Surveying the competitive landscape of marketing mix modeling

In conversations with organizations, we’re often asked about the competitive benefits and unique selling points of AIM (Always-On Incrementality Measurement) by Kochava within the marketing mix modeling (MMM) space. Any answer we provide inevitably holds some bias, and the same is true for competitors. None of us fully knows the inner workings of each other’s businesses to offer a comprehensive comparison, and with the sheer number of MMM service providers out there, it’s impossible to fully assess every player in the market.

The other factor to consider: When you ask an MMM provider about their unique selling point (USP), you inevitably get a list of technical and data science buzzwords that, while sounding impressive, mean little to most people outside the data science field. Instead of adding clarity, this often further muddies the waters for decision makers trying to understand what sets each provider apart.

Organizations we’ve worked with find it helpful to have MMM providers grouped into clear cohorts based on their approach and the types of businesses they best serve. In this article, we unpack the matrix of MMM solutions available, from consultative services to internal builds, open-source tools, and finally, SaaS platforms. By understanding these categories and their specific strengths, you’ll be better equipped to find the MMM solution that truly aligns with your unique needs.

1. Consultative MMM Services

Consultancy-based services deploy a team of experts (typically from large analytics or management consulting firms) to build and manage MMMs for clients.

Pros

  • High Customization: Tailored models built to specific client needs and KPIs
  • Expert-Led: Access to experienced consultants who provide strategic insights and interpretation
  • End-to-End Service: Typically includes data sourcing and cleaning, model building, and results analysis

Cons

  • Costly: Often the most expensive option, especially for ongoing support and updates
  • No Real-Time Capabilities: Reporting often conducted on a quarterly basis, most commonly once or twice per year; each MMM report incurs additional costs
  • Requires Expertise to Interpret: Output usually requires specialized knowledge to interpret and may not be immediately actionable by marketing teams
  • Longer Turnaround: Generally longer lead times due to model customization and consultant availability

Ideal for: Large enterprises or businesses needing highly tailored, complex MMM solutions with robust support and guidance, for whom real-time decision making is less critical.

2. Build Your Own Internal MMM

Large companies may employ an internal data science team to build, manage, and optimize their own MMM within the organization.

Pros

  • Full Control: Complete ownership over the model, data, and analysis, allowing for precise customization
  • Cost Control Over Time: Lower ongoing costs following initial investment in setup and expertise
  • Confidentiality: Greater data security and control without external third-party access

Cons

  • High Cost: Significant expenses associated with setup, including recruiting and retaining skilled resources
  • Resource-Intensive & Time-Consuming: Requires a team of skilled data scientists, data engineers, and possibly dedicated project managers, drastically lengthening deployment timelines
  • Narrow Knowledge Base: Lacks the broad experience and industry insights of service providers who have built hundreds of models across multiple verticals and understand the evolving digital marketing ecosystem
  • Internal Knowledge Dependency: Risks associated with turnover and loss of critical team members

Ideal for: Large, data-rich organizations with the resources to invest in and maintain a dedicated MMM team for customized modeling, for whom control over proprietary modeling is a priority.

3. Open-Source MMM Products

Open-source tools provide frameworks for MMM that are flexible, free to access, and can be adapted by organizations as needed.

Pros

  • Low Cost: Free to use, reducing software expenses
  • Customizable: Fully open-source, allowing for extensive customization by skilled users
  • Community-Driven Improvements: Regular updates and innovations driven by a global user community

Cons

  • Requires Skilled Resources: Significant technical expertise required to adapt, implement, and maintain
  • Limited Support: No official support, leaving users dependent on community forums and documentation
  • Not Turnkey: Typically requires data engineers and data scientists to operationalize and manage the tool effectively

Ideal for: Organizations with technical expertise and limited budget that need a highly customizable and adaptable MMM solution.

4. Next-Generation, Real-Time SaaS MMM Products

SaaS solutions integrate MMM capabilities with real-time or near real-time data processing. These platforms typically provide pre-built, advanced algorithms, intuitive user interfaces, and automated workflows, with entry-level access at relatively low cost.

Pros

  • Scalability: Easily scalable to various marketing budgets and data inputs
  • Real-Time Analytics: Real-time or near real-time analytics for agile decision making, enabling teams to react swiftly to dynamic market demands
  • Minimal Setup Time: Usually quick to deploy, with minimal technical setup, relative to all other MMM products and services
  • Standardized & Validated Models: Typically built on industry-standard MMM methodology, ensuring reliability and accuracy
  • Cost-Effective for Small Scale: Offers an accessible entry point for MMM at lower scales, without significant upfront investment
  • Regular Technology Updates: Continuous updates that integrate the latest technological advances and improvements
  • Strong Client Support: Established support infrastructure with dedicated teams to assist with setup, maintenance, and troubleshooting

Cons

  • Potentially Higher Costs at Scale: Usage-based pricing can become expensive as data volumes increase
  • Limited Customization: Customization options may be constrained to fit the platform’s capabilities and may not meet all use cases or edge use cases

Ideal for: Marketing teams who need real-time data to respond quickly in fast-paced environments. Organizations seeking a quick-to-deploy, out-of-the-box solution with ongoing technical support and regular updates, especially when looking for an accessible entry point to MMM without the need for internal development.

For a deeper dive into the advantages of SaaS MMM solutions, please refer to this blog.

A Summary of Your MMM Options

The following table provides a concise summary of your choices when approaching MMM for your organization. If you’re interested in exploring a SaaS MMM platform, please contact our team.

Feature SaaS MMM
(Including AIM)		 Consultative MMM Services BYO Internal MMM Open-Source MMM Products
Cost $-$$$ (scales with use) $$$ $$ (high initial, lower ongoing) $
Customization Medium High High High
Real-Time Capabilities Yes No Possible but not realistic No
Setup Time Fast Slow Slow Slow
Support Strong client support Consultant-led Internal team required Community-driven
Industry Knowledge & Expertise Regular, industry-wide updates Extensive, from cross-vertical projects Limited to internal knowledge Community-shared expertise
Technical Expertise Required Low to medium Medium High High
Ideal For Marketing teams needing real-time data, scalability, and fast deployment Large enterprises needing deep customization Large organizations with extensive resources Budget-conscious organizations with technical expertise