In 2025, the pressures on marketing technology (MarTech) budgets are high. Customer data has grown, and so have analytics pipelines. Many marketing teams find themselves spending more on infrastructure than on innovation. Here are four ways to reduce MarTech spend without sacrificing the insight your business requires.

4 Best Ways to Lower Martech Spend Without Data Loss

1. Right-Size Your Analytics Pipelines

Many companies run large data pipelines that are capable of much more than needed, often running too frequently or processing duplicate data. After you detect where over-provisioning is happening, you can optimize cloud resources and save compute costs without losing fidelity of the data. Here are some steps to follow:

  • Audit your analytical jobs for low-value or duplicate queries
  • Move from always-on to scheduled or event-based analytics
  • Use data-tiering so less-accessed datasets move to cheaper storage classes

Risk Consideration

Over-optimizing may introduce latency in dashboards or ineffective campaign reporting. Marketers should establish clarity on which reports require real-time analytics versus those that are acceptable for a daily data trigger.

2. Automate AWS Cost Optimization

Due to ever-increasing AWS costs, manual cost monitoring can take too long and is generally reactive if cost overruns occur. Automating any execution of commitments, in this case AWS savings plans and reserved instances, means teams are always right-sizing their spend, eliminating the need for human intervention.

Consider using an automation platform that can automate AWS cost optimization and ensure full MarTech stack utilization of all best-available discounts. These platforms analyze usage-trends and purchase commitments. They help adjust the allocations dynamically to wring out waste.

Risk Consideration

Automation will still always need oversight to ensure any long-term usage commitment doesn’t lock you into an outdated configuration. Always review your governance policies to ensure flexibility to shrink and expand spend while procuring savings.

3. Employ Brighter Data Retention and Compression

Every marketing event adds up quickly. Keeping all the data forever adds up quickly, costs a lot of money, and is hardly necessary. Instead, data retention policies should be created that balance compliance with cost. Take these steps:

  • Hold full data for key KPIs, but aggregate or archive older logs
  • Use compression capabilities to reduce event data size by up to 70% before storing it
  • Partition hot (frequently used) from cold (rarely used) data.

Risk Consideration

Aggressive deletions or compressions may hinder reconstruction of historical performance reports. Ensure retention schedules meet regulatory and analytical requirements.

4. Move to Serverless and Spot Instances for Elastic Workloads

Marketing workloads, especially campaign simulations, attribution modeling, or audience segmentation, come in bursts. Instead of keeping servers idle, put them in serverless architectures or use spot instances for batch workloads. Take the following steps:

  • Open non-production jobs (testing, QA, etc.) on schedules not 24/7
  •  Use and explore AWS Lambda or Google Cloud Functions for event-driven workloads

Risk Consideration

Spot instances are subject to interruption due to capacity reclamation, so important pipelines should have some checkpointing or fall back on demand capacity. For marketing reports, it’s important to think about the time to introduce a hybrid model of on-demand and spot.

Endnote

Reducing costs may not necessarily equal losing the ability to continue providing data-driven marketing services. By right-sizing analytics, controlling data retention, and the overall ability to automate cost optimization, you can save money with MarTech infrastructure.