility quicky. If someone asks an AI tool for the best options in a category and your company appears in the response, you have already earned attention before the user ever reaches your website.

3. Discovery is becoming more “zero-click”

AI answers often give users what they need without requiring them to open multiple websites.This shift toward zero-click discovery means brands cannot rely on rankings alone. They need to make sure their expertise is visible directly inside AI responses.

How Brands Can Improve AI Visibility

The good news is that improving AI visibility does not require starting from scratch. Many of the same principles that drive strong content and search performance still apply. They just need to be adapted for the way AI systems gather and summarize information.

1. Answer real questions clearly

AI assistants prioritize content that provides straightforward answers.

That means creating resources such as:

• FAQs
• decision guides
• comparison articles
• step-by-step explanations
• educational content that clarifies complex topics

The clearer the answer, the easier it is for AI systems to reference it.

2. Build authority around a topic

AI tools tend to reference websites that demonstrate consistent expertise.

Brands that publish thoughtful, helpful content about their industry are far more likely to be cited than sites that only publish promotional material. Think educational resources, glossaries, guides, and insights that genuinely help users understand a topic.

3. Structure content so AI can read it easily

Formatting matters more than many brands realize. Content that performs well in AI answers often includes:

• clear headings and subheads
• concise paragraphs
• bullet lists
• direct definitions
• logical page structure

In other words, content that is easy for humans to read is also easier for AI to interpret.

4. Maintain strong search fundamentals

Traditional SEO still plays a major role. Fast websites, clear navigation, strong internal linking, and authoritative backlinks all help search engines and AI systems understand your content and trust it as a source. AI visibility builds on top of these foundations.

The Yalo AMPLIFI Way

This is exactly the kind of shift we help our clients navigate with our proprietary AI methodology, AMPLIFI.

Strategy, creativity, and storytelling matter just as much as technology. And therefore, we believe the future of AI must still feel human and authentic, because humans engage with authority and authenticity.

Our team applies AMPLIFI for brands to ensure their digital presence is built for the way people use AI to search today. That includes:

• developing AI-ready content strategies
• structuring websites so information is easy for AI systems to interpret
• building topical authority through helpful educational content
• aligning SEO and GEO strategies so brands perform well in both search engines and AI assistants

Sometimes that means a website overhaul. Other times, it’s a content strategy designed around the real questions customers ask every day.

The goal is simple. When someone asks an AI tool about your industry, your brand should show up in the answer. AMPLIFI accelerates our clients’ progress toward their goals.

The Bottom Line

Traditional SEO is still important, it just is not the whole picture anymore. Today, brands need to think about visibility across multiple discovery channels, including search engines, AI assistants, social platforms, and voice interfaces.

The companies pulling ahead are the ones making sure their expertise is easy to find, easy to understand, and easy for AI systems to reference.

Because when someone asks AI a question in your category, your brand should be part of the answer.

Throughout the modern marketing industry’s short, dynamic history, one question has always dominated: What’s next?

Marketers spend millions each year chasing the next big thing, gambling on what’s going to hit and following trendmakers wherever they lead. But following usually leads to a huge problem: chasing doesn’t work. By the time you catch up to culture, it has already moved on.

Think Different (Not the Apple “Think Different,” a Different Think Different)

Brands that create culture instead of chasing it are the ones that win, but those cases are rare. You either need the budget to constantly experiment until something sticks (think: funny, intriguing daily video social content), or you need a lot of luck (think: Stanley Cup’s influencer strategy). Even the smartest, funniest, most award-winning work doesn’t guarantee a place in the conversation. After all, how many people outside of advertising know who won a Cannes Lion, or even what that is?

So maybe we should stop thinking about what’s next and start talking about what matters. All this chasing, creating, and throwing things at the wall in hopes that something sticks has created an incredibly crowded space, making the ability to stand out more important than ever. And rising above in the new year is going to require taking a higher road. 

The High Road? That Sounds Like Something a Nerd Would Use.

By now, you may have seen a recent Wall Street Journal piece on the role of storytelling in building brand loyalty. It wasn’t about the brand-anthemy, long-form copy kind of storytelling. It was about the kind of storytelling that gives brands context. The kind that tells the world who a company is, where it fits within the competitive set, why it exists at all, and, most importantly, why anyone should care. Because in a world where AI can write a brand anthem, a “big, bold rally cry” means nothing without the substance to back it up.

In a world flooded with content, the brands that win aren’t the loudest; they’re the clearest. They’re the ones that can articulate a point of view and sustain it across channels, leadership voices, customer experiences, and culture. Audiences are tired of being targeted, optimized, segmented, and “journeyed.” They’ve developed an almost supernatural ability to sniff out content that exists solely to sell them something.

But You Just Told Me AI Is the Future. What Gives?

Which brings us to AI. By 2026, AI won’t be the headline anymore, it’ll be background noise. As we’ve said before, AI is a tool, and it will remain one. It will quietly power personalization, media buying, forecasting, content testing, and a hundred other things we no longer think twice about.

The mistake brands are already making is assuming that because AI can generate, it can also connect. It can’t, at least not on its own. The brands that get it right will use AI the way great teams use great tools: to move faster, spot patterns sooner, and free up time for real thinking.

Show Up Authentically, Confidently, and Wearing a Snazzy Jacket 

At the same time, trust is becoming the real currency of marketing. Privacy changes, disappearing cookies, and growing consumer awareness have shifted the power dynamic. There’s a reason word of mouth and unpaid recommendations remain the most powerful forms of advertising: they’re among the few sources people still trust (most of the time). By 2026, ethical data practices will be a brand signal. Companies that are clear about what they collect, why they collect it, and how it benefits the customer will stand apart in a market that still struggles with transparency.

Another shift that’s impossible to ignore is the move away from one-off influencer moments toward true creator ecosystems and brand communities. Audiences don’t want to be “influenced” anymore; they want to belong. They want to see brands show up consistently, collaborate authentically, and earn their place in culture rather than rent it for a campaign cycle. Once again, it comes back to honesty and meaning.

But Wait, There’s More! It’s Media!

But how will people be reached? Short-form video, live formats, and immersive experiences aren’t trends so much as the default language of modern communication. The brands that perform best aren’t necessarily producing more content; they’re producing content that understands how people actually consume it: quickly, emotionally, and often on mute.

Behind the scenes, marketing teams are changing too. Roles are blurring, with strategy, creative, data, and technology increasingly overlapping. The most effective teams heading into 2026 are built for adaptability, not perfection. They test, learn, adjust, and move on. They value judgment as much as output, and curiosity as much as efficiency.

But can brands be authentic without authenticity becoming just another marketing buzzword? That’s a blog for another time. In the meantime, marketing is still about making people feel something and then do something. The tools have changed. The pressure has intensified. The margin for error has shrunk. But the core truth hasn’t moved an inch.

So What’s Next? (Hey, There’s That Question Again) 

For Yalo, it’s not about chasing every new platform, format, or promise. It’s about using every tool at our disposal (technology, data, creativity, and yes, AI) to help brands show up honestly and with intention. We’ll keep focusing on work that earns attention instead of demanding it, builds trust instead of gaming the system, and creates real connection instead of noise. Because the brands that win next won’t be the loudest, they’ll be the ones that know who they are, why they exist, and how to show up meaningfully in people’s lives.

When a client asks, “What’s the ROI of [insert ad channel here]?” what they’re really asking is, “Which magic button can I press to make results appear?”

We get it. Attribution is intoxicating. ROAS feels like truth. And with the rise of AI-powered buying tools, real-time dashboards, and third-party data integrations, it’s never been easier to see results. 

But here’s the kicker: the numbers you can track are only part of the story. The rest? That’s where we come in.

Our Approach

At Yalo, our media team is built differently, with the knowledge that data is a critical tool, but it’s not the whole tool belt. 

