Senior Amazon Brand Manager PPC/Listing SEO/Sales/Logistics

I started on Amazon as a PPC Ads Manager in 2015. My employer recognized my ability to analyze buyer behaviors and keyword matching, drawing on my earlier work as a WordPress Site Manager. Back then, I also just graduated from college with a Bachelor's degree in Psychology, and later on, I would acquire a license in Psychometry. In 2015, PPC spending and sales were seen as bonus sales rather than a more complete tool, not just to gain ad sales but also to boost BSR and algorithmic favor with Amazon. And so, I was able to scale our account from just $400 in daily sales (around 20 units per day across 2 SKUs) to $1,800 in daily sales after a year. The most SKUs I have handled were a catalog of 700 child ASINs across 150 parent ASINs, with daily sales of around $50k and a daily ad budget of $4k (targeting a TACoS around 9%, with ACoS varying by product lifecycle stage). I am most comfortable scaling Amazon accounts that have plateaued, are moving slowly, or are just starting. The reason for this is that I thrive most on dealing with compliance policies, listing errors, stockouts on significant ASINs/overstock in slow movers, flat files, and auditing accounts, whether it's with the current inventory and logistics process, optimizing listings and keywords, or pruning and optimizing ad campaigns. As a licensed Psychometrician, I have mastered buyer behavior, and thus create listings that convert well while also being keyword-rich for Amazon's post-A9/A10/Rufus algorithm and Bayesian ranking. I also know how to overwrite Amazon-persistent backend listing attributes (e.g., Amazon forcing a specific SizeName format, any listing attributes, or the listing variation theme). As someone who has also recently experienced working in a corporate environment in an energy company as a regional HR associate, I am well-versed with compliance policies, EPA and FIFRA regulations, California Proposition 65, and other possible listing, product, and compliance violations that may need compliance papers, Safety Data Sheet (SDS) or Technical Data Sheet (TDS), flatfile submission, or even creating Root Cause Analysis, Preventive Action, and Corrective Action reports so Amazon can lift listing or even account level suspensions. I am the person you need if you urgently need someone to scale your Amazon business for sustainable growth —whether it's lifting your account from listing suppressions, bad listing content, poorly performing launches, unprofitable ad campaigns, or substandard inventory and logistics management.

Writing, auditing, and optimizing listings are both a science and an art, in the way that you have to strike a balance between strategically incorporating high search volume, conversion, and browse-node-defining exact match keywords for proper indexing and Amazon Bayesian algorithmic ranking, while cracking the art of making the listing title and bullets not too stuffed with keywords, such that it would convert well with real buyers. After all, what's the point of having high search-term relevance and ranking if people have a hard time reading and trusting your listing enough to avoid clicking the next product in the search results? I can tread that narrow line and strike a perfect balance between machine-readability and tapping into the buyer's psyche to convince them to purchase our product. Using tools such as DataRova, DataDive, Helium 10's Cerebro, or even with just Seller Central's free Product Opportunity Explorer, I can research (not just log and mindlessly record), analyze, digest, and prioritize which keywords to include as exact, phrase, or broad match in the listings. After that, I can incorporate the keywords into feature bullets that funnel customers into a journey designed to convert them into buyers. I recognize that each listing can be handled on a case-by-case basis, and so the strategy for each listing's write-up and tone should vary based on the target audience. For example, for the title, I meticulously check the Business Reports to see whether most buyers are on mobile or web, so I know the character count before Amazon truncates the title (80 for mobile, 110 for web). I then prioritize fitting the main keyword and a crucial customer-requested feature into that character count to maximize the likelihood of a higher click-through rate. Speaking of features, I scrape 2-3 top competitors to see which features from the positive reviews are expected to be in our listings, which deal breaker weaknesses from their negative reviews can we capitalize on and present our listing as a product that solves those problems with their specifications or product (thus breaking the barrier of competition), and finally which compromises from neutral 3-star reviews do people usually have to go through so we can capitalize on them by framing our listing as a product that does not compromise on any features. I also use this same research material to craft shoot notes and lifestyle image guidelines to present, through images, to our customers that we are the superior product amongst the competition, given that lifestyle images and A+ Content can drive most of the sales and conversions for many categories. This narrative-driven listing management approach, which focuses on the psychology of buyers by presenting our listing as the best product not through our lens but through theirs, coupled with analytical keyword research on the backend, is a crucial skill set every Amazon brand needs now. And this is something I can deliver beyond expectations if you make me part of your team.

