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Index › Products › LeveragePoint · October 2026 Edition
1 category · Ranked

LeveragePoint

31Judge labels
5First choices
4Negative labels
13 / 14Models named it
1Category
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
4% in Value selling for mid-market buyers
Rank 8 of 116 in the mid-market standingaccepted challenger
2 of 14 models made it the first choice on the direct prompt; 8% of its 12 labels there were negative.
What the models named instead of LeveragePoint →
By buyer segmentRead the same way at every buyer size.
In value selling · 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 LeveragePoint 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 rateLabelsQuadrantSince September 2026
Value selling toolsSales4%8 of 1168%12accepted challenger

Movement

This is the first edition on this tier, so no move can be computed for LeveragePoint yet. From the next edition this section shows, per buyer segment and per category, whether its share moved by more than the measured noise floor.

By model

How each model treated LeveragePoint across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
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ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash01001
Perplexity Sonar00000
Grok 4.1 Fast01001
Mistral Small01001
DeepSeek V4 Flash00213
Llama 4 Maverick00000
Qwen 3.7 Flash00000
Kimi K202002
GLM 4.7 FlashX00000
MiniMax M2.500101
GPT-6 Luna11002
Muse Glimmer 30B10001

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
Direct13 labels5
Paraphrase3 labelsNone
Comparative8 labelsNone
Budget-constrained4 labelsNone
Scale-constrained1 labelNone
Negative2 labelsNone
First choiceAlternativeMentionNegative31 labels in all, every segment counted; 5 of the 5 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.

“mid-market teams that want a purpose-built quantification engine with collaborative Value Models often start with LeveragePoint” Muse Glimmer 30B · Value selling · direct prompt · first choice
“my mid-market pick is LeveragePoint for a team building a repeatable value-selling process” GPT-6 Luna · Value selling · direct prompt · first choice
“Choose LeveragePoint if you want to align product, pricing, and sales teams around a unified value narrative.” Kimi K2 · Value selling · comparative prompt · alternative
“Renowned for building incredibly solid, transparent value-based pricing and ROI models.” Gemini 3.5 Flash · Value selling · scale 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.

“enterprise-focused pricing and complexity” DeepSeek V4 Flash · Value selling · direct prompt · soft negative

Named alongside

The products named in the same answers as LeveragePoint, over the 31 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and LeveragePoint was named but was not.
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ProductSame answerTook the first choice insteadHead to head
Mediafly18 of 312Not among the top eight
Cuvama10 of 310Not among the top eight
Ecosystems7 of 311Not among the top eight
Mediafly Value5 of 311Not among the top eight
Seismic5 of 310Not among the top eight
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 LeveragePoint. 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 31 of the 31 answers that named LeveragePoint and are not a share of its labels.

Domains cited

guideflow.com29
g2.com24
sourceforge.net23
minoa.io18
us.fitgap.com17
gartner.com14
slashdot.org10
prospeo.io9
valuenova.ai8
valuevisualizer.com7

159 of the 159 domain citations in answers naming LeveragePoint came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Search and answers

leveragepoint.com ranks 3 on Google for the category's searches. In the answers, LeveragePoint takes 4% of first choices and Minoa takes 21%.
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In search

Google, US estimates
Position for “value selling tool”
3
Position for “best value selling tool”
–
not in the top ten
Searches for its name, Google
590 a month (“leveragepoint”)
AI search demand for its name, est.
0 a month
Organic visits to its site
about 1,277 a month
Searches its site ranks for
305 · 14 in the top three
Sites linking to it
632
Paid Google search
No ads found in the estimate; that does not mean it runs none
Ads on Google
None found in Google's ad transparency records for the US

In answers

This edition
Share of first choices
4%
rank 8 of 116 in value selling
Segment leader
21%
Minoa
First choices
5 across its categories
Named in
31 answers
Its own site cited
in 31 of the answers that named it

Search figures are US estimates from DataForSEO, read October 5, 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

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Addresses on leveragepoint.com
788
subdomains included
Content
741
counted in the table below
Documentation
1
Product · Integration
0 · 0
KindPagesLast 90 days2025-11 to 2026-10LatestCategories named
Blog58662026-09-15ABM, Pricing optimization
Webinar or virtual event9702025-05-19
Case study1702024-06-24
Conference or event16undated
Comparison10undated
Glossary or explainer7undated
Template or tool402019-04-17
Report or ebook3undated
News or press1undated
How it is countedHide how it is counted

Every page leveragepoint.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 October 5, 2026.

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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.

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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 LeveragePoint'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 LeveragePoint, 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 LeveragePoint by email, built from the raw record of the edition. It shows:

  • where LeveragePoint 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 LeveragePoint, 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.
The subscriber app

A verification link goes to your work email; an address at leveragepoint.com is approved on the spot, any other is reviewed by hand. Your email is never published. Claiming gives no say over labels, shares, verdicts or which quotes appear.