A live, same-day, fully-aggregated view of your Amazon business. Sales, forecasts, sell-through, inventory, and profitability, categorized any way you run it and unified across Vendor Central, Seller Central, or both. By operators who actually use it.
Every problem Amazon operators face has a direct answer inside TQ Central.
TQ Central works however your business sells on Amazon.
One conversation. We’ll show you exactly what TQ Central looks like with real Amazon data.
These capabilities don’t exist in Amazon’s native tools. We built them because our own team needed them to run real Amazon businesses.
One conversation. We’ll show you what it looks like with real data.
Most tools are Seller-only point solutions. TQ Central is the only platform that unifies 1P and 3P data with custom category tagging, PO visibility, and full enterprise customization.
| Capability | TQ Central | Helium 10 | Jungle Scout | SmartScout | Sellerboard | Perpetua | Pacvue |
|---|---|---|---|---|---|---|---|
| Vendor Central (1P) analytics | ✓ | — | — | — | — | — | partial |
| Seller Central (3P) analytics | ✓ | partial | partial | partial | ✓ | partial | partial |
| Real-time Vendor Central data | ✓ | — | — | — | — | — | — |
| Category-level catalog slice & dice | ✓ | partial | partial | partial | — | — | partial |
| Custom tagging | ✓ | — | — | — | — | — | — |
| Multi-account / portfolio rollup | ✓ | partial | partial | partial | partial | ✓ | ✓ |
| Agency oversight & accountability | ✓ | — | — | partial | — | partial | ✓ |
| Executive high-level dashboards | ✓ | — | — | — | — | partial | ✓ |
| Amazon PO visibility | ✓ | — | — | — | — | — | partial |
| Fully customizable / enterprise | ✓ | — | — | — | — | partial | partial |
| Real-time Monday morning refresh | ✓ | partial | partial | partial | ✓ | partial | partial |
⚠ Competitor data is a draft based on general category knowledge. Verify each cell against each vendor’s current website before publishing.
Book a demo and see TQ Central live with real data.
TQ Central is not a fixed template. Dashboards, tags, and views are tailored per brand and per client, to match how you actually run the business.
Let’s show you what a configured TQ Central looks like for your operation.
TQ Central gives Vendor Central brands a live, fully-aggregated view of POs, sell-through, forecasts, and inventory, across every account, every morning.
For Vendor Central brands, pulling a clean picture of purchase orders, accept/reject status, and sell-through by ASIN means exporting, joining, and building a spreadsheet from scratch. Every week. TQ Central does that aggregation automatically, so the picture that used to take two hours is ready when you open your laptop.
See exactly what TQ Central surfaces for a Vendor Central business like yours.
TQ Central gives Seller Central brands a live view of TACOS trends by category, inventory health, and profitability, without the weekly spreadsheet build.
Seller Central brands often rely on their agency for the numbers. TQ Central gives you direct access to a live view of your own data, by category and by tag, so every conversation with your agency starts from a position of knowledge.
See what TQ Central looks like for a Seller Central business like yours.
Replace the weekly reporting SOP with a command center your whole team can use. Every client’s Amazon business, live, aggregated, and ready to share.
TQ Central was built by an Amazon agency to run a real client roster. Every feature exists because the same wall your team hits was hit first: pulling client reports manually, reconciling exports, and building decks from data that was already two days old.
Your clients’ data is fully isolated. You control exactly what each client sees and which reports they can access.
See how the agency view works with a live walkthrough.
Contact UsChoose the package that fits how you sell. Introductory pricing available for the first six months.
* Data fee applies during the introductory period and is included in the standard rate thereafter.
* Data fee applies during the introductory period and is included in the standard rate thereafter.
All prices in USD. Contact us for multi-brand or enterprise arrangements.
Book a demo and we’ll show you the platform live.
TQ Central is powered by TAQTFUL, a working Amazon agency. We built it because the tools we needed didn’t exist.
TAQTFUL is an Amazon agency. We manage real Vendor Central and Seller Central businesses for brands that take Amazon seriously. For years, running those accounts meant exporting data, joining spreadsheets, building decks, and making decisions on numbers that were already two days old.
We looked at every reporting platform we could find. None of them went deep enough on Vendor Central, none unified VC and SC at the ASIN level the way our clients needed, and none let us run custom tagging without a development project. So we built TQ Central.