Amazon PPC has shifted from optional add-ons to now critical BSR drivers, as the system now takes into account not only sales for your BSR but also clicks, conversions, traffic, add-to-carts, and even impressions. In my decade's worth of advertising experience on Amazon, I know which metrics to consider, while recognizing that Ad Spend and the general strategy per listing for PPC are case-by-case. Personally, I am comfortable with TACoS levels of 9%-11% and ACoS around 25% - 30% (assuming a conversion rate of 25% and a PPC: Organic ratio of 30% from ads). More importantly, it is crucial that our ad spending makes sense. I make sure every penny you spend on ads is well spent by bidding on keywords that not only generate sales but also help us rank faster within the categories (there are more superior keywords, algorithm-wise, given their relevance to the root keywords associated with the leaf node). I also consider that our ad spend is aligned with and nuanced by our COGs; if we have a 40% margin, it is imperative that we don't exceed specific ad spend percentages across different parts of the product's life cycle. As for tools, if you want me to automate and create nested if-then and complex rules for PPC campaign management, I have extensive experience with Scale Insights, Helium 10 PPC Manager, Seller Board, and Perpetua. In keyword research, I use Helium 10, DataRova, DataDive, or even Seller Central's own Product Opportunity Explorer. I always begin by documenting actual COGs, including manufacturing, variable shipping, FBA fees, and any fee exemptions we can apply for (such as small and light packaging). Once I know the real margins and break-even point, I set the correct TACoS target for each product. For new launches, a heavier ad spend is to be expected, but if you are not comfortable with that, then I can also adjust our spending based on your appetite for risk. For SKUs in the middle of their life cycle, I aim to keep TACoS between 9 and 11 percent, depending on costs and our urgent need for clicks, traffic, and sales (we might be eyeing a best-seller badge or anticipating organic traffic to spike). From there, I optimize each ASIN through data: I analyze search term reports, adjust bids, test day-parting when conversion spikes happen, target top-of-search placements only where they matter, and use display or video ads when they outperform keyword campaigns. My approach is structured and data-driven, but with a focus on human behavior and buying patterns (depending on the niche, our target buyers might be active and even more susceptible to conversion at certain hours of the day). Also, I focus ad spend on keywords that actually move rank and increase the chances of earning badges like Amazon’s Choice, Overall Pick (by tracking our rank in listing trackers like DataRova or Helium 10), or Best Seller, which strengthens organic conversions.

I know Seller Central by heart. I know where we can extract data from Business Reports, Sales Data, Ad Search Term Reports, Product Opportunity Reports, Brand Reports, Inventory Reports, and Brand Health Reports from Seller Central. I know these data can be gathered from premium 3rd-party services such as Seller Board, Seller Locker, Helium 10, and other web apps, but in case of blackouts, outages, or lag in data, I can extract them from whichever platform you ask me to. But more importantly, I know how to resolve issues, ASIN restrictions, and violations, and even account-level violations. Having experience in corporate, industrial, and academic settings, I can create Safety Data Sheets, Root Cause Analysis, and Preventive and Corrective Action Plan Reports, and I can also manage flat files and analyze extracted data into pivot tables to resolve ASIN listing or account-level restrictions. I understand that it is frustrating when the Seller Support team refuses to resolve our issue and instead gives us generic, "canned" messages that are not even remotely related to the specifics of our case. And in those cases, if you need a problem solver on your team, I can efficiently close out cases and issues on the account. I also don't just download and extract data; I analyze and digest it. For instance, by cross-referencing our COGs data with Sales Data, Search Term reports, and PPC Data, we can accurately determine how much more (or less) we can spend on our ads given our TACoS, to squeeze in as much BSR boost as possible while remaining profitable. I know how to manipulate flat files to merge listings or to OVERWRITE Amazon-overwritten listing attributes, such as variation themes or variation attributes (Amazon sometimes implements and insists on its own SizeName, ColorName, Flavor, NumberOfItems, and Unit Count on listings, even when that information is wrong). Whenever evaluating a listing, I painstakingly search for browse nodes and leaf nodes where our BSR can actually land an Overall Pick, Amazon's Choice, or Best Seller badge. Hiring me does not only mean hiring an Amazon VA. If you need a manager who can solve problems and issues that matter to the account's future, I am a perfect match for your team.

