Real-Time Marketing Techniques

🛑 𝗗𝗼𝗻’𝘁 𝗙𝗹𝘆 𝗕𝗹𝗶𝗻𝗱: 𝗨𝘀𝗲 𝗔𝗜 𝘁𝗼 𝗞𝗻𝗼𝘄 𝗬𝗼𝘂𝗿 𝗖𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 Having trouble keeping pace with your customers' desires and needs? If you're not leveraging real-time data on customer behavior and preferences, you're essentially flying blind. 💥 This lack of insight can cripple your marketing and sales efforts, leading to ineffective customer engagements and stunted sales growth. Here’s where Voice AI steps in as a powerful ally: ❇️ Real-Time Data Collection: Implement Voice AI to engage with customers directly. This technology collects essential data on preferences, concerns, and feedback as the conversation happens. ❇️ Instant Feedback Loop: Set up your Voice AI to provide real-time feedback to your marketing and sales teams. This means they can pivot and adjust strategies instantly, enhancing the effectiveness of your campaigns on the fly. ❇️ Real-Time Alert System: Integrate a real-time alert system within your Voice AI setup. This can notify team members immediately when it detects key customer triggers, like expressions of dissatisfaction or excitement, prompting swift and appropriate action. By integrating these strategies, you'll not only meet but exceed customer expectations, enhancing engagement and driving sales. How are you leveraging technology to stay on top of customer preferences? Share your strategies below! #innovation #digitalmarketing #technology #bigdata #entrepreneurship #voiceai

📌 How to Spot Trends in Your Data (Before Your Competition Does) Data isn’t just numbers on a dashboard, it's your competitive advantage. Spotting trends quickly can help you act on opportunities or avoid pitfalls before it’s too late. But here's the reality: Most organizations struggle to extract meaningful insights from their data. 👉 Let me break down 5 actionable steps to help you uncover trends in your data more efficiently: 1️⃣ Standardize Your Data Sources Inconsistent data is the biggest barrier to trend analysis. Ensure your data is standardized across sources before diving in. Key standardization elements: ⤷ Unified date formats (YYYY-MM-DD) ⤷ Consistent naming conventions ⤷ Standardized currencies and units ⤷ Aligned categorizations 2️⃣ Time-Based Comparisons Raw numbers are hard to interpret, but visualizing them makes trends easier to identify. ⤷ Use line charts to see how metrics evolve over time. ⤷ Add a trendline to highlight the overall trajectory. For example: If you’re tracking website traffic, a YoY chart can reveal seasonality or long-term growth patterns. 3️⃣ Leverage Moving Averages This is my favorite one. Data can be noisy, especially in fast-paced industries like eCommerce. You can smooth out short-term fluctuations by calculating moving averages. Example: ⤷ Instead of focusing on daily sales data (which can be erratic), use a 7-day moving average to understand the overall trends. 4️⃣ Use Filters to Isolate Key Segments Trends often hide within specific segments. That’s why applying filters can help you find them. ⤷ Break down data by geography, demographics, or product categories. ⤷ Look for patterns like higher engagement in certain regions or spikes in specific age groups. For example: Segmenting performance by audience age might show that 25–34-year-olds respond better to your sales campaigns. 5️⃣ Watch for Leading Indicators Not all trends are obvious. But EVERY business has early warning signals. That’s why you need to identify leading indicators in your business. Here are industry-specific examples: ⤷ In e-commerce: Cart abandonment rates often predict future revenue dips. ⤷ In SaaS: Trial sign-ups indicate subscription growth potential. Focus on these early signals to stay ahead of the curve. Spotting trends in data is not necessarily difficult—you just need the right tools and methods. The good thing is that once you understand this, you can go to the next level by setting up automation alerts and be notified when there are unusual trends or patterns in your business (good and bad). 👉 Question for you: Which leading indicators do you track in your business? Share your experience in the comments! #DataAnalytics #BusinessIntelligence #DataVisualization