TQ Central connects to your Vendor Central, Seller Central, and advertising accounts through secure authorization. Once connected, it pulls your data daily, aggregates it the way your business runs, and surfaces it through fully customizable dashboards built for Amazon operators. Accessible from any browser, no software to install, built on enterprise Microsoft architecture.
One conversation to see what that means for your operation.
Practical insights for brands and agencies running serious Amazon businesses.
If you run a Vendor Central business, you already know the Monday morning ritual. You log in, pull the sell-through report, wait for the export, open Excel, and spend the first hour of your week building a picture of what happened last week. By the time you have it, you are already reacting to Thursday.
Amazon's native Vendor Central reporting updates sell-through data with a 48-hour delay. That means on Monday morning, the most current sell-through data reflects Saturday. For any brand managing replenishment, promotions, or purchase order responses, this is a structural disadvantage built into how you operate.
The lag exists because Amazon aggregates sell-through across its fulfillment network before surfacing it in Vendor Central. The data is there. Amazon has it. It simply is not delivered to you in real time through native tools.
Purchase order management is the other side of the problem. A Vendor Central brand managing multiple categories and SKUs receives POs continuously. Aggregating accepted totals, rejected totals, and open POs by category or by custom tag requires exporting, joining, and building a spreadsheet from scratch. Every week. For many operations teams this takes two to three hours that could be spent acting on the data instead of assembling it.
Most mid-size Vendor Central brands operate multiple vendor accounts. Amazon has no native way to see across those accounts simultaneously. Each account is its own silo. Cross-account reporting requires manual consolidation, which means manual error risk and more time lost.
When sell-through data is available the same day, Monday morning looks different. Instead of building the picture, you arrive to it. PO totals are aggregated, accept/reject status is visible by ASIN and by tag, and the category-level pulse you need to make replenishment decisions is already there when you open your laptop.
Amazon generates forecast models for Vendor Central brands: mean, P70, P80, and P90. These models are useful. What Amazon does not do is aggregate them. You can see a P80 forecast for a single ASIN. You cannot see the P80 forecast for a category or for your whole business rolled up. That aggregation has to be built manually, and it has to be rebuilt every time the underlying ASINs change.
A reporting layer that aggregates forecast models by month and by tag, automatically, solves a problem that has no native solution in Vendor Central.
Total Advertising Cost of Sale (TACOS) is the metric that separates Seller Central brands that scale profitably from those that grow revenue while quietly destroying margin. It is also one of the most time-consuming numbers to track, because Amazon does not surface it the way operators need to see it.
ACoS measures ad spend against ad-attributed revenue. TACOS measures ad spend against total revenue, including organic. The difference matters because a brand with strong organic momentum will show a high ACoS and a low TACOS simultaneously. A brand becoming dependent on advertising will show a rising TACOS even as ACoS holds steady.
TACOS is the health check that ACoS cannot perform. If TACOS is rising over time, your advertising is becoming a larger share of what is keeping the business running. If TACOS is falling, your organic is growing relative to your ad spend.
Most Seller Central brands do not have one TACOS. They have a TACOS for every category, every product line, and every campaign structure. A blended account-level TACOS hides what is actually happening. A category with 4% TACOS and a category with 22% TACOS average to something that looks acceptable and tells you nothing useful.
Seeing TACOS by category requires joining advertising data with sales data at the ASIN level, then rolling that up through a product taxonomy that Amazon does not maintain on your behalf.
TACOS trends over time are more useful than any single TACOS reading. A category where TACOS has moved from 8% to 14% over three months is telling a story a single-month view will not reveal. The story is usually one of three things: competition increased and you followed; organic performance dropped and advertising filled the gap; or a campaign structure changed and the new structure is less efficient.
Each story has a different response. You cannot tell which story it is without the trend.
One of the most practical uses of category-level TACOS data is asking your agency sharper questions. When you can see that TACOS in your core category rose 3 points last quarter while TACOS in a secondary category fell, you can ask specifically what changed and why. Without that data, the conversation defaults to account-level blended numbers and general explanations.
The weekly reporting SOP is one of the most expensive processes in an Amazon agency's operation, and most agencies do not account for that cost honestly. An analyst spending four to six hours per client per week building a deck is not doing analysis. They are doing data assembly. And the client receives a document that is already four to seven days old by the time they open it.
Consider a mid-size Amazon agency with fifteen clients. If each client requires five hours of reporting work per week, that is seventy-five hours of analyst time weekly, or roughly $234,000 per year in reporting labor alone at a modest fully-loaded rate. Most agencies undercount this cost because reporting labor is spread across the team and feels like part of the job.