I have 10 years of experience in Amazon brand and ad management, with a background in psychology and psychometrics, which enables me to focus on how shoppers read listings, interpret cues, and make purchase decisions. When it comes to product optimization, it should be viewed through two lenses- improving the actual physical product while maximizing the algorithmic and human appeal of listings. We can optimize our listings only to an extent because, at the end of the day, a product must be of good quality for it to be successful on Amazon. I am very keen on evaluating product samples using structured tests grounded in ASTM and ISO practices, and I have connections with labs such as SGS and Intertek for technical validation. I also analyze competitor reviews (scraped from competitor listings) as behavioral data to identify the features customers consistently want and the glaring frustrations across competitors, then turn those insights into precise, actionable product specifications and features that can be the key to breaking the initial barrier to the competition whenever we enter a new niche. On the listing side, I write and structure content around buyer cognition and intent, not keyword stuffing. Using Helium 10 tools, DataRova, DataDive, or any other tools, I target high-value search terms while shaping titles, bullets, and images to reduce decision friction and strengthen trust. As a licensed Psychometrician, I have mastered buyer behavior, and thus create listings that convert well while also being keyword-rich for Amazon's post-A9/A10/Rufus algorithm and Bayesian ranking. For instance, even if the title allows for 200 characters (and words can only be repeated a maximum of twice), Amazon actually truncates the number of characters that they show on the search results, depending on the platform you're viewing it from (mobile vs. web). We can capitalize on this by learning where our customers usually purchase our product (whether mobile or web), and then frame our title based on that trunctuation, so we can insert both high-priority keywords and features at the early tail of the title, thus increasing our click-through rate. This is one of the many strategies I employ that melds data science with human behavior to increase our chances of clicks and conversions. I can also create review-driven shoot notes and lifestyle image plans that address objections and highlight advantages. This mix of psychological insight and market data consistently improves rankings, click-through rates, and conversions.

I’ve done product research every day since 2016, and my process mixes marketplace data with buyer-behavior analysis. I use Helium 10 Black Box, DataRova, DataDive, and Amazon’s Product Opportunity Explorer to determine whether demand is genuinely shared across competitors or trapped in the top 1–2 ASINs. For example, I avoid “$1M named-brand-dominated niches” where two listings absorb 70 to 80 percent of the revenue, and instead prioritize healthier $300K–$600K niches where sales are spread across multiple sellers, creating real room for new entrants. I also model PPC economics and dynamics from the earliest product research phase. A product priced at $12–$14 becomes a trap if the niche’s average winning CPC costs $0.90–$1.20, because the margins cannot sustain that for the full lifecycle without TACoS slowly eroding profitability. I eliminate products that look good in Black Box but collapse once ad costs, COGS, and lifecycle spend are accounted for. My background in psychology also shapes how I evaluate customer intent behind keywords and, thus, predict how easy or difficult it will be to tackle that niche or launch products within it. Some dominant keywords show clear and stable intent, such as “silver duct tape,” where buyers mostly care about color, width, and pack count. Niches like that are predictable and easier to execute. Others have fragmented or subjective intent, like “backsplash adhesive tiles,” where buyers vary widely in what they want: subway vs. brick vs. square tiles, glossy vs. matte, color variations, thickness, form factor, and pack size, even the general vibe, design, pattern, and vibrance of the dyes used. Those niches have so many moving parts in terms of customer intent that it will be challenging to break through the competition, especially if the top competitors already have a head start of thousands of customer reviews. But if demand and margin justify the complexity, I’ll still explore them. This blend of behavioral insight, cost modeling, keyword intent mapping, and data validation helps me identify products that are simple to launch, defensible in their niche, and profitable under real Amazon conditions.