People don’t say what they mean. They feel what they mean. And that’s where most businesses fail. Today, customer insight means analyzing text such as tweets, reviews, feedback, support tickets. But how do you detect when "This was fine" actually means "Never again"? You don’t need guesses. You need sentiment analysis powered by Machine Learning. There are various method for sentiment analysis with Machine Learning using techniques such as : • Boolean Multinomial Naive Bayes • Maximum Entropy Classifiers (MaxEnt) • NLP features like negation handling, tokenization, and feature binarization • Training on real-world messy data: slang, hashtags, sarcasm, emojis 𝐌𝐋 𝐦𝐚𝐤𝐞𝐬 𝐭𝐡𝐢𝐬 𝐩𝐨𝐬𝐬𝐢𝐛𝐥𝐞. 𝐁𝐮𝐭, 𝐰𝐡𝐲 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐦𝐚𝐭𝐭𝐞𝐫? Because: 👉Twitter sentiment predicts the stock market (Bollen et al., 2011) 👉Mood analytics correlate with consumer confidence 👉Real-time sentiment can forecast market trends, election outcomes, and even product recalls 𝐁𝐮𝐭 𝐡𝐞𝐫𝐞’𝐬 𝐭𝐡𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦: Building this from scratch takes engineers, labeled datasets, and months of work. That’s why we built ARIF Analytics; a no-code AI personal data analyst platform. Just upload your dataset. Ask a plain-language prompt: “What’s the top emotion trend this week?” “Which product reviews mention fear, anger, or surprise?” And we’ll return clean insights. Backed by classifiers. Visualized in dashboards. Explained in plain English. No Python. No API struggle. 𝐉𝐮𝐬𝐭 𝐲𝐨𝐮 + 𝐲𝐨𝐮𝐫 𝐫𝐚𝐰 𝐝𝐚𝐭𝐚 + 𝐚 𝐬𝐢𝐦𝐩𝐥𝐞 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 = 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐢𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞. 🧠 Built for marketers, product teams, researcher, founders. 📊 Works on tweets, emails, support logs, surveys. 🚀 Ready to give your business a boost? 𝑪𝒍𝒂𝒊𝒎 𝒀𝒐𝒖𝒓 𝑭𝑹𝑬𝑬 𝑻𝒓𝒊𝒂𝒍 𝒏𝒐𝒘 → https://app.goarif.co/ As a bonus, here is Sentiment Analysis introduction by Stanford University. Don't miss it!

