Introduction
In the rapidly evolving world of marketing, businesses are constantly looking for ways to maximize their returns on investment. One of the most powerful tools for understanding what’s driving sales and optimizing future strategies is Marketing Mix Modeling (MMM). MMM uses historical data to analyze how different elements of a marketing strategy—like media spending, promotions, or price changes—contribute to key performance indicators (KPIs) such as sales or customer acquisitions.
In recent years, the trend of in-housing marketing capabilities has gained traction, particularly for MMM. Companies and media agencies alike are beginning to realize the benefits of taking ownership of these models, from cost efficiency to more strategic insights. However, this shift isn’t without its challenges. Building the internal expertise needed to manage MMM requires time, resources, and a clear plan.
In this article, we’ll explore how businesses can strategically in-house their MMM capabilities, moving from a full-service approach to a hybrid model and eventually to complete self-service. We’ll highlight the benefits, barriers, and how this transition can be both empowering and cost-effective for businesses. Whether you’re a company looking to build internal expertise or a media agency aiming to provide value as a hybrid partner, this article will guide you on the path to success.
Full Service: The Starting Point
For many businesses, the journey to in-housing MMM starts with a Full Service solution. In this model, an external partner manages the entire process—from data collection and validation to model creation and insights generation. This is ideal for companies that don’t yet have the internal resources or expertise to manage complex MMM projects but still want to benefit from its powerful insights.
By working with experienced professionals, businesses can ensure they’re getting the most accurate and valuable insights from their marketing data without having to build the capability internally from day one. Media agencies, for example, are well-positioned to act as these external partners, leveraging their in-depth understanding of the business and its goals. For companies that already have strong relationships with these agencies, continuing that partnership in an MMM capacity can be a natural fit. There’s no need to change the trusted teams you’re already working with—these partners can deliver a full-service MMM solution.
While the Full Service model offers immediate benefits, it can also be the first step in a longer journey. As businesses start to see the value of MMM, they may begin considering how to bring some of these processes in-house. That’s where the transition to a Hybrid Service comes in, allowing businesses to gradually build their internal capabilities with the guidance of their existing external partners.
Hybrid Service: Building Internal Competency
As companies grow more familiar with the insights generated from MMM and start developing a deeper understanding of how the process works, the next logical step is transitioning to a Hybrid Service. In this model, businesses begin taking more control over aspects of their marketing mix modeling, while still relying on external partners or experts for support where needed.
The Hybrid Service model is a bridge between full outsourcing and complete in-housing. It allows businesses to gradually build their in-house expertise without the pressure of managing everything from day one. Teams can start by learning the basics, like validating data or interpreting model results, and then move toward more complex tasks, such as model building and optimization. Throughout this process, external partners—whether it’s Alviss AI or a trusted media agency—can step in when needed, providing expert guidance and ensuring that the MMM process remains on track.
The key advantage of the Hybrid Service is flexibility. Businesses can decide which parts of the MMM process they want to handle internally and which they prefer to leave to their external partners. This setup also allows for a smoother transition as internal teams gain confidence and competence, gradually taking on more responsibility. Over time, this model can evolve, allowing the business to bring more processes in-house as their skill sets grow.
Self-Service: Full Control and Autonomy
For businesses that have developed the necessary internal expertise, the Self-Service model offers the ultimate goal—full control over their marketing mix models. In this stage, companies manage all aspects of MMM in-house, from data selection and validation to model building, interpretation, and decision-making. This level of autonomy allows businesses to adapt their models more rapidly to shifting market conditions and optimize their strategies without depending on external support.
Self-Service is ideal for organizations that have already built a strong internal foundation of data scientists, analysts, and marketing experts capable of handling the complexities of MMM. This model provides complete access to the Alviss AI platform, offering all the tools needed for robust model development and the flexibility to customize models to specific business needs.
