Working paperNot peer-reviewed

ContentIQ working paperCIQ-WP-2026-36CategoryVersion 11 Oct 2026

Pet Supplies on TikTok Shop is shrinking faster than average, and its sales sit in higher-priced products

Pet Supplies, 1 category: 279 videos tracked, 101 analysed in depth, 100 top-selling products, 2 Sept–1 Oct 2026

MediaLabs Research · in collaboration with Coherence Limited

Scope
Category
Data
2 Sep – 1 Oct 2026
Sample
279 videos · 101 watched · 100 products · 1 category
−19.7%: change in category revenue, latest 4 weeks against the previous 4

Key findings

  1. 01−19.7%change in category revenue, latest 4 weeks against the previous 4
  2. 0222 of 28category rank by revenue, with 1.3% of market revenue
  3. 0371%of category revenue sold through shoppable video (market: 65%)
  4. 041.45×revenue per product for items priced $100 and over, against the average product
  5. 058%of top-product revenue from products launched in the last 90 days
  6. 060.64AUC of the top-seller model (90% range 0.57–0.70)
Contents
  1. Abstract
  2. 1.Introduction
  3. 2.Data
  4. 3.Methods
  5. 4.Results: momentum and sales channels
  6. 5.Results: prices, commission and competition
  7. 6.Results: hooks, formats and production
  8. 7.Discussion
  9. 8.Conclusion
  10. Methodology
  11. Limitations
  12. References
  13. Cite as

Abstract

We analysed Pet Supplies on TikTok Shop over the 30 days to 1 October 2026. The category ranks 22nd of 28 by revenue, and its revenue in the latest 4 weeks was 19.7% below the previous 4 weeks. Products priced at $100 and over earned 33% of top-product revenue, and video accounted for 71% of sales. Differences in sales per view between hooks and formats are mostly small relative to their uncertainty, and our predictive model ranks top-selling videos only modestly (AUC 0.64).

1. Introduction

Brands and creators choosing what to sell and what to film on TikTok Shop face two questions: is the category growing, and which products and video approaches are associated with sales within it? This paper asks both for Pet Supplies, using our analysis of top-selling videos and products in the 30 days to 1 October 2026.

Prior work on short-video popularity finds that attention is long-tailed and that early popularity predicts later popularity [1]. Recent benchmarks show that creator-level features carry most of the predictive signal and that video content adds comparatively little [2, 3]. Work on social commerce suggests that trust-building formats such as live selling matter for conversion [4], and that online retail sells a long tail of products beyond the bestsellers [5]. Affiliate commissions are set by sellers for reasons that vary by product and margin [6].

We describe associations only. None of the patterns below shows that a hook, format or price causes sales.

2. Data

The window runs from 2 September to 1 October 2026. We tracked 279 videos in Pet Supplies, and our AI analyst watched and analysed 101 of them in depth. Marketplace figures rest on 100 top-selling products in the category. Across all categories, 3,342 videos were analysed in depth, which gives the market benchmark for sales per view.

For each analysed video we recorded its hook, format and production style. Hook and format labels exist for 92 videos and production for 74, so the group sizes below are smaller than 101. For products we recorded price, affiliate commission, launch date and the share of revenue sold through video. Shop counts, active products and channel splits are from the latest week (to 29 September).

Daily rankings of top-selling TikTok Shop videos in the US were collected from several independent sources and merged into one record per video. Where sources overlap, their sales estimates are cross-checked against each other, and videos whose estimates disagree by more than half are flagged. An AI analyst watched each video and recorded its opening, format, angle, production style, use of AI, hook source, length, pacing and what appears in the first second, without seeing how the video sold. Sales per view is a video group’s revenue per view divided by the market’s, shrunk toward the average for small groups, with 90% ranges. Weekly category figures for the US (estimated revenue, its split between video, LIVE and the shop tab, affiliate revenue, shops and active products, and a year of weekly revenue) and daily rankings of each category’s top-selling products (unit price, commission rate, launch date and revenue by channel) were collected from several independent sources. Medians of price and commission are weighted by revenue; momentum compares the latest weeks with the same number of weeks before. This paper covers 2026-09-02 to 2026-10-01: 279 videos tracked in Pet Supplies, 101 of them watched and analysed; the market baseline uses all 3,342 watched videos; 100 top-selling products in Pet Supplies. Predictions come from a logistic model retrained daily and tested on recent weeks it had not seen.

