Does star power really sell gadgets?
The hook is massive.
The close is not.
Celebrity backing matches heavy discounting as a purchase driver and puts three-quarters of buyers at defection risk — but build quality and specs still decide the sale.
Explore the findingsStars steal the customer.
Specs keep them.
Near-universal penetration on base n=1,676 (about 1,490 buyers); the battle is conquest, not education.
Report pp. 7-8, 30-34Top-two-box switching intent on base n=1,676; loyalty sits with the endorser, not the product.
Report pp. 8-9, 30-34Rated 4-5 of 5 on trusting sensor and sound claims purely from star backing, base n=1,676.
Report pp. 11, 28, 30-34All figures are stated intent on base n=1,676, not observed purchases. Executive-summary n=300 tags are template leftovers; tabulated counts resolve to 1,676 throughout.
Stars open the funnel. Specs close it.
Penetration is near-total, loyalty is rented from whoever holds the talent contract, and the same respondents who say they trust stars demand build quality and reviews before paying.
Celebrity endorsement in budget tech is a conquest weapon with no retention power — it steals attention at the same weight as a deep discount, then hands the decision back to build quality and sensors.
A saturated market
Acquired a sub-Rs 10,000 gadget in the last 12 months, base n=1,676. Organic growth is over; every point of growth is stolen share.
Loyalty is rented
Highly likely to switch if a rival signs their favourite celebrity or athlete, base n=1,676. Retention needs exclusive talent contracts, not feature lists.
Borrowed credibility
High trust (4-5 of 5) in health-tracking and sound claims purely from star backing, base n=1,676. Stars bypass verification barriers in the abstract.
Movie stars beat tech experts
Pick screen and movie stars as the ambassador that makes a budget brand look reliable and premium, base n=1,676 (n about 916), vs 22.5% tech YouTubers and 19.3% athletes.
Stars match discounts
Cite celebrity endorsement as the primary purchase driver, exactly tying heavy discounting (base n=1,676 each); fashion and lifestyle matching is 17.1%. Star power protects margin.
Buzz without proof leaks
Say a celebrity ad influenced their last accessory buy (base n=1,676), yet build quality and display decide the smartwatch ranking — tabulated first-choice 50.5% vs narrative 71.0%; either way specs decide.
Shift from feature-led defence to celebrity-backed conquest for attention, then convert with specs at retail: exclusive entertainment-icon contracts in task-specific e-commerce and OTT creative, every asset carrying build, display and sensor proof.
Male-skewed, metro-scattered, single-device.
The volume buyer is an urban man; demand is spread across Tier-1 hubs and most owners hold just one sub-10k device.
Who took part
Gender, n=1,676
Top five metros
Demand spread across Tier-1 hubs
| Response | Respondents |
|---|---|
| Kolkata | 6.4% |
| Delhi | 6% |
| Hyderabad | 5.2% |
| Bangalore | 5.1% |
| Mumbai | 4.4% |
Ownership is concentrated: grooming and styling tools 40.5% lead smartwatches 36.8% and TWS 34.8% (multi-select, base n=1,676); 60.4% (1,013) own only one device. Source: pp. 25-26.
Three in four will follow their star to a rival.
Switching intent is the commercial spine of the report — and it rises with age, against youth-marketing intuition.
Switching likelihood
Would switch for a rival ambassador, n=1,676
| Response | Respondents |
|---|---|
| Highly likely (top-two-box) | 73.6% |
| Not likely or neutral | 26.4% |
Top-two-box by age
Switching intent rises with age
| Response | Highly likely |
|---|---|
| 55+ years | 78.1% |
| 36-45 years | 76.5% |
| 25-35 years | 72.3% |
Ambassador-cohort means
1-5 scale| Cohort | Switching mean | Trust mean |
|---|---|---|
| Movie-star fans (n=916) | 4.032 | 4.005 |
| Athlete fans (n=323) | 4.012 | 3.994 |
| Tech-influencer fans (about 377) | 3.830 | 3.934 |
| No-face preference (about 60) | 3.217 | 3.350 |
None-cohort at about 60 is directional. Source: pp. 12, 28.
Celebrity hooks half the buyers; hardware closes them.
Stars trigger the journey for 52.3%, but only 17.5% buy because of them and only 1.6% rank them first on a smartwatch.
Last-purchase influence
Celebrity influence on the last buy, n=1,676
| Response | Respondents |
|---|---|
| Celebrity ad influenced journey | 52.3% |
| Not primary driver | 47.7% |
Primary purchase reason
Top stated drivers, n=1,676
| Response | Respondents |
|---|---|
| Celebrity endorsement | 17.5% |
| Heavy discount | 17.5% |
| Fashion and lifestyle match | 17.1% |
Smartwatch driver ranking
n=1,676| Driver | First-choice | Top-3 | Mean rank | Borda |
|---|---|---|---|---|
| Build and display | 50.5% | 67.7% | 1.469 | 2637 |
| Sensors | 26.0% | 37.7% | 1.889 | 1874 |
| Discount | 15.8% | 37.5% | 2.313 | 1684 |
| Aesthetics | 6.1% | 23.0% | 2.881 | 1315 |
| Celebrity | 1.6% | 8.2% | 3.902 | 764 |
Tabulated figures used; narrative quotes 71.0% build-first and 6.6% celebrity-first, which contradict this table. First-places sum to 100.0. Source: p. 27.
73% trust stars — until you name the pairing.
General endorsement trust collapses when respondents rate concrete actor and athlete matchups.
Highly credible by pairing
Concrete endorsement matchups, n=1,676
| Response | Highly credible |
|---|---|
| Athlete and workout earbuds | 23.6% |
| Bollywood and fashion audio | 20.1% |
| Bollywood and lifestyle smartwatch | 19.2% |
| Athlete and fitness tracker | 15.2% |
find Bollywood and fashion-audio hard to believe — the single worst mismatch signal.
General trust in stars runs at 73.3% — but concrete pairings never clear 24% highly credible.
Alignment alone does not buy belief; show lived-in, long-term use, not glamour shots.
Retail banners and OTT beat the feed.
Attention concentrates at the point of purchase and on streaming; recall concentrates on one brand per head.
Where celebrity ads were noticed
Attention by channel, n=1,676
| Response | Selected |
|---|---|
| E-commerce banners | 37.8% |
| OTT | 36.8% |
| YouTube | 34.1% |
| TV | 23.9% |
| Outdoor | 21.8% |
Brand awareness
Celebrity-brand recall, n=1,676
| Response | Selected |
|---|---|
| boAt | 41.2% |
Co-recall is rival-bundled: OnePlus-Realme support 16.65% at lift 1.42; Boult-Fire-Boltt lift 1.57. Generic star-lifestyle ads cause mental bundling — differentiate on features. Source: pp. 28-29.
What to do before paying for a face.
Four priorities weighted to the tensions, not the headlines.
Lock out rivals with exclusive entertainment-icon contracts
73.6% defection risk and 54.7% premium cue from movie stars — exclusivity is retention.
Cast by task, not by fame
74.6% use devices in limited windows; avoid the 37.4%-hard-to-believe mismatches with task-specific casting.
Make every star asset carry specs plus reviews
52.3% hook vs 50.5% spec-first ranking — satisfy the verifiers or the stolen attention leaks.
Buy e-commerce plus OTT, not TV and outdoor
37.8 and 36.8 vs 23.9 and 21.8 — with a 25-35 retail skew at 44.7% e-commerce notice.
Recommendations synthesised from report pp. 2-3, 27-34.
