Shivali Patel Reveals What Data Most Amazon Sellers Ignore

Strategy

27 May

Amazon Seller Tools, Product Research & Prime Day Tips with Helium 10

Most sellers are sitting on more data than they know what to do with, and still making decisions on gut instinct. Shivali Patel, senior brand evangelist at Helium 10 and a seller in her own right since 2019, breaks down exactly which tools to use at every stage, from a complete beginner with no product yet to an established brand prepping for Prime Day.

In this episode: Shivali Patel from Helium 10 on the tools worth using at each stage of the Amazon journey, why so many sellers ignore the data they already have access to, and what to check before Prime Day hits.

Key takeaways

Complete beginners really only need three tools to start: Black Box for product research (filtered down from over 2 billion products so you're reviewing dozens of options, not hundreds), X-Ray for checking real profitability and competition, and Cerebro for keyword research before you ever launch.
Established sellers should build their routine around Search Query Analyzer, which pulls Amazon's own Search Query Performance data and sorts it into outperforming converters, low performing converters, and sales-generating keywords, work Amazon's own Seller Central makes you build manually in pivot tables.
What worked in 2012 doesn't work twice. Sellers still rely on old playbooks like a single differentiator, but any differentiator that works gets copied within months, so the fix is going in with several differentiators nobody else can easily match, not one.
Pairing a physical product with a digital one (a course, coaching calls, or even an AI-generated avatar built with tools like HeyGen) gives a brand a second revenue stream that survives a bad batch of inventory.
A repeat bad batch of stock is a real reason to pull inventory entirely rather than just discount it, especially if a digital offer already exists to fall back on.
Prime Day prep should already be finished before the event: fix underperforming listings using conversion data, favour bundles over blanket discounts, and pull last year's Prime Day data specifically, since even the event's length has changed year to year.

Timestamps

00:00 — Cold open
00:33 — Shivali's backstory: pre-med to Amazon FBA
02:03 — Her first brand, the first negative review, and how the mistake led to Helium 10
04:24 — KDP publishing: writing books in a day
05:57 — What a Monday morning looks like running multiple brands
07:15 — Why sellers underestimate how much more competitive Amazon's become since 2012
09:33 — The gut-instinct trap: ignoring the data you already have
11:13 — Three tools for complete beginners: Black Box, X-Ray, Cerebro
14:53 — Three tools once you're established: Search Query Analyzer
20:29 — Turning data into action: Ads, Listing Analyzer, Listing Builder
24:55 — The biggest mistake new sellers make: no real differentiators
28:30 — Is Amazon selling still a side hustle, or a full-time job?
29:05 — Why Shivali pulled all the inventory from her own brand
32:02 — The Prime Day playbook: what to check right now
35:02 — Where to find Shivali, and the Helium 10 discount codes

The detail

Why sellers still get caught out in 2026
Amazon didn't get complicated overnight, customer behaviour did. Sellers who've been in the game for years, some with hundreds or thousands of reviews, are still competing for the same attention as everyone launching new. It's still a good time to launch, but only if you know what terrain you're walking into: look at the historical data, work out how to justify a premium price against people who've seen the same product idea, and plan for events like Prime Day rather than reacting to them. The most common trap is sellers relying on gut instinct and building a story around why something worked, instead of checking what the data actually says.

Three tools for a complete beginner
With a $5,000–$10,000 budget and nothing built yet, Black Box is the starting point: it filters over 2 billion products down by revenue, word count, and marketplace so you're reviewing 60–120 realistic options instead of scrolling through hundreds. From there, the Chrome extension's X-Ray tool checks profitability and shows what competitors are actually doing (dimensions, variations, price points), so you can see whether sellers with zero reviews are still making money in that space. Cerebro rounds it out with keyword research before launch, making sure you're targeting a pattern of related phrases with real demand, not just one obvious term. We go deeper on building that keyword list in How Do I Find the Right Keywords for My Amazon Products?

Search Query Analyzer, for sellers already established
Once a brand is running, the tool to build around is Search Query Analyzer, which pulls directly from Amazon's own Search Query Performance data rather than the manual week-by-week pivot tables Seller Central forces on you. It sorts a year of data into outperforming converters (double down on ads and bids here), low performing converters (a signal something in the listing needs fixing), and sales-generating keywords. One Helium 10 podcast guest attributed over $100k in revenue to working this report weekly. From there, acting on what it shows means feeding outperforming keywords into Helium 10 Ads, and fixing underperforming ones through Listing Analyzer or a rebuilt listing in Your Listing Was Never a Keyword Container, which pulls keyword sources (including Search Query Performance and brand analytics) directly into the rewrite.

Differentiators, and the pivot that saved a failing brand
The biggest mistake in new launches is stopping at one differentiator, since anything that works gets copied within months of appearing on the market. The fix is going in with a full list of differentiators nobody else can easily replicate. That same instinct for the pivot showed up when a repeat bad batch of inventory kept coming back damaged despite passing two inspections: rather than discount stock that was falling apart in customers' hands, the call was to pull it entirely and reposition the brand around the existing digital coaching offer, with the physical product repositioned as a bonus rather than the thing being sold.

The Prime Day playbook
By the time Prime Day arrives, the prep should already be done: stock levels and deadlines confirmed, listings tweaked based on Search Query Analyzer data, and brand analytics checked to see where competitors are getting clicks without converting (a keyword worth adding to your own campaigns) versus where they're converting without much traffic (a listing detail worth copying). Bundles and value deals are the better lever over blanket discounts, since coupons for coupon's sake erode margin without necessarily building anything lasting. Worth pulling last year's Prime Day data specifically, in Cerebro's historical trends view, since even the event's own length has changed year to year.