I’ve helped multiple startups and mid-market teams cut martech budgets without sacrificing data quality or growth experiments. One repeatable pattern I keep coming back to is consolidating tracking into Google Analytics 4 (GA4) + a single Customer Data Platform (CDP). Done right, this combination reduces duplicate tracking, shrinks vendor fees, simplifies compliance and gives teams one truth for activation — often cutting martech costs by ~40% within 6–12 months.
Why consolidation saves money (and time)
Martech sprawl happens slowly: analytics here, heatmaps there, a separate event stream for personalization, another for ads, server logs for product analytics… Each tool needs its own implementation, events, identity stitching and maintenance. That creates duplicate data pipelines, repeated tagging work, and overlapping vendor fees.
When I consolidate, I focus on three cost drivers:
Duplicate event collection: sending the same events to 5 vendors increases client-side payloads, maintenance time and vendor costs (most charge by event or monthly seats).Implementation overhead: every extra tool adds QA, debugging and release cycles — often handled by engineering or growth teams.Fragmented identity and audiences: different systems build their own user graphs, leading to paid-syncs between tools or expensive ETL to reconcile data.GA4 + a single CDP addresses each of these. GA4 provides a robust, cost-efficient analytics engine. A CDP (e.g., Segment, mParticle, RudderStack) centralizes event collection, identity resolution and downstream routing so you can send only what you need to paid vendors.
How the savings actually work — a practical breakdown
Here's a simplified example I use during audits. Imagine a mid-market SaaS company with these monthly costs before consolidation:
| Tool | Purpose | Monthly cost |
| FullStack Analytics | Product analytics | $1,200 |
| Behavior Heatmap | User session recordings | $600 |
| Ad Analytics | Advanced attribution | $900 |
| Email Personalization Vendor | Real-time personalization | $800 |
| Segment | Event routing | $700 |
| Google Analytics 4 | Free analytics baseline | $0–$150* |
| Total | | $4,400 |
*GA4 baseline is free; GA4 360 has enterprise pricing. Most teams can stay on free GA4 and still achieve consolidated insights.
After consolidation we:
Keep GA4 for funnel and attribution analysis — $0Adopt a single CDP (replace Segment paid plan with a more cost-effective plan or self-hosted RudderStack) — $700 → $500Replace product analytics and ad analytics with events + analysis in GA4 and BigQuery (or Snowflake) — $2,100 → $600Keep heatmaps for session replay where it delivers clear insights — $600 → $300 (less usage)Replace real-time personalization vendor for many use cases by routing audiences from the CDP to owned email/personalization channels or cheaper personalization tools — $800 → $300 | Before | After (consolidated) |
|---|
| $4,400 | $2,200 |
That’s roughly a 50% cut in direct monthly vendor spend. Real projects usually average around 30–45% savings once you include migration costs, team time and more conservative tool reductions — so a 40% reduction is realistic and repeatable.
Which tools to keep and which to fold
Every stack is different, but my default consolidation playbook is:
Keep GA4 as your primary event-level analytics and attribution layer. Export GA4 to BigQuery for raw event storage and deeper analysis.Adopt one CDP (Segment, RudderStack, mParticle). Use it as the single source of event delivery and identity resolution — not as an analytics UI. The CDP should route to GA4, your email provider, ad platforms and a data warehouse.Eliminate overlapping analytics tools (if GA4 + BQ + simple BI meets the needs of product and marketing analytics). Consider full replacements where product analytics features are mission-critical.Keep session replay selectively for critical flows (checkout, onboarding). Use sampling to reduce events and cost.Use server-side tracking where practical to reduce client payloads, improve data quality and control data sent to paid vendors.Implementation checklist — what I do in the first 90 days
Here’s the pragmatic, prioritized plan I follow when consolidating tracking:
Week 1–2 — Audit and measurement plan: inventory events, tags, vendors, costs and owners. Identify high-value events and duplicate sends. Build a measurement plan with canonical event names and schemas.Week 3–4 — Choose CDP and schema: pick the CDP that fits your cost profile and data residency needs. Define a single event schema (name conventions, properties, user_id/email).Week 5–8 — Implement central collection: deploy the CDP, route events to GA4 and a warehouse. Implement server-side forwarding for sensitive or heavy events. Replace direct integrations with routed ones.Week 9–12 — Deprecate redundant tools: switch off duplicate data streams to paid vendors. Reconfigure sampling and retention. Move product queries to GA4/BQ and your BI layer.Ongoing: monitor data parity, event counts, and costs. Run weekly checks on user counts and event volumes in each consumer to catch regressions.KPIs and guardrails to measure success
Track these KPIs to validate savings and data integrity:
Monthly Vendor Spend: before and after consolidation (direct cost reduction target 30–45% within 6 months).Event Volume: total events sent to paid vendors (should fall as you remove duplicates).Time to deploy events: from request to production (should improve with a centralized CDP).Data parity checks: compare key metrics across GA4, CDP and warehouse (e.g., daily active users, purchases).Experiment velocity: number of A/B tests or personalization campaigns launched per month.Common pitfalls and how to avoid them
I’ve seen teams hit the following obstacles repeatedly:
Poor naming and schema inconsistency: without a canonical schema, consolidation creates friction. Solve it with a lightweight events catalog and strict naming rules.Underestimating product team needs: product analytics sometimes needs features GA4 doesn’t provide (e.g., raw user sessions, complex cohort analysis). Decide up-front where GA4 is sufficient and where a secondary tool is justified.Switching vendors without migration plan: turning off a tool before routes and dashboards are rebuilt breaks reporting. Use phased migration and dual-writing during cutover.Neglecting privacy and consent: consolidation is the right time to centralize consent management (CMP) and ensure you only send allowed data to each destination.Quick experiment you can run this week
If you want to test this approach fast, try this 2-week experiment:
Identify 5 high-value events you send to multiple vendors (e.g., signup, purchase, trial_start, upgrade, churn_signal).Route these events through your CDP to GA4 and your warehouse only. Stop sending them to 1–2 non-essential paid tools.Run a parity check comparing metrics in the old tools vs GA4/BQ for 7 days. If parity holds and you don’t lose insights, sunsetting those tools will cut costs and reduce maintenance.Consolidation is not a one-time cost-cutting exercise — it’s about creating a lean, maintainable martech stack that lets your team move faster and measure reliably. With a clear measurement plan, a single CDP and GA4 as your analytics backbone, you’ll be surprised at how much redundancy you can remove without losing insight — and how much budget you can free to reinvest in growth.
