Analyzing Customer Behavior Trends

🚨The greatest drop-off is from Product Details Page To Cart Page, so we must improve our Product Details Page! Not so fast ✋ In today's age of data obsession, almost every company has an analytics infrastructure that pumps out a tonne of numbers. But rarely do teams invest time, discipline & curiosity to interpret numbers meaningfully. I will illustrate with an example. Let's take a simple e-commerce funnel. Home Page ~ 100 users List Page ~ 90 users Product Display Page ~ 70 users Cart Page ~ 20 users Address Page ~ 15 users Payments Page ~12 users Order Confirmation Page ~ 9 users A team that just "looks" at data will immediately conclude that the drop-off is most steep between Product Details Page & Cart Page. As a consequence they will start putting in a lot of fire power into solving user problems on Product Display Page. But if the team were data "curious", would frame hypothesis such as "do certain types of users reach cart page more effectively than others?" and go on to look at users by purchase buckets, geography, category etc and look at the entire funnel end to end to observe patterns. In the above scenario, it's likely that the 20 cart users were power users whilst new & early purchasers don't make it to this stage. The reason could be poor recommendations on the list page or customers are only visiting the product display page to see a larger close up of the product. So how should one go about looking at data ? Do ✅ Start with an open & curious mind ✅ Start with hypothesis ✅ Identify metrics & counter metrics that will help prove/disprove hypothesis ✅ Identify the various dimensions that could influence behaviours - user type, geography, category, device type, gender, price point, day, time etc. The dimensions will be specific to your line of business. ✅ Check for data quality and consistency ✅ Look at upstream and downstream behaviour to see how the behaviour is influenced upstream and what happens to the behaviour downstream. ✅ Check for historical evidence of causality Dont ❌ Look at data to satisfy your bias ❌ Rush to conclude your interpretation ❌ Look at data in isolation - - - TLDR - Be curious. Not confirmed. #metrics #analytics #productmanagement #productmanager #productcraft #deepdiveswithdsk

Most brands segment by demographics. Top performing brands segment by behavior. Demographics tell you who someone is. Behavior tells you what they're about to do. 𝗧𝗵𝗲 𝘀𝗲𝗴𝗺𝗲𝗻𝘁𝘀 𝘁𝗵𝗮𝘁 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗱𝗿𝗶𝘃𝗲 𝗿𝗲𝘃𝗲𝗻𝘂𝗲: → Engaged non-buyers (opened 3+ emails, no purchase) → One-time buyers who haven't returned in 60 days → High AOV repeat customers → Cart abandoners by product category → Browse abandoners by price tier 𝗧𝗵𝗲 𝘀𝗲𝗴𝗺𝗲𝗻𝘁𝘀 𝗺𝗼𝘀𝘁 𝗯𝗿𝗮𝗻𝗱𝘀 𝗼𝘃𝗲𝗿𝗶𝗻𝘃𝗲𝘀𝘁 𝗶𝗻: → Age ranges → Location → Gender → "VIP" based on spend alone These aren't useless. But they don't predict action. 𝗧𝗵𝗲 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸: Start with purchase behavior. Recency, frequency, monetary value. Layer in engagement. Opens, clicks, site visits. Add intent signals. Browse history, cart activity, wishlist adds. Build flows around each segment. Not one welcome series for everyone. 𝗧𝗵𝗲 𝗿𝗲𝗮𝗹𝗶𝘁𝘆: A 35-year-old in Texas and a 35-year-old in New York might have nothing in common. But two people who both browsed the same $80 product three times this week? They're the same segment. Segment by what people do. Not just who they are.

What trends will shape the real estate market over the next six months? Here’s what I’m watching as a quiet observer of how India feels about its future: 1. From Price Sensitivity → Value Consciousness People aren’t just looking for cheaper homes. They want more innovative layouts, efficient maintenance, and ROI—not just resale, but in living well. The home is no longer a status symbol. It’s becoming a system of well-being. 2. From Location → Livability The adage “location, location, location” is now “infrastructure, infrastructure, infrastructure.” People follow roads, metros, schools, and air quality. Cities are reshaping not through skylines, but via underground cables and flyovers. Tier 2 cities? Not the next big thing. They are the thing. 3. From Marketing → Trust Capital The new buyer doesn’t believe ads. They believe in testimonials, track record, and transparency. Builders with brand equity, no matter the scale, will win. Your reputation is your marketing now. 4. From Real Estate → Real Utility Warehousing, data centres, fractional ownership, mixed-use microcities— We’re witnessing the “Unbundling of Real Estate.” No longer just brick and mortar. Now: platform, ecosystem, experience. These shifts are quiet, but once they tip, they reshape the demand curve. So if you’re in real estate—stop chasing virality. Build something buyers trust, infrastructure respects, and families stay in. “The best returns come from long-term thinking in spaces where others chase the short term.” Let’s play that long game.