I manage Amazon inventory with a blend of data discipline and practical supply chain experience. I use Sellerboard, Sellics, and Helium 10 to track daily sales, lead times, and remaining stock, then match those numbers against real constraints like production schedules, freight timing, and 3PL capacity. I’ve dealt with supplier delays, inconsistent lead times, container shortages, and forwarder bottlenecks, so my forecasting process is grounded in operational reality, not just best-case spreadsheet scenarios (clarification: I use spreadsheets as a core platform for inventory management, but grounded on other realistic performance metrics such as considering stockouts, using running averages and considering medians and spikes instead of plain averages). During the global supply chain crunch during the past pandemic, I worked through delays, quota limits, port congestion, and inconsistent supplier lead times, so forecasting for Amazon became an extension of that experience. I monitor daily sales, turnaround times, and remaining stock using Sellerboard, Sellics, and Helium 10, then match those numbers against the realities of production capacity, freight schedules, and forwarder availability. I also manage Amazon inventory using a data-driven process, drawing on my years of experience in both HR (which helps deal with people, agents, forwarders, brokers, and suppliers) and marketplace operations. As a licensed psychometrician, I’m comfortable reading people, setting expectations, and pushing suppliers, forwarders, and 3PL partners firmly but without damaging relationships. Integrity matters to me, and it is saddening to hear about VAs in logistics sometimes capitalizing on their positions for “side profits” or questionable charges, and I’m strict about avoiding that. I abhor dishonest processes that put the reputation of Philippine online job workers in a bad light. I keep and will even demand transactions to be clean, well-documented, and fair, with spreadsheets and paper trails that can be easily reviewed, recalled, and audited. Operationally, I use Sellerboard, Sellics, and Helium 10 to track daily sales, lead times, and stock levels, then map them against real constraints such as manufacturing schedules, port delays, and warehouse capacity. I’ve seen the usual Amazon imbalance where best sellers run out of stock while slow movers sit overstocked. I correct this by cleaning the data: removing B2B spikes, separating PPC-driven surges from actual demand, and checking FBA distribution since low stock in major regions kills delivery badges and conversion. I know how to push forwarders and warehouses to stay on schedule without creating hostility, and I adjust forecasts based on realistic turnaround times rather than ideal ones. My approach is straightforward: understand what’s driving sales, confirm demand is stable, account for logistical friction, and order only what the business can move. This keeps best sellers in stock while protecting cash flow from dead inventory.

I write articles that blend creativity, behavioral insight, and SEO discipline. My background in psychology and content work on Amazon taught me how to keep readers engaged and convert them (whether by clicking a product or actually purchasing it). Back in my early years, before I worked on Amazon brands, I wrote WordPress blogs, ad copy, and social media posts. At the start of my Amazon work, I even wrote keyword-structured web blog entries for their website before being allowed to write Amazon listings. I approach each piece with research, clarity, and purpose, ensuring it will please both the human reader and the platform's web crawler (whether Google or Amazon). I integrate SEO tools and data (search volume, semantic intent, competitor language) without letting the writing feel mechanical. I make sure that the content I write ranks well, reads naturally, and persuades, even in competitive niches.

Having experience in corporate, industrial, and academic settings, I can create Safety Data Sheets, Root Cause Analysis, and Preventive and Corrective Action Plan Reports, and I can also manage flat files and analyze extracted data into pivot tables to resolve ASIN listing or account-level restrictions. I can translate complex specifications into clear, accessible content tailored to any audience. With a strong analytical foundation and experience in both psychology and technical documentation, I’m able to write detailed materials while simplifying them for non-technical readers when needed. I create accurate SDS that prevent further account safety scrutiny, Product Data Sheets, Action Plan Reports, and other compliance documents required by Amazon and Walmart, ensuring they meet formal standards without losing readability or precision. My psychology and analytical background help me break down complex issues into logical steps, document corrective actions, and present them in a format that satisfies internal teams and marketplace reviewers.

