Marketing

Old content marketing: - Find high-volume keywords in your industry - Write articles starting with the lowest DA - Make sure your Yoast light turns green - Post a link to the article on all socials New content marketing: - Understand your audience and their pain points - Find product- and pain point-focused keywords - Take time to learn the searcher's true intent - Write great content with distribution in mind - Embed a content upgrade to capture emails - Turn the article into your next email newsletter - Create videos to promote on TikTok/YouTube/Instagram - Write a Twitter thread and promote the blog at the end - Screenshot the Twitter thread for a LinkedIn carousel - Extract and write 5+ LinkedIn posts from the article - Extract and write 10+ Twitter posts from the article - Repurpose and redistribute every 3+ months Do new content marketing in 2025. 1 long-form → 20+ short-form 1 channel → Multi-channel distribution Publish → Promote and repurpose forever

Everyone seems to be talking about AI agents. The biggest problem not enough people are talking about: how to monetize & capture the value of them. Manny Medina, the founder of Outreach (last valued at $4.4B), just took his new startup (called Paid) out of stealth — and announced €10M in pre-seed funding — to tackle this very problem. After analyzing patterns from 60+ AI agent companies, Manny has put together a new framework for AI agent pricing. It's 🔥 — and here's the TL;DR. There are 4 AI agent pricing models dominating the market. Many companies are using just 1 of the 4; others take a hybrid approach. 1️⃣ Price per agent, aka the FTE replacement model See: 11x, Harvey, Vivun Why folks like it: You get to draw from the headcount budget which is at least 10x larger than the tech tools budget. Biggest challenge: Low competitive differentiation. This pricing leaves you exposed to “I-do-the-same-but-cheaper” competitors. 2️⃣ Price per agent action, aka the consumption model See: Bland, Parloa, HappyRobot Why folks like it: It is fairly easy to go after the BPO budget as well as other freelancing agencies with a higher performing offer with better SLAs and lower costs. Biggest challenge: Pricing per activity essentially makes you a commodity and prices only go down. 3️⃣ Price per agent workflow, aka the process automation model See: Rox, Salesforce, Artisan Why folks like it: It strikes a balance between consumption-based and outcome-based pricing, making it ideal for complex but standardized processes. Biggest challenge: If the workflow is complex, it will be hard to price and you may end up upside down with negative margin for a workflow that ran longer and you couldn’t charge for it. 4️⃣ Price per agent outcome, aka the results-based model See: Zendesk, Intercom, Airhelp, Chargeflow Why folks like it: This model creates the clearest value proposition for customers, as they only pay when they receive tangible results. Biggest challenge:  Outcomes may be highly customized which may lead to proliferation of bespoke contracts. And you need a clear path to attribute results to your agent. --- Get the full framework, including an epic decision tree, in today's Growth Unhinged newsletter here: https://lnkd.in/ed8g68wh Can't wait to hear what you think 🙏 #ai #aiagent #monetization

🔵 Stripe just paid $1 billion for something it could have built. That tells you everything about the complexity and urgency of usage-based billing in the AI era. The biggest shift in software monetization since SaaS is happening. Patrick Collison isn't mincing words: 𝐮𝐬𝐚𝐠𝐞-𝐛𝐚𝐬𝐞𝐝 𝐩𝐫𝐢𝐜𝐢𝐧𝐠 𝐢𝐬 "𝐭𝐡𝐞 𝐧𝐚𝐭𝐢𝐯𝐞 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐦𝐨𝐝𝐞𝐥 𝐟𝐨𝐫 𝐭𝐡𝐞 𝐀𝐈 𝐞𝐫𝐚," potentially as big as (or bigger than) the advent of SaaS itself. UBB - Usage Based Billing Payment processing is one layer; monetization logic is another. Stripe is focused now on both. 🔷 𝐓𝐡𝐞 𝐂𝐨𝐧𝐭𝐞𝐱𝐭 Metronome's valuation doubled in less than a year (from $470M in February to $1B now), with 8x growth in platform volume during 2024. Their client roster speaks volumes: OpenAI, Anthropic, Databricks, Nvidia—companies where consumption-based pricing isn't optional, it's essential. The shift makes sense. AI value correlates directly with consumption: API calls, compute time, tokens processed. Traditional seat-based subscriptions simply don't capture how customers actually derive value. 🔷 𝐁𝐞𝐲𝐨𝐧𝐝 𝐌𝐞𝐭𝐫𝐨𝐧𝐨𝐦𝐞: 𝐓𝐡𝐞 𝐔𝐬𝐚𝐠𝐞-𝐁𝐚𝐬𝐞𝐝 𝐁𝐢𝐥𝐥𝐢𝐧𝐠 𝐄𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦 This isn't a one-company phenomenon. This market has exploded with specialized players, each carving out territory. Here are four infrastructure players comparable to Metronome: ‣ Orb – Usage-based billing and pricing infra with strong adoption among modern SaaS and AI companies; Metronome itself positions Orb as its primary direct comparator. ‣ m3ter – Purpose-built usage metering and rating engine for complex B2B SaaS and hybrid models, often grouped with Metronome and Amberflo as the core UBB infra cohort. ‣ Amberflo.ai – Developer-first consumption billing that focuses on metering at scale and “AWS-style” usage pricing; regularly listed alongside Metronome and m3ter as leading UBB startups. ‣ Lago – Open‑source usage-based billing and metering, explicitly branded as a Metronome alternative and highlighted as the strongest choice when teams want control and self-hosting. Stripe chose to acquire rather than build. That signals how complex and critical this capability has become. 🔷 𝐖𝐡𝐲 𝐓𝐡𝐢𝐬 𝐌𝐚𝐭𝐭𝐞𝐫𝐬 Usage-based pricing aligns revenue with value delivery in ways subscriptions never could. It's more transparent for customers, more scalable for providers, and infinitely more adaptable to hybrid models. For financial services and fintech, this is an infrastructure-level transformation. We're not just talking about billing—we're talking about how companies capture value in real-time, optimize pricing dynamically, and build monetization as a competitive advantage. The question isn't whether to consider usage-based models. It's how quickly you can implement them before your competitors do. #Fintech #AI #monetization

