How DataGlass automatically optimizes your Shopee store.
Connect once. Decide daily. Deploy in one click.
DataGlass turns marketplace data into the next profit-maximizing decision — for ads, pricing, inventory, and promotions — and lets you deploy it in one click. Five minutes to connect, working recommendations on day one.
01/The flow
From shop connection to one-click deploy.
Five steps that move every seller from "we need to figure this out" to "we deployed the next move before lunch".
- Step 01
Sign up
Create your DataGlass account in about thirty seconds. The first month is free, with no sales call and no setup fee, so you can evaluate the product on your real store data.
- First month free
- Email or Google sign-in
- About thirty seconds end-to-end
- Step 02
Connect your shop
Authorize DataGlass to Shopee with the platform's official OAuth. Lazada and TikTok Shop are coming soon. No CSV exports, no manual data cleaning. Multi-shop support is first-class — connect what you run in the same flow, then bind matching products into one canonical SKU.
- Shopee included today; Lazada and TikTok Shop coming soon
- About five minutes per shop
- Multi-shop friendly — historic data backfills automatically
- Step 03
Start deploying
DataGlass surfaces a ranked decision queue — ads to pause, prices to adjust, vouchers to publish, SKUs to restock — each with the expected profit lift in real Baht. One click writes the change back to the platform through the official API. The system keeps optimizing as campaign days shift the market.
- Daily ranked decisions, sorted by expected profit lift
- One-click deploy — every action reversible and audit-logged
- Continuous optimization through 11.11, 12.12, Pay Day, and live events
02/In practice
A Shopee shop spending ฿10,000 a day on ads.
A multi-shop Shopee operator runs ฿10,000 in daily ad spend across three campaigns. The platform reports a healthy 4.0 ROAS — on paper, the campaigns look like they are working.
On day one, DataGlass reconstructs the order economics. After deducting COGS, marketplace fees, platform-funded vouchers, and fulfillment, the true ROAS on those campaigns is closer to 1.4. Roughly ฿2,800 per day is being spent on broad-match keywords whose attributed revenue does not cover full cost.
DataGlass surfaces the underperforming keywords in a ranked decision queue, projects the contribution-margin lift of pausing them and reallocating the budget, and the operator deploys with one click.
Projected lift
฿8,400 / month
Projected profit recovery, computed against the shop's real economics.
03/Status quo
Why the same operator can't do this in a spreadsheet anymore.
Sellers can run a single shop on a clean Google Sheet for a while. Two platforms, three campaign days, four vouchers stacking, and the math falls apart. DataGlass closes that gap.
Without DataGlass
- COGS scattered across spreadsheets — never reconciled to real platform fees
- Decisions made on platform-reported ROAS, not true ROAS
- Ad waste discovered weeks after the budget already shipped
- Stockouts on hero SKUs in the middle of campaign days
- Late nights reconciling vouchers, fees, fulfillment by hand
With DataGlass
- Per-order economics reconstructed automatically, every day
- True profit and true ROAS — the numbers that fund next month
- Ad waste flagged in the decision queue before the budget ships
- Stockout-day forecasting against the campaign calendar
- One-click deploy back to Shopee, Lazada, TikTok Shop — with the math behind every move