Every category where a model named Voucherify 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
Loyalty, advocacy and referrals	Marketing	0%	35 of 124	0%	4	under 10 labels · led by Smile.io at 24%
Referral and partner programs	Partner and channel	0%	47 of 107	0%	2	under 10 labels · led by PartnerStack at 19%

Movement

This is the first edition on this tier, so no move can be computed for Voucherify 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 Voucherify across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Mention	Labels
Claude Haiku 4.5	0	0	0
GPT-5.4 mini	0	0	0
Gemini 3.5 Flash	2	0	2
Perplexity Sonar	0	0	0
Grok 4.1 Fast	0	0	0
Mistral Small	0	1	1
DeepSeek V4 Flash	1	0	1
Llama 4 Maverick	0	1	1
Qwen 3.7 Flash	0	0	0
Kimi K2	0	1	1
GLM 4.7 FlashX	0	0	0
MiniMax M2.5	0	0	0

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

Direct3 labelsNone

Paraphrase0 labelsNone

Comparative14 labelsNone

Budget-constrained5 labels3

Scale-constrained4 labelsNone

Negative4 labels1not counted in share

First choiceAlternativeMentionNegative30 labels in all, every segment counted; 3 of the 4 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.

“A developer-friendly, API-first platform for coupons, referrals, and loyalty programs. Highly flexible and cost-effective for mid-market tech companies.” Gemini 3.5 Flash · Loyalty · scale prompt · alternative

“Look for software with automated fraud-blocking features (like ReferralHero or Voucherify).” Gemini 3.5 Flash · Referrals · negative prompt · alternative

“Voucherify \u2014 Strong anti-fraud features and flexible pricing.” DeepSeek V4 Flash · Loyalty · negative prompt · alternative

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.

No model argued against it.

Named alongside

The products named in the same answers as Voucherify, over the 30 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Voucherify was named but was not.

ProductSame answerTook the first choice insteadHead to head

Open Loyalty23 of 304Not in the top three

Talon.One19 of 305Not in the top three

Extole18 of 308Not in the top three

Ambassador12 of 302Not in the top three

Friendbuy12 of 300Not in the top three

Annex Cloud11 of 302Not in the top three

Referral Rock11 of 300Not in the top three

Antavo10 of 301Not in the top three

Smile.io10 of 301Not in the top three

LoyaltyLion10 of 300Not 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 Voucherify. 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 5 of the 30 answers that named Voucherify and are not a share of its labels.

Domains cited

openloyalty.io5

voucherify.ioYour site4

gartner.com3

neoday.com3

whitelabel-loyalty.com3

devglan.com2

directiveconsulting.com2

firstpromoter.com2

gitnux.org2

guideflow.com2

Twenty-four of the twenty-eight domain citations in answers naming Voucherify came from somebody else's page.

Pages cited

gartner.com/reviews/market/loyalty-program-vendors3

neoday.com/blog/best-customer-loyalty-platforms-20263

openloyalty.io/insider/best-loyalty-software-comparison-guide3

devglan.com/guest-post/15-best-enterprise-loyalty-software-in-20262

directiveconsulting.com/blog/blog-b2b-loyalty-program-software2

firstpromoter.com/blog/best-referral-marketing-software2

mention-me.com/blog/best-referral-marketing-software2

mokahr.io/myblog/25f09219-c679-4bd1-a8ee-dcd9131d5e212

Pages are listed as the models cited 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 Voucherify'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 Voucherify, 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 voucherify.io 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.