We’re full-funnel, full-service, and fully fluent in the nuances of both digital and traditional channels. And yes, when to trust ROAS metrics, and when to be a healthy skeptic. From CTV and podcasts to SEM, print, programmatic, and beyond—we’re not here to rack up views, we’re here to make them count.

How? We use in-platform and third-party AI tools not just to chase efficiency, but to ensure impact. 

Whether it’s uploading a CRM list through LiveRamp, creating historical geotargeting audiences via third-party partners, or running brand lift studies across healthcare or general market categories, we’re not guessing—we’re pinpointing.

The Planning Process

Our planning process is powered by research partners like MRI Simmons and Comscore. 

Our buying is enriched with purchase-level data from credit bureaus and intent signals. And our reporting? Custom dashboards that are live, accessible, and actually usable, so clients aren’t stuck staring at a spreadsheet asking ‘so what?’

Get Creative

But tech alone won’t win the war.

You still need great creative. An integrated media mix. A message that lands. And yes, that includes a team that understands your business well enough to challenge your assumptions.

While it’s tempting to chase short-term wins with last-click logic, the truth is: 91% of people who buy your product saw your ads and didn’t click them (Nielsen). 80% bounce between devices before purchase. And 40% use more than one screen to complete a transaction (eMarketer).

So, what’s the ROI of that?

Truth is, the most impactful plans don’t just ask, “What channel will convert?” They ask:

• Where does your audience live, scroll, shop, or tune out?
  
• What will they remember tomorrow?
  
• What combination of message, medium, and moment creates action?
  

That’s what we do.

The Yalo Difference

Our tribe connects the dots between strategy, storytelling, and sales. Between the art and the algorithm. Between “what you’re doing” and “why it’s working.”

There’s no magic button. Just media done right. And that’s the Yalo way.

There’s a moment in music history that changed everything. When Bob Dylan plugged in his electric guitar at the Newport Folk Festival in 1965, it was a declaration: the world was evolving, and music had to evolve with it. The purists scoffed, but Dylan saw the electric guitar not as a replacement for folk music but as a way to amplify its impact. The result? A new era of sound that pushed the boundaries of what was possible.

At Yalo, we see AI the same way. It’s not here to replace creativity, it’s here to amplify it. That’s why we’ve spent the last year developing AMPLIFI, our proprietary process for integrating AI into every facet of our agency. Much like the artists who shaped rock & roll, we’re not just adopting new tools; we’re shaping the future of how they’re used. And just like rock music didn’t kill live performances—it made them bigger, bolder, and more electrifying—AMPLIFI isn’t replacing our talent. It’s giving them the means to amp it up to 11!

Training the Band, Not Just Adding New Instruments

The greatest bands didn’t just pick up new instruments and hope for the best. They learned how to master them. The Beatles didn’t stumble into pioneering studio techniques; they experimented, innovated, and learned. That’s exactly what we’ve done with AMPLIFI.

Instead of simply handing our team AI tools and saying, “Figure it out,” we made a bold investment: we created a structured training program to ensure that every single member of our tribe—whether in operations, media, or creative development—knows how to harness AI effectively. AMPLIFI isn’t just a piece of software or a new workflow. It’s a mindset shift. It’s our way of ensuring that AI doesn’t just exist in our agency, it enhances everything we do.

AI as an Amplification, Not the Replacement

There’s a difference between evolution and replacement. When synthesizers came onto the scene, they didn’t replace guitars—they expanded what was possible in music. AI is the synthesizer of the marketing world. It’s not here to write our stories, strategize our campaigns, or concept our creative. It’s here to help us create faster, sharper, and even more resourcefully. 

With AMPLIFI, we’re integrating AI into:

• Creative Development – Providing new ways to visualize, iterate, and innovate without losing the human touch that makes great creative work sing.
• Media Strategies – Enhancing data analysis, audience insights, and campaign efficiency to hit the right notes with precision.
• Operations – Automating the tedious so our people can focus on strategy, relationships, and big-picture thinking.

And that’s just to name a few. Hey, we can’t give away every ingredient in our secret sauce.

Every major shift in music—whether it was MTV changing how artists connected with fans or streaming services reshaping how music is distributed—has been met with resistance. But the artists who embraced these changes didn’t just survive; they thrived. AI is our industry’s next big shift, and at Yalo, we’re not just riding the wave, we’re playing lead guitar.

Why AMPLIFI Matters

We’re living in a time where many agencies are taking a wait-and-see approach to AI. They’re hesitant, uncertain, or even dismissive of its potential. That’s not how we operate. We believe in being ahead of the curve, setting the tempo, and ensuring our team has the knowledge and confidence to use AI to its fullest potential.

Because here’s the truth: AI in marketing isn’t a fad. It’s not going away. And just like rock & roll, it will keep evolving. The question is, who’s going to step up and own it? At Yalo, we’ve made our choice. We’re not just accepting AI—we’re amplifying it.

So plug in, turn up the volume, and get ready. The future isn’t waiting, and neither are we. This is AMPLIFI. And trust us, the show is just getting started.

Our souls are singing. Is yours? I’d love to chat with you about how Yalo can make AI work for your brand. 

If you’ve ever cracked open a Statement of Work (SOW) and felt your soul leave your body, you’re not alone. SOWs are critical for defining the scope of a project, but they’re also dense, jargon-packed, and, let’s be honest, a little soul-crushing. As an agency, we thrive on collaboration across multiple disciplines—but that means translating a SOW into an actionable, digestible plan that all disciplines can understand. That’s where AI can be a huge help. 

Working with Cortland Apartments, we faced a complex mix of deliverables when it came to their sponsorship with the Atlanta Braves: stadium digital assets, video production, physical signage, and message development that unified the Cortland and Braves brands. Managing these moving parts within the constraints of a real-world budget meant we needed an optimal way to prioritize, allocate resources, and ensure every hour counted. AI helped us do exactly that.

Prioritizing the Heavy Hitters First

Traditionally, turning an SOW into a project plan required a painful process of manually combing through pages of details, highlighting key milestones, and cross-referencing dependencies. It was slow, inefficient, and left way too much room for human error.

By integrating AI into our workflow, we could instantly identify:

• Key deliverables and their dependencies
• Specific format and functional requirements
• Due dates, milestones, and approval checkpoints
• Responsibilities across different disciplines
• Which tasks to prioritize based on business impact and sponsorship visibility

AI enabled us to prioritize high-impact deliverables, such as stadium digital assets and signage with game-day visibility, based on urgency and partnership impact. Its structured workstreams kept us focused on what mattered most, rather than playing catch-up.

Calling the Right Plays for Hours and Budget

Project management isn’t just about keeping tasks in order, it’s about making sure we don’t blow the budget. AI helped us estimate hours needed for each task based on actual historical data from our team, rather than industry benchmarks that don’t reflect real-world agency constraints. This meant we could:

• Allocate time accurately to creative, production, and strategy teams
• Avoid overloading staff or underestimating effort for high-complexity deliverables
• Ensure that the total hours tracked aligned with the budget approved for the sponsorship

This level of precision gave us a clear roadmap that balanced creative ambition with financial reality. AI didn’t just organize our tasks, it actively made sure our strategy was financially viable from day one.

How AI Keeps Every Position Covered

Once we had the core details extracted and prioritized, the next challenge was ensuring every discipline—creative, strategy, media, development—was aligned and working from the same playbook. AI didn’t just stop at summarization; it powered our task management system by:

• Automatically generating timelines and tasks based on our suggested project timing templates and key milestone dates
• Setting up dependencies between tasks and teams so the work flowed logically
• Sending deadline reminders to alert team members that a status update on the project has been requested 
• Suggesting days for internal review meetings as based on our project intake timing
• Highlighting priority items so nothing fell through the cracks

Instead of each department working in a silo and hoping everything lined up in the end, AI gave us a shared source of truth. No more guessing games, no more frantic Slack messages asking, “Wait, when is this due?”

Playing Smart: More Hits, Fewer Scrambles

By putting AI to work in project management, we didn’t just make life easier, we fundamentally improved how we deliver work. The biggest benefits?