70% of outbound doesn’t fail because of bad tools. It fails because it’s "forgettable". Nobody remembers: → How many tools you used → How long your sequence was → How many emails you blasted → How much jargon you packed in Buyers don’t care how hard you worked. They care if you respected their time. What they do remember: → You respected their time → You followed up with care → Your message was relevant → You solved a real pain point Outbound isn’t a numbers game. It’s a relevance game. Too many teams treat it like a lottery: → Blast 1,000 emails → Hope for 10 replies → Call it a win The real cost is huge: → Wasted money on tools → Burned credibility with your ICP → Demoralized teams when nothing sticks That’s why outbound feels dead. But the truth is simple: It’s not dead. Bad outbound is. And I’ve seen this across 50+ B2B teams. The ones who win don’t send more. They send better. The best teams use intent signals, triggers, and activities. Not to spam. But to enrich their data so every message feels relevant. Think funding rounds. Think job changes. Think new hires. Think tech installs. Even a post your prospect engaged with last week. That’s what makes outreach feel relevant even at scale. Here’s what to do instead: → Follow up with care → Lead with relevance → Send fewer, better emails → Keep it short, clear, human Outbound is simple. Respect people. Deliver value. Repeat. Do that, and your pipeline grows. What’s the most memorable cold email you’ve received? - Like the post? Repost ♻️ to help others. Follow Arpit Singh and tap the 🔔 