3. Methods

Sales per view is a group of videos' revenue per view divided by the market's, so 1 is the market average. Small groups are shrunk toward the average by empirical Bayes [7], and we report 90% intervals on the log scale. Confidence labels (low, medium, high) reflect group size and interval width.

The predictive model is a logistic model of top-selling videos, retrained daily and tested on recent weeks it had not seen. We report AUC as a ranking measure [8] with a bootstrap range [9]. Momentum compares estimated revenue in the latest 4 and 13 weeks with the same number of weeks before. Channels split the latest week's revenue into shoppable video, LIVE and the shop tab.

Prices and commission rates are revenue-weighted medians across the tracked top products. Concentration is the top ten products' share of top-product revenue and the Herfindahl–Hirschman index [10]. Seasonality compares each month's revenue with the category's average month over the past year, excluding the partial first and last months, in the spirit of seasonal-trend separation [11].

4. Results: momentum and sales channels

Pet Supplies took 1.3% of market revenue in the latest 4 weeks, ranking 22nd of 28 categories. Revenue in those 4 weeks was 19.7% below the previous 4. Over 13 weeks the category fell 6.6% against a market-wide fall of 11.1%, so the longer-run decline is milder than the market's even though the recent month is weak.

Sales are concentrated in shoppable video: 70.8% of latest-week revenue, against 64.9% for the market. LIVE accounts for 12.6% (market 17.1%) and the shop tab for 16.6% (market 18%). Affiliate creators were credited with 76.7% of category revenue. Video and affiliates are therefore the main routes to sales here, and LIVE is a smaller route than elsewhere.

Pet Supplies: revenue per week, last six months
Figure 1. Pet Supplies: revenue per week, last six months

5. Results: prices, commission and competition

The revenue-weighted median price of top products is $58, and the middle half falls between $22 and $129. Products at $100 and over (23 products) earned 33.3% of top-product revenue, and each earned 1.45× the average product. Every other band earned 0.82–0.91× the average product per item. Only one top product sold under $10, so that band says little.

The revenue-weighted median commission is 9%. The 5–10% band holds 42 products and 51% of revenue, and products in the 10–15% band earned 1.10× the average. Products at 15–20% earned 0.68×, and the three under 5% earned 0.48×. Between 81% and 98% of revenue in every commission band was sold through video. Higher commission is not associated with higher revenue per product.

Competition is broad rather than top-heavy. There are 4,368 shops and 15,031 active products, and average revenue per shop is $1,332 against $2,401 in the median category. The top ten products hold 36.3% of top-product revenue, the same as the median category, and the HHI is 223. Products launched within 90 days brought 8% of top-product revenue, while the 3–6 month band earned 1.42× the average product (13 products).

Table 1. Pet Supplies: top-selling products by price band
BandProducts (n)Share of revenueRevenue per product vs average
Under $1010.8%0.84×
$10–202119.1%0.91×
$20–351714.4%0.85×
$35–602117.2%0.82×
$60–1001715.2%0.89×
$100 and over2333.3%1.45×

Note. Among the top-selling products we track in the latest week; revenue per product is against the average product in the same set (1.00 = average).

6. Results: hooks, formats and production

Most differences in sales per view are small relative to their uncertainty. Bold-claim hooks sold at 1.5× the market (90% range 0.98–2.36), but this rests on 7 videos and has low confidence. Problem call-outs, the largest hook group with 28 videos and 28.7% of sales, sold at 1.2× (0.92–1.66). Comparison hooks (0.82×, 0.62–1.09) and straight-into-the-demo openings (0.80×, 0.54–1.17) sat below the market average, but their ranges also include 1.

