Real-Time Marketing Techniques

Is it possible the playbook never actually worked? What we’ve long called a “tried-and-true” GTM strategy might’ve just been a byproduct of a growth-at-all-costs era—one we’ve clung to far beyond its expiration date. The reality... Today, most marketing teams are scrambling. GTM motions are in shambles. Channels that once felt like cheat codes? No longer delivering. Tactics that used to scale? Now barely move the needle. So why are we still pretending those were ever the answers? The environment shapes the strategy—and we’re in a completely new one: AI dominates. Differentiation is minimal. Channels are saturated. There’s no single playbook left to follow. It's time to stop tweaking the old model. It’s time to flip the script entirely. Here’s where I believe modern marketing should focus next: 🔁 Feedback Loops > Funnels Stop optimizing for a static funnel. Build dynamic, real-time loops between product, marketing, sales, and customers. Fast iteration beats perfect planning—every time. 🎯 Hyper-Relevance and Targeting Over Reach Mass reach is dead. Precision wins. Own one narrative for one audience and say it louder, smarter, and more personally than anyone else. Incorporate voices from your existing customers, your dream customers, and everyone else in-between. 🧠 AI-Augmented Creativity Don’t just use AI to scale content. Use it to amplify creative thinking, simulate campaigns, and uncover new angles. The future isn't less human—it’s more amplified. 🤝 Build Communities, Not Campaigns Trust doesn’t come from impressions. It comes from consistency. Long-term relationships > short-term spikes. 📈 Revenue-Centric GTM Vanity metrics are easy to inflate. Revenue impact is not. Align GTM efforts directly with sales and customer success. These teams should be more integrated than ever. ⚙️ Engineer for Adaptability You don’t need more tools—you need more flexibility. Modular stacks, agile workflows, and cross-functional teams that can move fast together.

Markets have reacted swiftly to the escalation of the conflict in the Middle East with moves across equities, credit, currencies, and (most notably) energy—reflecting a rapid reassessment of geopolitical risk. As volatility rises across asset classes, the adjustment to date has largely taken markets (excluding commodities) back toward levels seen late last year. The most immediate potential transmission channel to credit has been energy, where higher oil and gas prices are beginning to reshape regional market dynamics and macroeconomic expectations. While global financial conditions remain broadly supportive and liquidity indicators are still holding up, a sustained energy shock would pose clear risks to growth, inflation, and financing costs that would particularly affect energy-importing regions. For now, credit fundamentals and ratings performance remain stable, suggesting markets are absorbing the shock from a position of relative strength. That resilience, however, is highly contingent on the duration of the conflict—and the balance of risks remains highly sensitive and could swiftly shift. S&P Global Ratings' latest edition of #CreditWeek analyzes the market reaction to the Middle East conflict and what it means for credit, with insights from our subject matter specialists Patrick Drury Byrne, Alexandre Birry, and Nick Kraemer, FRM. Read the full edition this weekend via the link below.

Yesterday’s trading session wiped out lakhs of crores in minutes. At the center of it was HDFC Bank. Not a weak quarter Not a balance sheet issue A leadership exit citing ethical differences was enough. Because markets don’t react only to numbers. And in banking, trust is the core asset. The moment governance uncertainty appears, markets don’t wait for explanations. They price the risk instantly. There’s also a structural layer. With 11% weight in the Nifty 50, a sharp move in one stock doesn’t stay isolated, it impacts the entire index. We as investors are not just investing in financials. We invest in leadership, governance, and credibility too. PS: In the market, perception doesn’t follow reality, it moves ahead of it.