𝗗𝗿𝗼𝗽 𝘁𝗵𝗲 𝗮𝗻𝗰𝗵𝗼𝗿 𝗳𝗶𝗿𝘀𝘁! One of the simplest, most powerful ways to control a negotiation is to drop the anchor. What’s an anchor? It’s the first offer you make. The number that sets the tone for the entire conversation. Once you set the anchor, every other number will be compared to it. Imagine you’re negotiating a contract. You’re selling, so you throw out a high anchor: “𝙒𝙚’𝙙 𝙡𝙞𝙠𝙚 𝙩𝙤 𝙨𝙩𝙖𝙧𝙩 𝙖𝙩 $𝟮𝟱𝟬𝙠 𝙛𝙤𝙧 𝙩𝙝𝙚 𝙛𝙞𝙧𝙨𝙩 𝙥𝙝𝙖𝙨𝙚 𝙤𝙛 𝙩𝙝𝙞𝙨 𝙥𝙧𝙤𝙟𝙚𝙘𝙩” What happens next? → The other party will compare their expectations to your figure → $𝟮𝟬𝟬𝗸 now feels like a compromise—even if it was their original target Anchoring isn’t just about numbers—it’s 𝗽𝘀𝘆𝗰𝗵𝗼𝗹𝗼𝗴𝘆 Use it to your advantage. 𝗣𝗿𝗲𝗽𝗮𝗿𝗲 𝗬𝗼𝘂𝗿 𝗔𝗻𝗰𝗵𝗼𝗿 → Define your ZOPA (Zone of Possible Agreement) → If you’re buying, aim low - If you’re selling, aim high 𝗧𝗲𝘀𝘁 𝗬𝗼𝘂𝗿 𝗔𝗻𝗰𝗵𝗼𝗿 𝗕𝗲𝗳𝗼𝗿𝗲 𝘆𝗼𝘂 𝘀𝗽𝗲𝗮𝗸, 𝗮𝘀𝗸 𝘆𝗼𝘂𝗿𝘀𝗲𝗹𝗳: → “𝘈𝘮 𝘐 𝘭𝘦𝘢𝘷𝘪𝘯𝘨 𝘳𝘰𝘰𝘮 𝘵𝘰 𝘯𝘦𝘨𝘰𝘵𝘪𝘢𝘵𝘦?” → “𝘐𝘴 𝘵𝘩𝘪𝘴 𝘯𝘶𝘮𝘣𝘦𝘳 𝘨𝘰𝘪𝘯𝘨 𝘵𝘰 𝘰𝘧𝘧𝘦𝘯𝘥 𝘵𝘩𝘦𝘮?” → “𝘞𝘩𝘢𝘵 𝘩𝘢𝘱𝘱𝘦𝘯𝘴 𝘪𝘧 𝘸𝘦 𝘥𝘰𝘯’𝘵 𝘮𝘢𝘬𝘦 𝘢 𝘥𝘦𝘢𝘭—𝘤𝘢𝘯 𝘐 𝘢𝘧𝘧𝘰𝘳𝘥 𝘵𝘰 𝘱𝘶𝘴𝘩 𝘩𝘢𝘳𝘥𝘦𝘳?” 𝗗𝗲𝗹𝗶𝘃𝗲𝗿 𝘆𝗼𝘂𝗿 𝗮𝗻𝗰𝗵𝗼𝗿 𝗰𝗼𝗻𝗳𝗶𝗱𝗲𝗻𝘁𝗹𝘆. It must sound like a fact. No hesitation. No over-explaining. Say: “𝙒𝙚’𝙧𝙚 𝙥𝙧𝙚𝙥𝙖𝙧𝙚𝙙 𝙩𝙤 𝙨𝙩𝙖𝙧𝙩 𝙖𝙩 $𝟮𝟱𝟬𝙠 𝙛𝙤𝙧 𝙩𝙝𝙞𝙨 𝙥𝙝𝙖𝙨𝙚.” Then 𝙎𝙏𝙊𝙋 𝙩𝙖𝙡𝙠𝙞𝙣𝙜. Let them respond. Anchoring works because it sets the stage for the negotiation. It also sets the rules. You know me, I always do my research, and on anchoring it shows: → The final price is often 𝟴𝟱% 𝗰𝗹𝗼𝘀𝗲𝗿 𝘁𝗼 𝘁𝗵𝗲 𝗳𝗶𝗿𝘀𝘁 𝗼𝗳𝗳𝗲𝗿 than the midpoint between both parties → Sellers who anchor high usually 𝗱𝗼 𝗯𝗲𝘁𝘁𝗲𝗿 than those who wait But remember: anchoring is a tool, not a weapon. Push too hard, and you risk losing the deal or the relationship. So, have you ever used anchoring in a negotiation? → Did it give you the upper hand? → Or did it backfire? Drop your story in the comments. I’d love to hear how you’ve used this strategy. Or DM me if you’re curious about how to apply it in your next big deal. ----------------------------- I’m Scott Harrison, and I help professionals master negotiation in high-pressure, high-stakes situations. 📩 Subscribe on LinkedIn: to my weekly 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿, "𝗡𝗲𝗴𝗼𝘁𝗶𝗮𝘁𝗶𝗼𝗻 𝗠𝗮𝘀𝘁𝗲𝗿𝘆": https://lnkd.in/g2wWGJGQ - ICF Coach | EQ-i Practitioner | IAF Facilitator - 24 yrs | 44 countries | 200+ B2B clients - Negotiation | Conflict resolution | Closing deals

