Platform · Tokopedia

Tokopedia Data Scraping Services

Where shipping choice moves total cost more than item price does, so the courier matrix belongs in the dataset.

Tokopedia data scraping is the automated collection of publicly visible Tokopedia data for Indonesia — with the courier option matrix captured per listing because shipping cost varies widely by courier and origin, plus seller location, payment method availability and Indonesian text normalisation.

Indonesia is an archipelago, and shipping reflects that. On a mid-priced item the gap between the cheapest and most expensive courier can exceed the price difference between competing listings entirely.

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tokopedia_couriers.jsonl LIVE FEED

{"tokopedia_product_id":"tk-771204", "product_key":"aw-id-44810", "price_idr":185000, "seller_city":"Jakarta Pusat", "courier_options":[{"courier":"Reg","cost":14000, "lead_days":3}, {"courier":"Express","cost":38000,"lead_days":1}], "shipping_cost_min":14000, "shipping_cost_max":38000, "total_cost_cheapest_courier":199000, "payment_methods_available":["virtual_account", "convenience_store","card"], "cod_available":true} {"tokopedia_product_id":"tk-889012", "price_idr":179000, "seller_city":"Makassar", "shipping_cost_min":46000, "total_cost_cheapest_courier":225000, "note":"cheaper item, 13% more delivered"}

2 of 4,412,880 listing rowscourier matrix captured · text normalised 89.7% · schema v2.0

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Tokopedia or its owners. Tokopedia and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

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Tokopedia at a glance

How we handle Tokopedia specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Platform: Tokopedia across Indonesia
Distinctive field: Courier option matrix per listing, with cost and lead time each
Why it matters: Shipping spread often exceeds the price spread between listings
Seller origin: Seller city captured, since it drives shipping cost
Payment: Payment method availability captured, including non-card methods
Language: Indonesian text normalised for cross-listing matching
Refresh: Daily standard; sub-daily during campaign dates
Region: Indonesia

Platform specifics

What makes Indonesian marketplace data different

These are the reasons a Tokopedia dataset needs its own handling rather than a shared retail schema.

The courier matrix, not a single shipping cost

Most marketplaces have one shipping cost per listing, or a free-shipping flag. Tokopedia listings typically expose several courier options with materially different costs and lead times, and the shopper chooses.

Why a single shipping field is wrong here

The spread is wide. Cheapest to fastest can be a multiple, not a margin.
Seller origin drives it. The same item from a Jakarta seller and a seller on another island have very different courier costs to the same buyer.
A cheaper item can cost more delivered, and often does.
Lead times differ by days across options on one listing.

We capture courier_options as an array with cost and lead time per option, plus shipping_cost_min and shipping_cost_max so the spread is visible at a glance. We also compute total_cost_cheapest_courier because that is the figure a like-for-like comparison actually needs.

We do not collapse to one shipping figure. Which courier a shopper picks depends on their urgency, and a dataset that picks for them has embedded an assumption in what looks like a fact.

Payment method availability is a real field

Card penetration in Indonesia is lower than in Western markets, and a large share of transactions use bank transfer, virtual account, convenience store payment or cash on delivery.

Payment method availability differs by seller and sometimes by price band.
COD availability affects conversion materially and carries higher refusal rates, which is a caveat on availability data.
Instalment options appear on higher-value items.
A listing without the buyer's preferred method is effectively unavailable to them regardless of price.

We capture available payment methods as a structured list with COD flagged separately, since COD carries the same availability caveat we apply on Myntra: returns and refusals mean stock re-entering availability is a weaker demand signal.

Seller location and Indonesian text normalisation

Two practical requirements without which this dataset is not usable.

Seller location

Seller city is displayed and it is not decoration — it determines courier cost and lead time to any given buyer. We capture seller_city so shipping cost is interpretable rather than an unexplained variable, and so a brand can see where its unauthorised sellers are physically operating from.

Text normalisation

Indonesian product titles are long, seller-formatted, and mix Bahasa with English brand and model terms. Pack and quantity information is embedded in the title rather than structured. Matching on raw title fails.

