AI Indexes
GTM AI Index
Index › GTM data and infrastructure › Product analytics › PostHog vs Pendo
Product analytics · October 2026 Edition

PostHog vs Pendo

One of fourteen models named PostHog first on the direct prompt; two named Pendo. PostHog was named by thirteen of the fourteen models and Pendo by fourteen and PostHog carries 56 labels and Pendo 46, so the shares are not directly comparable.

PostHog

accepted challenger

Named in seven categories this edition.

Pendo

accepted challenger

Named in eleven categories this edition.

First-choice share22%10%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate5%13%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#4A position in a field of 7; printed, not drawn.
Labels5646A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, PostHog reading right to left. Rank and label count are printed, not drawn.Amplitude Analytics was named alongside these two in fourteen of the fourteen direct answers. Amplitude Analytics vs PostHog · Amplitude Analytics vs Pendo · Mixpanel vs PostHog

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 product analytics page.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
PostHogFirst choices, of fourteen modelsPendo
Direct121 against PostHog · 1 against Pendo
Paraphrase12
Comparative10
Budget-constrained110
Scale-constrained02
Negative302 against PostHog · 5 against Pendo
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.

Across every category in the October 2026 Edition, PostHog and Pendo were named in the same answer ninety-seven times, of the 386 answers naming PostHog and the 453 naming Pendo. In those answers Pendo took the first choice ten times and PostHog eighteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where PostHog and Pendo 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
PostHog Pendo first choice named as an alternative argued againstblank: not namedEach cell is one answer, PostHog on the left and Pendo on the right.

The direct prompt

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

PostHog first, Pendo not the choice

1 of 14 modelsPendo was named in the answer but not as the choice, or not at all.
Kimi K2Mixpanel, PostHog alternatives: Amplitude Analytics, Heap

Pendo first, PostHog an alternative

2 of 14 modelsPostHog was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5Pendo alternatives: Amplitude Analytics, Heap, Mixpanel
MiniMax M2.5Amplitude Analytics, Pendo alternatives: Heap, Mixpanel, PostHog

Neither was the first choice, one was named

10 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniAmplitude Analytics alternatives: Mixpanel, Pendo, PostHog
Gemini 3.5 FlashMixpanel alternatives: Amplitude Analytics, Pendo, PostHog
Perplexity SonarAmplitude Analytics alternatives: Gainsight PX, June, Mixpanel, Pendo
Grok 4.20Amplitude Analytics alternatives: Mixpanel, Pendo
Mistral SmallAmplitude Analytics alternatives: Heap, Pendo
DeepSeek V4 FlashAmplitude Analytics alternatives: Mixpanel, PostHog
Qwen 3.7 FlashAmplitude Analytics alternatives: Heap, Mixpanel, Pendo, PostHog
GLM 4.7 FlashXAmplitude Analytics alternatives: Heap, Mixpanel, PostHog
GPT-6 LunaMixpanel alternatives: Amplitude Analytics, PostHog
Muse Glimmer 30BAmplitude Analytics alternatives: Heap, June, Mixpanel, Pendo, PostHog

Neither was named

1 of 14 modelsThe answer made no first choice from these two in this category.
Llama 4 MaverickAmplitude Analytics, Heap

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
PostHog leads by forty-eight points.
PostHog50%#1 of 8
Pendo2%#5 of 8
The full small business standing →
Mid-marketThe figures above
PostHog leads by twelve points.
PostHog22%#3 of 7
Pendo10%#4 of 7
The full mid-market standing →
Enterprise
The order flips: Pendo leads at enterprise.
Pendo18%#2 of 11
PostHog2%#5 of 11
The full enterprise standing →

What the models said about PostHog

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

“Usage- or event-metered tools—such as Mixpanel, Amplitude, and PostHog—when your event volume is hard to predict.” GPT-6 Luna · negative prompt · soft negative
“Choose PostHog if you are a startup/engineering team wanting analytics, replays, A/B tests, and feature flags in one place” Qwen 3.7 Flash · comparative prompt · first choice

What the models said about Pendo

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

“I'd recommend Amplitude for pure analytics power, or Pendo if you want to combine insights with in-product engagement” MiniMax M2.5 · direct prompt · first choice
“I'd suggest starting with Amplitude or Pendo as they balance powerful features with reasonable pricing” MiniMax M2.5 · paraphrase 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.