If digital commerce were a bustling city where your brand is just one of the cool spots to hang out, it would be New York City, Shanghai, or Mumbai. Can you visualize what your eCommerce, marketing, brand, IT, and supply chain teams deal daily? You've gotta know the hot spots, the trendy new joints, and the go-to tech that makes the city buzz while you tie all this to the business objective. Map out who's who and what's what, so you can see how your brand fits into this extraordinary landscape. What I'm trying to tell you is to stay aware of the hustle and bustle but see the big picture. Not every digital bell and whistle is going to be your jam. Figure out which ones will get your brand grooving and which ones are just noise. As a digital leader, you've got to make sure that everything jives together. Your tech should be like a great band—everything in sync. 📍Prioritization of digital capabilities is key. Not all digital capabilities are created equal, and not all will deliver the same level of impact. Assess the potential ROI of each capability and align them with your brand’s strategic goals. Develop a roadmap for implementation that reflects both short-term wins and long-term investments. That's what I did for 3 different companies, now I talk to many more CPGs about this thanks to my role at EPAM. 📍 Look for interoperability when selecting technologies. Your tech stack should not be a collection of independent tools, but a cohesive platform where data and processes flow seamlessly. Pilot programs to test how well solutions integrate with each other are imperative. 📍Digital strategies should not be one-size-fits-all. Customize your approach based on the retailer and market nuances. Understand the unique needs of each channel and region, and tailor your tech stack to address those specifics. 📍When Requesting Proposals (RFP) for new capabilities, be clear about your objectives, desired outcomes, and the metrics by which you will measure success. Look for partners who are not just vendors but strategic allies. 📍Create a visual model of your digital capabilities similar to the one we have developed. This should outline how each capability contributes to the customer journey and how they interact to drive overall value. 📍Digital commerce is an ever-evolving field. Adopt an agile mindset that allows for rapid iteration and continuous improvement. 📍Use actionable insights to drive decisions about your digital capabilities and to personalize the customer experience, making your teams' lives easier. 📍Ensure your teams have the skills necessary to leverage new technologies. Invest in ongoing training and upskilling more than hiring so many digital natives from outside. Above all, the end goal is to provide a superior customer experience. Every digital capability added should have a clear link to how it enhances the customer journey. EPAM Systems EPAM Continuum #ecommert #ecommerce #strategy #digitalshelf #retailmedia

⏳ Time-based billing is on life support. AI-first consultancies are proving you can charge only when the outcome happens—and still keep software-grade margins. Here’s why it matters: when an “AI teammate” handles ~80 % of the repetitive grind, blended gross margins climb to 60–70 %. Clients stop paying for slide decks; they pay for certainty. Need proof? Mayfield-backed Gruve bought a $5 M security shop, plugged AI into incident response, and hit $15 M ARR in six months—while holding an 80 % margin because customers pay $0 unless a breach is investigated. And the real prize isn’t Fortune 500 boardrooms; it’s the 100 M small businesses worldwide that can’t afford big-ticket advisors. Outcome-based pricing opens that door overnight. Your move: if your SOWs still track billable hours, what would it take to flip the model and get paid purely for impact? Or, for clients, purely pay for impact? #AI #Consulting #OutcomeBasedPricing #FutureOfWork #Growth https://lnkd.in/eUPVba8P

Since posting our guide on how to price AI software, I've been inundated with founders looking to talk through pricing strategies for their startups. Unfortunately, most are skipping the critical first step.   They are spending lots of cycles iterating on "how" to charge (e.g., usage-based, outcome-based, hybrid, etc).   But they're neglecting the most foundational element: how much to charge. We're finding that with proper ROI frameworks, AI products are able to capture 25-50% of created value, which is significantly higher than traditional SaaS's 10-20%.   Here's how the best founders are achieving these pricing levels:   1️⃣ They bring pricing discussions into the sales conversation early   The worst thing is waiting until procurement to talk about pricing. The role of enterprise procurement departments is to minimize spend, not to assess value. They lack budget categories for 'AI that does the work of 3 people'—so they'll try to squeeze you into their existing software line items.   When prospects seem hesitant to discuss ROI upfront, don't push. Instead, propose a value audit session. Sit down with them after they've used your product for a few months and calculate ROI together based on real usage data.   I've seen founders use this brilliantly during negotiations: "I'll give you a discount, but in six months we need to do a value audit." It's a fair trade that shifts the conversation to outcomes.   Here's a bonus move: always offer outcome-based pricing even if customers don't choose it. Simply presenting it signals confidence and willingness to share risk. When positioned alongside a fixed fee, it makes the fixed fee look fair by comparison.   2️⃣ They calculate ROI holistically, not just hard savings   Most founders focus only on labor reduction or vendor spend cuts. But that leaves money on the table.   Factor in the opportunity cost of time efficiencies. Include potential implementation cost differences compared to traditional SaaS. In many cases, AI products deploy faster and cheaper, which should be reflected in your ROI calculations.   Work with buyers to agree on ROI inputs upfront. Once they've signed off on the framework, challenging the outputs becomes much harder.   3️⃣ They use the "acceptable, expensive, prohibitively expensive" technique   Rahul Vohra used this exact approach from Madhavan Ramanujam’s "Monetizing Innovation" to price Superhuman:   To gauge willingness to pay, ask three questions: 1. "What would be an acceptable price?" 2. "What would be an expensive price?" 3. "What would be a prohibitively expensive price?"   Willingness to pay typically lands near the "expensive" point.   --   I've watched too many brilliant AI founders build incredible products only to leave millions on the table by treating pricing level like an afterthought.   Don't be one of them.   P.S. The complete pricing guide (with the decision framework and tactical playbooks) is live on our website. Link is in comments.

