Why are client names anonymized in the case studies?

Engagements are referenced by internal client codes (e.g. DM-118) to protect commercial confidentiality while still publishing full KPI deltas. Verticals, channels, and spend tiers are disclosed; brand identities are not.

What metrics are typically reported in each case study?

Each case study surfaces the metrics that mattered to that engagement: ROAS, MER, CAC, and signal recovery for DTC ecommerce; MQL volume, CAC payback, and pipeline contribution for HR-tech SaaS; SQL volume and pipeline efficiency for B2B SaaS and fintech.

Do you share the dashboards behind these numbers?

Qualified prospects on a strategy call receive direct access to the live Looker dashboards for any anonymized case study discussed, including raw spend, revenue, and attribution splits.

Index 02 — Results

Receipts,
not promises.

Every engagement is filed under an internal client code. No logo wall, no "imagine if" case studies. What follows is a metric-led catalog of paid-media, SEO, and conversion work shipped across 182 active brands in 2024 — HR-tech, DTC ecommerce, B2B SaaS, and fintech. Scan the vertical that matches your stack.

Book a Strategy Call Browse by Vertical

Anonymized by design. Client codes (DM-###) map to internal verticals and KPI baselines — never to identifiable brands.

Browse the index

Five verticals. Twenty-three anonymized engagements.

DM-118 Applicant Tracking — Series C Q1 2024 → Q4 2024 · 11-month engagement

Cut paid-media CAC by 47% while doubling MQL volume from a flat budget.

Engagement scope: paid search, LinkedIn ABM, and SEO for a mid-market applicant-tracking platform. Rebuilt the closed-loop stack against iOS 17 signal loss, migrated from last-click to a MMM-informed attribution model, and shifted 38% of paid-search spend into non-brand intent clusters the in-house team had written off.

−47% Blended paid-media CAC

+104% MQL volume, flat budget

9.1 mo CAC payback (from 14 mo)

+41% Recovered attribution signal

DM-204 Payroll Infrastructure — Series B Q2 2023 → Q3 2024 · 14-month engagement

Reactivated dormant keyword clusters and tripled SQL volume from paid search.

Engagement scope: paid search rebuild, programmatic display suppression, and a 40-page programmatic SEO rollout across long-tail payroll-compliance queries. Co-developed with the client's RevOps team a lead-scoring model that prioritized accounts with HR-finance committee intent.

3.1× SQL volume from paid search

−58% Cost per SQL

+212% Organic sessions (programmatic SEO)

$4.2M Added pipeline, 12-mo attribution

DM-317 Employee Engagement — Series A Q3 2024 → ongoing · 6-month engagement

Launched paid social into a category nobody else had measured, then validated the incrementality.

Engagement scope: paid social on Meta and LinkedIn, with a geo-holdout incrementality test on TikTok. Built a custom signal-recovery layer that recovered 41% of the conversions standard GA4 was dropping, and rebalanced creative spend against the audiences that actually closed to demo.

+186% Qualified demos booked

−31% Demo no-show rate

+24% Demo-to-opportunity conversion

5.2× Paid-social ROAS, 90-day

DM-072 Apparel — 8-figure DTC Q4 2022 → Q3 2024 · 23-month engagement

Rebuilt paid social around new-customer acquisition and lifted MER from 2.4 to 4.8.

Engagement scope: Meta and TikTok paid social, Google Shopping, and a creator-led UGC program feeding top-of-funnel. Built a holdout-tested incrementality model and shifted spend from retargeting (which was over-attributing) to prospecting audiences with measurable net-new lift.

4.8× MER (from 2.4×)

+63% New-customer share of revenue

−42% New-customer CAC

$11.8M Incremental revenue, 2023

DM-156 Supplements — subscription DTC Q1 2024 → ongoing · 10-month engagement

Rebuilt creative production around cohort LTV and lifted 6-month subscriber value by 71%.

Engagement scope: Meta, TikTok, and YouTube paid media plus a CRO program on the product and checkout pages. Tested 38 creative concepts against cohort LTV rather than front-end ROAS, killing the "best" ads by blended ROAS that were actually worst on 6-month value.

+71% 6-month subscriber LTV

+28% First-order conversion rate

−19% Subscription churn, 90-day

3.9× Cohort-weighted ROAS

DM-289 Home goods — wholesale + DTC hybrid Q2 2024 → Q4 2024 · 8-month engagement

Cleaned up Google Shopping feed, then added Meta prospecting for a 2.3× revenue lift.