Manual reporting introduces selection bias, even when agencies have no intention of misleading clients. When an analyst builds a deck, they decide what to highlight and what to note briefly. Clients receive an interpretation of their data, not their data. This is not an ethical problem most of the time. It is a structural one.
The clients that ask the most questions are not the most demanding. They are the most engaged. An engaged client who has independent access to their data asks better questions because their questions are grounded in what they have already seen. Agencies that give clients direct dashboard access consistently report shorter and more productive client calls.
A common concern among agencies considering client-facing dashboards is that transparency will expose underperformance. This concern gets the incentive structure backwards. An agency that is performing well has nothing to fear from real-time client access. The agencies with the longest client relationships tend to be the most transparent.
A portfolio view showing every client's key metrics on one screen, updated daily, replaces the bulk of what weekly decks currently do. Clients get their own access. Analysts spend time on analysis instead of assembly. Account managers walk into client calls already knowing what the client has seen. The deck becomes a summary with agency commentary added on top. That is a product worth paying for.
The moment a brand operates more than one Amazon account, it enters a blind spot that Amazon's native tools do not help with. Each account is its own silo. Vendor Central shows you what is happening inside that vendor relationship. A second Vendor Central account shows you a separate, unrelated picture. And a Seller Central account adds a third data stream with no native connection to either.
Most multi-account Amazon operations did not start that way. They grew into it. A brand acquires another company and inherits its Amazon relationships. A licensing deal creates a new vendor account for a specific product line. A decision to test direct-to-consumer on Seller Central while maintaining the 1P relationship creates a hybrid structure.
Without a cross-account view, certain problems are invisible until they compound. A category with strong sell-through in one vendor account and inventory pressure in another reads as two separate situations in native reporting. With a unified view, it reads as a supply chain issue that needs attention across both accounts simultaneously.
Executives managing a multi-brand Amazon operation need a portfolio view that answers a different set of questions than operations teams ask. Which brands are growing? Where is inventory risk concentrated? Which categories produce the strongest TACOS efficiency? A portfolio view showing each brand's revenue trend, TACOS efficiency, and inventory position on one screen, updated daily, answers all of those without requiring a report request.
Custom tagging is the mechanism that makes multi-account analysis coherent. When the same product category tag is applied consistently across SKUs in multiple vendor accounts and a Seller Central account, the category-level rollup becomes meaningful. Revenue by category, TACOS by category, and inventory by category across all accounts in one view is not possible without a tagging layer that spans every account connection.
Vendor Central (1P) and Seller Central (3P) are not just different ways of selling on Amazon. They are different business models with different data structures, different reporting cadences, and different operational questions. Most comparisons focus on margin and control. This one focuses on data, because data is what you actually use to run the business day to day.
In Vendor Central, Amazon buys your inventory. Revenue to you is recognized when Amazon accepts a purchase order and you ship. In Seller Central, the transaction is between you and the end customer. Revenue is recognized when the customer buys. This structural difference flows directly into the data each model generates.
Vendor Central sell-through lags the real-time picture by roughly 48 hours in native reporting. This is a function of how Amazon aggregates data across its fulfillment network. Seller Central order data is closer to real time. But advertising data on the Seller Central side carries its own lag, and the combination of orders plus advertising performance required to calculate TACOS is not something Amazon aggregates natively.
Vendor Central POs are one of the most operationally important data points in the 1P model. Tracking PO accept/reject rates by ASIN, by category, and over time is essential for a well-run VC operation. None of that exists in Seller Central, because Seller Central does not have POs. The inventory decision is yours entirely.
Amazon provides forecast models to Vendor Central brands: mean, P70, P80, and P90. These are useful inputs for production planning. What Amazon does not do is aggregate these forecasts across ASINs. Seller Central brands do not receive the same forecast models. Demand planning on the SC side is based on the brand's own analysis of historical sales velocity, seasonality, and advertising performance.
A brand operating both VC and SC faces a reporting environment where the two data streams use different taxonomies, different timing, and different metrics. Unifying them at the ASIN level requires a data layer that connects both account types and applies a common product taxonomy through custom tagging. When that unification works, a hybrid brand can see total revenue across both channels by category, TACOS on the SC side contextualized against the broader VC picture, and inventory positions across both fulfillment relationships.