How Have Historical Tariff Announcements Affected The Stock Market Historically, tariff announcements have often caused significant volatility in the stock market, as they introduce uncertainty about global trade relationships, corporate earnings, and economic growth. Here are a few notable examples of how past tariff-related events have impacted the markets: 1. Smoot-Hawley Tariff Act (1930) What Happened: The U.S. imposed high tariffs on over 20,000 imported goods in an effort to protect domestic industries during the Great Depression. Market Reaction: The act is widely believed to have exacerbated the Great Depression by triggering retaliatory tariffs from other countries, reducing global trade. The stock market continued its downward spiral, with the Dow Jones losing nearly 90% of its value from its 1929 peak by 1932. 2. Steel and Aluminum Tariffs (2018) What Happened: In March 2018, President Trump announced tariffs of 25% on steel and 10% on aluminum imports. Market Reaction: The stock market initially dropped sharply due to fears of a trade war but later stabilised. However, specific sectors like manufacturing and agriculture faced prolonged pressure due to higher input costs and retaliatory tariffs from trading partners like China and the EU. 3. U.S.-China Trade War (2018–2019) What Happened: The U.S. imposed multiple rounds of tariffs on Chinese goods, prompting retaliatory measures from China. Market Reaction: Markets experienced heightened volatility throughout the trade war. For example: . In May 2019, when additional tariffs were announced, the Dow Jones fell over 600 points in a single day. . Tech stocks were hit particularly hard due to concerns about supply chain disruptions and reduced demand in China. . By late 2019, partial agreements (e.g., "Phase One" deal) helped markets recover. 4. Tariffs on Mexico (2019) What Happened: President Trump threatened tariffs on Mexican imports unless Mexico took action to curb illegal immigration. Market Reaction: The Dow fell nearly 1,000 points over several days as investors feared disruptions to North American trade. Markets rebounded after the tariffs were called off following negotiations. Key Takeaways from Historical Trends Short-Term Volatility: Markets typically react negatively to tariff announcements due to uncertainty about their economic impact. Sector-Specific Impacts: Industries reliant on global supply chains—such as technology, manufacturing, and agriculture—are often hit hardest. Long-Term Effects Depend on Retaliation: If trading partners impose countermeasures, the economic impact can deepen, prolonging market instability. Safe-Haven Assets Rise: Gold and U.S. Treasury bonds tend to rally during tariff-induced market turmoil as investors seek safer investments. While historical patterns suggest that markets often recover after initial shocks, prolonged or widespread trade disputes can lead to lasting economic consequences.

After 19 years building marketing automation, I can finally see what replaces it: AI systems that reason, not just execute rules. That's why the entire martech stack is about to be rebuilt. Legacy marketing automation platforms remain what they've always been: rules engines wearing a user interface. Those rules are brittle. They can't learn from outcomes. They break when market conditions shift. They require expert-level knowledge and constant maintenance. And they can't handle the ambiguity that defines real buyer behavior. Consider data management. Simple capitalization logic turns MCCOY into Mccoy (instead of McCoy). "Director of Operations" could mean IT Ops, RevOps, or Business Ops? In L2A, a consultant using personal email can't match to their Fortune 500 client. Rules can't handle that ambiguity. THE REASONING BREAKTHROUGH GPT-5 shows 80% fewer hallucinations with Ph.D.-level performance. Claude Sonnet 4.5 runs autonomously for 30+ hours on complex tasks, up from 7 hours four months earlier. DeepSeek R1 achieves comparable performance while being open source. These models reason through problems, understand context, test hypotheses. And the pace of improvement shows no signs of slowing. Applying this to marketing automation, reasoning models can recognize patterns across similar situations without explicit rules, infer relationships from available data, and handle ambiguity by considering multiple signals simultaneously. Journey orchestration becomes adaptive. Today we build flowcharts: if industry = SaaS AND role = VP, send email series A. Reasoning AI orchestrates personalized lists of actions based on actual behavior patterns — understanding when someone is researching versus ready to buy without programmed triggers. Personalization becomes dynamic. Current systems require paths for every persona, stage, industry, personality. Reasoning models determine relevance contextually based on each individual’s history, context, and behavioral patterns. WHAT THIS MEANS FOR MOPS Marketing ops teams won't disappear. But their role will shift from configuring rules-based MAPs to providing context: setting business goals, defining success metrics, establishing guardrails. They'll build data pipelines that give AI access to engagement data, intent signals, product usage, CRM data. The technical work changes. The strategic value increases. After helping build Marketo and watching marketing automation define the last era of martech, I'm seeing the next one take shape. What parts of your rules-based MAP could benefit from reasoning AI? Let me know in the comments, and if you found this useful, please comment or reshare! ♻️ #MarketingAutomation

