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Who promotes home and garden brands: 2026 affiliate data

Who promotes home and garden brands? In a first search, most people shown had a review or roundup page as their best evidence (61%). Next came a blog-style page (24%) and a podcast (14%). This page gives the counts for six brands, how many have an email found, and what to do first.

An affiliate promotes your product and earns a cut of each sale they send. A roundup is a page that ranks several brands, such as "best bedding brands". The median is the middle brand when you line the six up from smallest to largest. "Email found" means an address was on record for that person. We did not check it.

What did the scan find for home and garden brands?

On 22 October 2026 we ran one first search on each of six public Shopify home and garden brands. Three were UK and three were US. The topics we typed included tableware, eco cleaning and heirloom seeds.

Type of pageMedian per brandRangeShare of people shown
Review or roundup page63.526 to 9061%
Blog-style page11.50 to 8324%
Podcast13.51 to 3314%
TikTok, Instagram or newsletter10 to 11%
All people shown9235 to 160100%
With an email found315 to 5329% of all shown

Median and range are per brand. With six brands, the median is the average of the middle two, so it can end in .5. The share column adds each type's people across all six brands. So the shares add up to about 100% after rounding, but the medians do not. A check of 30 random rows from all five categories found 9 that were not promoters (how we counted).

We ran this · 22 October 2026

One UK home and garden brand showed 91 people on its first search.

  • 56 had a review or roundup page, 19 were podcasts and 15 had a blog-style page.
  • 24 had an email found.

How we counted: We added the brand to RecruitAffiliates.ai with 2 rivals and 3 topics typed by hand. Then we ran the product's normal first search. The counts are the people it showed after its own filter. The scan stopped at emails found and ran no email checks. Sample: One of six public Shopify home and garden brands, estimated sales of $25k to $50k a month (the list's own estimate). Searched once on 22 October 2026.

Does it differ in the UK and the US?

Market (3 brands each)Sales a monthPeople shown, medianRangeEmail found, median
UK$25k to $50k9135 to 9324
US$100k to $250k15178 to 16032

The UK median was 91 and the US median was 151. All brands were searched in the same six countries with our own offer. Size and country move together here, because the UK brands are smaller than the US brands. So don't read the gap as a market effect. All five categories side by side are in how we scanned 30 Shopify brands.

What does this mean for a home and garden brand?

  • Expect a wide range. One brand showed 35 people and another 160. Your count may depend on how clear your product and your rivals are, so run your own search.
  • The typical brand showed 12 blog-style pages. The median was 11 to 12 in every category. One brand showed 83, which lifts the share to 24%. We can't tell why from the scan.
  • Add podcasts and roundups. Podcasts were 14% and review or roundup pages 61%. Both are worth a short list.

What should you do next?

  1. Search the product you sell most and list the blogs that rank for it.
  2. Offer each writer a sample and a clear commission.
  3. Add the roundup pages that name your rivals as a second list.

Then set your offer. Public home and garden programs state a median base commission of 10%. The middle half state 8% to 18.5%, the widest of the five categories. That is from 14 public program pages, not the six brands we scanned. Read what commission Shopify brands pay for the full table. Our page on affiliates for homeware brands covers the basics.

RecruitAffiliates.ai runs this search on your own store and shows the page where it found each person. Already use an affiliate app? Our guides cover Shopify Collabs, UpPromote, GoAffPro, Social Snowball and Refersion.

How did we count?

We added each brand to RecruitAffiliates.ai with two rivals and three topics typed by hand. Then we ran the normal first search. The first search reads web pages, podcasts, TikTok and Instagram. The counts are the people it showed after its own filter, and each brand was searched once. An AI model read the title and address of 30 random rows from all five categories, and we opened no pages. 19 were a clear fit and 2 a loose fit. Nine were not promoters (30%, likely range 17% to 48%). A review or roundup label comes from the page, not the publisher, so some are single-post bloggers. Six brands a category is a small, hand-picked sample, so read medians as rough. The full method and limits are in how we scanned 30 Shopify brands. The 2026 data report has the press summary.

Questions people ask

How many people could promote my home and garden brand?

In our sample, a first search showed a median of 92 people per brand. The range was 35 to 160. A full setup shows more. In a follow-up on a paid plan with every source on, 3 of the 30 public brands showed a median of 693 people each, and 71% of them came from YouTube. Run it on your own store to see your number.

Where do the email addresses come from?

178 of the 608 people shown had an email found. The product records the page each address came from. The scan did not check them. The product checks an address when you look it up, and you keep it only if you get a verified email (what each result means).

Do US home and garden brands show more people than UK ones?

The US median was 151 and the UK median was 91, but the ranges overlap (UK 35 to 93, US 78 to 160). The US brands were also the larger ones, so we can't tell size from country.

Are blogs worth chasing for home and garden?

The typical brand showed 12 blog-style pages. The median was 11 to 12 in every category. One brand showed 83, and the scan can't tell us why. A short list of bloggers is still a cheap thing to build.

Can I use these numbers?

Yes. Please link to this page and name RecruitAffiliates.ai as the source. Give the date, 22 October 2026. The per-brand counts are open, with no brand names: download the CSV.

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