Building a Brand in the Digital Age: Key Strategies for Startups 🚀 Hi everyone! Ankita here, sharing some essential branding strategies for startups navigating our digital-first world. In today's crowded space, strong branding isn’t just an asset—it’s crucial for standing out, building trust, and driving growth. Why Branding Matters In a world flooded with options, effective branding helps your startup connect, build loyalty, and grow. Here’s how: 🌟Craft Your Brand Story A compelling story makes a lasting emotional connection with your audience. Brands with strong narratives see increased loyalty. Tip: Share behind-the-scenes moments and customer testimonials. 🌟Use Data-Driven Marketing Data insights let you understand your audience better, boosting effectiveness. Companies using customer data can increase profitability by 10-15%. Tip: Utilize tools like Google Analytics to tailor your strategies. 🌟Invest in Visual Branding Consistent branding enhances recognition. Professional visuals, from logos to websites, are essential. Tip: Create a style guide for colors, fonts, and elements. 🌟Embrace Social Responsibility Consumers lean toward brands that share their values. Aligning with social causes can drive loyalty. Tip: Be transparent about eco-friendly practices on your platforms. 🌟Leverage User-Generated Content (UGC) Encourage customers to share experiences with your brand, boosting authenticity and engagement. Tip: Use branded hashtags and UGC campaigns. 🌟Optimize for SEO Strong SEO improves visibility, especially as 75% of users don’t scroll past the first page of search results. Tip: Integrate relevant keywords into your content. 🌟Engage Actively with Your Audience Building a community requires real interaction. Responding to comments fosters trust. Tip: Use polls, Q&As, and live chats to connect and gather feedback. 🌟Monitor Brand Health Tracking metrics like awareness and loyalty helps inform growth strategies. Tip: Use surveys and brand tools to keep tabs on audience perception. 🌟Moving Forward Digital tools give startups unique branding opportunities. By focusing on these strategies, we can build brands that connect, engage, and thrive in today’s landscape. Let’s share ideas on enhancing our branding in this digital age! 💡 #StartupBranding #DigitalMarketing #BrandingEssentials

Assuming your firm still follows the practice of billing for time, you can run the calculations that will chart the eventual demise of your revenue model. If you’re like most firms, Generative Artificial Intelligence currently shaves somewhere between 20 and 30 percent off the time it takes to deliver work to your clients. What do you think that figure will be next year, or five years from now? Consider what kind of revenue stream will you have when time-tracking humans are doing only 5 or 10 percent of the work. Even the most hard-core defenders of hourly billing can see this compensation model is wholly unsustainable in the world of the AI-optimized agency. There is simply no way to monetize the value of AI within the framework of hourly billing. The solution to this dilemma requires agency professionals to remove the blinders that have them trapped in the illusion that they are selling time, efforts and activities to their clients. That’s not what clients buy; they buy solutions to their business problems. So the way to capture the value you create for your clients is to stop charging for the cost of your services and start charging for the value of your solutions. Every firm of every size can make this change much easier than they think. Instead of a chart of hourly rates, develop a chart of deliverables — a “pricing guide” that indicates the price (market value) of every deliverable your agency produces, and base your pricing on the work or solution delivered instead of the hours worked. In context of an output/outcome driven compensation model, it should be of no consequence to your clients that AI-powered tools are helping you create and produce your work. Again, they’re buying the outputs, not the inputs. So as AI helps you deliver your work faster and better, both parties benefit. Your clients get better quality work faster and the agency incurs lower costs — a win/win. Even if clients insist on slightly lower pricing (because they assume AI lowers the costs of your human capital), agencies can provide lower prices and still make a healthy margin on their work. In fact, agencies should be able to earn a much higher profit, even if they agree to lower prices, because AI is such a powerful force multiplier. It’s not inevitable that agency revenues will decline, because as AI continues to enable faster work, clients are assigning higher volumes of work to their agency partners. The result can be the best of both worlds: higher revenues from a higher volume of work, and stronger margins because AI is such an efficient virtual knowledge worker.