Engagement scope: Google Shopping feed remediation, Meta prospecting for net-new buyers, and a CRO program that simplified PDP-to-cart. The feed clean alone recovered 31% of disapproved SKUs and lifted Shopping revenue inside the first quarter.

2.3× Quarterly revenue, YoY

+57% Shopping revenue

+34% PDP-to-cart conversion

4.1× MER, Q4 2024

Methodology note

“Every number on this page passed through the Signal Recovery Framework — a closed-loop tracking stack audited against iOS privacy changes, with weekly recalibration against our in-house media mix model. If we can't attribute the lift, we don't claim the lift. Clients see the same dashboard our analysts work from, every Tuesday morning.”

DM-091 Vertical SaaS — Revenue Intelligence Q1 2023 → Q4 2024 · 22-month engagement

Built an ABM program against named accounts and lifted SQL-to-close rate by 41%.

Engagement scope: LinkedIn ABM, paid search on competitor keywords, and a content program that produced 14 long-form teardowns per quarter. The Drum Awards "Best Integrated Campaign" work (NYC, 2023) came out of this engagement for a category-shaping HR-tech client — anonymized here under DM-118 adjacent.

+41% SQL-to-close conversion

$8.4M Added ARR, 2023

−36% Sales cycle length

3.6× Pipeline coverage on target accounts

DM-142 B2B SaaS — Developer Tools Q3 2023 → Q2 2024 · 11-month engagement

Replaced gated-content MQLs with product-led signal scoring, lifting SQL quality.

Engagement scope: paid search on developer-intent queries, sponsored content on engineering publications, and a CRO rebuild of the trial-signup flow. Worked with the client's data team to ingest product-usage signals into the lead score so sales spent time on accounts that had actually run the SDK.

+58% SQL volume from product-led signals

−44% Cost per SQL

+29% Trial-to-paid conversion

$3.1M Added ARR, 9-month attribution

DM-258 Fintech — Treasury & Payments Q2 2024 → ongoing · 7-month engagement

Cut CFO-committee sales cycle from 11 months to 7 with a category-content engine.

Engagement scope: SEO-led category content, paid search on regulatory-intent queries, and a CRO rebuild of the enterprise-demo request flow. Built a 22-article quarterly content cadence that targeted the exact questions CFO committees were Googling during their vendor shortlisting phase.

−36% Enterprise sales cycle (11 mo → 7 mo)

+187% Organic sessions, category content

+47% Demo requests from CFO-tier accounts

$2.6M Pipeline added, Q3 2024

Receipts,
not promises.

Five verticals. Twenty-three anonymized engagements.

Pipeline efficiency, recovered signal, and MQL volume gains.

Cut paid-media CAC by 47% while doubling MQL volume from a flat budget.

Reactivated dormant keyword clusters and tripled SQL volume from paid search.

Launched paid social into a category nobody else had measured, then validated the incrementality.

MER, incremental ROAS, and new-customer CAC — the metrics a board actually sees.

Rebuilt paid social around new-customer acquisition and lifted MER from 2.4 to 4.8.

Rebuilt creative production around cohort LTV and lifted 6-month subscriber value by 71%.

Cleaned up Google Shopping feed, then added Meta prospecting for a 2.3× revenue lift.

Considered-buying verticals where attribution is harder and stakes are higher.

Built an ABM program against named accounts and lifted SQL-to-close rate by 41%.

Replaced gated-content MQLs with product-led signal scoring, lifting SQL quality.

Cut CFO-committee sales cycle from 11 months to 7 with a category-content engine.

Receipts,not promises.

Five verticals. Twenty-three anonymized engagements.

Pipeline efficiency, recovered signal, and MQL volume gains.

Cut paid-media CAC by 47% while doubling MQL volume from a flat budget.

Reactivated dormant keyword clusters and tripled SQL volume from paid search.

Launched paid social into a category nobody else had measured, then validated the incrementality.

MER, incremental ROAS, and new-customer CAC — the metrics a board actually sees.

Rebuilt paid social around new-customer acquisition and lifted MER from 2.4 to 4.8.

Rebuilt creative production around cohort LTV and lifted 6-month subscriber value by 71%.

Cleaned up Google Shopping feed, then added Meta prospecting for a 2.3× revenue lift.

Considered-buying verticals where attribution is harder and stakes are higher.

Built an ABM program against named accounts and lifted SQL-to-close rate by 41%.

Replaced gated-content MQLs with product-led signal scoring, lifting SQL quality.

Cut CFO-committee sales cycle from 11 months to 7 with a category-content engine.

Receipts,
not promises.