“𝗬𝗼𝘂 𝗱𝗼𝗻’𝘁 𝗵𝗮𝘃𝗲 𝗮 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗽𝗿𝗼𝗯𝗹𝗲𝗺. 𝗬𝗼𝘂 𝗵𝗮𝘃𝗲 𝗮 *𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻* 𝗽𝗿𝗼𝗯𝗹𝗲𝗺.” This is the sentence I repeat to almost every coach or writer who comes to me feeling stuck. They’re brilliant at what they do. They have great content. They can write with clarity, depth, and even persuasion. But somehow… their posts aren’t landing. They’re not growing. They’re not attracting leads. Here’s the uncomfortable truth: With AI, 𝗲𝘃𝗲𝗿𝘆𝗼𝗻𝗲 can write decent content now. And they can do it 10x faster than ever before. So what really separates you in 2025? → Distribution. And ironically, most people have a strategy for content... But none for distribution. 𝗛𝗲𝗿𝗲’𝘀 𝘁𝗵𝗲 𝟯-𝘀𝘁𝗲𝗽 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗜 𝗴𝗶𝘃𝗲 𝗺𝘆 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 (𝗮𝗻𝗱 𝘂𝘀𝗲 𝗺𝘆𝘀𝗲𝗹𝗳): 𝟭. 𝗕𝘂𝗶𝗹𝗱 𝘁𝘄𝗼 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗰 𝗹𝗶𝘀𝘁𝘀: → 50 niche creators in your exact domain → 50 broad creators with large, adjacent audiences 𝟮. 𝗗𝗼𝗻’𝘁 𝗷𝘂𝘀𝘁 “𝗲𝗻𝗴𝗮𝗴𝗲” — 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 → Read their posts deeply. → Add an angle they 𝗵𝗮𝘃𝗲𝗻’𝘁 covered. → Be early. Top 5 comments = maximum visibility. → Avoid shallow praise. Make it a real conversation starter. 𝟯. 𝗦𝘁𝗮𝘆 𝗰𝗼𝗻𝘀𝗶𝘀𝘁𝗲𝗻𝘁 → Commenting once isn’t distribution. → Building relationships over weeks is. → Get into the habit of 𝗴𝗲𝗻𝘂𝗶𝗻𝗲𝗹𝘆 𝘀𝗵𝗼𝘄𝗶𝗻𝗴 𝘂𝗽. This isn’t about farming likes . It’s about earning trust. And getting your genius 𝘀𝗲𝗲𝗻 by the right people. Because again: You don’t need another content calendar. You need a 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 𝘀𝘆𝘀𝘁𝗲𝗺 P.S. Are you focusing more on content or distribution right now? ♻️ Repost this if it gave you a lightbulb moment. 𝗔𝗹𝘀𝗼, 𝗜 𝗮𝗺 𝗼𝗻 𝗮 𝘀𝘁𝗿𝗲𝗮𝗸 𝘁𝗼 𝗽𝘂𝗯𝗹𝗶𝘀𝗵 𝗱𝗮𝗶𝗹𝘆, 𝗮𝗻𝗱 𝘁𝗼𝗱𝗮𝘆 𝗶𝘀 𝗗𝗮𝘆 𝟵𝟮/𝟯𝟱𝟬. 𝗣.𝗦. 𝗜 𝗵𝗲𝗹𝗽 𝗳𝗶𝗻𝗮𝗻𝗰𝗲 𝗰𝗿𝗲𝗮𝘁𝗼𝗿𝘀, 𝗳𝗼𝘂𝗻𝗱𝗲𝗿𝘀, 𝗖𝗫𝗢𝘀, 𝗮𝗻𝗱 𝗰𝗼𝗮𝗰𝗵𝗲𝘀 𝗴𝗿𝗼𝘄 𝗼𝗻 𝗟𝗶𝗻𝗸𝗲𝗱𝗜𝗻 𝘄𝗶𝘁𝗵 𝗽𝗼𝘄𝗲𝗿𝗳𝘂𝗹 𝗰𝗼𝗻𝘁𝗲𝗻𝘁. 𝗗𝗠 𝗺𝗲, 𝗮𝗻𝗱 𝗹𝗲𝘁’𝘀 𝗺𝗮𝗸𝗲 𝗶𝘁 𝗵𝗮𝗽𝗽𝗲𝗻.

Ever noticed how some brands spend millions on ads but barely anyone shares them? Back in 2014, got fired from my job. Driving home in a tiny Tata Nano, swishing past BMWs, something hit me. With no degree, no guru's blessings, just had to act fast. Created a video, spent ₹350 on it. It went viral. But here's the thing - viral wasn't the goal. Share-worthy was. Those early days taught me the most valuable lesson in content: Stop creating for your brand, start creating for your audience. For some it was a lucky hit. The obsession became cracking the code. Every detail about what makes content share-worthy went into notes. 80 viral videos and 510M+ views later, the core insight remains the same: When you genuinely solve audience pain points, they become your media. No algorithm in the world can stop organic sharing. But most brands? Still stuck in the 'please the boss' cycle, creating content that wins awards but not hearts. Your audience is waiting. Their problems are waiting to be solved. The question is - are you creating for them, or for your quarterly review? Today marks 11 years since that first video. Time flies when you're having fun solving problems worth solving.. #ContentMarketing #ViralContent

