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Session replay and heatmaps · November 2026 Edition

Dealfront vs Fullstory

Zero of fourteen models named Dealfront first on the direct prompt; three named Fullstory. Dealfront was named by ten of the fourteen models and Fullstory by fourteen and Dealfront carries 10 labels and Fullstory 52, so the shares are not directly comparable.

Dealfront

accepted challenger

Named in seven categories this edition.

Fullstory

criticized challenger

Named in six categories this edition.

First-choice share12%10%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%31%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#4A position in a field of 16; printed, not drawn.
Labels1052A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Dealfront reading right to left. Rank and label count are printed, not drawn.Microsoft Clarity was named alongside these two in eleven of the fourteen direct answers. Microsoft Clarity vs Dealfront · Microsoft Clarity vs Fullstory · Hotjar vs Dealfront

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 session replay and heatmaps page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
DealfrontFirst choices, of fourteen modelsFullstory
Direct032 against Fullstory
Paraphrase603 against Fullstory
Comparative00
Budget-constrained00
Scale-constrained021 against Fullstory
Negative0110 against Fullstory
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Dealfront and Fullstory stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Dealfront Fullstory first choice named as an alternative argued againstblank: not namedEach cell is one answer, Dealfront on the left and Fullstory on the right.

The direct prompt

The plain question, one answer per model, grouped by where Dealfront and Fullstory stood in it.

Fullstory first, Dealfront not the choice

3 of 14 modelsDealfront was named in the answer but not as the choice, or not at all.
GPT-5.4 miniFullstory alternatives: Contentsquare, Glassbox, Hotjar, LogRocket
GPT-6 LunaFullstory alternatives: Contentsquare, PostHog
Muse Glimmer 30BFullstory alternatives: Contentsquare, Hotjar, Microsoft Clarity

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Hotjar, Mouseflow alternatives: Fullstory, Microsoft Clarity
Gemini 3.5 FlashPostHog alternatives: Fullstory, Hotjar, LogRocket, Microsoft Clarity
Mistral SmallHotjar alternatives: Fullstory, LogRocket, Microsoft Clarity, PostHog
DeepSeek V4 FlashHotjar alternatives: Amplitude Session Replay, Fullstory, LogRocket, Microsoft Clarity, Mouseflow
Llama 4 MaverickMouseflow alternatives: Fullstory, Hotjar, Microsoft Clarity, UXCam
MiniMax M2.5Microsoft Clarity alternatives: Fullstory, Hotjar, LogRocket

Neither was named

5 of 14 modelsThe answer made no first choice from these two in this category.
Perplexity SonarHotjar alternatives: Amplitude Session Replay, Microsoft Clarity, Mouseflow
Grok 4.20Hotjar alternatives: Microsoft Clarity, Mouseflow
Qwen 3.7 FlashLogRocket alternatives: Hotjar, Microsoft Clarity, PostHog
Kimi K2PostHog alternatives: LogRocket, Mouseflow
GLM 4.7 FlashXMicrosoft Clarity alternatives: Contentsquare, Glassbox, LogRocket, UXCam

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Dealfront leads by eight points.
Dealfront8%#– of 11
Fullstory0%#11 of 11
The full small business standing →
Mid-marketThe figures above
Dealfront leads by two points.
Dealfront12%#3 of 16
Fullstory10%#4 of 16
The full mid-market standing →
Enterprise
The order flips: Fullstory leads at enterprise.
Fullstory36%#1 of 12
Dealfront0%#– of 12
The full enterprise standing →

What the models said about Dealfront

No label in this category carried a quote.

What the models said about Fullstory

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“Captures extensive session data (including potential PII). Noted in older FTC/exfiltration discussions; demands strict default masking and governance.” Grok 4.20 · negative prompt · hard negative
“Another high-risk tool due to its ability to capture keystrokes and sensitive form data... best avoided” Mistral Small · negative prompt · hard negative
“Named in active CIPA lawsuits; Princeton research found it capturing passwords, credit card numbers” Kimi K2 · negative prompt · hard negative
“FullStory is consistently positioned as the mid-market / enterprise pick when replay needs to connect to product analytics, developer context and data workflows.” Muse Glimmer 30B · direct prompt · first choice
“A comparatively stronger starting point—not a guarantee: Fullstory's *Private by Default* mode says text isn't sent unless explicitly allowlisted.” GPT-6 Luna · negative prompt · first choice
“FullStory | UX/Product analytics, zero-config, enterprise-grade masking, AI insights | Captures 100% sessions. Strong privacy controls.” DeepSeek V4 Flash · scale prompt · first choice
Also compared

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.