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

While everyone’s focused on inventory and interest rates… I’m seeing deeper shifts in buyer behavior... ones that could define Bay Area real estate for years to come. 1. International buyers are quietly returning 🌏 During COVID, foreign investment dried up almost entirely. But now? I’m seeing strategic buyers from Asia and Europe returning and locking in long-term U.S. assets while headlines still talk “cooling.” These are not speculators but planners. Buying for kids, diversification, or future migration. 2. Empty nesters are upsizing, not downsizing 🏡 Traditional wisdom said: sell the big house, move into a condo. Today’s reality: they want more space for home offices, adult kids returning home, or even hobbies and wellness rooms. Hybrid work and multigenerational living are redefining retirement housing. 3. First-time buyers are outbidding investors on starter homes 👨👩👦 In the past, cash-heavy investors snapped up sub-$1M homes. Now, I’m seeing tech couples with strong financing and heartfelt letters win out. Investors are backing off or shifting to higher-end flips or long-term multi-units. The starter home market is becoming more personal again. 💡 So what does this all mean? → The Bay Area is still a global safe haven quietly drawing international capital → “Downsizing” is no longer the rule for affluent retirees → First-time buyers are gaining ground as investor activity shifts The media may say we’re in a slowdown but on the ground, the story is far more dynamic. 👀 What unexpected trends are you seeing in your market? #bayarea #realestate #housingmarket #property #realtor

Measurement obsession is creating significant gaps in our marketing understanding. I recently observed a company significantly reduce their paid social budget after their last-click attribution model suggested Google search was driving all meaningful conversions. The pipeline showed a marked decline as a result. The reason was straightforward: social had been priming their audience before they searched, but this connection wasn't visible in their outdated attribution model. This pattern is more common than typically acknowledged: • 64% of marketing leaders express scepticism about their tracking data reliability • 42% of the buying decision process occurs before tracking systems detect intent • The average B2B buying committee consists of 5.4 stakeholders • Only 5% of your addressable market is actively purchasing at any given time Most prospect journeys happen in unmeasurable channels: private WhatsApp conversations, Slack communities, LinkedIn DMs, and professional networks where buyers exchange perspectives. This measurement gap is particularly evident in mature B2B categories with higher annual contract values. As sale complexity increases, attribution systems capture proportionally less of the complete journey. Practical approaches to address this: • Develop content that stimulates genuine conversation, reaching your ideal customer profile before active purchase intent • Implement intent-based and behavioural signals to help your sales team prioritise meaningfully engaged prospects • Utilise brand tracking metrics such as share of voice to better understand your brand's presence prior to measurable touchpoints • Account for what you can measure while acknowledging the limitations Marketing strategies that focus exclusively on immediate, attributable ROI often miss critical engagement points. Your brand exists in unmeasured spaces—in professional conversations and prospect consideration—long before formal engagement. Balance short-term metrics with long-term brand development. This isn't about abandoning measurement but rather complementing it with a more complete view of market engagement.

I just finished reading Flywheel's "The Big Shift" report on redefining ROI with Return on Consumer, and it crystallized something I've been thinking about for months. Here are my key takeaways and what they mean for Amazon advertisers. While ROAS has served us well for immediate conversion optimization, it falls short in identifying and nurturing long-term customer relationships. What's exciting about Amazon's canvas is the quality of identity resolution we can achieve. When customers interact with ads and make purchases, we can connect those touchpoints with much higher confidence than other platforms. This isn't just about tracking sales – it's about understanding the complete customer journey. Amazon Marketing Cloud: A Bridge to the Future The recent expansion of AMC's lookback window to five years is more than just a feature update. It represents a fundamental shift in how brands can understand and activate their customer data. This unprecedented access to purchase history, combined with privacy-safe behavioral insights, allows brands to: • Measure true customer lifetime value • Identify high-potential audience segments • Optimize point of market entry (POME) • Drive sustainable growth through data-driven decisions Beyond Last-Touch Attribution One of the most common conversations I have with advertisers centers around breaking free from last-touch attribution. The reality is that customer journeys are complex and non-linear. With AMC, brands can now see how different touchpoints – from Sponsored Products to Streaming TV – work together to drive both immediate sales and long-term customer value. Real-World Impact The report illustrates this perfectly: a consumer might enter a brand's portfolio with hand soap one year, then purchase detergent and dryer sheets the next year, followed by air fresheners and storage products in the third year. This insight, only possible through long-term customer journey analysis, completely transforms how we should think about acquisition strategy and budget allocation. Looking Ahead • The future belongs to brands that can effectively: • Verticalize their ROI approach within Amazon's canvas • Focus on customer lifetime value rather than individual transactions • Use behavioral signals to fuel sustainable growth • Balance immediate performance with long-term customer value The Question for Advertisers The shift to ROC isn't just about new metrics – it's about fundamentally rethinking how we measure success. Are you still optimizing for short-term ROAS, or are you building for sustainable customer lifetime value? Want to learn more? Read the report: https://lnkd.in/gd2DNBfT Like to listen? Check out the podcast: https://lnkd.in/gPzvS7ci How is your organization adapting to this evolution in measurement and optimization?

