Menswear & Underwear on TikTok Shop: rebounding in the short run, video-led, and priced mostly at $20–60

1. Introduction

Menswear & Underwear is a staple category on TikTok Shop, and brands and creators within it face two practical questions: which products and price points to back, and which kinds of video to make. Both are hard to answer from intuition, because a small number of videos and products capture most of the revenue.

Prior work on short-video popularity finds that attention is long-tailed and that early popularity predicts later popularity [1]. Recent benchmark and competition work shows that predicting popularity from content is difficult, with creator features often mattering most [2, 3]. Work on live-stream selling suggests it can build trust and engagement with social commerce sellers [4], and work on affiliate marketing explains why referral fees vary [5]. Online retail also sells a long tail of niche products beyond the bestsellers [6].

We ask four things of this category: how it is moving, where and at what price it sells, how crowded it is, and which video formats are associated with higher sales per view. All findings are associations, not causal effects; the returns to advertising are notoriously hard to measure from observational data [7].

2. Data

Our analysis covers 231 videos tracked in Menswear & Underwear between 2 September and 1 October 2026. Our AI analyst watched and analysed 128 of them in depth, recording attributes such as hook, format and production style. Marketplace figures (prices, commission, product age, concentration) rest on the 100 top-selling products tracked in the category. Market comparisons for video sales per view use a market-wide set of 3,342 watched videos.

Channel, momentum and competition figures are as of 29 September 2026, and price and commission figures as of 1 October 2026. Seasonality uses monthly revenue over the past year, leaving out the partial first and last months.

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: 231 videos tracked in Menswear & Underwear, 128 of them watched and analysed; the market baseline uses all 3,342 watched videos; 100 top-selling products in Menswear & Underwear. 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. Estimates for small groups are shrunk toward the average by empirical Bayes [8], and we report 90% intervals computed on the log scale. Confidence labels (high, medium, low) 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 (a time split). We report AUC as a ranking measure [9], with a bootstrap range [10]. Odds ratios come from the same model.

Momentum compares the category's estimated revenue in the latest 4 and 13 weeks with the same number of weeks before; shares are of all categories tracked. Channels split the latest week's revenue into shoppable video, LIVE and the shop tab, plus the share credited to affiliate creators. Prices, commission rates and product age are for the top-selling products, with medians and ranges weighted by revenue. Competition uses shops and active products, revenue per shop, the top ten's share of top-product revenue and the Herfindahl–Hirschman index [11]. Seasonality compares each month with the category's average month (1 = normal), following the logic of separating season from trend [12].

4. Results: momentum, channels and competition

Menswear & Underwear took 3.5% of market revenue in the latest 4 weeks, ranking 8th of 28 categories. Revenue in those 4 weeks was 20.7% above the previous 4 weeks. Over a longer horizon the picture is weaker: the latest 13 weeks were 19.4% below the previous 13, against a market decline of 11.1%. The recent rise is therefore a rebound within a softer quarter, not clear evidence of sustained growth.

Sales lean on shoppable video: 68.9% of category revenue, against 64.9% across the market. The shop tab takes 25.4% (market 18%) and LIVE only 5.7% (market 17.1%). Affiliate creators are credited with 70.5% of category revenue.

Competition is broad but not unusually concentrated. The category has 7,456 shops (the median category has 4,461) and 83,217 active products. Average revenue per shop is $2,586, against $2,401 in the median category. The top ten products hold 24.6% of top-product revenue, the same as the median category, and the Herfindahl–Hirschman index among tracked top products is 142, which is low.

5. Results: formats, hooks and what the model captures

Among watched videos, talking-head videos sell at 1.5× the market's sales per view (90% range 1.17–1.97, 15 videos, medium confidence). This is the only format whose range sits clearly above 1. Demo or tutorial videos are the largest group (43 videos, 35.4% of watched-video sales) and sell at 1.09× (0.91–1.30, high confidence), so a result near average is well established. Skits (0.76×, 5 videos) and comparisons (0.84×, 6 videos) are low-confidence, and routine or GRWM videos sell at 0.82× (0.61–1.10).

Hooks matter less. Bold claim is highest at 1.15× (0.89–1.50), and every hook range with medium confidence includes 1. The comparison hook is lowest at 0.69× (0.47–1.02, 7 videos, low confidence). Filmed live action (76 videos, 86.2% of sales) sells at 0.99× (0.86–1.14) and photo slideshows (10 videos) at 0.93× (0.66–1.29), so we find no reliable gap between them in sales per view.

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), so it should be read as descriptive. Its largest odds ratios are for filmed live action (2.54), a visual pattern-break combined with a review or testimonial (1.92) and no visible AI (1.71). That is only modest ranking power.

6. Results: prices, commission and product age

The revenue-weighted median price of top products is $31, with the middle half between $25 and $49. Revenue is concentrated in two bands: $20–35 (39 products, 38.8% of revenue) and $35–60 (32 products, 35.6%). Revenue per product is highest in the $35–60 band, at 1.11× the average product. The $20–35 band is at 1.00×, and $10–20 at 1.01×. Products at $60–100 earn 0.70× the average (9 products). The under-$10 and $100-and-over bands hold only 2 and 1 products, so we draw no conclusion from them.

The revenue-weighted median commission is 9%. Most revenue (70.8%) is in the 5–10% band (59 products, 1.06× average revenue per product). The 10–15% band (25 products) is at 0.87×. The 15–20% band (3 products) is at 1.15× but is too small to interpret. Across bands, 91.5–98.1% of product revenue is sold through video.

Products launched in the last 90 days account for 20.8% of top-product revenue (24 products), but each earns about 0.87× the average. Products over 2 years old (14 products) hold 20% of revenue and earn 1.43× the average, so established products remain strong.

7. Discussion

For brands, the evidence points to a mid-priced, video-led category. Products at $20–60 hold 74.4% of top-product revenue, commission is typically 9%, and established products out-earn new ones per product. A high commission band shows no clear revenue advantage in our data. Low LIVE share (5.7% against 17.1%) may signal an under-used channel, but we cannot tell from this analysis whether LIVE would work here, only that it is currently small.

For creators, talking-head videos are associated with higher sales per view, but from a small group of 15 videos and a wide range. Most formats and hooks sit within noise of the average, and the model's AUC of 0.64 is modest. Choice of product, price and creator audience likely matters more than any single creative choice, consistent with prior work [2]. Alternative explanations include creator reach, product mix, advertising spend and survivorship among top-selling products, none of which we can separate here.

Seasonality over the past year shows a stronger March (1.20×), May (1.13×) and June (1.21×) and weaker February (0.82×) and August (0.79×). November and December 2025 were 1.02× and 0.92× a normal month, so holiday months did not clearly lift the category; this rests on one year of data. Halloween is under way, Black Friday / Cyber Monday starts in 40 days, Holiday gifting in 45 days and New Year resolutions in 92 days. We have no category-specific evidence for how these moments affect Menswear & Underwear.

8. Conclusion

Menswear & Underwear is a mid-sized category (8th of 28 by recent revenue) that is rebounding in the short term (+20.7%) but is still down over 13 weeks (-19.4%). It sells mainly through shoppable video at roughly $25–49, at modest commission, among many shops with little concentration.

Only talking-head videos show a clear, though uncertain, advantage in sales per view (1.5×, 90% range 1.17–1.97). Other creative choices matter less than the product, the price and the audience. These findings are associations from a single 30-day window, a small watched sample and a model with modest accuracy, and should guide tests rather than fixed rules.