LiquidCompass’ Post

📢📢Hiring📢📢 ✅ Assignment Based Task✅ I need someone to help me improve my Amazon product listings. They should know how to use popular keywords that people search for on Amazon. They should be good at: ✅ Making titles that are easy to find on search engines ✅ Writing interesting bullet points ✅ Creating product descriptions using HTML ✅ Choosing the right keywords for the backend search terms And they should write everything themselves, without using AI or copying from the internet.

3 steps to a great behavioral story that will get you hired by a company like Amazon: STEP 1. Outline the biggest outcome you are proud of Has to be quantifiable and easily measured (e.g. $$$, time / costs saved, % increase ) STEP 2. Explain step-by-step how you did it. That’s the most important part - list 3-5 things that helped you achieve the big outcome STEP 3. Add important details Why did you do each step? What insights did you get from them? Who did you work with? Boom. You got yourself a winning story. Don’t start writing before you nail these 3 things. Master the basics first. 

Amazon newbies obsess over "the algorithm" with hacks they think will game the system. The pros? They tap into human behavior that truly drives Amazon's algorithm. These newbies then use rule-based software tools designed to outsmart the algo. But these tools are full of human constraints, anchored to expiring tactics. Born from human thought, trapped by it too. So here's the truth: Unlocking human intent on Amazon makes those stiff rules irrelevant. Just look at Amazon's #1 core value: Customer Obsession That's where Profasee steps in. We understand that psychology stays constant, even when Amazon's algorithm doesn't. We read patterns, predict, and dynamically respond — perfectly in sync with the consumer vibe. Understanding the 'why' behind every click is beyond what any static tool can grasp. Most Amazon softwares? They're self-serving, missing the mark on true customer-centricity. Find tools that understand the patterns and psyche of why people purchase your product on Amazon. Build your business around that. A fool armed with a rule-managed tool remains just that — a fool. Understand this. Garbage in, garbage out. Gold in, gold out. When you truly understand Amazon's customers and why and when they purchase from you, you've already won. 🎤✋

Think you've cracked the code on Amazon Listing Conversion Rates(CVR)? 🤔 Think again! Today, I'm here to debunk common myths about your Amazon Listing's CVR. ❌ Myth 1: CVR is out of your control. ❌ Myth 2: You can't control your CVR. ❌ Myth 3: CVR doesn't affect visibility. ❌ Myth 4: CVR doesn't influence trust. ❌ Myth 5: A high CVR is not that important. ❌ Myth 6: Your efforts don't directly impact CVR. ❌ Myth 7: Maintaining a strong CVR isn't necessary. A strong CVR isn't just a metric; it's proof of your listing's effectiveness. A higher CVR means better visibility, trust, and ROI for your efforts. Don't fall for misleading information; let's spread the truth together! What are your thoughts on these myths? Have you also fallen for them before?

This is the area I focused on the most to crack Amazon: Prioritize problem-solving skills over blindly solving 1000+ LeetCode questions ✅ Here are some practices from my experience that can help you to become better at it: 🌴 Understand the question completely and try to solve it with multiple approaches. 🌴 Solve highly-voted questions using a timer. If you are not able to solve it, look into the solution and make sure you solve a similar question next time. 🌴 Lastly, don’t give up; be consistent while improving your problem-solving ability. I know the last one is the toughest to follow, especially if you have a full-time job. That’s why I recommend having an accountability partner who can guide and motivate you in your preparation. You can even connect with such experts for a FREE session - https://lnkd.in/gyjXDwH6 These SDEs at Preplaced have extensive experience and have switched to top companies. They can help you achieve the same results by training you on tech concepts and sharing insider strategies 🚀 Hit 👍 and share if you found it useful. #preplaced

Forced ranking. Stack ranking. Any HR professionals open to sharing your opinions or insights? Or managers in forced/stack ranking environments? Or individuals on their reactions when they realized they were working under these regimes? In the world, it is a shock to many employees when they encounter the annual ritual of sacrificing the "bottom ranking" members. 100% of many world class teams are all “above average.” So why let any of this creme de la creme go? fwiw, I am decidedly *not* a fan. However, we are all grown, consenting adults so let's not make believe that this does not exist. This is front of mind for me seeing AWS recently let go of what I know from my own personal experience to be dozens of top tier, world class professionals. Six months ago business news service CNBC posted the following exposé quoting a former Amazon attorney who defends the utility of ‘stack ranking’: Should a company rate its staff? A former Amazon exec says ‘stack ranking’ is useful when done right https://lnkd.in/gDbb52rb #forcedranking #hr #aws #annualreview #stackrank #stackranking

Is a CS background necessary to crack product-based companies like Google or Microsoft? (You might be surprised by the answer.) Omkar Sawant breaks down the real requirements in this short clip. Curious? 🎥 Watch the full video here: https://lnkd.in/gr7ArKtK What’s your take—do you think a CS degree is essential for landing roles in these companies? Let’s discuss. Share this post if you know someone who needs to hear this.

Gergely Orosz's recent article about why people leave Big Tech (https://lnkd.in/guPM_Z-C) is broadly on point. The article is very long, and methodologically lean (citing data from just "several" engineers), but IMHO the key themes hold: decreasing stability, more growth opportunities in other environments, closed or slower career paths, being forced out (way more common than LinkedIn would let you believe), etc. Ethan Evans had a similar point, saying that "Today there is a good argument that Amazon is more of a down escalator." I'll throw one personal observation into the mix: IMHO, working at Big Tech can be "high experience variance". Meaning: your opportunity to create value for the product or company, and also your experience while doing that work, can vary wildly. This is true even within the same team, let alone between teams or orgs. And of course it varies over time, both organically (e.g., as projects happen) and inorganically (e.g., reorgs, priority shifts). Of course, I am just drawing from my personal experience, so YMMV. My experience was not unidimensional (sometimes I grew technically, sometimes managerially, etc), and time-varying. For some people, high experience variance may seem obvious, but for others, it may be a surprise. Hence, I am sharing this thought for the latter group. If you think "I am joining company X, therefore I expect to do meaningful work, and ideally interesting work", I would suggest not assuming that. Maybe you will, and maybe you won't, sorry to say, it really, really depends. How to optimize for high value experiences is a topic for another time.

Here’s why your “listing optimization” isn’t producing results: Either your execution sucks or your content does. I can’t answer that. I changed this by treating any listing change like a science experiment. “I’m proposing making this adjustment, to effect this specific metric, and expect this type of change” Set a hypothesis. Set into action. Review your results in no less than 2 weeks. Amazon A/B testing tool is great. Use it when you can. Otherwise, the responsibility is on you to implement quality content in a trackable manner. —— Later this week I’m sharing my 78-point framework on turning the subjective content development process into an objective process to ensure you’re not posting crap content to your listings. ✌🏼

Lots of Amazon sellers do the 'fake work'. There's a term for that: 'Sisyphean task' → It's the illusion of making strides when in reality, you're merely spinning in circles. Here's what it often looks like: → Watching tutorials without implementation. → Researching niches without deciding. → Surveying without data analysis. → Perfecting product images. → Tweaking listings endlessly. This means focusing on everything except making that first sale and scaling up. Remember, motion doesn't always mean progress. Break the cycle, take meaningful action!