• Speed: What used to take hours to set up, now happens in minutes.
• Clarity: Teams know exactly what’s expected of them and when.
• Accountability: No more missed deadlines or surprise bottlenecks.
• Budget Control: Hours estimates aligned with actual resources, preventing overruns.

AI didn’t replace our expertise, it amplified it. It turned a process riddled with inefficiencies into a well-oiled machine, freeing us up to focus on what really matters: delivering great work.

The Final Score

SOWs might still be a necessary evil, but with AI, they don’t have to be a productivity killer. By automating the extraction of key details, prioritizing high-impact deliverables, and aligning resources with budgets, we transformed the way we ran the Cortland x Atlanta Braves sponsorship.

I know what you’re thinking: “SEO is dead. Again.” Our AI overlords are here and they’ve come not to harvest the energy of our body heat to power their hive mind (a la The Matrix) but to generate an endless onslaught of mediocre content and provide us with quick and easy answers that give us no reason to click into websites. Oh, the humanity.

But before you stock up on canned beans and crawl into the fallout shelter, hear me out. SEO has “died” at least a dozen times now according to every digital media news outlet and each time the practice has simply evolved. Let’s go over how AI is shaking up SEO, how you can use it to your advantage, and what you can do to keep organic traffic flowing

The Role of AI in Modern SEO

Content Creation

With tools like ChatGPT, Microsoft Copilot, and Google Gemini, creating content with AI is not only easy, it’s extremely accessible to anyone with an internet connection. The temptation is strong to generate hundreds of blog posts for your business, copy and paste them straight onto your website, and call it a day. But if you’re getting the eerie feeling that it was all too easy, you’re right.

AI is a brilliant tool for quickly creating content, but it’s not a miracle worker. Keep these in mind next time you generate something:

• Factuality: If you ask a Large Language Model (LLM) like ChatGPT to write a page about your mattress store’s new deals without giving it all the info, it will make stuff up. It’ll tell everyone about the 90%, BOGO special that it decided would sound good and suddenly you look silly because you didn’t proofread before posting it. It is imperative to go through anything you generate with an LLM with a keen eye to ensure you’re telling the truth, otherwise you’re simply creating clickbait spam.
• Originality: LLMs are trained on internet content. So if you’re asking it to write a blog post, it’s not just making it up on the spot like a writer would do, it’s pulling from other relevant articles for both the words and structure. A writer taking inspiration is one thing but this is verging on plagiarism in the eyes of Google, even if it doesn’t read the same to you. Consider giving it a true outline (you know, like you used to give human writers) instead of a simple prompt, and reword anything that doesn’t read like your tone of voice.

AI Overviews

Taking a look from the user’s perspective, Google has made it easier than ever to get a quick answer to whatever’s on their mind with AI overviews. While I find this wonderfully convenient outside of work, you can imagine how interesting this makes my job. But all is not lost because Google does credit the websites it pulls the information from so we’re right back to “not dead, just different”. So we’re not just fighting for traditional rankings anymore, we’re fighting to be the source of truth for these AI overviews, and you may not like what you’ll need to do to get there:

• High-Quality Content: I know, it burns. But as mentioned above, you need to make sure everything you put out there is completely original and tells the truth. Keep the fluff to a minimum, get to the point of the article as soon as you can, and try not to make it sound like an advertisement. When your website becomes a true resource for your field, not only will Google reward you, but users will trust you.
• Patience: Your mom was right, patience is a virtue. If you’re starting from scratch, it’ll take a while to get the good rankings and be seen as a resource. If you’ve been around awhile but your content isn’t reference-worthy, you can get there quicker but you’ll need to clean up your content and ensure it’s all useful. As the age-old adage goes: “The best time to start a high-quality content strategy was 20 years ago, the next best time is now”

Keywords and User Intent

Yes, keywords still matter—hurray, something old and familiar! But the game has changed. It’s no longer enough to cram a few phrases into an article (and frankly it never was, but hey, it worked!) and call it SEO-optimized. AI-driven search engines use advanced algorithms to understand user intent, context, and even synonyms. That means you need to shift your focus from “how many times can I say ‘best tacos in Austin’ without sounding ridiculous?” to “how can I answer every question a taco lover in Austin might have?”

Instead of obsessing over exact matches, think about the big picture:

• Long-Tail Keywords: These are your secret weapon. Instead of “tacos Austin,” aim for phrases like “authentic street tacos” or “best vegan tacos in South Austin.”
• Semantic Content: Google and AI tools thrive on context. Sprinkle in related terms, like “corn tortillas,” “salsa verde,” or “late-night eats,” to show your article is well-rounded and authoritative.
• User Intent: Are people looking for a quick taco joint recommendation, or are they researching Austin’s taco scene for an upcoming trip? Tailor your content to match their needs.

Technical SEO

You might think AI makes technical SEO irrelevant, but you’d be wrong. If anything, it’s become a non-negotiable. Why? Because even the smartest AI can’t recommend your page if it never finds it in the first place.

Here’s where you need to focus:

• Site Speed: If your website takes longer to load than it does for someone to finish their coffee, you’ve already lost them. Optimize images, use lazy loading, and remove unused code.
• Mobile Optimization: With mobile-first indexing, your website needs to look and function flawlessly on a phone. You know when you go to tap on something and suddenly it shifts down 10 inches and suddenly you’ve clicked on an ad? That’s called Cumulative Layout Shift and we all hate it. You know the name now, scare your dev team by yelling at them about it.
• Structured Data: This is the cheat code to modern SEO. By using schema markup, you can help search engines understand your content better and increase your chances of snagging that coveted AI overview snippet.

Link Building in the AI Era

Ah, backlinks—the bread and butter of SEO. They’re still relevant, but the landscape has shifted. You can’t buy a few links and watch your rankings soar anymore. Today, AI algorithms scrutinize link quality like a hyper-vigilant editor.

Here’s how to stay in the game:

• Authority Matters: A single backlink from a reputable site in your industry is worth more than a dozen links from no-name blogs.
• Content Partnerships: Think guest posts, co-branded content, or industry collaborations. These don’t just build links—they build relationships.
• Internal Links: Don’t overlook what’s in your control. Strategically link between your own pages to help both users and AI understand your site structure.

Staying Ahead of the Curve

Here’s the thing about SEO in the age of AI: it’s dynamic. If I told you today that I have a bulletproof SEO strategy that will keep your website at the top of the search results for years to come, I would be a snake oil salesman. As it has always been, staying informed is your best defense. Follow trusted SEO blogs, experiment with new tactics, and don’t be afraid to pivot when something stops working.

Above all, remember this: SEO isn’t dead, and AI isn’t the enemy. It’s just the next evolution. Adapt, innovate, and—most importantly—keep creating content that people actually want to read. Because at the end of the day, that’s what SEO has always been about.

It’s 2025, and the marketing world is spinning so fast it can be hard to keep up. AI is everywhere, customers are demanding more personalized experiences, and AR/VR is no longer just for gamers. So how do you stay on top of the trends without losing your mind?

We’ve got you. Here’s our take on the biggest marketing trends of 2025 and how you can conquer the digital marketing landscape while keeping your cool.

1. Personalization Through Technology

AI: whether you view it as a friend or foe, it’s here to stay. AI doesn’t just help make tasks more efficient, it can also assist you in personalizing your marketing efforts so that your audience feels like you really ‘get’ them. From AI-crafted emails to quizzes that feel eerily spot-on, personalization is no longer optional—it’s expected. 

How You Can Apply This:

• Automate your life. Let AI do the heavy lifting with tailored emails, product recommendations, and even dynamic website content. Then, have your great human minds refine the content from there.
• Ask, don’t guess. Quizzes and preference centers aren’t just fun—they’re sneaky-smart ways to gather zero-party data.

Our Tip: Customers love feeling understood, but they also love privacy. Be transparent about how you use their info, and they’ll love you even more.