The 5-Step Marketing Audit Framework That Transformed My Campaigns After auditing 150+ marketing campaigns across B2B and B2C sectors, I've refined this systematic approach that consistently uncovers hidden growth opportunities. Here's the exact framework I use: Step 1: Business Environment Analysis Start with the macro view - economic shifts, industry trends, and competitive landscape. This foundation shapes everything that follows. Step 2: Internal & External Assessment Honest SWOT analysis. Your strengths might be your biggest blind spots if you're not leveraging them correctly. Step 3: Market & Customer Analysis Segment beyond demographics. Behavioural patterns and unmet needs reveal your next breakthrough opportunity. Step 4: Marketing Strategy Review Audit your brand positioning, product offering, pricing strategy, and distribution channels. Misalignment here kills conversion rates. Step 5: Financial Metrics & Performance Focus on high-impact activities. I use the 80/20 rule religiously - 20% of your efforts drive 80% of results. The game-changer? Customer Lifetime Value (CLV) analysis. When I integrated CLV into campaign optimization at 411 Locals, we maintained $11 CPL while scaling to 130K leads. What's your biggest marketing audit revelation? Drop it in the comments - I'd love to hear your experience. P.S. Save this framework for your next campaign review. Trust me, your ROI will thank you.

In recent years, one key trend emerging within the real estate market has been the increasing percentage of homebuyers paying entirely in cash. According to recent data from the National Association of Realtors (NAR), 26% of home buyers last year chose to forego a mortgage entirely, opting instead for all-cash transactions. Notably, there's a significant generational divide among these cash buyers. Older Boomers represent the largest share, with 51% purchasing homes without financing. Younger Boomers also show a strong preference for cash transactions at 39%. In contrast, only 15% of Gen X buyers opted for cash, with Millennials at just 5%, reflecting a stark difference in financial capacity and wealth accumulation across generations. This generational gap reveals critical insights into current market dynamics. Older generations, particularly Boomers, often possess accumulated wealth and equity from previous homes, providing them with the liquidity to avoid higher interest rates altogether. Millennials and Gen X, however, face different financial circumstances. Rising home prices coupled with increased mortgage rates, currently hovering around 7%, are significantly affecting their home-buying capabilities. According to NAR Chief Economist Lawrence Yun, a shift back towards mortgage rates around 5.5% could invigorate buyer activity, especially for younger generations. This interest rate reduction would provide greater affordability, helping younger buyers enter the market or consider upgrading. For Family Offices, understanding this dynamic is crucial. Investments targeting properties appealing to cash-rich Boomers, such as downsized luxury homes or retirement-friendly communities, may provide strategic opportunities. Conversely, identifying and investing in assets attractive to Millennials and Gen X buyers, who remain heavily reliant on financing, requires careful attention to pricing and affordability metrics. The real estate market’s current environment highlights the importance of adapting investment strategies to demographic realities and financial behaviors. As mortgage rates continue to fluctuate, Family Offices should remain vigilant, adjusting their investment focus accordingly to capitalize on these evolving generational trends.

🚨 I've been teaching personalization wrong. After analyzing 1,000+ campaigns, I discovered what the 89% who see ROI actually do differently. It's not what you think. While most brands are personalizing EMAILS... The smart ones are personalizing PREDICTIONS. Here's what I found: The $82 Billion Secret: • Predictive analytics market exploding from $18.89B to $82.35B by 2030 • But 73% of companies still react to customer behavior instead of predicting it • The winners? They know what you want before YOU do 3 Things the 89% Do That You Probably Don't: 1️⃣ Entity Optimization (Not Just Keywords) → They use schema markup to make AI understand their content → Result: 2x more discoverable in AI search results → While you optimize for Google, they're optimizing for ChatGPT 2️⃣ Predictive Personalization (Not Reactive) → They analyze intent data to identify prospects before they're ready to buy → Result: 5x faster lead identification and 300% better accuracy → While you send "personalized" emails, they predict customer lifetime value 3️⃣ Behavioral Forecasting (Not Demographics) → They track micro-behaviors across 12+ touchpoints → Result: 122% higher email ROI and 202% better conversion rates → While you segment by age/location, they predict next purchase timing The brutal truth? 76% of consumers get frustrated when brands fail to deliver true personalization. Your customers can smell "Dear [First Name]" from a mile away. But here's what terrifies me: 71% of B2B buyers now EXPECT personalized digital interactions. If you're not using predictive analytics, your competitors who are will capture your market share while you're still guessing what customers want. The question that keeps me up at night: Are you predicting customer behavior or just reacting to it? What's the biggest challenge you face with implementing predictive analytics?