Based on real weekly marketplace operating data from Labu-Labu's commerce team. Brand, product and financial identifiers have been anonymised.
Running a TikTok Shop well is important. Orders need to go out on time. Customers need replies. Returns need to stay under control. Reviews need to remain healthy. Listings need to work.
But good operations are only the baseline. Once a store is operating properly, the more valuable question is: what should we change next to improve sales?
At Labu-Labu, we believe TikTok Shop analytics should not end with a dashboard. It should lead to a decision.
That means looking beyond GMV and asking: are customers seeing the product? Are they clicking? Are they converting? Are the right sizes or variants available? Is traffic increasing or falling? Should we restock? Should we change the display image? Should we increase affiliate exposure? Should we run a promotion? Should we clear the inventory? Or should we stop investing in the product?
That is the difference between reporting data and using data to operate commerce.
What should brands analyse on TikTok Shop?
A useful TikTok Shop product analysis should look at 4 layers:
Exposure, then interest, then conversion, then availability.
In practical terms, that means analysing impressions, click-through rate, product views, conversion rate, recent versus historical trends, stock availability, the percentage of variants out of stock, stock cover, returns, reviews, and the next recommended action.
No single metric is enough. A product can have low sales because it is receiving too little traffic. Another can have high traffic but a poor click-through rate. Another can attract clicks but fail to convert. Another can convert well but lose sales because popular sizes are unavailable.
The sales result may look similar. The correct action can be completely different.
Why is GMV alone not enough?
One of the easiest mistakes in e-commerce is to rank products purely by sales. Product A sells more than Product B, therefore Product A must be better. Not necessarily. Imagine these 3 scenarios.
Product A: impressions rise, CTR stays healthy, conversion stays strong
This usually suggests demand is healthy. The next questions may be: do we have enough inventory? Can we increase exposure? Should more affiliates carry the product? Should it receive more LIVE time?
Product B: impressions are high, but CTR is weak
Customers are seeing the product, but not enough of them are clicking. The problem may be the first impression. Possible actions include changing the main display image, testing a different thumbnail, improving the product title, repositioning the offer, changing the content angle, or making the value proposition clearer.
The product may not need a discount. It may simply need a better presentation.
Product C: CTR is healthy, but conversion is weak
Customers are interested enough to enter the product page, but they are not buying. Now we need to investigate a different set of questions. Is the price competitive? Is the promotion strong enough? Are reviews affecting trust? Are popular variants unavailable? Is the product information clear? Is there a voucher issue? Is the offer itself weak?
This is why we prefer to analyse the whole funnel instead of only looking at sales.
How do we read the TikTok Shop product funnel?
A simple way to analyse product performance is to break it into 3 stages: impressions, CTR and conversion.
1. Impressions: are enough people seeing the product?
Impressions tell us whether the product is receiving exposure. If impressions fall while conversion remains healthy, the product may not have a demand problem. It may have an exposure problem.
Possible actions include increasing LIVE rotation, giving the product to more affiliates, creating more short-form content, increasing paid traffic, adding the product to campaigns, or improving marketplace placement.
The key point is this: a product cannot sell if customers never see it.
2. CTR: are customers interested enough to click?
CTR, or click-through rate, tells us how effectively the product converts exposure into interest. If impressions are strong but CTR is weak, we usually look at presentation before touching the product itself: the main display image, thumbnail, product title, price presentation, promotional message, product positioning, content angle, or the first visual customers see.
This is where something as simple as reframing the display picture can matter. A weak CTR does not necessarily mean the merchandise is bad. Sometimes the product simply does not look compelling enough at first glance.
3. Conversion rate: do customers buy after they click?
Conversion tells us whether product-page interest becomes an order. If CTR is healthy but conversion is weak, the diagnosis changes. Possible causes include pricing, weak promotion, missing vouchers, poor reviews, unclear product information, low trust, unavailable variants, or a mismatch between the content promise and the actual product page.
This is why impressions, CTR and conversion should be analysed separately. They answer different questions.
How does stock availability distort conversion?
This is particularly important for fashion and products with multiple variants.
A product may technically still have inventory. But perhaps many of the popular sizes or colours are already unavailable. Customers continue to click. They enter the product page. Then they cannot buy the variant they want. Conversion falls.
If we only look at conversion, we may conclude that demand is getting weaker. But the real issue may be that customers still want the product and we simply do not have the right variants available.
That is why we analyse inventory at the variant level rather than only looking at total units. We also look at the percentage of variants out of stock, days of stock cover, recent sales velocity, and whether the missing inventory is concentrated in the best-selling variants.
A product can look "in stock" operationally while being almost unbuyable commercially.
What is the biggest lesson from our weekly analysis?
In one recent weekly review, 53% of sales came from products with less than 3 days of stock cover.