2. Immersive Experiences

Augmented reality (AR) and virtual reality (VR) are no longer the stuff of sci-fi. These tools are here, and they’re making brands more memorable. Throw in conversational tools like chatbots and voice assistants, and your customer experience game just leveled up.

How You Can Apply This:

• Invest in AR/VR. Let customers virtually see products in their space or take a VR tour of your commercial real estate. Bonus: It’s super cool.
• Don’t ghost your customers. Optimize for voice search and deploy chatbots that make interactions quicker and easier.

Our Tip: Don’t go AR/VR just because it’s trendy—make sure it genuinely enhances your customer’s experience. Otherwise, you’re just creating expensive gimmicks.

3. Data Is Your Crystal Ball

Big data isn’t just big—it’s colossal. Brands using predictive analytics are not only meeting customer needs but anticipating them before customers even know what they need.

How You Can Apply This:

• Use data like a psychic. Predictive marketing tools can help you time promotions and recommend products that your audience will actually want.
• Go omnichannel or go home. Make sure your customer experience is seamless whether they’re scrolling on Instagram, opening your email, visiting your website, or walking into your store.

Our Tip: Consistency is key. If your social media is quirky but your emails are all business, customers will feel the disconnect.

4. Digital Strategy: The Foundation You Can’t Skip

Despite advancements, nearly half of all businesses still lack a defined digital strategy. This gap limits growth potential and leaves opportunities on the table. Yikes.

How You Can Apply This:

• Conduct a digital marketing audit to identify strengths and weaknesses.
• Understand that an investment in strategy is a long-term one. Getting your marketing strategies up-to-speed earlier is much easier than scrambling to make a plan day-to-day.

Our Tip: No need to overhaul everything. Start with one underperforming area and build from there. If you need heavier lifting, consider reaching out to a marketing agency who can help (wink, wink). 

5. Purpose Over Profits

Customers want to know you care, and hiding behind just what you do or what you sell isn’t cutting it anymore. Brands that prioritize purpose-driven marketing aren’t just good for the world—they’re good for business.

How You Can Apply This:

• Walk the talk. Be authentic in your sustainability efforts, or risk being called out for greenwashing.
• Share your purpose. Purpose-driven campaigns connect with customers on an emotional level.

Our Tip: Don’t gloss over purpose. Dig into the ‘why’ behind your brand and what you want your audience to take away when they interact with your company.

6. Automation Meets Creativity

AI isn’t just helping with data—it’s creating, too. From AI-generated videos to automated graphic design, creativity just got an upgrade.

How You Can Apply This:

• Use AI tools for repetitive tasks like video editing or generating social media graphics.
• Channel your energy into storytelling. The tech handles the tedious stuff, leaving you to focus on the fun part—building emotional connections.
• Remember that AI is a tool, not a replacement. It can’t truly take over human creativity, but it can definitely help make your creatives more efficient.

Our Tip: Don’t let automation make your brand feel robotic. Keep the human touch alive.

7. Zero-Click Marketing and a Cookieless Future

AI-driven search features and the end of third-party cookies demand innovative approaches to engagement and attribution.

How You Can Apply This:

• Optimize for SERPs with clear, engaging answers to common questions.
• Embrace cookieless tracking methods while respecting privacy.

Our Tip: Shift your focus to building brand awareness and earning audience trust directly.

Marketing in 2025 proves that the digital landscape continues to grow at lightspeed. However, with the right tools and strategies, you’re not just keeping up—you’re leading the pack. With these trends, there’s no shortage of opportunities to make an impact.

So go forth and make 2025 your best marketing year yet. And if you need a little help? You know where to find us. 

They say all the world’s a stage, but when you’re running media for a historic theatre like The Strand, the real performance happens behind the scenes—in dashboards, data, and media spend optimizations. Our task? Drive ticket sales for a lineup of wildly different shows, from classic films to live concerts, all while ensuring our client got the best bang for their advertising buck. Enter AI, the ultimate understudy that helped us steal the show in media performance.

Act One: Understanding Our Audience with AI

The first challenge was figuring out exactly who we needed to have sitting in the proverbial front row: our target customer. But with such a diverse lineup of performances, that audience was a varied one. AI helped us break it down by analyzing Meta’s audience data at scale and identifying patterns in who was engaging, who was buying tickets to which types of shows, and (more importantly) who wasn’t.

• For classic movie nights, we saw higher engagement from an older demographic that responded well to nostalgic content.
• For concerts, AI pinpointed younger audiences that skewed towards certain music genres based on their social interactions.
• Theatre performances? A mix of local patrons and die-hard fans, depending on the production.

Engaging them on their terms added another layer to our efforts. Rather than relying on assumptions, AI helped us tailor our messaging and audience targeting to match the unique vibe of each show.

Act Two: Optimizing Spend Like a Broadway Producer

Once we had our audiences locked in, we made sure our ad dollars were putting on a Tony-winning performance. We wielded AI by continuously analyzing which channels and creative assets were hitting the right notes at the moment of transaction.

• If carousel ads were outperforming static images, AI flagged it.
• If video ads were getting stronger engagement, AI shifted more budget their way.
• If a particular behavioral subset was buying more tickets, AI made sure we prioritized their feeds (and in the process, we learned that behaviors trumped demographics when it came to driving sales).

This real-time, data-driven decision-making kept us from wasting budget on underperforming tactics and ensured we doubled down on what worked. Think of it as a media strategy that constantly fine-tuned itself, like a sound engineer tweaking the mix to get the perfect balance.

Act Three: ROI That Kept Getting Better

A great show builds momentum; our campaigns did too. Thanks to our team’s prowess in deploying AI to parse analytics at scale, we didn’t just see good performance, we saw better performance month over month.

• We refined audience segments based on actual purchase behavior, not just interest-based assumptions.
• We kept shifting budget dynamically to high-performing content types.
• We analyzed ad fatigue in real time, swapping out creative before engagement dipped.

By the time the final curtain fell, The Strand Theatre had maximized its media spend while continuously improving ROI. The result? More ticket sales, smarter budget allocation, and a digital media strategy that played to a standing ovation.

The Takeaway: AI is the Ultimate Tech Crew

We didn’t use AI to replace our expertise, we used it to enhance it. It helped us make smarter, faster, and more data-driven decisions, allowing us to move budget with precision and drive higher returns. In the world of media strategy, it was a box-office smash.

And with AI in the mix? Let’s just say we’re already looking forward to several encores. 

AI is a lot like a teenager learning to drive. It’s got potential, but it still needs guidance to get where you want it to go. And when we were tasked with bringing Precision Tune Auto Care’s “Any Make, Any Break, Fixed” campaign to life, we knew AI could help us generate some truly out-there vehicle concepts. But AI alone wasn’t enough. We had to steer it, gearshift it, and a bunch of other car metaphors, ultimately using our creative expertise to refine its output into something that truly hit the mark. Or like, the parking spot. 

The Concept: Any Car, Any Problem, Fixed

Precision Tune Auto Care owns a network of automotive shops throughout Atlanta, and they wanted to emphasize their ability to fix anything. Not just your standard sedans and SUVs, but anything—no matter how strange, old, futuristic, or broken it might be. We needed imagery that wasn’t just cars, but wild, eccentric, AI-dreamed vehicles that captured the essence of the campaign.

Step 1: Letting AI Go Off the Rails…or Road? 

The first step was strategic prompting. We weren’t just telling AI to generate “a weird car.” We crafted specific prompts to create vehicles that were futuristic, absurd, unconventional, and unlike anything on the road.

Some of our initial prompt variations included:

• “A vehicle that looks like it was designed in the year 2099 but only had 1950s car parts to work with.”
• “A car that’s a mashup of a monster truck, a motorcycle, and a space shuttle.”
• “A tiny European city car that somehow has six wheels, two steering wheels, and a spoiler the size of a dining table.”