For formats, demos and tutorials were the largest group, with 37 videos and 36.5% of sales, and sold at 0.88× (0.69–1.11) with high confidence. Voice-over B-roll sold at 1.09× (0.76–1.56) and talking heads at 1.13× (0.74–1.74, low confidence). Among the 74 videos with a production label, all were filmed live action, at 1.00× (0.84–1.20).

The top-seller model has an AUC of 0.64 (90% range 0.57–0.70), trained on 2,667 rows. It was not restricted to analyses that never saw sales (cleanOnly is false). Its strongest associations include before-and-after videos (odds ratio 1.66), no visible AI (1.71) and boosting with ads (1.59). Education content is associated with lower odds (0.59). The model ranks videos only modestly better than chance.

Table 2. Sales per view and share of sales by hook
ValueVideos (n)Share of salesSales per view90% range
Bold claim79%1.52×0.98–2.36
Problem call-out2828.7%1.23×0.92–1.66
Price or deal87%1.03×0.66–1.60
Story opener58.1%1.02×0.57–1.81
Visual pattern-break106.4%0.97×0.65–1.46
Relatable POV1518.4%0.94×0.68–1.31
Comparison1113.3%0.82×0.61–1.09
Straight into the demo89.1%0.80×0.54–1.17

Note. Sales per view is relative to the market (1.00 = average), shrunk toward the average for small groups (empirical Bayes); ranges are 90% intervals on the log scale.

7. Discussion

For brands, the category is large in shops but weak in recent momentum. Revenue per shop is well below the median category, the top ten products hold a typical share of revenue, and the $100-and-over band stands out for revenue per product. This is consistent with a market where higher-ticket items do well, but we cannot say whether price drives that result. Product mix, bundle size or pet type could explain it. Commission shows no clear gradient in revenue per product, which fits the view that sellers set rates for reasons beyond demand [6].

For creators, the evidence does not support a single winning hook or format. Problem call-outs and bold claims lead on point estimates, but wide ranges and small groups mean we would treat them as hypotheses to test. The modest AUC fits earlier findings that video content alone predicts outcomes poorly [2]. Creator reach, ad boosting and product choice probably matter more, and the returns to advertising are hard to measure from observational data [12].

Seasonality is uneven. Over the past year the category ran at 1.24× a normal month in June and 1.20× in March, 1.12× in December and 0.86× in July. November 2025 was near normal (0.99×). Halloween is under way, Black Friday and Cyber Monday start in 40 days and holiday gifting in 45. The data do not show a clear November lift, so peak planning should not assume one.

Pet Supplies: monthly sales against its own average month (1 = a normal month)
Figure 2. Pet Supplies: monthly sales against its own average month (1 = a normal month)

8. Conclusion

Pet Supplies is a mid-sized, video- and affiliate-led category whose revenue fell 19.7% in the latest 4 weeks and 6.6% over 13 weeks, a milder fall than the market over the longer period. Revenue per product is highest at $100 and over, commission rates around 5–15% hold most revenue, and recent launches contribute only 8% of it.

Hook and format effects are mostly small compared with their uncertainty, and the predictive model is modest. Brands and creators should treat the leading hooks as tests, not rules, and watch the next weeks for whether holiday demand reverses the recent decline.

