{ "evaluation_id": "EVAL-20260402-193307", "question_id": "ANALYSIS-013", "question_text": "A mobile app shows: DAU 100K (up 50%), WAU 200K (up 20%), MAU 500K (up 10%), D1 retention 40%, D7 retention 15%, D30 retention 5%, Session length 8min (down 20%), Sessions/day 2.1 (up 30%). The PM says 'we're growing fast.' (1) What story does this data actually tell? (2) What's concerning about the DAU/MAU ratio? (3) Why might session length decrease as sessions increase? (4) What one metric would you focus on and why?", "category": "analysis", "timestamp": "2026-04-02T19:33:07.184Z", "display_date": "Apr 02, 2026", "winner": { "name": "Claude Sonnet 4.6", "provider": "openrouter", "score": 9.43 }, "avg_score": 8.906, "matrix_size": 90, "models_used": [ { "id": "gemini_31_pro", "name": "Gemini 3.1 Pro", "provider": "openrouter" }, { "id": "claude_opus_46", "name": "Claude Opus 4.6", "provider": "openrouter" }, { "id": "gpt_5_4", "name": "GPT-5.4", "provider": "openrouter" }, { "id": "deepseek_v4", "name": "DeepSeek V4", "provider": "openrouter" }, { "id": "mimo_v2_flash", "name": "MiMo-V2-Flash", "provider": "Xiaomi" }, { "id": "claude_sonnet_46", "name": "Claude Sonnet 4.6", "provider": "openrouter" }, { "id": "grok_420", "name": "Grok 4.20", "provider": "openrouter" }, { "id": "gpt_oss_120b", "name": "GPT-OSS-120B", "provider": "OpenAI" }, { "id": "gemini_3_flash", "name": "Gemini 3 Flash Preview", "provider": "Google" }, { "id": "minimax_m25", "name": "MiniMax M2.5", "provider": "openrouter" } ], "rankings": { "claude_sonnet_46": { "display_name": "Claude Sonnet 4.6", "provider": "openrouter", "average_score": 9.43, "score_count": 9, "min_score": 8.85, "max_score": 10, "rank": 1 }, "claude_opus_46": { "display_name": "Claude Opus 4.6", "provider": "openrouter", "average_score": 9.18, "score_count": 9, "min_score": 8.2, "max_score": 10, "rank": 2 }, "grok_420": { "display_name": "Grok 4.20", "provider": "openrouter", "average_score": 9.13, "score_count": 9, "min_score": 8.65, "max_score": 9.8, "rank": 3 }, "gpt_5_4": { "display_name": "GPT-5.4", "provider": "openrouter", "average_score": 9.07, "score_count": 9, "min_score": 8.45, "max_score": 9.8, "rank": 4 }, "gpt_oss_120b": { "display_name": "GPT-OSS-120B", "provider": "OpenAI", "average_score": 9.04, "score_count": 9, "min_score": 7.95, "max_score": 10, "rank": 5 }, "minimax_m25": { "display_name": "MiniMax M2.5", "provider": "openrouter", "average_score": 8.99, "score_count": 9, "min_score": 8.45, "max_score": 9.8, "rank": 6 }, "gemini_3_flash": { "display_name": "Gemini 3 Flash Preview", "provider": "Google", "average_score": 8.93, "score_count": 9, "min_score": 8.25, "max_score": 9.8, "rank": 7 }, "deepseek_v4": { "display_name": "DeepSeek V4", "provider": "openrouter", "average_score": 8.87, "score_count": 9, "min_score": 8, "max_score": 9.8, "rank": 8 }, "mimo_v2_flash": { "display_name": "MiMo-V2-Flash", "provider": "Xiaomi", "average_score": 8.7, "score_count": 9, "min_score": 6.25, "max_score": 9.8, "rank": 9 }, "gemini_31_pro": { "display_name": "Gemini 3.1 Pro", "provider": "openrouter", "average_score": 7.72, "score_count": 9, "min_score": 6.3, "max_score": 8.85, "rank": 10 } }, "judgments": [ { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 6.65, "brief_justification": "Accurate analysis and clear presentation, but missing answer to the final question and cuts off mid‑explanation, reducing completeness and practical usefulness." }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 8.8, "brief_justification": "The response provides highly accurate, insightful, and actionable analysis, answering all four questions thoroughly. However, the text cuts off abruptly at the very end, slightly impacting completeness." }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 9.8, "brief_justification": "Excellent analysis that accurately interprets the metrics, identifies the leaky bucket problem, provides nuanced reasons for session changes, and correctly prioritizes D30 retention. Calculating total daily time spent would have added slight additional depth." }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 9.8, "brief_justification": "The response accurately interprets the metrics, correctly calculates the DAU/MAU ratio, provides insightful reasons for the session behavior, and offers a highly actionable recommendation." }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 6.25, "brief_justification": "" }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 10, "brief_justification": "Exceptional response with accurate math, deep product insights, clear formatting, and highly actionable recommendations." }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9.6, "brief_justification": "" }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 8.5, "brief_justification": "" }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 9.8, "brief_justification": "The response accurately interprets the metrics, identifies the leaky bucket problem, provides insightful explanations for user behavior shifts, and offers a highly actionable recommendation." }, { "judge_key": "gemini_31_pro", "judge_name": "Gemini 3.1 Pro", "respondent_key": "minimax_m25", "respondent_name": "MiniMax M2.5", "weighted_score": 8.75, "brief_justification": "" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 