Databox vs Amplitude
Two of fourteen models named Databox first on the direct prompt; one named Amplitude. Databox was named by twelve of the fourteen models and Amplitude by thirteen and Databox carries 28 labels and Amplitude 27, so the shares are not directly comparable.
Named in two categories this edition.
Named in one category 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 saas metrics and analytics page.
By framing
DataboxFirst choices, of fourteen modelsAmplitude
Across every category in the October 2026 Edition, Databox and Amplitude were named in the same answer thirty-eight times, of the 99 answers naming Databox and the 81 naming Amplitude. In those answers Amplitude took the first choice four times and Databox two.
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 4.1 Fast | | | | | ||
| 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 | |
Databox Amplitude first choice named as an alternative argued againstblank: not namedEach cell is one answer, Databox on the left and Amplitude on the right.The direct prompt
Databox first, Amplitude an alternative
2 of 14 modelsAmplitude was named in the answer but not as the choice, or not at all.Amplitude first, Databox an alternative
1 of 14 modelsDatabox was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
7 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
4 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
Databox0%#10 of 11Amplitude0%#8 of 11What the models said about Databox
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“the best all-round dashboard is Databox combined with a subscription-revenue backend like ChartMogul” GLM 4.7 FlashX · direct prompt · first choice
“the best SaaS metrics dashboard is likely Databox's free plan or Google Looker Studio” Grok 4.1 Fast · budget prompt · first choice
“ChartMogul and Databox are the top recommendations” Mistral Small · direct prompt · first choice
What the models said about Amplitude
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Amplitude is terrible at calculating Net Revenue Retention (NRR), churn reasons, LTV:CAC ratios, or forecasting cash flow accurately” Llama 4 Maverick · negative prompt · hard negative
“it's not recommended for CFO-level financial reporting or accurate calculation of key SaaS metrics” Mistral Small · negative prompt · hard negative
“Avoid using these as your primary SaaS revenue metrics tool.” DeepSeek V4 Flash · negative prompt · hard negative
“Amplitude is best for mid-market to enterprise SaaS with dedicated data teams... very strong for B2B SaaS companies, and its cohort analysis is the best.” Claude Haiku 4.5 · direct prompt · first choice
“If you want to know what users do in the app: start with Amplitude or Mixpanel.” GPT-5.4 mini · comparative prompt · first choice
“Need deep product behavior insights with AI? → Amplitude” Kimi K2 · comparative 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.