Clarification: This skill is essentially the same as "Amazon PPC," which I labeled as a 5-star skill. I added this skill (and I am forced to rate it as 3-star because of the limit on how many we can rate as 5-star or 4-star skills), as there are two Amazon PPC skills on Online Jobs PH. Amazon PPC has shifted from optional add-ons to now critical BSR drivers, as the system now takes into account not only sales for your BSR but also clicks, conversions, traffic, add-to-carts, and even impressions. In my decade's worth of advertising experience on Amazon, I know which metrics to consider, while recognizing that Ad Spend and the general strategy per listing for PPC are case-by-case. Personally, I am comfortable with TACoS levels of 9%-11% and ACoS around 25% - 30% (assuming a conversion rate of 25% and a PPC: Organic ratio of 30% from ads). More importantly, it is crucial that our ad spending makes sense. I make sure every penny you spend on ads is well spent by bidding on keywords that not only generate sales but also help us rank faster within the categories (there are more superior keywords, algorithm-wise, given their relevance to the root keywords associated with the leaf node). I also consider that our ad spend is aligned with and nuanced by our COGs; if we have a 40% margin, it is imperative that we don't exceed specific ad spend percentages across different parts of the product's life cycle. As for tools, if you want me to automate and create nested if-then and complex rules for PPC campaign management, I have extensive experience with Scale Insights, Helium 10 PPC Manager, Seller Board, and Perpetua. In keyword research, I use Helium 10, DataRova, DataDive, or even Seller Central's own Product Opportunity Explorer. I always begin by documenting actual COGs, including manufacturing, variable shipping, FBA fees, and any fee exemptions we can apply for (such as small and light packaging). Once I know the real margins and break-even point, I set the correct TACoS target for each product. For new launches, a heavier ad spend is to be expected, but if you are not comfortable with that, then I can also adjust our spending based on your appetite for risk. For SKUs in the middle of their life cycle, I aim to keep TACoS between 9 and 11 percent, depending on costs and our urgent need for clicks, traffic, and sales (we might be eyeing a best-seller badge or anticipating organic traffic to spike). From there, I optimize each ASIN through data: I analyze search term reports, adjust bids, test day-parting when conversion spikes happen, target top-of-search placements only where they matter, and use display or video ads when they outperform keyword campaigns. My approach is structured and data-driven, but with a focus on human behavior and buying patterns (depending on the niche, our target buyers might be active and even more susceptible to conversion at certain hours of the day). Also, I focus ad spend on keywords that actually move rank and increase the chances of earning badges like Amazon’s Choice, Overall Pick (by tracking our rank in listing trackers like DataRova or Helium 10), or Best Seller, which strengthens organic conversions.

Firstly, I would like to clarify that this skill is only rated 3-star because accounts here have a limit on how many we can rate as 5-star or 3-star. I manage logistics with a data-first approach, supported by Sellerboard, Sellics, and Helium 10 for forecasting, inventory planning, and understanding the split between organic and PPC-driven sales. As a licensed psychometrician with HR experience, I’m comfortable coordinating with suppliers, forwarders, and 3PL warehouses, pushing them firmly when needed without creating hostility. Integrity is non-negotiable for me, and I document every transaction and communication so they are easy to audit. Operationally, I choose between FOB and EXW terms and between FCL and LCL shipments based on cost, reliability, and turnaround times. I also adjust plans based on port delays, freight capacity, and realistic lead times to prevent stockouts without incurring the expense of long-term storage. I filter out B2B bulk orders that distort forecasts, monitor seasonality, and track TACoS/ACoS trends to avoid over-ordering products that move only due to heavy PPC spend. I manage shipment plans on Seller Central, negotiate timelines with suppliers, and stay up to date on trade rules, tariffs, and taxes to avoid unexpected costs. My process is straightforward: clean the data, understand what drives the sales, push logistics partners ethically but effectively, and keep inventory healthy across all FBA regions so the business never loses momentum.

