Boost Your ROI with Marketing Mix Modeling
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Express Analytics’ marketing optimization solution streamlines the entire Marketing Mix Modeling (MMM) process from start to finish. Built with a focus on user experience, it empowers CMOs and their marketing teams to easily navigate complex datasets and gain meaningful insights. By removing the technical barriers often associated with data analytics, our solution ensures that strategic decisions can be made faster and with greater confidence—without requiring advanced technical expertise.
Use ML-powered data analytics to improve future results.
Customer Analytics
Evaluate the performance of franchises and stores by analyzing recent trends in customer footfall, transaction volumes, and overall sales activity across locations.
Optimization of Trade Promotions
Maximize the effectiveness of trade promotions, discounts, and special offers across all product variants and categories to boost overall returns and sales performance.
Power BI and dashboarding
Provide instant updates, enhance team collaboration, forecast outcomes, and monitor key performance indicators effectively to drive better business decisions and improved results continuously.
Optimize marketing performance.
- Optimize media spend
- Measure campaign uplift
- Learn from ads
- Boost media ROI
- Track market share
Optimize, measure, grow.
Market Mix Modeling helps you analyze past marketing impacts, forecast campaign outcomes, optimize budgets to reduce CPA by 30%, and improve ROI. It provides fast, accurate insights with channel-level saturation curves for smarter media spend decisions.
Our Comprehensive Approach to Marketing Mix Modeling for Data-Driven Growth
Understanding of business
- Identify and understand business challenges
- Define the KPIs that can be measured
- Define the input data set
Data collection
- Communicate with several stakeholders
- Gather all the required data
- Prepare, clean, and match data
Data research
- Inspect all the data gathered
- Visualize and examine variables
- Build theory for modeling
Modeling
- Test combinations of all variables
- Test various theories
- Develop statistically and commercially perfect models
Evaluation
- Verify models to ensure they are stable
- Evaluate model soundness and results
- Tweak models with clients
Deployment
- Offer simulation and optimization insight
- Deploy outcomes and share suggestions