Smartwatches: cheap ones can raise prices, mid-priced ones gain little from cuts
I measured 1,935 price changes across 347 smartwatches and compared each one against the products that held their price. A 10 percent cut improved the sales rank by about 8 percent within two weeks, and a 10 percent increase cost about 7 percent. Below €40 an increase cost clearly less than above. This is report 4 of twelve in this quarter's consumer electronics series.
In short
- A cut lifts the rank. A 10 percent cut improved the rank by about 8 percent (range 6 to 10) within two weeks.
- Increases cost about as much. A 10 percent increase cost about 7 percent of rank (range 6 to 8). I cannot separate the two directions.
- Below €40, a price rise costs little. Budget watches lost about 4 percent of rank per 10 percent increase (range 2 to 5). Between €40 and €68 it was about 9 percent, above €68 about 8 percent.
- Between €40 and €68, a cut does the least. Mid-priced watches gained about 5 percent of rank per 10 percent cut (range 3 to 8). Above €68 it was about 12 percent (range 9 to 15).
- Competitors move less after a cut. In the two weeks after a cut, other sellers changed their prices about 15 percent less often than usual.
Price cuts
A 10% cut improved rank by roughly 6 to 10 percent.
Price increases
A 10% increase cost roughly 6 to 8 percent of rank.
Cheap watches shrug off a rise, mid-priced ones shrug off a cut
Below €40, an increase cost only a little rank. Its range runs from 0.25 to 0.54 and stays below the ranges of both pricier groups, so this difference holds up in the data.
Cuts show a second split. Between €40 and €68 a cut moved the rank about half as far as the price, clearly less than above €68. The budget group overlaps both, so I cannot place it.
Put together, the cheap end tolerates price rises best, and the middle responds least to discounts.
The full picture
01 · Does discount depth matter?
Somewhat. Deeper cuts did more, the steps blur into each other.
Every move counts, big rises hurt most
A cut of 5 to 15 percent improved the rank by 13 percent, 15 to 25 percent by 20 percent and more than 25 percent by 30 percent. Neighbouring steps overlap, so I cannot show that each extra step adds more.
Rises of 5 to 15 and 15 to 25 percent both cost about 16 percent of rank. A rise of more than 25 percent cost 33 percent, clearly more. Every step stays away from the no-change line.
02 · Will competitors follow?
They move less often than usual.
After a cut, the shelf goes quieter
I looked at 2,456 cuts on 433 products. Within 14 days, some competitor changed a price after 99 percent of them. Compared with a normal two-week window, competitors moved about 15 percent less often after a cut.
After an increase it was about 10 percent less often. 76 percent of first moves fell on the same day as the trigger, which I cannot read as a reaction.
03 · Where can a new product get in?
Between €43 and €55, where most judged newcomers made it.
The one band where newcomers win often
In the last 24 months, 360 new products entered this shelf. 76 of them now rank in the top third, and 41 have left again.
The scoring in my tool points to €190 to €243. I overrule it, because only one newcomer there could be judged. Between €43.04 and €55.13 I could judge 20 newcomers, and 12 of them reached the top third. That band also holds more than its fair share of top products. It is the best-supported way in that I found in this report.
04 · What does the shelf look like?
A busy shelf where newcomers arrive and leave fast.
Of the 639 products I could place on the price map, 156 sit in the three cheapest bands, up to €43.04. 44 sit in the four most expensive bands, from €148.
The typical product in a band has between 80 and 863 reviews. A typical price held for 44 to 365 days, depending on the band.
Data appendix
I started from a list of 4,990 listings on amazon.de. I removed 1,164 listings that were not smartwatches, such as bands, cases, chargers, smart rings and watches for children or seniors. I also removed 5 multipacks and sets, 466 listings outside €20 to €500 and 817 listings with fewer than 20 reviews. To keep single brands from dominating, I kept at most three products per brand, which removed 1,776. Of the remaining 762 listings, 438 were variation groups that cannot be bought themselves. I replaced each with one sellable variant, the one with the longest price history, and checked the variants against the same rules. That gave 700 products. Titles such as "smartwatch for men and women" are keyword filler, so I did not treat them as separate lines. After the price history came in, I removed 16 whose typical price fell outside €20 to €500, which left 684. Of these, 187 never showed a price on amazon.de, so they add nothing to the figures.
I compare each product only against products in the same Amazon category, here "Smartwatches". That is stricter than title keywords, because many fitness bands call themselves a smartwatch in their title. 45 products sat outside this category, and their 253 price changes were left out. The product list is available on request for methodological review.
| Step | Events | Removed because |
|---|---|---|
| Price changes found | 5,156 | n/a |
| Gaps in the price history | −252 | the price history had holes around the change |
| Too little ranking data | −361 | the rank was missing on too many days |
| Overlapping price change | −1,080 | another price change fell inside the measuring window |
| Deal or coupon markers | 0 | a deal or coupon ran at the same time |
| Stockout signals | −384 | the product looked out of stock |
| Burst of new reviews | −1,211 | reviews jumped at the same time |
| Listing too young | −448 | the listing was less than 60 days old |
| Too few control products | −340 | fewer than 5 comparable products held their price |
| Passed every check | 2,368 | one event can fail several checks |
| Used for the figures | 1,935 | minus 213 with a trend already running before the change and 253 from products outside the category, 33 of them counted in both |
price change ≥ 5% and ≥ €0.30, held ≥ 7 days · comparison: 14 days before, days 3 to 14 after · control products: same category, price moved less than 2%, at least 5 of them · rank coverage ≥ 70% of days · listing older than 60 days · review burst = more than 10% and at least 15 new reviews · ranges are 90%, from a bootstrap clustered by product · study protocol v1.1
The price changes I found range from −79 percent to +488 percent. The extreme values are listings returning from a nominal placeholder price after being unavailable. They do not drive the figures, which come from the dense middle. 63 percent of the used changes were cuts or increases of up to 25 percent.
Limits
- LIMITS: I measure the ranking, not units sold, and only over two weeks after a change. Every figure holds only for the price moves sellers actually made in this category. The price groups are thirds of this set, so "premium" means €68.99 to €436.75 here. Competitor reactions are counted as any price change by another product in the category, which says nothing about intent. The entry view looks back 24 months and judges newcomers only once they have been listed long enough.
- 684 products
- 5,156 price changes found
- 2,368 passed every check
- 1,935 used for the figures
- 347 products in the fit set
- ref 5f1ced16
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