The Self-Service stage is not only cost-effective in the long run but also empowers teams to fine-tune their models continuously and derive real-time insights to inform decisions. However, reaching this stage requires a well-planned path, with structured learning and hands-on experience—something that the Full Service and Hybrid Service models help facilitate. Even in Self-Service mode, Alviss AI ensures that technical support is readily available to troubleshoot any issues, making sure the platform operates smoothly.
Embracing Self-Service: A Strategic Transition
As you approach a Self-Service model, it’s crucial to make the transition smooth and manageable. One of the significant advantages of the Hybrid Service phase is the flexibility it offers in choosing which areas to take over first. This approach allows you to focus on specific components of the marketing mix modeling process, such as data management, data validation, or business insights, based on your team’s readiness and priorities.
1. Prioritize Your Focus Areas:
You can start by selecting the aspect of marketing mix modeling that aligns best with your team’s current capabilities and needs. For instance:
- Data Management: Begin with taking control of data management, including the collection, organization, and integration of data from various sources. This step is fundamental, as accurate and well-organized data forms the backbone of effective modeling.
- Data Validation: Alternatively, you might choose to focus on data validation, ensuring that the data used in models is accurate and reliable. This step involves implementing checks and processes to verify data quality before it enters the modeling phase.
- Business Insights: If your team is confident in interpreting insights, bringing the analysis of model results in-house offers faster insights generation, a deeper connection between the results and your unique business context, and the flexibility to address specific, business-driven questions.
2. Collaborate with Your Full-Service Partner:
As you gradually transition to Self-Service, your Full-Service partner can shift roles to act as a validator. This collaboration ensures that as you assume more responsibility, the quality and accuracy of your work remain high. Your partner can provide:
- Validation of Processes: Review and validate the new processes and workflows you implement, ensuring they meet the necessary standards and maintain model integrity.
- Quality Assurance: Offer oversight and quality checks to catch potential mistakes and refine methodologies, helping to prevent errors and ensure reliable results.
- Ongoing Support: Continue providing support as needed, answering questions, and offering guidance as you become more proficient in managing the platform independently.
By strategically taking over these areas and leveraging your Full-Service partner as a validation resource, you can build confidence and competence in managing marketing mix models. This phased approach not only helps in mitigating risks but also supports a smoother transition to a fully in-house Self-Service model.
The Path to In-Housing: Maximizing Efficiency, Control, and Cost Savings
One of the biggest advantages of in-housing your marketing mix modeling is the ability to generate insights faster, with greater precision. When your team manages the entire process, the lag between data collection, running models, and turning results into actionable strategies is minimized. This agility allows your business to adapt quickly to market changes, seize opportunities faster, and make data-driven decisions in real time.
Cost savings are another major benefit of in-housing. Outsourcing MMM services can be expensive, and while the investment in external expertise can be justified early on, bringing these capabilities in-house reduces the long-term financial burden. By managing your own models and insights, you can eliminate recurring fees and external consultancy costs while still delivering high-quality analysis internally. Over time, the savings can be reinvested into other areas of the business, such as expanding your marketing efforts or enhancing data capabilities.
Additionally, no external partner will ever have as deep an understanding of your business as your own team. In-housing gives you the power to align insights more closely with your company’s strategic goals. With bespoke, business-specific questions, your internal team can dig deeper into the data, uncovering insights that are directly relevant to your unique challenges. If your organization already has business intelligence or data science experts, they can further refine models to reflect ongoing changes in the market or your business.
Alviss AI is designed to support this transition smoothly. The platform’s flexibility allows you to choose which parts of the MMM process to in-house first—whether that’s managing insights, handling data, or fully owning the model-building process. As your internal team grows in capability, you can gradually take over more responsibility while still ensuring high-quality results. Alviss AI bridges the gap between external support and internal expertise, helping you build competency at your own pace.
Conclusion
In-housing marketing mix modeling not only enhances control and agility but also results in significant cost savings. With Alviss AI’s platform, you can scale your in-house capabilities step by step, while gaining faster insights and building models that are aligned with your business’s specific needs—all without compromising on quality. This approach provides businesses with the tools to evolve from relying on external partners to becoming fully self-sufficient in driving data-driven strategies.