economics · GTM World Model v3.3

T1

The claim: Retention and acquisition alter different stock flows; their relative investment value depends on horizon, feasible response, costs and quality. Long-run denominator sensitivity does not prove universal retention dominance.
contested Model updated 2026-10-05

Evidence boundary

See the scoped evidence_register and qualification_protocol. Structural plausibility, descriptive surveys and laboratory benchmarks do not alone identify a local commercial policy effect.

Why this claim matters

See the scoped evidence_register and qualification_protocol. Structural plausibility, descriptive surveys and laboratory benchmarks do not alone identify a local commercial policy effect.

The mechanism

L counts active logos; M measures recurring monetary value. New-logo inflow has units logos/time; new-value inflow has units currency/time. Expansion changes value without adding logos. With n=delta_value-g_expansion, M(T)=M0*exp(-n*T)+a_value*(1-exp(-n*T))/n for n!=0; at n=0, M(T)=M0+a_value*T. Near zero net attrition the long-run equilibrium is not a finite-horizon ROI comparison. Retention versus acquisition depends on feasible responses, costs, horizon and quality.

Evidence for

  • Wei, Bencina, Nguyen, Ribeiro and Zelditch — From Prediction to Incrementality — 10 August 2026. Full preprint. Field intervention; full methods/limitations inspected. Eight-week member-randomized 50/50 LinkedIn comparison of causal scoring, exploration, constrained allocation and withholding versus propensity targeting, with a matched delivery envelope. The reported value lift concerns the complete policy. Static audience definitions and segment lineage protect assignment. Source: https://arxiv.org/html/2608.10182v1
  • Li, Yuan, Yang, Chen and Song — Attributed But Not Incremental — 25 June 2026. Full preprint. Production calibration against 18 rounds of channel experiments across up to eight TikTok markets, with rolling forward evaluation and daily hierarchical correction. Source: https://arxiv.org/html/2606.26690v1
  • Heusch — Structural Estimation of MMM Parameters from Geo Experiments — 21 August, revised 7 September 2026. Full v2. Synthetic structural study: 156-week fictional retailer, three channels, four four-week go-dark tests plus cooldown. Uses time paths to estimate effectiveness, carryover and saturation. Source: https://arxiv.org/html/2608.21128v2
  • Filippou, Quach and Jha — Pseudo Incrementality Testing — 16 September 2026. Full preprint. Changepoint detection plus counterfactual forecasting, two GeoLift benchmarks and synthetic stress tests. Only one of three nominal 90% intervals covers truth in the stress test; weak controls yield large bias. Source: https://arxiv.org/html/2609.18257v1
  • Ningyin Xu — Reference Dependent Pricing — deposited 16 July 2026. Repository and dissertation. Full PDF inspected. Randomized base-price histories across 818 food-vending locations during 2024, followed by equal current-price discount conditions in 2025. Source: https://knowledge.uchicago.edu/records/8v3yz-xrr12

Evidence against / limitations

  • No fitted local coefficient or complete-policy deployment evidence is supplied.
  • one platform, short experiment, no isolation of individual components, no autonomous B2B seller economics. C3/C5/C6.
  • normalized confidential errors; child-level credit is allocated rather than independently causally identified. A later cannibalization decline is before/after deployment evidence, not a randomized business-impact estimate. Complementarity and spillover remain limitations. C3/C5.
  • stable parameters, specified adstock/saturation, no spillover and tested spend support. It is not an empirical estimate of SaaS brand decay. C3/C5.

So what: the operator implication

With n=delta_value-g_expansion, M(T)=M0*exp(-n*T)+a_value*(1-exp(-n*T))/n for n!=0; at n=0, M(T)=M0+a_value*T. Near zero net attrition the long-run equilibrium is not a finite-horizon ROI comparison. Retention versus acquisition depends on feasible responses, costs, horizon and quality.

Related theses

All theses

How to cite this

@misc{shalvi_gtm_thesis_t1_2026,
  author = {Singh, Shalvi},
  title  = {GTM World Model Thesis T1},
  year   = {2026},
  url    = {https://shalvisingh.com/gtm/theses/t1}
}

Singh, Shalvi. "GTM World Model Thesis T1." shalvisingh.com, 2026. https://shalvisingh.com/gtm/theses/t1