AI happily obliged, and delivered some of the most bizarre, delightfully wrong car designs we’d ever seen. The results were wild, unpredictable, and often completely impractical… but that was exactly what we wanted.

Step 2: Embracing Imperfection (and Fixing It Ourselves)

Here’s the thing about AI-generated art: it’s not final art. AI doesn’t understand engineering or design principles; it doesn’t know why a wheel shouldn’t be inside the car instead of underneath it. The beauty of AI is that it gets you a starting point, not a finished piece.

That’s where human expertise comes in. The art director took the best of the AI-generated images and pulled them into Adobe Photoshop and Illustrator to refine them. That meant:

• Adjusting proportions so the vehicles looked surreal but still functional
• Fixing AI-generated distortions (like cars with 12 headlights but no tires)
• Enhancing textures, lighting, and details to make them campaign-ready

The result? A set of visually striking, one-of-a-kind vehicles that perfectly communicated the idea: No matter how weird, wild, or worn-down your car is, Precision Tune can fix it.

The Takeaway: AI is a Tool, Not a Replacement

The big lesson here? AI is great at generating ideas, but it takes real creative expertise to shape those ideas into something usable. AI gave us the raw material, but it took a human touch to refine, manipulate, and make it truly work for the campaign.

Could AI replace artists and designers? No. But can it act as an accelerator for creativity, giving us unexpected ideas and a head start? Absolutely. And in this case, it helped us take a fun, conceptual idea and turn it into a visual campaign that was as inventive as the message itself.

Final Thoughts

At the end of the day, “Any Make, Any Break, Fixed” wasn’t just a tagline, it was our approach to creative problem-solving. AI gave us something weird, we broke it apart, and then we fixed it into something truly impactful.

Because just like Precision Tune Auto Care, we believe that with the right expertise, anything can be made to run smoothly—even AI-generated mayhem.

In today’s hypercompetitive market, breaking into a new region isn’t just about having a great product, it’s about knowing exactly how to position it. The right insights can be the difference between a brand that eats, like, Wagyu beef versus a bowl of cold gristle. 

When tasked with developing a go-to-market strategy for Apollo, a commercial tire brand entering the North American market, Yalo turned to AI to help synthesize massive amounts of data and translate it into actionable marketing intelligence. AI wasn’t just a research tool; it was the foundation of a smarter, more strategic approach to brand positioning. 

Using AI to Define the Competitive Set

Step one in any strategic contest is understanding the battlefield. Who are the key players? What are their strengths, weaknesses, and differentiators? Leveraging the artificial intelligence tools at our disposal helped us analyze the competitive landscape at scale. Rather than sifting through whitepapers, industry overviews, competitive positioning and anecdotal insights, we used AI to process everything from customer sentiment analysis and industry trends to competitor marketing messages. We were even privy to some designated fiscal media buys.

What we uncovered was a landscape dominated by a handful of legacy brands, each staking its claim with a “unique” (these are air quotes, FYI) value proposition. Many highlighted their durability, emphasizing their ability to withstand brutal mileage. Others touted affordability, positioning themselves as the best “value” (though value seems to be a dirty word). In looking at larger brands in the space, many emphasized brand trust, leveraging decades of experience to reassure buyers. Through AI-driven sentiment tracking, we could see how these narratives played out in real-world conversations, allowing us to pinpoint white space where Apollo could step in and own a distinct position. Ideally one that appeals to the motivations and needs of our North American audience…

Cracking the Code on North American Fleet Owners & Distributors

The next challenge? You guessed it: understanding our target audience. Not just who they are, but what makes them tick. Fleet owners and distributors are the gatekeepers of the commercial tire industry, and if you don’t speak their language, you’re not getting through the door.

AI-powered audience analysis allowed us to segment North American fleet owners and distributors based on their key motivators, purchasing behaviors, and industry pain points. The data painted a clear picture: these buyers aren’t just looking for tires—they’re looking for reliability, efficiency, and solutions that address the specific challenges of North American roads.

And those roads? They’re a damn mess. From the snow-packed highways of the Northeast to the blistering heat of the Southwest, truckers face a gauntlet of conditions that demand more from their tires. AI helped us quantify these challenges, analyzing regional weather patterns, accident reports, and fleet maintenance logs to validate a crucial insight: North American truckers don’t just need tough tires; they need intelligent tires engineered to anticipate and overcome the unpredictable nature of the road.

From Insight to Impact: Crafting the Right Message

With a clear understanding of the competitive landscape and our audience’s needs, we built a strategic brief that cut right to the core of Apollo’s differentiation. Unlike competitors who leaned on vague promises of durability or affordability, Apollo had something unique: engineering intelligence. Their approach to tire manufacturing wasn’t just about toughness; it was about smart, calculated performance backed by data, research, and world-class engineering.

That insight led us to a creative platform that not only set Apollo apart but also resonated deeply with our audience: Smart Tires for Stupid Roads.

This wasn’t just a tagline; it was a rallying cry. It acknowledged the reality that truckers face every day—roads riddled with potholes, black ice, and extreme conditions—and positioned Apollo as the solution that could take on those challenges with intelligence and precision. The best part? Despite the high-quality, Apollo is a more affordable tire, backed by a road-hazard guarantee. That’s tier one performance at a tier two price. That way, we wouldn’t have to lean on value as a motivator, but rather let it be the closer when it’s time to make a sale. 

The Takeaway

AI isn’t just a tool for efficiency, it’s a weapon for marketers who want to outthink the competition and a megaphone for us to amplify our message. By leveraging AI-driven industry analysis, audience segmentation, and competitive intelligence, we were able to craft a positioning strategy for Apollo that was both authentic and compelling. Hell, I feel like I am getting nostalgic about the future.

The result? A market entry strategy that didn’t just introduce a new brand but made a bold statement: when the roads are unpredictable, your tires shouldn’t be.

In the ever changing business world, staying ahead of the competition requires more than just a keen eye for opportunities – it demands a strategic embrace of cutting-edge technology. The right tools can revolutionize the way you manage and analyze your business, paving the way for unprecedented growth and efficiency. Today, we’ll explore the myriad benefits of leveraging technology to propel your business forward.

1. Data-Driven Decision Making:

In the age of information, data is the new currency. Technology equips businesses with powerful tools to collect, process, and analyze vast amounts of data in real-time. With accurate insights at your fingertips, decision-makers can make informed choices, mitigate risks, and identify lucrative opportunities swiftly.

2. Efficiency Redefined:

Streamlining operations is at the heart of every successful business, and technology is the catalyst for achieving unparalleled efficiency. Automated workflows, project management tools, and cloud-based solutions empower teams to collaborate seamlessly, reducing time spent on mundane tasks and allowing employees to focus on high-value activities.

3. Enhanced Customer Experiences:

The right technology enables businesses to deliver personalized and immersive customer experiences. From advanced CRM systems to AI-driven chatbots, companies can engage with their audience in real-time, addressing queries promptly and tailoring products or services to individual preferences.

4. Scalability and Adaptability:

As businesses evolve, so do their needs. Technology provides the scalability and adaptability necessary to accommodate growth and changing market dynamics. Cloud computing, for instance, allows businesses to scale their infrastructure effortlessly, ensuring that technological capabilities grow in tandem with the organization.

5. Competitive Edge:

In a hyper-competitive market, staying ahead requires innovation. Businesses that harness the latest technologies gain a competitive edge, whether it’s through predictive analytics, artificial intelligence, or Internet of Things (IoT) devices. Early adopters often find themselves leading the pack, setting industry standards and trends.

The benefits of utilizing the right technology to manage and analyze your business are vast and transformative. Embracing these tools is not merely an option but a strategic imperative for those aspiring to thrive in today’s dynamic business landscape. By investing in technology, you’re not just adapting to change – you’re shaping the future success of your business. So, let Yalo help you equip your enterprise with the tools it deserves and embark on a journey of innovation and unparalleled growth.