We normalise, extract model numbers, map brands across spellings and compare attributes, delivering product_key with match_confidence. Uncertain matches are flagged rather than merged, for the same reason as everywhere else: a wrong merge hides a genuine second product.

Scope

What we collect on Tokopedia, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

Courier option array with cost and lead time per option
Shipping cost minimum and maximum, so the spread is visible
Total cost on the cheapest courier, computed for like-for-like comparison
Seller city, since it drives shipping cost and lead time
Payment method availability as a structured list, with COD flagged separately
Instalment options where offered on higher-value items
Indonesian text normalised with a stable product key and match confidence
Campaign date context on records collected during campaigns
Ratings and review text without reviewer profiles

❌ What we do not, and why

A single collapsed shipping figure, which embeds a courier choice we cannot make for the shopper
Merged product identities where match confidence is low
Seller portal or any credentialed Tokopedia system
Sales volumes or seller economics
Reviewer names, profiles or review histories

Core Tokopedia fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
tokopedia_product_id	Platform product identifier, the join key
product_key / match_confidence	Normalised cross-listing identity with confidence
price_idr	Item price in IDR exactly as displayed
courier_options	Array of courier name, cost and lead time per option
shipping_cost_min / shipping_cost_max	Cheapest and most expensive courier cost
total_cost_cheapest_courier	Item price plus cheapest shipping, for like-for-like comparison
seller_name / seller_city	Seller identity and origin city, which drives shipping
payment_methods_available	Structured list of accepted payment methods
cod_available	COD flagged separately, since it carries an availability caveat
instalments_available	Whether instalment payment is offered
campaign_context	Which campaign date, if any, the observation falls within

Use cases

What teams do with Tokopedia data

Delivered-cost competitive comparison

Courier options with cost and lead time make total delivered cost comparable, revealing where a cheaper item is more expensive to receive.

Shipping spread analysis by seller origin

Seller city with the courier matrix shows how origin drives delivered cost, which explains price differences that item-price analysis leaves unexplained.

Payment method coverage assessment

Available payment methods per listing show where a competitor accepts methods you do not, which affects conversion independently of price.

Unauthorised seller location mapping

Seller city alongside identity shows where unauthorised sellers physically operate from, which supports enforcement targeting.

The 24-hour sample — run on your sources, not ours

Send us a Tokopedia item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned within 24 hours
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Tokopedia is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Tokopedia data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what ecommerce data scraping covers, and a Tokopedia-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Tokopedia data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Because the spread is wide enough to change conclusions. Cheapest to fastest can be a multiple rather than a margin, and a cheaper item frequently costs more delivered.

We deliver the full option array plus minimum, maximum and total cost on the cheapest courier. Collapsing to one shipping figure would embed a courier choice we cannot make for the shopper.

Because Indonesia is an archipelago and origin drives courier cost and lead time. The same item from a Jakarta seller and one on another island costs very differently to deliver to the same buyer.

Without seller city, shipping cost is an unexplained variable. It also shows a brand where unauthorised sellers physically operate from, which helps enforcement targeting.

Yes, as a structured list with COD flagged separately. Card penetration is lower here, so bank transfer, virtual account, convenience store payment and COD carry a large share of transactions.

A listing without a buyer's preferred method is effectively unavailable to them regardless of price. COD also carries the same availability caveat we apply on Myntra, since refusals mean stock returning to availability is a weaker demand signal.

Normalisation with model number extraction, brand mapping across spellings and attribute comparison, delivering a stable product key with confidence.

Titles are long, seller-formatted and mix Bahasa with English brand terms, with pack information embedded rather than structured. Raw title matching fails, and uncertain matches are flagged rather than merged.

Yes, joining on product identity. The three need different collection designs though — voucher stacking dominates on Shopee, cross-border sellers on Lazada, and the courier matrix here.

Running them together costs less than three separate engagements because product matching and scoping are shared.

We quote individually. Drivers are category scope, whether the full courier matrix is required per listing, refresh frequency and whether payment method capture is needed.

Courier matrix capture adds meaningful work per listing since it requires the shipping selection step. One scoping call, a free pilot within 24 hours, then a fixed monthly quote. Request a quote.

See real Tokopedia data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

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