7.45, "brief_justification": "The response is well-structured, insightful, and clearly written. The 'leaky bucket' framing is accurate and the DAU/MAU analysis is strong. However, the response is incomplete - it cuts off mid-sentence in section 3 and never addresses section 4 (the most important metric to focus on), which significantly hurts completeness and usefulness. The retention analysis is solid but could note that 40% D1 retention isn't actually 'abysmal' - it's decent for many app categories. The DAU/MAU threshold of" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 9.2, "brief_justification": "Excellent analysis that correctly identifies the core tension between acquisition growth and retention weakness. The DAU/MAU interpretation is accurate and well-contextualized. The session length analysis covers multiple plausible explanations with appropriate nuance. The choice of D30 retention as the focal metric is well-justified with clear reasoning about durability of growth. The follow-up questions at the end add practical value. Minor gap: could have mentioned cohort analysis more explici" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8, "brief_justification": "The response is well-structured, accurate, and covers all four questions clearly. The DAU/MAU analysis is correct at 20%, though the interpretation could be sharper—the key concern is the divergence between DAU growth (50%) and MAU growth (10%), which suggests growth is heavily acquisition-driven and the ratio may be temporarily inflated by new users who won't stick. The session length analysis is solid with multiple plausible explanations. The D7 retention focus is a defensible choice with good" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 9.2, "brief_justification": "Excellent analysis across all four questions. The response correctly identifies the core narrative of shallow, acquisition-driven growth with poor retention. The DAU/MAU calculation is correct at 20%, and the insight about the growth paradox (the ratio being inflated by acquisition spikes rather than genuine stickiness) is particularly astute. The session length analysis covers multiple plausible explanations well. The choice of D7 retention as the focus metric is well-justified with clear reaso" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 9.75, "brief_justification": "Exceptional response that goes far beyond surface-level analysis. The data interpretation is accurate and insightful — correctly identifying the leaky bucket dynamic, the DAU/MAU stickiness concern, and the acquisition-masking-retention narrative. The session length analysis is particularly strong, offering multiple hypotheses with diagnostic approaches. The choice of cohort-segmented D30 retention as the focus metric is well-justified with concrete scenarios and actionable next steps. The forma" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9.2, "brief_justification": "Excellent, well-structured analysis that correctly identifies the leaky bucket problem, explains the DAU/MAU ratio concerns with appropriate nuance about how new user influx artificially props it up, provides multiple plausible explanations for the session length paradox, and makes a well-reasoned case for D7 retention as the focal metric. The summary recommendation to the PM is practical and actionable. Minor quibble: the response could have noted that 20% DAU/MAU is actually at the low end of " }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9.4, "brief_justification": "Exceptionally thorough and well-structured response. The analysis correctly identifies the core tension between acquisition growth and retention weakness. The DAU/MAU analysis is accurate, though the claim that the ratio is 'falling' is slightly misleading—DAU growing faster than MAU actually means the ratio is currently rising, but the low absolute level and poor retention suggest it will eventually decline. The session length analysis covers multiple plausible explanations including the often-" }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 9.2, "brief_justification": "Excellent analysis that correctly identifies the 'leaky bucket' pattern, accurately computes the DAU/MAU ratio at 20%, provides nuanced explanations for the session length decrease, and makes a well-reasoned argument for focusing on D7 retention. The response is exceptionally well-structured with clear headers and bullet points. Minor quibble: some might argue D30 retention or a cohort-based metric would be even more strategic than D7, but the D7 choice is well-defended. The depth of insight on " }, { "judge_key": "claude_opus_46", "judge_name": "Claude Opus 4.6", "respondent_key": "minimax_m25", "respondent_name": "MiniMax M2.5", "weighted_score": 9.2, "brief_justification": "Exceptionally well-structured and analytically rigorous response. Each section is addressed with accurate interpretation of the metrics, appropriate benchmarks (DAU/MAU ratios for different app categories), and insightful reasoning (leaky bucket metaphor, notification-driven usage hypothesis). The D30 retention focus is well-justified with the compounding argument. Minor nitpick: the 20% DAU/MAU benchmark comparison could be slightly more nuanced (20% isn't necessarily low for all app categories" }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 6.3, "brief_justification": "Clear and mostly reasonable interpretation, especially on retention and DAU/MAU, but it overstates some conclusions from aggregate growth rates, relies on debatable benchmarks, and the answer is incomplete/truncated without finishing part 3 or addressing part 4." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 8.2, "brief_justification": "Strong diagnosis of acquisition-led growth with weak retention, correctly computes DAU/MAU at 20%, and gives a sensible focus metric (D7 cohort retention). Minor issues: some claims are speculative (acquisition spend, ratio declining) and one retention explanation overstates what can be inferred from cross-sectional growth rates." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.8, "brief_justification": "Accurately identifies acquisition-led growth with weak retention, correctly flags DAU/MAU at 20% as concerning, gives plausible reasons for shorter sessions with more frequency, and chooses a sensible focus metric. Clear and practical, though it could more explicitly note that rising DAU faster than MAU may reflect recent acquisition spikes rather than durable engagement." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 9, "brief_justification": "Accurate and well-structured analysis. Correctly identifies acquisition-led growth with weak retention, computes DAU/MAU at 20%, explains plausible reasons for shorter sessions with higher frequency, and selects a sensible focus metric. Minor caveat: the claim that an acquisition spike would drive DAU/MAU up despite low retention is somewhat speculative from the given snapshot." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 9.2, "brief_justification": "Accurate and insightful read: strong acquisition but weak retention/stickiness, correctly computes DAU/MAU at 20%, gives plausible reasons for shorter sessions with more frequency, and sensibly prioritizes cohort-based D30 retention. Minor caveat: benchmark ranges and some causal claims are somewhat generalized/speculative." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 8.8, "brief_justification": "Accurately identifies acquisition-led growth masking weak retention, correctly computes DAU/MAU at 20%, gives plausible reasons for shorter sessions with higher frequency, and recommends D7 retention with solid rationale. Minor caveat: some benchmark language and the claim that DAU/MAU is being 'artificially propped up' are somewhat interpretive rather than directly provable from the snapshot." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 7.95, "brief_justification": "Well-structured and insightful, with strong retention-focused analysis. Main issue is a notable logic error around DAU/MAU trend interpretation: given DAU growth exceeds MAU growth, the ratio would rise this period, not imply denominator expanding faster or stickiness falling from the provided data alone." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 8.55, "brief_justification": "Accurately identifies likely acquisition-led growth with weak retention and explains the session tradeoff well. Strong structure and practical focus on retention, though it overstates some conclusions from aggregate growth rates and treats a 20% DAU/MAU ratio somewhat simplistically without noting cohort/mix caveats." }, { "judge_key": "gpt_5_4", "judge_name": "GPT-5.4", "respondent_key": "minimax_m25", "respondent_name": "MiniMax M2.5", "weighted_score": 8.8, "brief_justification": "Accurately identifies acquisition-led growth with weak retention, correctly computes DAU/MAU at 20%, gives plausible explanations for shorter sessions, and sensibly prioritizes D30 retention. Minor caveat: benchmark claims are somewhat generalized and it could have noted DAU growth outpacing MAU as a slight positive nuance." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 8.6, "brief_justification": "Accurate, detailed analysis with clear insights and actionable focus." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 10, "brief_justification": "Comprehensive, accurate, and insightful analysis with clear actionable recommendations." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 9, "brief_justification": "Comprehensive and insightful analysis with clear actionable insights." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 9, "brief_justification": "Comprehensive, insightful, and actionable analysis with clear reasoning." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 9.55, "brief_justification": "Comprehensive, insightful, and actionable analysis with clear structure." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9, "brief_justification": "Highly accurate, thorough, clear, insightful, and actionable response." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9, "brief_justification": "Comprehensive, insightful, and actionable analysis with clear structure." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 9, "brief_justification": "Comprehensive, insightful, and actionable analysis with clear explanations." }, { "judge_key": "deepseek_v4", "judge_name": "DeepSeek V4", "respondent_key": "minimax_m25", "respondent_name": "MiniMax M2.5", "weighted_score": 8.8, "brief_justification": "Detailed, insightful analysis with actionable focus." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 8.6, "brief_justification": "Accurate analysis of leaky bucket, DAU/MAU ratio, and session dynamics; clear structure and actionable insights." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 9.55, "brief_justification": "Comprehensive, accurate analysis with strong insights and actionable recommendations." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 8.8, "brief_justification": "Accurate analysis of all metrics, strong insights on retention vs acquisition, and actionable recommendation." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 9.2, "brief_justification": "Accurate analysis, thorough coverage, clear structure, insightful explanations, and actionable recommendations." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 9.55, "brief_justification": "Comprehensive, accurate, and actionable analysis with exceptional depth and structure." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9.35, "brief_justification": "Accurate analysis of all data points, thorough coverage, clear structure, insightful explanations, and highly actionable recommendations." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9.2, "brief_justification": "The response is highly accurate, comprehensive, and well-structured. It correctly interprets the data, identifies the critical DAU/MAU trend, explains the session behavior paradox, and provides a strong, actionable recommendation focused on D7 retention." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 9.35, "brief_justification": "Excellent analysis. Correctly identifies the 'leaky bucket' nature of the growth, accurately calculates the stickiness ratio, and provides a nuanced explanation for the session length vs frequency trade-off. The recommendation to focus on D7 retention is highly actionable and well-justified." }, { "judge_key": "mimo_v2_flash", "judge_name": "MiMo-V2-Flash", "respondent_key": "minimax_m25", "respondent_name": "MiniMax M2.5", "weighted_score": 9.35, "brief_justification": "Excellent analysis. Correctly identifies the 'leaky bucket' issue, accurately calculates the DAU/MAU ratio, provides nuanced reasons for the session length vs frequency paradox, and recommends a high-impact retention metric with clear justification." }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 8.05, "brief_justification": "The response is analytically strong and well-structured, correctly identifying the leaky bucket pattern, accurately calculating the DAU/MAU ratio, and providing insightful explanations for the session length/frequency tradeoff. However, the response appears to be cut off mid-sentence in section 3, and section 4 (the one metric to focus on) is entirely missing. This significantly impacts completeness. The analysis provided is high quality with good depth and practical framing." }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 9.55, "brief_justification": "Exceptional analysis that goes well beyond surface-level interpretation. The response correctly identifies the leaky bucket pattern, accurately calculates DAU/MAU ratio and benchmarks it appropriately, provides nuanced explanations for session length changes with cohort segmentation advice, and makes a well-reasoned case for D7 cohort retention as the key metric. The structured format, concrete calculations, and strategic framing make this highly actionable. Minor deduction on correctness only b" }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 8.8, "brief_justification": "Excellent analysis that correctly identifies the acquisition vs retention tension, accurately calculates and interprets the DAU/MAU ratio at 20%, provides multiple plausible explanations for the session length paradox, and makes a well-reasoned case for D30 retention as the key metric. The response is well-structured, actionable, and goes beyond surface-level observations with nuanced interpretations. Minor gap: could have quantified the retention funnel drop more explicitly (40%→15%→5% represen" }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.6, "brief_justification": "Strong analysis with accurate DAU/MAU calculation and interpretation. Correctly identifies the retention funnel collapse and provides actionable insights. The D7 retention focus is well-justified. Could have noted that DAU growth outpacing MAU growth suggests new user surge rather than retained user engagement, and could have explored the stickiness ratio more deeply. Session length analysis covers key hypotheses. Overall very practical and well-structured." }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 8.8, "brief_justification": "Excellent analysis that correctly identifies the growth paradox, accurately calculates the DAU/MAU ratio and its implications, provides multiple plausible explanations for the session length/frequency inverse relationship, and gives a well-reasoned metric prioritization with actionable rationale. The secondary priority note adds practical value. Minor gap: doesn't explicitly note that DAU/MAU ratio improved from ~13% to 20% given the differential growth rates, which would strengthen the paradox " }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 8.8, "brief_justification": "Excellent analysis covering