In the dynamic world of marketing, staying ahead of the curve is not just a competitive advantage—it’s a necessity. As we step into 2024, the marketing landscape is set to evolve yet again, presenting exciting opportunities for businesses to thrive in an ever-changing digital ecosystem. Today we’ll delve into the marketing trends that will shape the industry in 2024 and provide invaluable insights for marketers aiming to stay at the forefront of innovation.

1. AI-Driven Personalization: Elevating Customer Experiences
   In 2024, artificial intelligence (AI) will play a pivotal role in transforming customer experiences. AI algorithms will analyze vast amounts of data to understand consumer behavior, preferences, and habits, enabling marketers to deliver hyper-personalized content. From tailored product recommendations to customized marketing messages, AI-driven personalization will enhance engagement and foster stronger connections between brands and consumers.

2. Immersive Technologies: The Rise of Augmented and Virtual Reality
   The immersive experience is the future of marketing. Augmented Reality (AR) and Virtual Reality (VR) will take center stage, providing innovative ways for brands to engage with their audiences. Imagine customers trying out products virtually before making a purchase decision or experiencing a brand’s story through immersive VR campaigns. These technologies will not only capture attention but also leave a lasting impression, creating memorable interactions that drive brand loyalty.

3. Voice Search Optimization: Conversational Commerce
   As voice-enabled devices become increasingly ubiquitous, optimizing for voice search will be a game-changer in 2024. Marketers must adapt their SEO strategies to accommodate natural language queries, as consumers embrace the convenience of voice-activated search. Brands that prioritize voice search optimization will have a competitive edge, ensuring their products and services are easily discoverable in the era of conversational commerce.

4. Sustainability Marketing: A Shift Towards Purpose-Driven Brands
   In 2024, consumers will place a higher premium on sustainability, and brands that embrace eco-friendly practices will resonate more with their target audiences. Sustainability marketing will go beyond mere greenwashing, with consumers expecting transparency and authenticity. Brands that genuinely commit to environmental and social responsibility will not only contribute to a better world but also build a positive brand image that resonates with conscious consumers.

5. Influencer Partnerships and Collaborations
   Influencer marketing remains a potent tool for reaching targeted audiences and building brand credibility. However, 2024 will see a shift towards more authentic and long-term influencer partnerships rather than one-off collaborations. Brands will seek to establish genuine relationships with influencers who align with their values and resonate with their target demographics, fostering trust and credibility among consumers.

As we navigate the complexities of the marketing landscape in 2024, embracing these emerging trends will be crucial for staying competitive and driving meaningful engagement with consumers. By harnessing the power of AI-driven personalization, voice search optimization, augmented reality experiences, purpose-driven marketing, and authentic influencer partnerships, brands can forge stronger connections, foster loyalty, and achieve sustainable growth in the years to come.

So, gear up for an exciting year ahead and let Yalo help you embrace these trends to propel your marketing efforts to new heights in 2024!

As a new year begins, marketers are predicting which marketing trends will matter the most and placing their bets (and budgets) on those they believe will show the most return on investment. Here below are five tactical trends that we see adding value to the market(ing) place in 2023.

1. A Greater Emphasis On Building A Strong Brand

A strong brand can build customer loyalty, increase customer lifetime value, drive business growth, and increase the perceived value of your products or services, which can lead to higher prices and more profitability.

A few benefits of building a strong brand:

1. A strong brand helps to establish a company’s identity and sets it apart from competitors.
2. A well-known brand helps to build trust with customers, which can lead to increased customer loyalty and repeat business.
3. A powerful brand can lead to higher levels of customer satisfaction, as customers are more likely to have positive experiences with a well-known and trusted brand.
4. In today’s digital age, a strong brand is also important for online visibility and search engine optimization (SEO). A well-known brand is more likely to show up at the top of search engine results, which can lead to increased traffic and sales.

Full disclosure: Yalo offers our Brand Strategy Bootcamp to help fledgling as well as established brands to dip their toes in the world of brand strategy for greater awareness in the public sector. It’s a fun, informative, effective exercise our clients love to experience!

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2. The Burgeoning Creator Economy

Creators are the beating heart of social media, and their endorsements can shape consumer behavior drastically. The creator economy refers to the network of people who create and share content online, often for a large and engaged audience. Brands can tap into the creator economy in a number of ways:

1. Collaboration: Brands can work with creators to produce sponsored content or to promote their products. This can be a win-win for both parties, as creators get paid for their work and brands get exposure to the creator’s audience.
2. Sponsorship: Brands can sponsor events or projects featuring creators, or they can sponsor a creator’s content directly. This can help the brand reach the creator’s audience and establish a relationship with the creator.
3. Affiliate marketing: Brands can work with creators to promote their products through affiliate links. When a creator’s audience makes a purchase using the link, the creator earns a commission.
4. Product development: Brands can work with creators to develop products based on their content or ideas. This can be a great way to tap into the creator’s audience and get valuable feedback on product development.
5. User-generated content: Brands can encourage their customers to create content featuring their products and share it online. This can help to increase brand awareness and engagement.

Overall, the key to success in the creator economy is to build authentic and mutually beneficial relationships with creators. This can help brands to reach new audiences and stay relevant in an increasingly digital world.

3. The Implementation Of Automation And AI

Artificial intelligence (AI) and automation are being increasingly used in marketing to help companies save time and resources, as well as to improve their marketing efforts. Some common applications of AI in marketing include:

1. Customer segmentation: AI can help companies segment their customers based on various characteristics, such as demographics, behaviors, and interests. This allows companies to tailor their marketing efforts to specific groups of customers.
2. Personalization: AI can be used to personalize marketing messages, content, and recommendations based on a customer’s past interactions with a company. This can help increase the relevance and effectiveness of marketing efforts.
3. Predictive analysis: AI can be used to analyze customer data and make predictions about their future behavior. This can help companies plan and execute more effective marketing campaigns.
4. Chatbots: AI-powered chatbots can be used to interact with customers in real-time, answering questions and providing assistance. This can help companies scale their customer service efforts and improve the customer experience.
5. Content creation: AI can be used to generate marketing content, such as social media posts and email subject lines. This can help companies save time and resources on content creation.

Another disclosure! Yalo has been offering Sentiment Analysis services powered by AI for some time now for business intelligence for our clients.

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4. The Cost-Efficiency Of User-Generated Social Media Videos

TikTok and user-generated social media videos that organically draw in an audience or create word-of-mouth are the best bang for your buck. There are several benefits of user-generated social media videos:

1. Authenticity: User-generated content is typically more authentic and genuine than content created by brands. This can help increase trust and credibility with your audience.
2. Cost-effective: User-generated content is often free or low-cost to produce, as it is created by individuals rather than professional marketers.
3. Increased reach: User-generated content has the potential to go viral, which can significantly increase the reach of your brand.
4. Customer engagement: User-generated content can help increase customer engagement by giving them a way to participate in your brand and share their experiences with others.
5. User-generated content can also provide valuable insights and ideas for your marketing campaigns.

5. The Rise Of Web3 And Virtual Influencer Marketing

Brands can leverage web3 technology and virtual influencers in a number of ways. Here are a few potential strategies:

1. Partnering with virtual influencers: Brands can partner with virtual influencers by sponsoring their content, creating sponsored posts together, or collaborating on projects. This can help brands reach new audiences and tap into the influence of virtual influencers.
2. Creating their own virtual influencers: Some brands have created their own virtual influencers to promote their products or services. These virtual influencers can be used to reach specific demographics or to promote products in a more immersive way.
3. Utilizing non-fungible tokens (NFTs): Brands can use non-fungible tokens (NFTs) to create unique, collectible experiences for their customers. This could include exclusive virtual events with virtual influencers, or limited-edition digital goods that are only available through the use of NFTs.
4. Experimenting with new web3 platforms: There are many new web3 platforms emerging that allow for immersive and interactive experiences. Brands can experiment with these platforms to find new ways to engage with their audience and promote their products.

