Category share
Which brands are moving?
Track share changes by category and sub-category instead of relying on topline marketplace impressions.
Use case
See which brands are gaining, where share is slipping, and which platforms are driving movement across Shopee, Lazada, TikTok Shop, Tokopedia, and Blibli.
What you can measure
Category share
Track share changes by category and sub-category instead of relying on topline marketplace impressions.
Drivers
Link movement to pricing, stock, assortment, promo mechanics, and competitor activity.
Platform mix
See how category share differs across Shopee, Lazada, TikTok Shop, and other marketplaces.
Common market share questions
Related topics
Share shifts only become actionable when they are tied to pricing, assortment, and platform mix. That is exactly the context Magpie IQ is built to provide.
Related pages
Measurement precision
Most brand managers talk about "category share" without agreeing on what is being measured. Magpie IQ uses a precise definition: brand GMV ÷ total category GMV, where GMV equals final post-discount price multiplied by units sold, measured within a defined category taxonomy, on a defined set of platforms, in a defined time period.
Each of those parameters changes the number materially:
The measurement choices are not neutral. Magpie IQ's approach is transparent about each parameter so that share comparisons across time periods and across brands are valid. A share number without a definition attached to it is not an analytical input — it is a conversation starter at best.
The Magpie IQ definition
Four dimensions
Standard market share tools report brand GMV as a percentage of category GMV. That is one dimension. It tells you whether you are gaining or losing, but not where, how, or through which channel. Magpie IQ tracks four distinct dimensions simultaneously.
Dimension 1
Your brand's GMV as a percentage of total category GMV. This is the headline number — and the one most market share tools provide. It tells you whether you are gaining or losing relative to the category, but not which platforms or seller types are driving the movement.
Dimension 2
How category GMV distributes across Shopee, Lazada, TikTok Shop, Tokopedia, and Blibli — and how your brand's share differs across those platforms. A brand with 35% category share on Shopee and 12% on TikTok Shop faces a structurally different competitive challenge than one with 25% across both. Platform share tells you where the battleground is shifting.
Dimension 3
How GMV within your brand splits between Official Store, C2C resellers, and platform grocery channels (Shopee Mart, Lazada Express). High reseller share is a distribution signal: it means transactions are happening outside your controlled channel, which limits pricing authority and customer relationship capture. Brands moving from 40% Official Store share to 65%+ over 12 months are building structural advantage, not just topline GMV.
Dimension 4
Which pack sizes, formats, and variants are winning within your brand and across the category. A category leader in 400g SKUs can be invisible in 200g single-serve formats — the entry format where new consumers form brand preference. SKU-level share tracking shows where the growth is actually happening versus where the bulk GMV sits. These are often different parts of the assortment.
Why this matters
A brand share number without the platform, seller-type, and SKU breakdown is not actionable. It tells you something happened but not where or how. The three additional dimensions are what convert market share from a reporting metric into a commercial decision tool. Magpie IQ was built to serve all four dimensions from the same underlying data pipeline covering 10 million+ SKUs and 78 billion+ data points.
Category taxonomy
If you define the category incorrectly, the share number is wrong. This sounds obvious, but it is the most common source of error in ecommerce market share reporting — especially for teams using category taxonomies imported from retail or from Western classification systems that were not built for the Indonesian or Southeast Asian FMCG landscape.
A concrete example: formula milk. Define it as a single category (all stages, all formats) and you get one set of share numbers. Define it by stage — Stage 1, 2, 3, and 4 separately — and the picture changes significantly. Stage 3 formula accounts for approximately 65% of total formula milk GMV in Indonesia. A brand that is strong in Stage 3 but weak in Stage 1 will look healthy at the category level and fragile at the sub-category level. The brand that is quietly gaining in Stage 1 is building the pipeline of Stage 3 buyers for the next two years.
The same issue applies across categories. Facial wash and facial moisturiser are sometimes grouped into "facial care" — but the competitive dynamics are entirely different. Premium skincare imports dominate moisturiser; domestic mass-market brands dominate facial wash. Grouping them produces a share number that represents neither competitive reality.
