Small business=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 76 → 75 of 76
2 categories · RankedFriendbuy
127Judge labels
9First choices
37Negative labels
14 / 14Models named it
2Categories
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10-05.2, every buyer segment counted.
Best standing
6% in Loyalty for enterprise buyers
Rank 7 of 112 in the mid-market standingaccepted challenger
1 of 14 models made it the first choice on the direct prompt; 9% of its 23 labels there were negative.
What the models named instead of Friendbuy →By buyer segmentRead the same way at every buyer size.
Small business83 of 83
0%18 labels
criticized challenger
Mid-market7 of 112
4%23 labels
accepted challenger
Enterprise5 of 69
6%36 labels
accepted challenger
In referrals · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading
Standing by category
Every category where a model named Friendbuy for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Referral and partner programs | Partner and channel | 4% | 7 of 112 | 9% | 23 | accepted challenger | ▲+4Since September 2026: 0% → 4%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
| Loyalty, advocacy and referrals | Marketing | 2% | 12 of 110 | 30% | 23 | criticized challenger | ▲+3Since September 2026: 0% → 3%, +3 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
Movement
Since September 2026, Friendbuy held within the floor in all two categories: no change cleared 11 points.
Best category · Referrals · by segment
Mid-market▲+4Since September 2026: 0% → 4%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
4%from 0% in September 2026
Inside the floor by 7 pointsRank 22 → 6 of 106
Enterprise▲+4Since September 2026: 0% → 4%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
4%from 0% in September 2026
Inside the floor by 7 pointsRank 18 → 6 of 65
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Referrals | 0% | 4% | ▲+4Since September 2026: 0% → 4%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 22 → 7 of 112 |
| Loyalty | 0% | 3% | ▲+3Since September 2026: 0% → 3%, +3 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 23 → 12 of 110 |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
By model
How each model treated Friendbuy across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated Friendbuy across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 2 | 1 | 1 | 4 |
| GPT-5.4 mini | 0 | 2 | 0 | 1 | 3 |
| Gemini 3.5 Flash | 0 | 2 | 2 | 1 | 5 |
| Perplexity Sonar | 1 | 0 | 0 | 0 | 1 |
| Grok 4.20 | 1 | 1 | 1 | 0 | 3 |
| Mistral Small | 1 | 1 | 1 | 0 | 3 |
| DeepSeek V4 Flash | 0 | 3 | 0 | 0 | 3 |
| Llama 4 Maverick | 1 | 2 | 1 | 1 | 5 |
| Qwen 3.7 Flash | 0 | 2 | 0 | 2 | 4 |
| Kimi K2 | 0 | 0 | 2 | 1 | 3 |
| GLM 4.7 FlashX | 0 | 0 | 2 | 1 | 3 |
| MiniMax M2.5 | 0 | 1 | 1 | 0 | 2 |
| GPT-6 Luna | 0 | 2 | 0 | 0 | 2 |
| Muse Glimmer 30B | 0 | 1 | 3 | 1 | 5 |
By framing
Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct17 labels4
Paraphrase5 labelsNone
Comparative41 labels3not counted in share
Budget-constrained18 labels4
Scale-constrained11 labels1
Negative35 labels3not counted in share
First choiceAlternativeMentionNegative127 labels in all, every segment counted; 9 of the 15 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.
What the models said for it
Verbatim evidence the judge attached to positive labels.
“Use Referral Factory or Friendbuy if you want a customer referral program that is relatively easy to launch and optimize.” Perplexity Sonar · Referrals · comparative prompt · first choice
“Friendbuy - Best for mid-market and enterprise eCommerce brands that want customization and testing.” Llama 4 Maverick · Referrals · direct prompt · first choice
“Influitive and Friendbuy are the most highly recommended” Mistral Small · Loyalty · direct prompt · first choice
“Popular picks like Friendbuy or Talkable excel for enterprises” Grok 4.20 · Referrals · scale prompt · first choice
And against it
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“High-Friction Enterprise Platforms with Opaque Pricing & Long Contracts (e.g., Friendbuy, SaaSquatch, Annex Cloud) ... generally ill-suited for growing businesses” Muse Glimmer 30B · Loyalty · negative prompt · hard negative
“Premium pricing without proportional value... Competitors offer similar core features for 60-90% less.” Kimi K2 · Loyalty · negative prompt · hard negative
“has opaque pricing and long contracts, making it ill-suited for growing businesses” Llama 4 Maverick · Loyalty · negative prompt · hard negative
“often good at referrals, but you should verify reporting, customization, and whether they cover loyalty/advocacy needs too” GPT-5.4 mini · Loyalty · negative prompt · soft negative
Named alongside
The products named in the same answers as Friendbuy, over the 127 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Friendbuy was named but was not.ShowHide
Named alongside
The products named in the same answers as Friendbuy, over the 127 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Friendbuy was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
A head-to-head page exists where both products are among a category's top eight. The other rows are the same fact without a page behind them, so they link to the product instead.