New Update: Amazon DSP campaign and creative APIs are now generally available. This is a build on many of the announcements from #unBoxed2024 What is it? This new feature allows users to create, read, and update their Amazon DSP campaigns, ad groups, targets, and creatives through a programmatic interface. How does it work? These APIs enable technology providers and advertisers to develop custom experiences within their own applications and seamlessly run Amazon DSP campaigns within existing workflows. The new APIs can be used in conjunction with existing audience and deal resources, providing a comprehensive toolkit for end-to-end campaign management. Users can now store Amazon DSP campaign data locally, simplify campaign and creative creation, and automate optimizations to maximize campaign performance. Why should I care? This update is a game-changer for Amazon DSP users. Here's why it matters: 1. Efficiency boost: Streamline your campaign and creative creation process, significantly reducing activation time for new campaigns. 2. Better data control: Store and manage Amazon DSP campaign data locally, giving you more control over your data and analytics. 3. Custom optimization: Automate optimizations across campaign, ad group, and targeting settings, allowing for data-driven decisions on bids and budgets. 4. Seamless integration: Easily integrate Amazon DSP into your existing tech stack, enabling you to track campaigns in your own tools and sync campaign metadata with your data storage solutions. 5. Performance improvement: Experiment with new audiences and quickly remove underperforming ones to maximize campaign performance. 6. Real-time adjustments: Automatically adjust bids and budgets in real-time, ensuring your campaigns are always performing at their best. Bottom line: Whether you're a large agency or tech partner looking to integrate Amazon DSP more deeply into your operations or an individual advertiser seeking to automate and optimize your campaigns, these new APIs offer exciting possibilities to enhance your advertising efforts on Amazon's platform. Want to check it out? You can learn more about these new features at the Amazon Ads website (https://lnkd.in/gESdMWhy). For those ready to dive in, check out the developer guide (https://lnkd.in/gQAPRdcs) and reference documentation (https://lnkd.in/gBV-BbVb) to start leveraging these powerful new APIs in your advertising strategy.

Your brand is an illusion if it exists only as a feeling. When you celebrate campaigns and "brand health" but track nothing, your "blind faith" costs you loyalty, growth, and profits. The truth: your most valuable asset is invisible. Unless you measure it. Precisely. Stop guessing about your brand's strength. Start measuring: - Audit Deeply: Understand current health and equity sources. - Track Relentlessly: Monitor awareness, image, and loyalty over time. - Systematize Insights: Build dashboards and reports, making brand equity actionable across the business. - Drive Action: Translate data into recommendations that move the needle. Remember: What gets measured gets managed. Your brand is no exception. Art+Science Analytics Institute | University of Notre Dame | University of Notre Dame - Mendoza College of Business | University of Illinois Urbana-Champaign | University of Chicago | D'Amore-McKim School of Business at Northeastern University | ELVTR | Grow with Google - Data Analytics #Analytics #DataStorytelling

Content is only half the battle. The other half? Getting the right eyes on it. Most B2B marketers focus 80% of their energy on creation: - Let's write another blog post - We need more case studies - Should we make a video series? But they spend 20% on distribution. This is backwards. Here's the reality: - Average content gets 10x results with great distribution - Great content gets 0 results with poor distribution Your competitors aren't creating better content than you They're just better at getting it seen. The best B2B teams flip the equation: → 30% creation, 70% distribution Here's how they do it: 1. Build a distribution-first mindset - Before creating, ask: How will this reach my ICP? - Map out 5+ channels for every piece of content - Plan repurposing before you hit publish 2. Turn 1 insight into 20 touch points LinkedIn post → Newsletter → Blog → Podcast → Email sequence Interview → Short videos → Quotes → Infographics → Thread Case study → Social proof → Sales collateral → Webinar content 3. Leverage other people's audiences - Guest on industry podcasts - Collaborate with complementary brands - Get featured in newsletters your buyers read - Comment strategically on industry leaders' posts 4. Activate your internal network - Train your team to share and engage - Create employee advocacy programs - Turn customers into content amplifiers - Get your CEO posting regularly The biggest mistake? Creating content in isolation and hoping it finds its audience. Your content deserve an audience. Your distribution strategy earns one. Need help building a distribution system that actually works? We help B2B founders create content strategies that generate qualified pipeline, not vanity metrics. → DM me "DISTRIBUTION" to discuss your content marketing strategy.