I don’t believe markets hated the Budget. They hated the surprise. The special Sunday trading session after Budget 2026 turned brutal. Sensex fell 1,546 points, Nifty slipped nearly 2%, and at the day’s low, investor wealth eroded by close to ₹10 lakh crore. Headlines quickly labelled it a “historic budget-day crash.” But markets don’t fall this sharply only on policy disappointment. They fall when positioning, expectations, and sentiment collide. The Real Trigger Wasn’t Growth. It Was Trading Costs. The sell-off was not a referendum on India’s growth story. It was a reaction to one unexpected line item: 👉 The hike in (STT) on derivatives. Futures STT raised from 0.02% to 0.05% Options STT increased to 0.15% This directly hits: High-frequency traders Arbitrage strategies Short-term retail participants When trading costs jump suddenly, liquidity withdraws first prices adjust later. Another factor weighing on sentiment was the absence of direct FPI relief. Despite over $23 billion of equity outflows in the past year: No capital gains tax relief was announced No transaction-cost rollback was offered While foreign individual ownership limits were relaxed, markets felt this was structural but not immediately comforting, especially when trading costs were rising simultaneously. Defence stocks corrected sharply, but not because the policy outlook weakened. The market had priced in a 25–30% capex jump. The actual increase came at ~18%. That gap triggered a classic sell-the-news reaction in a sector that had already delivered strong returns. From a household lens, disappointment was natural. No change in income tax slabs No hike in standard deduction Higher tax impact on leveraged investments Capital gains tax on secondary-market SGBs This Budget did not stimulate consumption today. It prioritised stability tomorrow. That trade-off is rarely popular especially in an inflation-aware economy. Here’s an angle many are overlooking. While the Budget shock hurt sentiment, external tailwinds may now support follow-up buying. The US has reduced reciprocal tariffs on Indian goods from 25% to 18% yesterday. For bulls to regain control, policy clarity must meet global relief and this tariff reduction offers exactly that opening. Markets don’t need good news everywhere. They just need bad news to stop getting worse.

At Forrester’s B2B Summit we heard about some big changes ahead. Here are three I've been thinking about … 1. Buying Networks Are the New Reality Buyers include internal champions, external advisors, partners, even AI agents. Forrester calls this the "Buying Network" and points out that it’s messy, massive, and in motion. ➡️ My take: ABM has always been about reaching buying groups, not individual decision-makers. The “Buying Network” theory expands who we need to influence beyond just the buying group to include a whole network of stakeholders. This makes marketing orchestration more important than ever! Practical tips: • Auto-enrich the buying group as accounts move through the buying stages. • Design always-on, persona-based plays for pre- and post-open opportunity. Email agents can work GREAT here. • Analyze won deals to look at the actual buying network and update the above accordingly. • Pro move: Do this for post-sale renewals as well! :) 2. Growth Strategies Have to Adapt in Real Time Forrester made the case for adaptive growth strategies — rooted in direction, not detailed playbooks. Think bottom-up creativity, cross-functional flexibility, and a culture that adjusts as fast as your market does. ➡️ My take: Easier said than done. Flexibility can feel like chaos if it’s not communicated well to your team. Trying a bunch of things can be confusing and deliver a poor experience to customers if not orchestrated well. Practical tips: • Have capacity dedicated to market-relevant plays. We call these tier 2 plays. They're in-quarter and timely. Tier 1 “lightning strike” campaigns are ones we want to see through for 6 months or more. Tier 3s are the bread and butter, always-on campaigns that get tweaked but consistently deliver well and inherently adapt to buying journey. • Shameless plug: 6sense Intelligent Workflows auto-adjusts campaigns to buying signals, buying groups, and buying stage across all your channels! Like a cheat code for adapting in real-time. 3. GenAI Is Moving From Hype to Habits 89% of buyers use GenAI during the buying process, but only 19% of marketers are using it in production. Why? Gaps in literacy, collaboration, and data readiness. Forrester challenged us to stop tinkering and start transforming. ➡️ My take: In the (paraphrased) words of Seth Godin: Either you make GenAI work for you, or YOU work for GenAI. Practical tips: • Set a goal or your AI agents will always be a side project. We set (and achieved) the goal of using AI agents to generate 20% of our pipeline, allowing BDRs to focus on calling, social touches, and warm intros. • Have a GenAI guru. Sounds cheesy, but someone needs to be testing things, pushing the team, and helping you drive change at the ground level. I think this is our only shot to go from fringe usage to really changing the way we work. If you were at Summit, what were your biggest takeaways? Do you agree/disagree with the above? Let me know ⬇️

