The data platform

Your decisions are only as good as the data underneath them.

Visual Verb cleans, transforms and reports on your data before anything gets mapped, modelled or spent against. Every module works on its own — together, they give you a single source of truth you can actually trust.

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Data cleansing Transformation Reporting Statements Connectors
MODULE 01

Data preparation & cleansing

Orders live in Shopify. Payments land in Razorpay. Returns are in a spreadsheet someone emailed last Tuesday. Customer records don't match across any of them.

Visual Verb reconciles every source into one clean dataset before you ever try to make a decision on top of it.

The Monday-morning problem: you can't look at last week's numbers without first spending two hours fixing a CSV. We fix it once, automatically, on every sync.
Deduplication — merge customer records that are the same person across sources, even when names and phone numbers don't match exactly.
Address normalisation — standardise addresses and postal codes to a clean, mappable format across India, the US, and other markets.
Field standardisation — align column names, date formats, currencies, and category labels across every source you connect.
Source reconciliation — match orders against payments against returns, flag mismatches, and surface gaps before they compound.
Data cleansing
BEFORE → AFTER
RAW INPUT — 3 SOURCES, 4 PROBLEMS
NAMEPHONECITYPIN
Priya S.98451 12345Bangalore560001
priya sharma+91-9845112345Bengaluru560001
Rahul M.77889 90012Chn60028
Sneha K.bombay400001
↓
CLEANED OUTPUT — DEDUPLICATED, NORMALISED
NAMEPHONECITYPIN
Priya Sharma+91 98451 12345Bengaluru560001
Rahul M.+91 77889 90012Chennai600028
Sneha K.— missingMumbai400001
MODULE 02

Data transformation

Clean data still isn't analysis-ready. You need aggregations, derived metrics, time-window calculations, and category mappings before a report can say anything useful.

Visual Verb lets you define transform pipelines that run every time your data syncs — so the numbers you look at are always in the shape you need.

The spreadsheet trap: someone built a VLOOKUP monster six months ago. Nobody else understands it, and it breaks every time a new product category is added. Pipelines replace that.
Calculated columns — revenue per unit, contribution margin, LTV estimates, RTO rate — defined once, recomputed on every sync.
Aggregation rules — roll up daily orders to weekly, monthly, or by cohort, without exporting to Sheets and pivoting by hand.
Category & tag mapping — map SKUs to product lines, cities to regions, channels to attribution groups — maintainable by non-engineers.
Time-window metrics — trailing 7-day, 30-day, same-period-last-year comparisons, computed automatically alongside each sync.
Transform pipeline
4 STEPS · AUTO
01Ingest & validateShopify + Razorpay
↓
02Map categoriesSKU → product line → vertical
↓
03Compute metricsmargin, LTV, RTO rate, AOV
↓
04Aggregate & snapshotdaily → weekly → monthly roll-ups
Runs on every sync · last run 14 min ago · 0 errors
MODULE 03

Reporting & dashboards

You shouldn't need a data team to answer "how did last week go?" Reports should refresh themselves, live on a warehouse you own, and tell you when something moves in a way it shouldn't.

Visual Verb gives you self-serve dashboards on clean, transformed data — not a raw dump of whatever Shopify exported.

The Friday ritual: someone spends three hours pulling numbers from four tabs into a Google Sheet, formatting it, and emailing it to the founder. That report should build itself.
Self-serve dashboards — drag, filter, and explore without writing queries. Built on your warehouse, not a third-party BI tool.
Scheduled reports — daily, weekly, or monthly — generated and delivered without anyone remembering to run them.
Anomaly alerts — get notified when a metric moves more than you'd expect, before it becomes a problem you discover in a meeting.
Exportable — download as PDF, CSV, or share a live link with your team or investors. No screenshots of dashboards in slide decks.
Weekly overview
LIVE · DEMO DATA
REVENUE
₹18.4L
▲ 12.3% vs last week
ORDERS
1,247
▲ 8.1% vs last week
AOV
₹1,475
▼ 3.8% vs last week
RTO RATE
6.2%
▼ 1.1pp vs last week
DAILY REVENUE — LAST 14 DAYS
MODULE 04

Statement creation

Reconciling marketplace statements, payment gateway reports, and your own books is days of work — and a single missed row means the numbers don't close.

Visual Verb generates statements automatically: party-level, marketplace-level, daily cash flow — created from your synced data, not assembled by hand.

The end-of-month scramble: your accountant chases three marketplace reports, matches them against Razorpay, finds a ₹14,000 gap, and spends two days tracing it to a refund that hit a different date. That trace should take seconds.
Party-level statements — per-vendor, per-marketplace, or per-customer ledgers generated from your transaction data.
Marketplace reconciliation — match your orders against what Amazon, Flipkart, or any marketplace says it paid you, line by line.
Daily cash flow — money in, money out, by source — without waiting for the accountant's month-end summary.
Gap detection — flag mismatches instantly, with a trace to the originating transaction, so reconciliation is a review, not a hunt.
Statement · Amazon IN
JUL 2026
DATEDESCRIPTIONAMOUNT
01 JulSettlement #AMZ-4821+₹2,84,500
03 JulRefund · Order #9917−₹4,200
07 JulSettlement #AMZ-4834+₹3,11,800
10 JulCommission deduction−₹47,600
14 JulSettlement #AMZ-4851+₹2,96,100
NET RECEIVABLE₹8,40,600
Reconciled — matches gateway payout within ₹0.00
Connectors

Plug into the tools you already run on.

Visual Verb syncs from your existing sources — no migration, no data team, no changing how you work. We read from them; you keep using them.

Shopify
Zoho
PostgreSQL
MongoDB
CSV / Excel upload
Razorpay
Google Sheets
Shopify App — in build
Amazon Seller Central
Flipkart Seller

Need a connector we don't have? Tell us — most integrations take under a week.

What comes next

Once your data is clean, the map is one step away.

Visual Verb's geo-intelligence layer reads your cleaned, transformed data and tells you where your next customers are. The platform you just saw is what makes those answers trustworthy.

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