Overall, virtual influencers and web3 technology offer brands new and innovative ways to reach and engage with their audience. By staying up-to-date on the latest trends and technologies, brands can find creative ways to leverage these tools to their advantage.

Let Yalo keep you on-trend in 2023. Subscribe to our free e-blasts below for informative, entertaining and stimulating analysis and critiques on what‘s happening in the worlds of marketing, advertising and pop culture. Scroll down to the bottom of the page if you’d like to start a conversation with us!

Natural Language Processing and text analysis are AI techniques for isolating, selecting and measuring the effective nature of unstructured information. With these techniques, sentiment analysis is applied for understanding customer feedback (reviews, surveys), analyzing social media traffic, creating website content and shaping marketing campaign messaging. 

Sentiment Analysis Techniques

A scored word list is a supervised learning technique for completing sentiment analysis. The scored list or lexicon contains words with scores from most negative to most positive. Numbers assigned depend on the lexicon being used, for example AFINN scores range from -4 to +4. Text is decomposed into its individual words. The individual words are matched against the lexicon, summed and divided by the number of words to get an average score. Lexicons can be developed using surveys and adjusted to address specific domains. This approach can be enhanced with a rules base to address other language features, such as context, multipolarity and negation resulting in a compound calculated score for a piece of text.  The power of this approach is in understanding the effect of each word and then being able to adjust the rules.

Using clustering, unsupervised learning can also be used for sentiment analysis. Like any unsupervised technique data is fed into the model, in this case, text – and in real time the model returns the overall results of positive, neutral or negative. To build the module, representative embeddings must be isolated and scored. Clustering is then completed on the data. The relative location of words in a cluster determines their positive or negative value. Then each word is considered for how unique it is in each sentence. This along with the sentiment scores are used to complete sentence scoring.

Application of Sentiment Analysis Tools

Some applications of sentiment analysis tools include:

Content Creation – confirming intended sentiment for social media and website content

Customer Feedback – analyzing market sentiment towards products and/or services

Product Review – capturing the most valued product features

Brand Image – monitoring social media by segment for sentiments on brand

Stock Market – real time assessment of investor sentiment on stocks, influencing long/short positions

Regulatory Compliance – identify, extract and understand regulatory, legal and medical documents that traditional data analytics techniques can’t handle

Competitor Intelligence – comparing sentiment on social media against competitors

Sentimental Analysis Tools Value

Sentiment analysis confirms the intent of communications: emails, website content and social media postings. This contributes to the reach, impressions and engagement of these communications. With studies indicating positive emotions increase the speed and reach of social messages, sentiment analysis has significant value. In addition to social media applications, sentiment analysis tools also provide value in tracking customer service feedback and product reviews.

Learn about Yalo’s own Sentiment Analysis services for our clients. Contact us please for any general inquiries, here.

Many historical perspectives identify the genesis of Natural Language Processing with Alan Turing’s efforts during World War II cracking the Nazi’s Enigma code machine. By any measure, his Ultra intelligence and Turing machine saved millions of lives and shortened the war by multiple years.

NLP Evolution

After World War II, Turing’s direction involved establishing the foundation of NLP in his article, “Computing Machinery and Intelligence.”  This ground-breaking article is viewed as the first treatise on artificial intelligence. He proposed the “Turing test,” (see below) for addressing the question,” can machines think?” He supported his position by rebutting nine arguments against intelligent machines. The nutshell result -thinking machines do not just isolate the words; they identify what the words mean in context.  

“A computer would deserve to be called intelligent if it could deceive a human into believing that it was human.”  – Alan Turing

NLP Components

Building on this foundation, language translation, language theory, probabilistic and data driven models have yielded what we know of as NLP today. Using NLP, computers dissect, absorb and draw meaning from language in context by:

• Decomposing posts, text, paragraphs and sentences into meaningful words
• Applying a lexicon containing words, expressions and symbols
• Transforming words into a grammatical structure which shows how the words are related
• Defining word structures and their meaning from their context
• Abstracting language meaning for social situations by applying rules

NLP Applications

It is surprising how many everyday situations benefit from the application of NLP. Some of them include:

• Web search – allowing algorithms to read text on a page and translate to another language
• Word processing – supporting grammar and spelling checks
• Translation – computer applications to translate speech or text into another natural language
• Speech recognition – decoding the human voice for mobile telephony, virtual assistance
• Summarization – condensing a text source into a shorter version
• Sentiment analysis – analyzing text before distribution, analyzing customer/product feedback

NLP and Sentiment Analysis

Natural Language Processing as part of the artificial intelligence discipline is the foundation for sentiment analysis. Both supervised and unsupervised learning techniques can be applied to complete sentiment analysis. The approach being used relies on the input word, sentiment values definition, and the level of control desired in understanding, modifying and acting on the results.

NLP Strengths 

Natural Language Processing’s power is derived by its ability to understand and manipulate the human language. This ability delivers exact answers to questions without extraneous information. In addition, NLP can provide structure and sequence to ambiguous information. Yalo utilizes these functions as part of our new Sentiment Analysis services for expanded social media success for our clients.

Unsupervised Learning Defined

In unsupervised learning the model works independently discovering patterns and information that were not previously defined. This learning technique works predominantly with unlabeled data (no defined relationship between inputs and outputs). Using this technique affords the opportunity to address more complex processing tasks vs. supervised learning.

Unsupervised Learning Techniques

An important unsupervised learning technique is clustering. Cluster algorithms find groups within the input data. Clustering allows the user to define the number of clusters that should be identified. The number of clusters determines the specificity of each cluster (e.g. the more clusters the more specific the data within a cluster). Unsupervised learning cluster types include:

• Exclusive – data belongs to only one cluster
• Agglomerative – every data is a cluster with joins to nearest clusters reducing the # of clusters
• Overlapping – data can belong to multiple clusters with an associated membership value
• Probabilistic – probability distribution used for cluster creation

Clustering techniques include:

• Hierarchical – each data is a cluster; related clusters are combined until there is only one cluster
• K-means – Iteration defines the specified number of clusters with cluster centroids being close to assigned cluster data and maximizing the distance between cluster centroids
• K-Nearest Neighbor – algorithm storing all cases and new instances are classified based on a similarity measure

Another unsupervised learning technique is association. In this technique, rules are used to establish associations among objects in large data bases. An application of this technique experienced every day is shopping groups based on eCommerce searches and purchases.

Unsupervised Learning Applications

Customer Segmentation – understanding customer groups for building business strategies and marketing campaigns

Genetics – grouping DNA patterns to study evolutionary biology.

Predictive Maintenance – detecting defective mechanical parts

Dimensionality Reduction – problem simplification by reducing random variables resulting in better data visualization

Ecology – comparison of audio recording of regions for comparison of species population for biodiversity

Delivery Routes – optimize delivery efficiency by determining the optimal number of regional locations and efficient truck routes.

Crime Zones – crime data by specific location including area and category for defining crime concentration locations within a city.

System Alert Management – operations alert messages from IT system components prioritized based on mean time to repair, downstream impact and failure predictions.

Unsupervised Learning Advantages & Disadvantages

Plus

• No prior data knowledge is needed
• Reduces human error
• Identifies relationships between data not obvious through normal inspection
• Excels when there is insufficient labelled data, unknown patterns or evolving learning patterns.
• Simplify human labelling by grouping similar data and differentiating from remaining data

Minus

• Less outcome specificity due to data relationships not being known or named in advance of model building
• Clusters or groupings may not match information areas of interest
• Little control of how clusters or groupings are formed.
• Patterns are identified but uncertainty on next steps to take
• Less appropriate in resolving a well-define problem

One Application Plus that Yalo is investing in for our clients is our new sentiment analysis service – capable of several insightful deliverables that can boost your marketing & branding campaign successes. Contact us today to learn how our new tools powered by AI can be a boon for your 21^st century business.