What carried it into the answer
The sites and pages cited by the answers that named Friendbuy. A fact about retrieval, not a lever on the model.
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 125 of the 127 answers that named Friendbuy and are not a share of its labels.
Domains cited
openloyalty.io75
moosend.com44
tremendous.com44
growsurf.com39
voucherify.io39
referralrock.com29
cello.so28
guideflow.com28
referral-factory.com27
extole.com26
379 of the 379 domain citations in answers naming Friendbuy came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
friendbuy.com is not in Google's top ten for any of the category's searches. In the answers, Friendbuy takes 4% of first choices and PartnerStack takes 22%.ShowHide
Search and answers
friendbuy.com is not in Google's top ten for any of the category's searches. In the answers, Friendbuy takes 4% of first choices and PartnerStack takes 22%.
ShowHideIn search
Google, US estimatesPosition for “referral program software”
–
not in the top ten
Position for “best referral program software”
–
not in the top ten
- Searches for its name, Google
- 480 a month (“friendbuy”)
- AI search demand for its name, est.
- 1 a month
- Organic visits to its site
- about 1,138 a month
- Searches its site ranks for
- 912 · 18 in the top three
- Sites linking to it
- 1,792
- Paid Google search
- No ads found in the estimate; that does not mean it runs none
In answers
This editionShare of first choices
4%
rank 7 of 112 in referrals
Segment leader
22%
PartnerStack
- First choices
- 9 across its categories
- Named in
- 127 answers
- Its own site cited
- in 125 of the answers that named it
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
What it publishes
ShowHide
What it publishes
ShowHideAddresses on friendbuy.com
471
subdomains included
Content
184
counted in the table below
Documentation
210
Product · Integration
5 · 4
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 154 | undated | Ecommerce marketing | ||
| Case study | 21 | undated | |||
| Comparison | 7 | undated | |||
| Webinar or virtual event | 1 | undated | |||
| Template or tool | 1 | undated |
How it is countedHide how it is counted
Every page friendbuy.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.
Names read as Friendbuy
What the judge wrote, as written, with how often. The vendor table decides that these count as Friendbuy; a claim can dispute any of them.
Friendbuy (by ReferralCandy) 1Friendbuy (formerly CXL) 1
Follow Friendbuy
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
The company
Friendbuy.ShowHide
The company
Friendbuy.
ShowHideOn record
Wikidata- Website
- friendbuy.com
- Headquarters
- Palos Verdes Estates, United States
- Founded
- 2010
Fetched September 14, 2026. These describe the company, not the product's standing, and a claimed page can dispute any of them. · Wikidata · LinkedIn
In its own words
Stated by the vendor, not checked- Positioning
- Referral, Loyalty & Influencer Marketing Platform
- For
- leading ecommerce and B2B brands
- Integrations claimed
- 7 friendbuy.com/features/cashback · 6 friendbuy.com/integrations pages disagree
- Certifications
- G2 Leader5-star rated onboarding
- Customers named
- Outdoor VoicesSPANXOLLYProsewoomOluKaiBathhousePedalheads
- Not stated on the pages read
- Price, starting price, free plan or trial, hosting
What Friendbuy's own pages state, read September 28, 2026: friendbuy.com, friendbuy.com/features/cashback, friendbuy.com/customers, friendbuy.com/integrations. A claimed page can correct any of them.
Is this your product?
Claim this page
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Friendbuy's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Friendbuy, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for Friendbuy by email, built from the raw record of the edition. It shows:
- where Friendbuy is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name Friendbuy, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.