This is an important insight. It means one of the biggest risks to future sales was not lack of demand. It was availability.
When this happens, the first action should not automatically be "spend more on marketing". The first question is: can we protect the products that are already winning?
Because more impressions cannot solve an empty shelf. More affiliates cannot solve missing sizes. A stronger LIVE cannot sell a variant that is unavailable.
Marketing and inventory need to be analysed together.
Why is restocking not just "buy more stock"?
Another common mistake is restocking at product level without understanding the variant curve. For a fashion product, total stock can be misleading. A listing might show hundreds of units remaining while the most important sizes are already sold out.
So when we review replenishment, we do not simply ask how many units are left. We also ask which sizes sold, which variants are unavailable, what the recent sales rate is, what the longer-term sales rate is, whether this week's performance was boosted by a campaign, whether it was a launch week, how many days of stock remain, and which variants actually need replenishment.
This reduces the risk of solving a stockout problem by creating a future overstock problem.
Why compare short-term performance with a longer baseline?
7-day data is useful. But 7-day data can also be noisy. A product may have just entered a campaign. A creator may have generated a viral video. A LIVE session may have driven unusual traffic. A payday event may temporarily increase conversion.
That is why we compare recent performance with a longer baseline. For example:
- Impressions +80%, conversion unchanged. The product likely received more exposure and converted normally.
- Impressions flat, conversion +40%. The product or offer may have become more attractive.
- Impressions -50%, conversion stable. This may indicate an exposure problem.
- Impressions stable, conversion -40%. This may indicate a product or offer problem.
- Sales fall, but many variants are out of stock. This may indicate an inventory problem rather than weaker demand.
The same headline result, sales down, can lead to 5 completely different actions.
When should you change the display picture?
A display-picture test makes sense when exposure is healthy but customers are not clicking at the expected rate. For example, impressions are sufficient, CTR is below the normal range, and conversion among people who do click is still acceptable.
That pattern suggests the product itself may not be the first problem. The listing may not be attracting enough interest. Possible tests include a new main image, clearer product styling, stronger before-and-after framing, better price communication, a different model shot, a clearer product benefit, a different crop, or a new thumbnail designed around the use case.
This is a good example of why data should lead to an action. "CTR is low" is not the action. "Test a new primary image this week" is the action.
When should you increase affiliate exposure?
Affiliate exposure makes more sense when the product converts well but does not receive enough traffic. If CTR is healthy, conversion is healthy, inventory is sufficient, but impressions remain low, the product may deserve more distribution.
Possible actions include sending samples to more creators, increasing affiliate outreach, adjusting commission, prioritising the product in creator recruitment, or asking existing successful affiliates to create more content.
The product has already shown that customers will buy it. Now the business needs to solve distribution.
When should you use promotions?
We do not believe promotions should be the default response to weak sales. A promotion should solve a specific problem.
- Strong traffic and weak conversion. Test a voucher, price point, bundle, limited-time offer, or promotional mechanics.
- Strong conversion and weak traffic. Discounting may be unnecessary. The better answer may be more exposure.
- Slow inventory and weak velocity. A promotion may be used to release inventory and capital.
- Strong LIVE performance. A LIVE-only offer may be more efficient than discounting the product across the entire marketplace.
The important question is not "should we discount?". It is "what commercial problem is this promotion supposed to solve?"
When should you stop a product?
Not every product deserves unlimited attempts. Some products need more exposure. Some need a better listing. Some need another promotion test. Some are simply too new to judge. But eventually, the evidence may become strong enough to stop investing.
A stop decision usually requires more than one weak week. We look for a combination of signals: sufficient traffic, weak CTR, weak conversion, a poor trend, no stock constraint, enough time to test, and little evidence that another intervention will materially change the outcome.
This distinction is important. A low-performing product with no traffic is not the same as a low-performing product that has already received enough traffic to be judged. Data quality matters before the decision.
Why do we prefer actions over product rankings?
We do not find "top 10 products" and "bottom 10 products" particularly useful on their own. Instead, we prefer to place products into action groups.
| Action | What it means |
|---|---|
| SCALE | Demand is strong. Give the product more opportunity. |
| RESTOCK | Demand exists, but inventory is restricting sales. |
| RE-EXPOSE | Conversion is healthy, but traffic has weakened. |
| FIX | Something in the listing, presentation or offer needs improvement. |
| TEST | There is not enough evidence yet. |
| PROMOTE | A specific commercial offer may improve performance. |
| CLEAR | Inventory is moving too slowly and should be released. |
| STOP | There is enough evidence to reduce or end further investment. |
This makes the weekly meeting much more practical. Instead of asking "which product did badly?", we ask "what should we do with this product next?"
What should a TikTok Shop weekly report contain?
