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

Buyapowa

26Judge labels
1First choices
3Negative labels
12 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
2% in Loyalty for enterprise buyers
Rank 37 of 107 in the mid-market standing
0 of 12 models made it the first choice on the direct prompt; 0% of its 4 labels there were negative.
By buyer segmentRead the same way at every buyer size.
Small businessnot named
0%
No model named it for this buyer.
Mid-market37 of 107
0%4 labels
under the label threshold
Enterprise22 of 75
0%11 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 Buyapowa 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 channel0%37 of 1070%4under 10 labels · led by PartnerStack at 19%
Loyalty, advocacy and referralsMarketing0%81 of 1240%1under 10 labels · led by Smile.io at 24%

Movement

This is the first edition on this tier, so no move can be computed for Buyapowa 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 Buyapowa 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 Sonar00000
Grok 4.1 Fast00000
Mistral Small00000
DeepSeek V4 Flash00101
Llama 4 Maverick00000
Qwen 3.7 Flash00202
Kimi K200000
GLM 4.7 FlashX00101
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
Direct1 labelNone
Paraphrase0 labelsNone
Comparative17 labelsNone
Budget-constrained1 label1
Scale-constrained0 labelsNone
Negative7 labelsNone
First choiceAlternativeMentionNegative26 labels in all, every segment counted; 1 of the 1 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.

No positive label carried a quote.

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 Buyapowa, over the 26 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Buyapowa was named but was not.
ProductSame answerTook the first choice insteadHead to head
Extole25 of 265Not in the top three
Ambassador20 of 262Not in the top three
Talkable18 of 262Not in the top three
Friendbuy18 of 260Not in the top three
ReferralCandy14 of 262Not in the top three
Mention Me14 of 260Not in the top three
Open Loyalty13 of 263Not in the top three
Yotpo12 of 261Not in the top three
Referral Rock12 of 260Not in the top three
LoyaltyLion9 of 260Not 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 Buyapowa. 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 4 of the 26 answers that named Buyapowa and are not a share of its labels.

Domains cited

openloyalty.io3
extole.com2
reverbico.com2
sourceforge.net2
aboutmartech.com1
affise.com1
blog.nextbee.com1
blog.usetada.com1
bubblehouse.com1
cello.so1

Fifteen of the fifteen domain citations in answers naming Buyapowa came from somebody else's page.

Pages cited

openloyalty.io/insider/best-referral-software3
sourceforge.net/software/referral/for-enterprise2
aboutmartech.com/blog/referral-program-software1
affise.com/blog/referral-software1
blog.nextbee.com/2026/03/02/best-referral-software-for-b2b-companies-a-strategic-growth-gu1
blog.usetada.com/en/best-loyalty-platforms-for-enterprise1
bubblehouse.com/blog/best-enterprise-loyalty-platform-for-retail-brands-2026-guide1
bubblehouse.com/blog/best-loyalty-referrals-platforms-in-2026-top-rewards-software-for-dtc1

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 Buyapowa'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 Buyapowa, 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 buyapowa.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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