GTM AI Index
Index Vendors › ReferralCandy · September 2026 Edition
4 categories · Ranked

ReferralCandy

158Judge labels
11First choices
50Negative labels
12 of 12Models named it
4Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.
Best standing
10% in Referrals for mid-market buyers
Rank 3 of 107 in the mid-market standingaccepted challenger
0 of 12 models made it the first choice on the direct prompt; 10% of its 31 labels there were negative.
By buyer segmentStrongest at mid-market.
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 ReferralCandy 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.
CategoryFunctionShareRankNegative rateLabelsQuadrant
Referral and partner programsPartner and channel10%3 of 10710%31accepted challenger
Affiliate and partner managementPartner and channel2%15 of 870%1under 10 labels · led by PartnerStack at 42%
Loyalty, advocacy and referralsMarketing0%27 of 12428%25criticized challenger
Ecommerce marketingMarketing0%99 of 1540%1under 10 labels · led by HubSpot Marketing Hub at 36%

Movement

This is the first edition on this tier, so no move can be computed for ReferralCandy yet. The next is due October 1, 2026. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated ReferralCandy across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500202
GPT-5.4 mini11204
Gemini 3.5 Flash03036
Perplexity Sonar10001
Grok 4.1 Fast12227
Mistral Small12104
DeepSeek V4 Flash11439
Llama 4 Maverick11204
Qwen 3.7 Flash31116
Kimi K214117
GLM 4.7 FlashX03104
MiniMax M2.511204

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
Direct11 labels1
Paraphrase2 labelsNone
Comparative43 labels15not counted in share
Budget-constrained49 labels9
Scale-constrained11 labels1
Negative42 labels5not counted in share
First choiceAlternativeMentionNegative158 labels in all, every segment counted; 11 of the 31 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.

“Most budget-constrained companies find ReferralCandy or ReferralHero provide the best balance of features versus cost” Qwen 3.7 Flash · Referrals · budget prompt · first choice
“If you can spend ~$40-50/month: ReferralCandy offers the best balance of features and ease-of-use for e-commerce” Kimi K2 · Referrals · budget prompt · first choice
“For most small-to-medium businesses, ReferralCandy or Viral Loops offer the best balance of features and ease of use” MiniMax M2.5 · Referrals · comparative prompt · first choice
“you may find better value in specialized, transparent tools like ReferralCandy or UpPromote” Qwen 3.7 Flash · Referrals · negative 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.

“What to avoid for mid-market B2B” DeepSeek V4 Flash · Referrals · direct prompt · hard negative
“it historically charges a 1.5% to 10.5% "success fee" on e-commerce sales generated through referrals... it becomes incredibly expensive as your brand grows.” Gemini 3.5 Flash · Referrals · negative prompt · soft negative
“Success fees (e.g., $39/mo + 10.5% on referred sales) scale poorly; fraud alerts vague; setup glitches, limited customization/reports.” Grok 4.1 Fast · Loyalty · negative prompt · soft negative
“*Cautious approach to pricing model* While generally well-reviewed (4.9/5 on Shopify), be aware of: Success fees” DeepSeek V4 Flash · Referrals · negative prompt · soft negative

Named alongside

The products named in the same answers as ReferralCandy, over the 158 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and ReferralCandy was named but was not.
ProductSame answerTook the first choice insteadHead to head
Friendbuy74 of 1581Not in the top three
Smile.io73 of 15828Not in the top three
Referral Factory59 of 1585Not in the top three
Extole56 of 1589Not in the top three
GrowSurf53 of 1581Not in the top three
Yotpo47 of 1581Not in the top three
Ambassador46 of 1582Not in the top three
Talkable46 of 1582Not in the top three
LoyaltyLion43 of 1581Not in the top three
A head-to-head page exists where both products are in a category's top three. 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 ReferralCandy. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 18 of the 158 answers that named ReferralCandy and are not a share of its labels.

Domains cited

referralcandy.comYour site9
openloyalty.io8
extole.com6
tremendous.com6
affise.com5
blossu.com4
capterra.com4
collegian.com4
customergauge.com4
referral-factory.com4

Forty-five of the fifty-four domain citations in answers naming ReferralCandy came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as ReferralCandy

What the judge wrote, as written, with how often. The vendor table decides that these count as ReferralCandy; a claim can dispute any of them.
ReferralCandy/Friendbuy 1
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 ReferralCandy'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 ReferralCandy, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at referralcandy.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.

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