Methodology

Daily rankings of top-selling TikTok Shop videos in the US were collected from several independent sources and merged into one record per video. Where sources overlap, their sales estimates are cross-checked against each other, and videos whose estimates disagree by more than half are flagged. An AI analyst watched each video and recorded its opening, format, angle, production style, use of AI, hook source, length, pacing and what appears in the first second, without seeing how the video sold. Sales per view is a video group’s revenue per view divided by the market’s, shrunk toward the average for small groups, with 90% ranges. Weekly category figures for the US (estimated revenue, its split between video, LIVE and the shop tab, affiliate revenue, shops and active products, and a year of weekly revenue) and daily rankings of each category’s top-selling products (unit price, commission rate, launch date and revenue by channel) were collected from several independent sources. Medians of price and commission are weighted by revenue; momentum compares the latest weeks with the same number of weeks before. This paper covers 2026-09-02 to 2026-10-01: 279 videos tracked in Pet Supplies, 101 of them watched and analysed; the market baseline uses all 3,342 watched videos; 100 top-selling products in Pet Supplies. Predictions come from a logistic model retrained daily and tested on recent weeks it had not seen.

Limitations

Most videos in the sample are top-ranked, so findings mostly separate strong sellers from good ones rather than from all videos; typical and weak videos are being added. Product figures cover the top-selling products we track in each category, not every listing, so they describe what sells best rather than everything on sale. Results are associations, not causes. Paid promotion, creator audience size and product price are not fully controlled for. Revenue, views and sales are estimates, not figures reported by TikTok. The in-depth sample is 101 videos, and hook and format labels exist for 92 of them. Several groups have fewer than 10 videos and low confidence. The production comparison has a single category, so it cannot show differences between styles. The model was not trained only on analyses that never saw sales, so its score may be flattered. The window is 30 days, the seasonal series covers about one year, and all figures are observational associations.

References

  1. [1]Szabo, G., & Huberman, B. A. (2010). Predicting the popularity of online content. Communications of the ACM, 53(8), 80–88. cacm.acm.org/research/predicting-the-popularity-of-online-content
  2. [2]Ye, L., Zhang, Y., Wu, Y., et al. (2025). MVP: Winning solution to SMP Challenge 2025 video track. arXiv:2507.00950. arxiv.org/abs/2507.00950
  3. [3]Lu, J., Wang, W., Xiao, M., et al. (2024). M3TR: Temporal retrieval enhanced multi-modal micro-video popularity prediction. arXiv:2411.15455. arxiv.org/abs/2411.15455
  4. [4]Wongkitrungrueng, A., & Assarut, N. (2020). The role of live streaming in building consumer trust and engagement with social commerce sellers. Journal of Business Research, 117, 543–556.
  5. [5]Brynjolfsson, E., Hu, Y. J., & Smith, M. D. (2003). Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers. Management Science, 49(11), 1580–1596.
  6. [6]Libai, B., Biyalogorsky, E., & Gerstner, E. (2003). Setting referral fees in affiliate marketing. Journal of Service Research, 5(4), 303–315.
  7. [7]Efron, B., & Morris, C. (1975). Data analysis using Stein’s estimator and its generalizations. Journal of the American Statistical Association, 70(350), 311–319.
  8. [8]Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27(8), 861–874.
  9. [9]Efron, B., & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. Chapman & Hall.
  10. [10]Rhoades, S. A. (1993). The Herfindahl–Hirschman index. Federal Reserve Bulletin, 79, 188–189.
  11. [11]Cleveland, R. B., Cleveland, W. S., McRae, J. E., & Terpenning, I. (1990). STL: A seasonal-trend decomposition procedure based on loess. Journal of Official Statistics, 6(1), 3–73.
  12. [12]Lewis, R. A., & Rao, J. M. (2015). The unfavorable economics of measuring the returns to advertising. The Quarterly Journal of Economics, 130(4), 1941–1973.

Cite as

MediaLabs Research, in collaboration with Coherence Limited (2026). Pet Supplies on TikTok Shop is shrinking faster than average, and its sales sit in higher-priced products. ContentIQ Working Paper CIQ-WP-2026-36, version 1. https://medialabs-co.com/research/category-pet-supplies

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Analysis and data: Coherence Research, Coherence ContentIQ. Published by MediaLabs in collaboration with Coherence Limited.

Version history

  • Version 11 Oct 2026This version

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