I manage sales through data, not guesswork. With ten years in Amazon operations and a background in psychology, I’m used to turning raw numbers into practical decisions that drive growth. I work closely with Amazon’s data ecosystem, Business Reports, COGS, Search Term Reports, ACoS/TACoS, CPC, CTR, and campaign analytics to identify which products can scale, which need spending cuts, and which listings need optimization to improve organic momentum. I evaluate how PPC performance interacts with COGS and total revenue, audit listings for keyword alignment, and use historical data to decide where investment actually produces results. I also pull insights from inventory and sales reports to avoid blind spots that slow brand growth. If a company values decisions grounded in evidence rather than theory, my approach to sales management will fit naturally into that environment. The most SKUs I have handled were a catalog of 700 child ASINs across 150 parent ASINs, with daily sales of around $50k and a daily ad budget of $4k (targeting a TACoS around 9%, with ACoS varying by product lifecycle stage). I am most comfortable scaling Amazon accounts that have plateaued, are moving slowly, or are just starting. The reason for this is that I thrive most on dealing with compliance policies, listing errors, stockouts on significant ASINs/overstock in slow movers, flat files, and auditing accounts, whether it's with the current inventory and logistics process, optimizing listings and keywords, or pruning and optimizing ad campaigns.

I approach data analytics with both technical discipline and behavioral insight. My work on Amazon relies on interpreting Business Reports, Search Term Reports, COGS data, ACoS/TACoS trends, CPC patterns, CTR behavior, and inventory metrics to spot what the numbers actually mean, not just what they show on the surface. My psychology background helps me read patterns in buyer behavior, seasonality, decision-making frictions, and even the exhaustion of choice (in cases of product families with many child variation choices) that typical dashboards don’t capture. I also don't just download and extract data; I analyze and digest it. For instance, by cross-referencing our COGs data with Sales Data, Search Term reports, and PPC Data, we can accurately determine how much more (or less) we can spend on our ads given our TACoS, to squeeze in as much BSR boost as possible while remaining profitable. My data analytics tenet is simple: clean the data, interpret the behavior, and turn it into actionable strategies that move the brand forward.

This should be a 4- or 5-star skill; however, since I am limited to just 3 top skills, I must prioritize this at the lower rating. I am well-equipped to source reliable, cost-effective forwarding companies and 3PL warehouses, ensuring we have sufficient stock, even with inventory limits. I understand the importance of striking a balance between having enough inventory versus avoiding excess inventory and long-term storage costs, and that having standby inventories at 3rd-party logistics companies and warehouses can prevent stockouts even if our account may have inventory limits. I can determine whether to use FoB (Free on Board) or EXW (Ex Works), and when to choose FCL (Full Container Load) over LCL (Less than Container Load), depending on the shipment size. For instance, FCL can be cost-effective for larger volumes, offering better security and faster transit (since all our inventory can be processed under a single universal batch). At the same time, LCL can be suitable for smaller shipments but requires more careful coordination to avoid delays and mix-ups. I can make these decisions strategically, optimizing shipping costs while ensuring on-time delivery. I excel in communicating with suppliers, negotiating fee changes, and adjusting ordering schedules. I am adept at creating Shipment Plans on Seller Central, and I keep a close eye on international trade regulations, including tariffs, anti-dumping laws, and taxes, in the context of a post-US-China trade war. During the global supply chain crunch during the past pandemic, I worked through delays, quota limits, port congestion, and inconsistent supplier lead times, so forecasting for Amazon became an extension of that experience. I monitor daily sales, turnaround times, and remaining stock using Sellerboard, Sellics, and Helium 10, then match those numbers against the realities of production capacity, freight schedules, and forwarder availability. I know how to push forwarders and warehouses to stay on schedule without creating hostility, and I adjust forecasts based on realistic turnaround times rather than ideal ones. With me, our supply chain and inventory health would be healthy, consistent, cost-effective, and run with complete transparency, integrity, with proper paper trail and documentation that are easily trackable and auditable for easy systems improvement.