Magpie IQ's category taxonomy was built from the ground up using six years of Indonesian FMCG ecommerce data. It was not imported from a retail scanner data system, a Nielsen framework designed for off-trade grocery, or a US-market SaaS platform trying to localise. The boundaries reflect how Indonesian and SEA consumers actually buy and search — which is the only definition that produces valid share measurements in this context.
The taxonomy foundation
Continuous tracking
A quarterly report that captures one data point every three months will miss every competitive move that happens in between. In ecommerce, the interval between a competitor taking a commercial action and that action showing up in a QBR is frequently long enough to turn a recoverable situation into a structural loss.
The events that move market share happen on a timeline measured in weeks, not quarters:
Price strategy changes
When a competitor reprices a core SKU — whether visibly (listed price cut) or invisibly (permanent voucher activation) — the effect on units sold and GMV is detectable within a month. A QBR report that aggregates the quarter sees the outcome but not the timing, which makes it impossible to attribute cause and mount a response.
New SKU launches
A competitor launching a new pack size or variant with aggressive introductory pricing will show GMV ramp-up within 6–8 weeks of launch. Catching this in the first month allows a response — whether that is matching the price point, accelerating your own variant launch, or increasing promotional spend on the SKU being challenged. Seeing it at Q+3 months means the competitor has already established shelf presence and review depth.
Platform algorithm changes
Shopee and Lazada both update their search and recommendation algorithms regularly. Brands that invest in sponsored listings or Shopee Mall compliance benefit immediately; those that do not will see organic rank degradation that compounds over months. Monthly share tracking surfaces this as a search-rank-to-GMV correlation — quarterly reports see only the GMV impact, with the mechanism invisible.
Magpie IQ tracks market share monthly at minimum, with weekly snapshots available for high-volatility categories — typically those with heavy promotional activity on Shopee (mega-campaigns: 9.9, 10.10, 11.11, 12.12) or categories experiencing rapid TikTok Shop-driven disruption. The combination of monthly baseline tracking and weekly event-level data is what allows share shifts to be attributed to specific actions rather than general trends.
Commercial use cases
Market share tracking is only valuable if it changes a decision. Below are three use cases that represent the most common commercial applications of Magpie IQ's share tracking capability across its 30+ FMCG brand clients.
Use case 1
A competitor gaining 3 percentage points of category share over 6 months rarely announces itself in distributor reports. It shows up first in ecommerce SKU-level data — as a GMV ramp on a specific pack size, as a price discount below the category floor, or as a new seller relationship that is moving volume outside of tracked distribution channels. Magpie IQ's continuous tracking allows brand teams to detect this accumulation before it is visible in total market data — typically 2–4 months earlier than traditional retail audit cycles.
Use case 2
When share falls, the instinct is to ask "what happened?" — but without temporal precision, the attribution is speculative. Magpie IQ's monthly data enables specific attribution: a competitor price cut of 18% ahead of the 12.12 campaign, sustained through January, caused a measured -2.1 percentage point share loss for the leading brand in that category. That level of specificity — which brand, which SKU, which price move, in which month — is what makes the post-mortem commercially actionable rather than a narrative post-rationalisation.
Use case 3
Commercial planning for ecommerce is most credible when it starts from measured share rather than estimated share. "Grow Official Store share from 61% to 70% of category GMV on Shopee by Q4" is a target that can be tracked monthly, attributed to specific actions (listing improvements, promotional investment, price architecture changes), and reported with confidence at each QBR. Building that kind of specific, trackable target requires a reliable baseline — which is what Magpie IQ's SKU-level historical data provides, going back to 2020 on Shopee and 2021 on Lazada.
FAQ
Yes, but only if the underlying data is cleaned and normalized consistently. That is one of the core reasons Magpie IQ exists.
Both. Country teams use it for local action; regional teams use it to compare category movement and prioritize where to intervene.