Supervised Learning Defined

Supervised learning for machine learning occurs independent of the process. A supervisor is available while a machine learns how to complete tasks. After training completion, the expectation is that for new data sets the machine will be able to arrive at correct outcomes. As the number of practices on training data increase, outcome accuracy is expected to increase.

Supervised Learning Techniques

This approach is used when we have enough known data (labeled data) for outcomes that a model is attempting to predict. The learning designs an algorithm which maps inputs to outputs. The supervisory learning uses two techniques. The classification technique is appropriate when inputs can be segregated into categories. A real-world application is where the algorithm categorizes financial transactions as fraudulent or non-fraudulent. The regression technique takes inputs and predicts a single outcome for either continuous or real variables. A real world application would be using baseball Sabermetrics to predict how many games a MLB team will win.

Applications of Supervised Learning

Home Pricing – input data on square footage, number of rooms/bathrooms, yard size for predicting price
Face Recognition – input image to identify matches in surveillance footage
Weather Forecasting – current/historical data for predicting weather and precipitation
Customer satisfaction – sentiment analysis for classifying satisfied/dissatisfied customers
Recycling – robots sorting removing non-recyclable items from a conveyor waste stream
Television Viewing – recommending new viewing alternatives/degree of match based on past viewing
Customer Lifetime Value – determines net business profit of a specific customer over time
Marketing – scheduling, customizing and personalizing content for more effective marketing campaigns

Yalo’s new Sentiment Analysis tools can be a huge help for the marketing tasks described above. Find out more by visiting this page.

Supervisory Learning Advantages & Disadvantages

Plus

• Most appropriate for classification problems and predicting values from known data sets
• More transparent approach compared to unsupervised learning
• Complete control of the content of the input training data set
• Classes and class boundaries are readily evident

Minus

• Not appropriate for more complex machine learning tasks
• Clustering cannot be completed based on input data features
• Large input files can over train the model and distort model accuracy
• Computation and classification processes are time-consuming efforts

While we submit that this is heady material you might not expect to encounter with a creative marketing agency, Yalo is not your typical agency so welcome to our world! We leave no stone unturned as we look for new and innovative methods & tools to give our clients a leg-up advantage in their pursuit of success. One does not need AI to know that this is a smart way to do business. Contact Us below, see examples of our recent work on this page.

What is Intelligence

First, some agreement on what constitutes intelligence is necessary. Depending on the discipline different attributes are valued and therefore constitute intelligence.

• Effective speakers select words considering the sounds, grammar and meaning
• Musicians create and communicate based on sound affect, pitch and rhythm.
• Mathematicians utilize relationships without actions and abstract complex ideas.
• Physicists can visualize/change/recreate images independent of referencing physical objects
• Athletes/dancers control part of or the entire body using motor skills to manipulate objects

A person’s intelligence within a discipline would be recognized by their mastery of the discipline’s attributes. An argument can be made that a machine can be intelligent by mastering one set or multiple sets of attributes.

Elements of Intelligence

When evaluating something as intangible as intelligence, what elements should be considered? It starts with reasoning processes that support extending observable facts/events to general beliefs and/or take general beliefs consider alternatives in coming to specific conclusions. For a baseball player it is baseball IQ; the musician it is a sense of timing or beat; physicist the thought experiment in visualizing the abstract. It includes learning by training, observing and experience which expands the understanding of the discipline. 

Depending on the discipline, listening, recalling experiences, duplicating physical activities and drawing conclusions by relating environmental cues are all techniques for expanding knowledge. These techniques make a decision or choose a process which resolves an issue. They must also consider their surroundings, sensing valid inputs and providing structure. Generating value and knowledge, machines must also have communications skills to understand inputs and document results.

Machine Intelligence

Humans rely on recognizing patterns in applying their intelligence. Each pattern, learned or experienced, has its information and heuristics for a situation. Familiar or stressful situations are facilitated by quick thinking in applying the most familiar pattern. New or complex situations require more thoughtful thinking in perceiving differences, altering existing or developing new patterns. 

Machine intelligence is programmed with attributes focused on a specific discipline. This intelligence relies on taking general beliefs, considering alternatives and arriving at conclusions. This can include understanding that a mistake has been made and avoiding it in the future. 

Intelligent machines evaluate inputs as data by applying sets of rules. While humans search for patterns, machines learning relies on rules/algorithms. Two different techniques are used to develop learning in machines. Supervised learning uses sample data with matched outputs (labelled data) to teach machines to approximate outcomes for new inputs. Unsupervised learning does not rely on labeled outputs – the learning occurs by inferring the natural structure of a set of data points. A differentiator between machine intelligence and human intelligence is in situations with incomplete or distorted inputs – humans can still determine outcomes where intelligent machines can have inconsistent results.

Yalo is embracing machine intelligence/AI with the arrival of our new sentiment analysis services that can recognize language patterns in order to determine social media feedback and popularity for a brand, amongst several other tasks. We are bringing AI to bear on the Web 2.0 world in our relentless pursuit of excellence for our customers. AI rocks!

The world is fast evolving, with Artificial intelligence (AI) at the forefront in changing the world and the way we live. AI is everywhere — at our workplace, in our homes, cars, in our phones and laptops — in short, in the things that have become integral in our lives. Moreover, AI devices know what kind of TV shows and movies we like, what we buy, and how we operate. Let’s explore this world a little deeper…

AI By Definition

It is the ability of a computer to imitate how we think. It is accomplished by learning from previous experience, object identification, language mastery, decision making and problem resolution. These and other capabilities can be combined to perform functions that would be performed by a human. Like a human, with AI, machines can combine input from multiple sources (sensors, digital), analyze information and act on analysis results. Designed by humans, these machines are expected to reach conclusions based on real-time analysis.

AI Explained

Today AI applications are not “artificial,” but focused and contained in functions and features we experience daily such as: word completion while typing, travel directions, eCommerce buying, and television watching recommendations. Although the value of these AI applications is taken for granted, there’s some degree of confusion on terminology. Key terminology that is used includes:

• Artificial Intelligence –used when discussing any computing alternative that demonstrates some human intelligence capability.
• Machine Learning – a subset of AI applying input data to a machine improving its mastery in completing a specific task.
• Deep Learning – a type of machine learning, without human intervention, is self-teaching in completing a specific task with greater proficiency.
  

AI runs the gamut of specific task completion to duplication of human activities by choosing and solving multiple problems without human intervention. The former we experience daily with new applications enabling humans to complete tasks with ever increasing efficiency and accuracy. The latter is currently theoretical and exists only in the realm of the TV series Next.

AI Applied

AI has found its way into our daily living. Some great examples include:

• Speech Recognition – enabling fast and accurate speech transcription in multiple languages for a variety of use cases as seen with IBM Watson
• Natural Language Processing – understanding, interpreting, and generating text, think of email filters, smart assistants, search results, and predictive texts. Learn about a more few prominent examples.
• Machine Vision – identifying/classifying visual images. As a fun example, consider a fill-level inspection system at a brewery. Each bottle of beer passes through an inspection sensor, which triggers a vision system to flash a strobe light and take a picture of the bottle. If the system detects an improperly filled bottle—a fail—it signals a diverter to reject the bottle to then be filled properly.
• Recommendations – suggest purchases/media based on past purchases/viewing. Do you ever wonder why your favorite stores or Amazon suggest certain products or why Netfllix curates certain shows for you? Recommendation engines play a huge role with collaboration filtering.

These use cases depend on machine learning and data analytics combined to deliver intelligent decisions. To remain relevant, they learn from and adapt to information changes in their environment.

What’s Next

Imagination is the only limitation where AI can improve lives but many questions remain.. What is machine intelligence? What tools are most appropriate for different AI use cases? What is the right balance of replacing humans performing tasks vs. supporting them? Want to know what comes next and how to balance the future of machine learning?

Let us help you navigate your business with AI-driven solutions. Yalo uses AI with our new Sentiment Analysis services to help your brand build content, segment customers, and leverage social media more successfully across the board. You don’t need a computer to know a smart idea when you hear one.