GTM AI Index
Index Vendors › Open Loyalty · September 2026 Edition
2 categories · Ranked

Open Loyalty

69Judge labels
7First choices
4Negative labels
11 of 12Models named it
2Categories
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
13% in Loyalty for enterprise buyers
Rank 9 of 124 in the mid-market standingaccepted challenger
1 of 12 models made it the first choice on the direct prompt; 0% of its 14 labels there were negative.
By buyer segmentStrongest at enterprise.
In loyalty · 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 Open Loyalty 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
Loyalty, advocacy and referralsMarketing2%9 of 1240%14accepted challenger
Referral and partner programsPartner and channel0%38 of 1070%2under 10 labels · led by PartnerStack at 19%

Movement

This is the first edition on this tier, so no move can be computed for Open Loyalty 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 Open Loyalty across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash00000
Perplexity Sonar11103
Grok 4.1 Fast01001
Mistral Small00101
DeepSeek V4 Flash00202
Llama 4 Maverick00101
Qwen 3.7 Flash01102
Kimi K200202
GLM 4.7 FlashX02103
MiniMax M2.500101

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 labels5
Paraphrase1 labelNone
Comparative32 labels4not counted in share
Budget-constrained12 labels2
Scale-constrained6 labelsNone
Negative7 labels2not counted in share
First choiceAlternativeMentionNegative69 labels in all, every segment counted; 7 of the 13 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.

“Open Loyalty is the best-fit option among the results for mid-market and enterprise companies” Perplexity Sonar · Loyalty · direct prompt · first choice
“Building a custom app or needing full code control? Look at Open Loyalty.” Qwen 3.7 Flash · Referrals · comparative prompt · alternative
“Best for: Enterprises with strong development teams” GLM 4.7 FlashX · Referrals · comparative prompt · alternative
“API-first, composable toolkit for custom builds” Perplexity Sonar · Loyalty · comparative 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 Open Loyalty, over the 69 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Open Loyalty was named but was not.
ProductSame answerTook the first choice insteadHead to head
Extole42 of 6910Not in the top three
Ambassador33 of 692Not in the top three
ReferralCandy31 of 691Not in the top three
Friendbuy30 of 691Not in the top three
Talon.One29 of 694Not in the top three
Smile.io25 of 695Not in the top three
Annex Cloud24 of 692Not in the top three
Yotpo24 of 691Not in the top three
Voucherify23 of 692Not in the top three
LoyaltyLion23 of 691Not 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 Open Loyalty. 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 14 of the 69 answers that named Open Loyalty and are not a share of its labels.

Domains cited

openloyalty.ioYour site12
voucherify.io10
whitelabel-loyalty.com8
gartner.com6
neoday.com6
directiveconsulting.com5
netguru.com5
reverbico.com5
raftlabs.com4
smile.io4

Fifty-three of the sixty-five domain citations in answers naming Open Loyalty came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as Open Loyalty

What the judge wrote, as written, with how often. The vendor table decides that these count as Open Loyalty; a claim can dispute any of them.
Antavo/Open Loyalty 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 Open Loyalty'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 Open Loyalty, 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 openloyalty.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.

Subscribe to the pack