Highspot vs Dock
Six of fourteen models named Highspot first on the direct prompt; one named Dock. Highspot was named by fourteen of the fourteen models and Dock by ten and Highspot carries 64 labels and Dock 19, so the shares are not directly comparable.
Seattle, United States, founded 2012. Named in seven categories this edition.
San Francisco, United States, founded 2021. Named in eight categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the sales enablement and content page.
By framing
HighspotFirst choices, of fourteen modelsDock
Across every category in the November 2026 Edition, Highspot and Dock were named in the same answer 105 times, of the 430 answers naming Highspot and the 281 naming Dock. In those answers Dock took the first choice sixteen times and Highspot eleven.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | |||||
| GPT-5.4 mini | | | | | ||
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | | | | |
| Grok 4.20 | | | | | | |
| Mistral Small | | | | |||
| DeepSeek V4 Flash | | | | | | |
| Llama 4 Maverick | | |||||
| Qwen 3.7 Flash | | | | | | |
| Kimi K2 | | | | | ||
| GLM 4.7 FlashX | | | | | | |
| MiniMax M2.5 | | | | | ||
| GPT-6 Luna | | |||||
| Muse Glimmer 30B | | | | | |
Highspot Dock first choice named as an alternative argued againstblank: not namedEach cell is one answer, Highspot on the left and Dock on the right.The direct prompt
Highspot first, Dock an alternative
6 of 14 modelsDock was named in the answer but not as the choice, or not at all.Dock first, Highspot not the choice
1 of 14 modelsHighspot was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
4 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
3 of 14 modelsThe answer made no first choice from these two in this category.Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
Highspot20%#2 of 14Dock2%#8 of 14Highspot29%#2 of 10Dock0%#– of 10What the models said about Highspot
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of six in this category shown.
“Highspot/Seismic (Merged Feb 2026) ⚠️ Structural Concerns ... "glorified Dropbox" ... integration risks and potential sunsetting of features” Kimi K2 · negative prompt · hard negative
“What I'd Avoid for Mid-Market - Seismic and Highspot: ... often overkill for mid-sized companies” Kimi K2 · paraphrase prompt · hard negative
“Platforms with Consistent Negative Reviews ... Highspot - Steep learning curve and confusing interface” GLM 4.7 FlashX · negative prompt · hard negative
“Highspot (now part of Seismic following their 2026 merger) is widely regarded as the top sales enablement platform for mid-market B2B companies.” Grok 4.20 · direct prompt · first choice
“Highspot: Excels in guided selling and content personalization... Often praised for ease of use in mid-market to enterprise.” Grok 4.20 · comparative prompt · first choice
“Known for having one of the most intuitive user interfaces and search engines (often described as "Google for sales content").” Gemini 3.5 Flash · comparative prompt · first choice
What the models said about Dock
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“Best for mid-market B2B teams that want to enable buyers and sellers with deal rooms, onboarding portals, CMS, and LMS in one platform” Claude Haiku 4.5 · direct prompt · first choice
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.