7 Marketing Newsletters To Follow on LinkedIn in 2025. AI Predicting Demand Generation. Ultimate Social Media Detective

Ever feel like marketing is changing so fast you can’t keep up?

One minute, you’re mastering email funnels. The next, some AI tool is rewriting your job. And don’t even get me started on social media—one algorithm tweak, and poof, your reach is gone.

That’s why smart marketers don’t just wing it. They follow the right people, read the right stuff, and stay ahead of the game.

Lucky for you, I’ve done the digging.

In the first part of Edition #47 of Vik’s M.I.X (Marketing Insights Exchange), I’ll share the seven newsletters you should absolutely follow on LinkedIn in 2025 if you want to stay sharp, relevant, and—most importantly—profitable.

Then, we’ll talk about how AI is becoming the future of demand forecasting.

Companies are now using AI to predict demand, move faster, stock smarter, and market better.

Quantum computing and generative simulations are anticipating everything.

And finally, we’ll dive into how brands are no longer relying on gut feelings and manual monitoring to track social sentiment.

Let’s see how AI processes millions of comments at lightning speed, giving businesses real-time insights to stay ahead of trends, fix issues fast, and connect with customers in a smarter way.

Here’s what I have for you.

7 marketing newsletters on LinkedIn in 2025 to follow
AI Predicting Demand Generation
Ultimate social media detective

Let’s go.

7 Must-Follow Marketing Newsletters on LinkedIn in 2025

1. Growth in Reverse by Chenell Basilio

What’s in it? A deep dive into how top newsletters grow. Real breakdowns, no fluff.

Why you’ll love it: Chenell reverse-engineers the biggest newsletter successes—so you don’t have to. She digs through archives, studies their moves, and lays out the growth hacks in plain English.

2. Creator Science by Jay Clouse

What’s in it? Strategies to grow your audience, monetize content, and turn creativity into cash.

Why you’ll love it: Jay’s like that friend who always knows the real game behind content. He tests what works, shares what flops, and gives you the playbook on making money online.

3. Marketing Dive

What’s in it? A daily dose of marketing news—straight, simple, and actually useful.

Why you’ll love it: No nonsense, no clickbait. Just clear updates on advertising trends, digital shifts, and what’s working right now.

4. Social Media Today

What’s in it? Social media trends, updates, and algorithm changes before they blindside you.

Why you’ll love it: If Meta, X (Twitter), or TikTok sneeze, this newsletter tells you first. Stay ahead of platform changes before they wreck your engagement.

5. Geekout by Matt Navarra

What’s in it? The only social media newsletter you’ll ever need.

Why you’ll love it: Matt’s a legend in the social media world. He’s got insider info, leaks, and insights straight from the source. If you work with social, you need this one.

6. MarketingProfs

What’s in it? A mix of everything—content marketing, email strategies, social media tips, and even analytics.

Why you’ll love it: Whether you’re a solopreneur or working at a big agency, this one keeps you in the

know without overwhelming you.

7. Social Media Examiner

What’s in it? The why behind social media trends, not just the what.

Why you’ll love it: Instead of just listing changes, this newsletter tells you how they affect your strategy—and what to do next.

AI Predicting Demand Generation

Back in the day, businesses looked at old sales data and made guesses about what might happen next.

But that’s like driving while looking in the rearview mirror. AI, on the other hand, takes in real-time data from all over the place and spots patterns humans would totally miss.

The Data Goldmine

AI pulls info from everywhere, like:

Purchase history: What people bought, when they bought it, and how often they come back.
Online behavior: Searches, social media likes, product reviews—everything a customer does online leaves clues.
External factors: Weather, economic trends, even what’s trending on TikTok—AI connects the dots between all of it.

Example? If searches for rain boots spike in a certain city, AI doesn’t just stock up stores—it tweaks ad campaigns to push waterproof gear in that region. Smart, right?

AI That Understands Customer Feelings

Numbers are great, but words tell a deeper story. AI with Natural Language Processing (NLP) digs into customer reviews, tweets, and blog posts to figure out what people really think about products.

A 2023 study showed AI could predict buying behavior with 91% accuracy just by analyzing 300,000 product reviews. So, when people start raving about a skincare ingredient, AI spots the trend before it blows up—and brands can act fast.

How AI Predicts the Next Big Thing

Machine Learning Models That See the Future

The real magic happens when AI takes all that data and runs it through predictive models like:

Gradient Boosting Machines (GBM): Keeps improving itself, learning from past mistakes to get more accurate over time.
Deep Learning Networks: Spots hidden patterns in sales cycles and consumer habits.
Ensemble Methods: Think of it like getting advice from multiple experts—AI combines different models for the best results.

