Synthetic Control Methods for Measuring a Single Campaign’s Impact

Bayesian Forecasting of Link Building Outcomes

Causal Inference for SEO: Difference-in-Differences for Backlinks

Media-Mix Modelling for Earned Links and Digital PR

Geo Holdout Experiments: A Practical Design for Link Campaigns

Incrementality Testing for Link Building: Proving Links Caused the Lift

Link Building in Francophone Africa: A Distinct Market Playbook

Link Building in Greece and the Balkans: The 2026 Playbook for a Wide-Open Region

Link Building in Poland and Central Europe: The 2026 Playbook

Link Building in Israel: Hebrew-Language and Tech-Sector Tactics

Synthetic Control Methods for Measuring a Single Campaign’s Impact

Perwez Alam

TL;DR —  Your biggest campaigns are your hardest to measure: one national PR hit, one flagship page, one target market. With a single treated unit there is no control group, so difference-in-differences and hierarchical models have nothing to work with. —  Synthetic control builds a bespoke counterfactual: a weighted blend of untreated “donor” units that […]

Bayesian Forecasting of Link Building Outcomes

Perwez Alam

TL;DR —  Link building is a small-data, high-uncertainty decision problem — a quarter’s campaign is a dozen links, not a dozen thousand. That is the exact regime where classical point-estimate forecasting quietly fails. —  A Bayesian forecast is a distribution, not a number. The distribution is the deliverable: it powers “70% chance of reaching the […]

Causal Inference for SEO: Difference-in-Differences for Backlinks

Manish

TL;DR —  Backlinks are a staggered treatment: links land on different pages at different times. That single fact breaks the before-and-after regression most SEOs reach for. —  The pooled two-way fixed-effects model silently averages in “forbidden comparisons” — using an already-linked page as a control for a newly-linked one — and because link effects grow […]

Media-Mix Modelling for Earned Links and Digital PR

Perwez Alam

TL;DR. Media-mix modelling (MMM) is the one measurement method that can finally put earned links and digital PR on the same budget chart as paid media — a top-down, privacy-safe model that estimates each input’s contribution to a business outcome, with no cookies required. But run it naively and it will tell you PR is […]

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Bayesian Forecasting of Link Building Outcomes

Perwez Alam

TL;DR —  Link building is a small-data, high-uncertainty decision problem — a quarter’s campaign is a dozen links, not a dozen thousand. That is the exact regime where classical point-estimate forecasting quietly fails. —  A Bayesian forecast is a distribution, not a number. The distribution is the deliverable: it powers “70% chance of reaching the […]

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