At 9:15 AM, the market opened normally. By noon, nearly ₹6 lakh crore of value was shaken. What changed? One line in Budget 2026. Securities Transaction Tax(STT) on derivatives was raised. Futures STT jumped 150%. Options taxes went up too. Cash equities were left untouched. That detail matters. This wasn’t an anti-market move. It was an anti-speculation move. SEBI says close to ~89% of options traders lose money. Yet F&O volumes kept exploding. So the reaction was swift. Sensex fell almost 1,900 points. Nifty slipped below 25,000. India VIX jumped. But the real signal wasn’t the index. It was the stocks that broke. BSE fell 13–14%. Angel One and Groww dropped over 10%. Why? Because their revenues depend on trading churn. This wasn’t about raising taxes. It was about adding friction. India is choosing market discipline over speed.

The Stock Market Index - Bangladesh’s Real-Time Economic Compass: Unlike banking or insurance metrics, which often arrive weeks or months after a policy change, the stock‐market index functions as a real-time barometer of investor confidence. Stock indices as a leading indicator - By reflecting expected corporate earnings and discount rates, equity indices often “lead” changes in GDP by 6–12 months. As a widely followed leading indicator, the stock market aggregates countless bits of forward-looking information, from central-bank minutes to government budget proposals, into a single gauge of economic sentiment. This makes the index a particularly agile tool: a tweet about a subsidy package or even a ministerial comment on a new export incentive can cause index gains or draws in real time, without waiting for a published bank-lending report. Banking and insurance metrics are lagging by design - Liquidity or capital ratios for banks are released only periodically. Regulators compile monthly deposit flows and NPL ratios, insurance firms report solvency margins, premium growth, and claim ratios once a quarter, so any tweak to underwriting rules or risk-buffer requirements takes months to register in publicly available data. Immediate feedback versus delayed confirmation - Because stock markets “price in” new information instantly, policymakers can gauge a measure’s reception within seconds of announcement. In contrast, waiting for banks’ balance-sheet data guarantees that feedback is already stale. This doesn’t mean equity indices tell the whole story, markets can overshoot or overreact. But they do offer a daily snapshot of how private-sector investors interpret policy intent. Why Bangladesh can’t wait - If the stock index is almost a live “macroeconomic scoreboard,” then any half-measures or procrastination in capital-market reform will be felt immediately: Regulatory tweaks (e.g., faster T+1 settlement, reduced stamp duties) will boost turnover and deepen liquidity right away. And incentives for new issuers, like easing corporate-bond registration or offering tax-breaks for IPOs, will prompt immediate underwriting or secondary-market activity. And stronger disclosure norms (e.g., real-time trade-reporting, tighter insider-trading rules) will improve investor trust and can arrest index declines on the same day they’re announced. Put simply: any capital-market policy in Bangladesh is effectively “live-on” the day it’s announced. Waiting for the “right time” only delays the positive impact and risks further erosion of investor confidence. The time to act is now. Policymakers, regulators, and market participants must recognize that every minute of indecision shows up as volatility, or worse, as a sustained slide, on the DSEX, DSE-30 and other indices. Use the index’s real-time feedback to fine-tune measures, rather than chasing lagging banking reports. Bangladesh’s capital market can’t afford to hit the pause button. Tanvir Ghani Masud Khan

One single news wiped out close to ₹1 lakh crore of wealth in minutes. It was HDFC Bank. The reason? The chairman resigned, citing “ethical differences.” No bad quarterly results. No sudden loss. No major financial red flags. And yet, the stock fell sharply and dragged the entire market down with it. This is where most people get confused. “How can such a strong company fall like this?” Because markets do not move only on numbers. They move on trust. And in banking, trust is everything. The moment there is even a small doubt around management or governance, the market reacts instantly. It does not wait for detailed explanations or future clarity. There is another important layer to this. HDFC Bank carries significant weight in the index. So when it falls, the impact is not limited to one stock. It pulls the entire Nifty down, even if other businesses remain fundamentally unchanged. What stood out to me today was not just the fall, but the speed of the reaction. A company that is widely considered stable can suddenly become uncertain in the eyes of the market. Not because the business changed overnight, but because perception did. This is something many investors learn only with time. You are not just investing in financial statements. You are investing in people, decisions, and governance. And sometimes, that matters more than the numbers on the balance sheet. Image credits - moneycontrol.com