A useful TikTok Shop weekly report should not only show historical sales. It should answer these questions:
| Metric | What it tells us |
|---|---|
| Impressions | Is the product receiving enough exposure? |
| CTR | Are customers interested enough to click? |
| Product views | Is traffic reaching the listing? |
| Conversion rate | Does product interest turn into orders? |
| 7-day vs 30-day trend | Is behaviour improving or weakening? |
| Variant availability | Can customers buy the version they want? |
| Stock cover | Are we at risk of stockout? |
| Returns | Is there a potential product-quality issue? |
| Reviews | Is customer satisfaction affecting conversion? |
| Next action | What should the team do now? |
The final line is the most important. Next action. Because a dashboard only describes the past. A useful operating report helps shape the future.
What does a healthy TikTok Shop operation look like?
Before product-level optimisation, the operational foundation still matters. For one recent account under management, the service indicators were within healthy ranges:
| Service indicator | Result |
|---|---|
| Seller-related negative review rate | 0.21% |
| Seller-fault return and refund rate | 0.63% |
| 12-hour customer response rate | 99.25% |
| Average response time | 0.75 hours |
| Chat satisfaction rate | 75.8% |
These metrics matter because weak operations can distort everything else. Poor fulfilment can damage reviews. Slow customer service can reduce trust. High refund rates can hide deeper product issues.
So our view is: operations first, analysis second, optimisation after that. The important part is not stopping at the first layer.
What should an e-commerce enabler do with TikTok Shop data?
A strong e-commerce enabler should do more than provide reports. It should help translate marketplace data into commercial actions.
That means answering questions such as: which products deserve more exposure? Which products should be restocked? Which variants are becoming unavailable? Which listing needs a new image? Which product needs a promotion? Which product should go into LIVE? Which product should be pushed to affiliates? Which product needs more testing? Which inventory should be cleared? Which products should not be reordered?
This is how data becomes useful.
Why does Labu-Labu work this way?
At Labu-Labu, we work across e-commerce and social commerce operations in Malaysia: marketplace operations, TikTok Shop, livestreaming, creators, affiliates, content, campaigns, customer service, fulfilment and commerce analytics.
Operations are important. But we do not think an enabler's job should end with "the store is running". That should be the minimum standard. The more valuable work begins when we can connect the different parts of the business.
A product has traffic. It has content. It has creators. It has CTR. It has conversion. It has inventory. It has customer feedback. And it has a next decision.
If every department looks at its own KPI separately, it is easy to optimise the wrong thing. Marketing may push more traffic. Merchandising may order more inventory. LIVE may keep pushing whatever stock is available. Affiliate teams may recruit more creators. Operations may focus only on fulfilment. Everybody can do their individual job correctly while the business still makes the wrong commercial decision.
That is why we prefer to connect the whole loop: operate, analyse, diagnose, decide, execute, measure again. Every week.
Because the goal is not to create a better dashboard. The goal is to make a better decision before the next week starts.
Frequently asked questions
What metrics should brands track on TikTok Shop?
Brands should track more than GMV. Useful product-level metrics include impressions, CTR, product views, conversion rate, sales trends, stock cover, variant availability, returns, reviews and the recommended next action.
What is a good way to analyse TikTok Shop product performance?
A simple framework is to analyse the funnel from impressions to CTR to conversion, then overlay stock availability and recent-versus-longer-term trends. This helps distinguish exposure problems, listing problems, conversion problems and inventory problems.
Why can TikTok Shop sales fall even when the product is good?
Sales can fall because impressions decline, popular variants go out of stock, creator exposure weakens, LIVE rotation changes or customers cannot purchase the variant they want. Lower sales do not automatically mean weaker product demand.
When should a TikTok Shop display picture be changed?
A display-picture test can be useful when impressions are sufficient but CTR is weak. If customers are seeing the product but not clicking, the listing's first impression may need improvement.
When should a product receive more affiliate traffic?
More affiliate exposure may make sense when CTR and conversion are healthy, inventory is sufficient and the main constraint is low traffic or distribution.
When should a TikTok Shop product be discounted?
Discounting should usually address a specific problem, such as weak conversion, excess inventory or a planned clearance strategy. Weak sales alone are not enough to determine that price is the problem.
How do stockouts affect TikTok Shop conversion?
Stockouts can reduce conversion when customers reach the product page but cannot buy their preferred size, colour or variant. Total inventory may therefore look healthy even while the commercially important variants are unavailable.
What does an e-commerce enabler do with marketplace analytics?
An e-commerce enabler should turn marketplace data into decisions about exposure, listings, inventory, promotions, affiliates, livestreaming, replenishment, clearance and product discontinuation rather than only reporting historical sales.
How can Labu-Labu help?
If you want this kind of weekly read on your own TikTok Shop catalogue, with a next action against every product rather than a sales ranking, talk to us.