Retail giants now use reinforcement learning to adjust prices on the fly, based on how much demand is about to spike. So, next time you see a price jump overnight—blame the bots.

Why People Buy: AI Meets Psychology

It’s not just about what people buy, but why they buy. AI now blends psychological theories, like the Theory of Planned Behavior, into its predictions. It analyzes:

Attitude: Do people like the product?
Social Influence: Are influencers hyping it up?
Control: Can they actually buy it (price, availability, etc.)?

With Explainable AI (XAI) tools like LIME, brands can even see what factors drive purchases—so they’re not just guessing.

AI in Action: How Businesses Use Predictions

Smarter Inventory Management

Gone are the days of warehouses stacked with unsold junk. AI predicts exactly how much of a product is needed and where. For example:

A fashion retailer can stock winter coats only in cities where cold weather is coming.
Car manufacturers adjust parts orders based on real-time dealership sales and economic trends.

This cuts overstock by 30% and avoids empty shelves when demand surges.

Marketing That Hits the Bullseye

Marketing teams use AI to test campaigns before they even launch. AI predicts:

Which ads will perform best (A/B testing with 85%+ accuracy).
The best time and platform to run campaigns.
The perfect budget split across channels.

Google’s Performance Max even uses AI to tweak ads in real time for max ROI. No more guessing games.

Crisis-Proofing the Supply Chain

When the 2024 global shipping crisis hit, AI-powered businesses dodged delays by predicting port congestion before it happened and rerouting shipments. The competition? Scrambling to keep up.

Challenges: AI Isn’t Perfect (Yet)

Biased Data = Bad Predictions

AI is only as good as the data it’s trained on. If that data is biased (say, it ignores certain demographics), predictions will be off. Companies now use fairness-aware algorithms to clean things up.

Balancing Personalization and Privacy

With laws like GDPR and CCPA, companies have to tread carefully. AI now uses differential privacy and federated learning to personalize experiences without storing sensitive user data.

AI on Social Media Comments

Social media is messy. It’s a firehose of opinions, emojis, and hashtags flying in all directions.

One minute, people love a brand. The next, they’re tearing it apart. So, how do companies make sense of this chaos?

AI is becoming the ultimate social media detective. It combs through millions of comments, posts, and tweets, turning random chatter into useful insights. Let’s break down how AI makes sense of unstructured data and why it matters.

1. AI Reads Between the Lines with NLP

Sentiment Analysis – AI figures out if people are loving or hating a brand by sorting comments into positive, negative, or neutral categories. If a sudden wave of angry tweets hits, AI flags it before it turns into a PR nightmare.

Topic Modeling – AI doesn’t just count likes; it digs deeper. It groups comments by themes—pricing complaints, product issues, delivery delays—helping brands see what’s really buzzing.

Entity Recognition – AI picks out key terms like brand names, competitor mentions, or product features. This helps businesses track how often their name pops up and in what context.

2. AI Sees What You Post, Not Just What You Say

Text is just one part of social media. AI also processes images and videos using convolutional neural networks (CNNs).

Logo Detection – AI spots brands in user-generated photos. That influencer rocking your sneakers? AI knows.
Visual Sentiment Analysis – AI studies facial expressions in videos to gauge emotions. Happy faces in product unboxings? That’s gold.

3. AI Turns Words into Numbers for Smarter Analysis

AI doesn’t “read” comments like a human—it converts them into something machines understand.

Word Embeddings – Models like BERT and Word2Vec map out the meaning of words and phrases.
Clustering Similar Comments – AI groups similar feedback together, making it easy to spot trends.

4. AI Works in Real Time—Because Social Media Never Sleeps

Social media moves fast, and so does AI. Generative AI models like LlamaParse and VisualBERT process social chatter as it happens.

Crisis Detection – AI can spot viral complaints before they explode.
Live Consumer Insights – AI updates customer profiles based on real-time social activity, predicting what they might buy next.

5. AI Connects the Dots Between Social Media and Sales

AI doesn’t just track comments—it links them to actual business data.

Customer Profiles – AI merges social interactions with CRM data, giving brands a 360-degree view of their customers.
Purchase Predictions – AI predicts who’s likely to buy based on what they post, helping businesses target ads more effectively.

Well, that’s the wrap for edition #47 of the Viks M.I.X (Marketing. Insights. Exchange) newsletter.

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