Surveys can serve an important purpose. We should use them to fill holes in our understanding of the customer experience or build better models with the customer data we have. As surveys tell you what customers explicitly choose to share, you should not be using them to measure the experience. Surveys are also inherently reactive, surface level, and increasingly ignored by customers who are overwhelmed by feedback requests. This is fact. There’s a different way. Some CX leaders understand that the most critical insights come from sources customers don’t even realize they’re providing from the “exhaust” of every day life with your brand. Real-time digital behavior, social listening, conversational analytics, and predictive modeling deliver insights that surveys alone never will. Voice and sentiment analytics, for example, go beyond simply reading customer comments. They reveal how customers genuinely feel by analyzing tone, frustration, or intent embedded within interactions. Behavioral analytics, meanwhile, uncover friction points by tracking real customer actions across websites or apps, highlighting issues users might never explicitly complain about. Predictive analytics are also becoming essential for modern CX strategies. They anticipate customer needs, allowing businesses to proactively address potential churn, rather than merely reacting after the fact. The capability can also help you maximize revenue in the experiences you are delivering (a use case not discussed often enough). The most forward-looking CX teams today are blending traditional feedback with these deeper, proactive techniques, creating a comprehensive view of their customers. If you’re just beginning to move beyond a survey-only approach, prioritizing these more advanced methods will help ensure your insights are not only deeper but actionable in real time. Surveys aren’t dead (much to my chagrin), but relying solely on them means leaving crucial insights behind. While many enterprises have moved beyond surveys, the majority are still overly reliant on them. And when you get to mid-market or small businesses? The survey slapping gets exponentially worse. Now is the time to start looking beyond the questionnaire and your Likert scales. The email survey is slowly becoming digital dust. And the capabilities to get you there are readily available. How are you evolving your customer listening strategy beyond traditional surveys? #customerexperience #cxstrategy #customerinsights #surveys

How to build a marketing team that’s set up to react, not just plan Back in the day, marketers won by planning everything in advance. You’d build a big campaign, map out the rollout, and hope it all landed perfectly. That’s not the game on social anymore. Culture moves too fast. Moments hit overnight. If you're planning a Super Bowl ad, of course you're thinking long term. You're storyboarding. You're lining up partners. You're building something iconic. But most brands aren't living in Super Bowl mode. They're living on TikTok. They're posting daily. They're trying to stay relevant without a $7 million media buy. If you're not already running platforms like TikTok or Instagram, you're missing the chance to fuel what matters in real time. These days, it’s often easier to react quickly and deliver something sharp than to wait for a long-term plan to play out. Most planning cycles don’t allow teams to move fast enough. That’s the disconnect. Here’s how I’d approach it 👇 → Build better systems You don’t need a six-month storyboard to be relevant. You need repeatable formats, clear tone of voice, and fast decision-making frameworks. → Empower small squads Big teams slow down when everyone needs to weigh in. Set up small, trusted groups that can ship content fast without waiting on approvals. → Plan 70%, leave 30% open You still need brand campaigns. But bake in flexibility, reserve time, budget, and energy for the cultural moments you can’t plan for. → Treat real-time like a core channel Build process and measurement around reactive content just like you would for anything else. Structure gives you the right to be spontaneous. If your team doesn’t know how to move, you won’t be able to react when it matters. Being first in the moment beats being flawless after the fact.