all four questions with accurate calculations (DAU/MAU = 20%), strong narrative framing, and actionable recommendations. The leaky bucket metaphor and 'growth masking retention' insight show genuine depth. Minor gap: could have quantified the retention math more explicitly (e.g., of 500K MAU, only 5% return monthly = 25K loyal users) to strengthen the argument. The session length analysis covers multiple plausible hypotheses well. The final recommendation is direct an" }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9.55, "brief_justification": "Exceptionally thorough and well-structured response. Correctly identifies the acquisition vs. retention disconnect, accurately calculates DAU/MAU at 20%, provides multiple plausible explanations for the session length paradox, and makes a compelling, actionable case for D7 retention as the key metric. The table format enhances clarity, benchmarks are appropriate, and the analysis goes well beyond surface-level observations. Minor note: the DAU/MAU trend analysis slightly misreads the direction (" }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 8.8, "brief_justification": "Excellent analysis that correctly identifies the leaky bucket growth pattern, accurately calculates the DAU/MAU ratio at 20%, and provides nuanced explanations for each question. The response correctly flags the divergence between DAU and MAU growth rates as the key concern. The session length explanation covers both benign and concerning interpretations well. The choice of D7 retention as the focus metric is well-justified with business reasoning. Minor gap: could have noted that DAU/MAU ratio " }, { "judge_key": "claude_sonnet_46", "judge_name": "Claude Sonnet 4.6", "respondent_key": "minimax_m25", "respondent_name": "MiniMax M2.5", "weighted_score": 9, "brief_justification": "Excellent analytical response that correctly identifies the acquisition-driven growth masking retention problems. The DAU/MAU analysis is accurate with good benchmarks. The session length explanation covers multiple plausible causes. The D30 retention recommendation is well-justified with clear reasoning about the leaky bucket problem and compounding effects. Minor gap: could have noted that DAU/MAU ratio is actually trending worse (DAU up 50% vs MAU up 10% means ratio was previously ~13%, so it" }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 8.05, "brief_justification": "The response is factually accurate and logically sound on metrics interpretation. It is clear and well-structured but incomplete as it cuts off mid-sentence in section 3 and omits section 4 entirely. Provides insightful analysis with good practical value for product management." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 8.85, "brief_justification": "Response is factually sound with logical analysis, covers all four questions thoroughly with benchmarks and calculations, structured clearly with tables and lists, provides insightful cohort-based reasoning and strategic implications, and offers actionable recommendations for the PM." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 8.8, "brief_justification": "The response accurately interprets the metrics, provides thorough analysis for each question with logical explanations, is clearly structured, offers insightful nuances on retention and engagement patterns, and gives actionable advice for the PM." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.8, "brief_justification": "The response accurately interprets all metrics, provides relevant benchmarks and implications, structures answers clearly by question, offers insightful reasons for trends, and gives actionable focus on D7 retention with strong rationale." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 8.8, "brief_justification": "The response is factually accurate, logically sound, and provides a thorough, well-structured analysis with meaningful insights on growth vs. retention dynamics, benchmarks, and actionable priorities. Minor deduction on depth as some industry benchmarks are approximate rather than deeply sourced." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 9, "brief_justification": "The response is factually accurate, logically sound, and provides thorough, insightful analysis with clear structure, practical recommendations, and relevant benchmarks. It fully addresses all four questions with depth beyond surface level." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 8.8, "brief_justification": "The response accurately interprets the metrics, provides a clear narrative, explains concerns with DAU/MAU using benchmarks and trends, offers multiple plausible reasons for session changes in a structured table, and justifies focusing on D7 retention with strong rationale and actionable steps. Minor deduction on depth as some industry benchmarks are approximate rather than deeply sourced." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 8.6, "brief_justification": "The response accurately interprets the metrics, provides logical analysis for each question, and offers actionable insights with good structure and depth." }, { "judge_key": "grok_420", "judge_name": "Grok 4.20", "respondent_key": "minimax_m25", "respondent_name": "MiniMax M2.5", "weighted_score": 8.8, "brief_justification": "The response accurately interprets the metrics, provides context with benchmarks, explains causal relationships, and gives actionable advice with clear reasoning." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 8.65, "brief_justification": "Accurate interpretation of metrics, thorough coverage of each question, clear structure with headings and tables, deep analysis including benchmarks and cohort segmentation, and actionable recommendation to focus on D7 retention." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 8.45, "brief_justification": "Accurate interpretation, covers all parts, clear structure, offers insightful analysis and actionable focus on D30 retention." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.4, "brief_justification": "Accurate interpretation of metrics, covers all questions clearly, offers insightful analysis and actionable focus, minor nuance on DAU/MAU benchmark." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 8.65, "brief_justification": "Accurate calculations and interpretations, covers all four questions with clear structure, offers insightful analysis and actionable focus on D7 retention, though could dive slightly deeper into cohort metrics." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 8.85, "brief_justification": "Accurately interprets metrics, covers all questions with detailed analysis, clear structure, deep insights into retention and engagement, and offers actionable focus on cohort D30 retention." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 8.65, "brief_justification": "Accurately interprets the metrics, covers all questions, clearly organized, offers insightful analysis and actionable focus on retention." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 8.25, "brief_justification": "Accurate interpretation of metrics, covers all questions clearly, offers solid analysis and actionable focus on D7 retention, though could delve deeper into cohort and monetization aspects." }, { "judge_key": "gpt_oss_120b", "judge_name": "GPT-OSS-120B", "respondent_key": "minimax_m25", "respondent_name": "MiniMax M2.5", "weighted_score": 8.45, "brief_justification": "Accurately interprets metrics, covers all questions, clear structure, offers insightful analysis and actionable focus on long-term retention." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 8.85, "brief_justification": "The analysis of the 'leaky bucket' and the DAU/MAU ratio is excellent and factually sound. However, the response is incomplete as it cuts off mid-sentence in section 3 and completely omits the answer to question 4." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 10, "brief_justification": "The response provides an exceptional analysis of the data. It correctly identifies the 'leaky bucket' syndrome, accurately calculates and benchmarks the DAU/MAU ratio, offers nuanced explanations for session length changes, and selects a highly strategic metric (D7 retention) with a sophisticated justification. The use of cohorts and segmentation shows expert-level product management thinking." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 9.8, "brief_justification": "The response provides a highly accurate and professional analysis of the product metrics. It correctly identifies the 'leaky bucket' growth pattern, accurately calculates the DAU/MAU ratio, and provides nuanced explanations for the inverse relationship between session frequency and length. The recommendation to focus on D30 retention is the industry-standard approach for this specific data profile." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 9.8, "brief_justification": "The response accurately interprets the data, correctly identifies the 'leaky bucket' growth problem, and provides a logical choice for the focus metric with sound reasoning." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 9.8, "brief_justification": "The response provides a highly accurate and professional analysis of the metrics. It correctly identifies the 'leaky bucket' growth story, accurately calculates the stickiness ratio, and provides nuanced explanations for the inverse relationship between session frequency and length. The choice of D7 retention is well-justified." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 10, "brief_justification": "This is an exceptional response. It correctly identifies the 'leaky bucket' phenomenon, provides a sophisticated analysis of the DAU/MAU ratio, offers multiple plausible hypotheses for the session length discrepancy, and selects the most strategic metric (Cohort D30 Retention) with a clear business case. The formatting and structure are professional and highly actionable." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9.8, "brief_justification": "The response provides a highly accurate and professional analysis of the data. It correctly identifies the 'leaky bucket' phenomenon, accurately calculates and interprets the DAU/MAU ratio, and offers insightful reasons for the inverse relationship between session frequency and length. The recommendation to focus on retention is the industry-standard correct answer for this scenario." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 10, "brief_justification": "The response is exceptional. It correctly identifies that the growth is acquisition-driven rather than retention-driven, accurately calculates the DAU/MAU ratio, provides nuanced reasons for the session length/frequency inverse relationship, and selects a highly logical focus metric (D7 retention) with a strong business justification." }, { "judge_key": "gemini_3_flash", "judge_name": "Gemini 3 Flash Preview", "respondent_key": "minimax_m25", "respondent_name": "MiniMax M2.5", "weighted_score": 9.8, "brief_justification": "The response is exceptionally accurate and insightful. It correctly identifies the 'leaky bucket' scenario, calculates the DAU/MAU ratio accurately, provides logical reasons for the inverse relationship between session frequency and length, and selects the most critical metric for long-term sustainability." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "gemini_31_pro", "respondent_name": "Gemini 3.1 Pro", "weighted_score": 6.95, "brief_justification": "Insightful analysis with correct calculations and good structure, but the response is truncated mid-sentence and fails to answer the final question about which metric to focus on, significantly reducing practical value." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "claude_opus_46", "respondent_name": "Claude Opus 4.6", "weighted_score": 9, "brief_justification": "Comprehensive analysis covering all four questions with accurate calculations, clear structure using tables and code blocks, insightful depth including cohort analysis and acquisition source segmentation, and highly actionable recommendations centered on D7 retention by cohort." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "gpt_5_4", "respondent_name": "GPT-5.4", "weighted_score": 9, "brief_justification": "Comprehensive analysis addressing all four questions with accurate calculations, insightful interpretations, clear structure, and actionable recommendations. Provides multiple plausible explanations for observed trends and identifies D30 retention as the key metric to focus on, with specific follow-up questions for the PM." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "deepseek_v4", "respondent_name": "DeepSeek V4", "weighted_score": 8.4, "brief_justification": "Accurate analysis covering all four questions with correct calculations (DAU/MAU=20%). Well-structured with clear headings and actionable recommendation (focus on D7 retention). Minor扣分 for slightly generic benchmark claims. Thorough explanation of session length decrease and retention funnel issues. Practical, PM-ready insights." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "mimo_v2_flash", "respondent_name": "MiMo-V2-Flash", "weighted_score": 8.8, "brief_justification": "Well-structured analysis covering all questions with accurate calculations, insightful explanations of the DAU/MAU ratio paradox, multiple plausible explanations for session length decrease, and a strong actionable recommendation to focus on D7 retention." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "claude_sonnet_46", "respondent_name": "Claude Sonnet 4.6", "weighted_score": 9, "brief_justification": "Comprehensive analysis addressing all four questions with accurate calculations, strong frameworks, multiple hypotheses where appropriate, and highly actionable recommendations. Excellent use of tables, benchmarks, and business case reasoning. The leaky bucket metaphor and cohort analysis recommendation demonstrate deep analytical thinking." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "grok_420", "respondent_name": "Grok 4.20", "weighted_score": 9, "brief_justification": "Comprehensive analysis addressing all four questions with accurate calculations, insightful interpretations (leaky bucket metaphor, growth masking retention problems), clear structure, and highly actionable recommendations. Correctly identifies the core problem: acquisition-driven growth masking poor retention, and provides specific focus metric (D7) with reasoned justification." }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "gpt_oss_120b", "respondent_name": "GPT-OSS-120B", "weighted_score": 9, "brief_justification": "Comprehensive analysis covering all four questions with accurate calculations, industry benchmarks, and insightful explanations. Well-structured with tables and clear headings. Provides actionable recommendation with specific targets and next steps. The response correctly identifies the core story (acquisition vs. retention disconnect), explains the DAU/MAU ratio concern with proper benchmarks, offers multiple plausible explanations for the session paradox, and recommends D7 retention with stron" }, { "judge_key": "minimax_m25", "judge_name": "MiniMax M2.5", "respondent_key": "gemini_3_flash", "respondent_name": "Gemini 3 Flash Preview", "weighted_score": 8.8, "brief_justification": "Accurately identifies leaky bucket growth pattern, correctly calculates DAU/MAU ratio at 20%, provides insightful analysis of session behavior, and recommends D7 retention with solid business reasoning. Well-structured and actionable." } ], "meta": { "source": "The Multivac (app.themultivac.com)", "methodology": "10x10 blind peer matrix evaluation", "criteria": "correctness, completeness, clarity, depth, usefulness", "self_judgments": "excluded from rankings", "license": "Open data — cite as: The Multivac (2026)" } }