Always-On Analytics Platform
Always-On Analytics is the next generation of Marketing Mix Modeling – faster, smarter, and more reliable.
Unique to MASS Analytics, it combines automation with expert oversight, creating a measurement framework that doesn’t just report results but anticipates what’s coming.
What It Does
Automates MMM
From data ingestion to modelling to reporting, MMM runs in the background without manual wrangling.
Provides early campaign reads
Pick up performance signals in days, not months, so you can adjust before budgets are wasted.
Acts as an early detection mechanism
Spot underperforming channels or market changes as they happen, not after.
Keeps MMM always up to date
Dashboards refresh automatically, delivering continuous insights your teams can trust.
Why It Matters
Proactive decision-making
Anticipate problems and act early, instead of reacting after the fact.
Future-proof MMM
Built to scale across new markets, channels, and data sources.
Connected view
All data and context aligned, so MMM reflects reality across the business.
Smarter resource allocation
Guide monthly shifts in channel mix and campaign strategy with confidence.
How It Works
1
Ingest
Always-On integrates directly with your systems to align all data sources.
2
Model
MMM runs continuously, integrating insights from all measurement sources to reflect campaigns, context, and market conditions.
3
Monitor
The system checks accuracy and provides early warnings if updates or rebuilds are needed.
4
Refresh
Time to insight in minutes, not months. So MMM stays current and decision-ready.
Powered by the MassTer Software Suite
Always-On Analytics runs on MASS Analytics’ MassTer Software Suite, a fully integrated engine designed to make advanced marketing measurement fast, accurate, and scalable.
MassFeeds
Handles data ingestion and preparation, aligning all sources and ensuring your models run smoothly every cycle.
MassTer
The core modeling software powering our MMM and experiments with advanced algorithms and robust statistical techniques.
Insight
Optimization, forecasting, and scenario planning, giving your teams the ability to test “what-if” strategies and make proactive decisions.
Built For…
Data Teams
Users with a statistical background who understand the business. They can monitor outputs, assess anomalies, and manage triggers for automatic model refreshes.
Marketing Teams
Professionals who need early campaign reads and proactive insights to optimize budgets and performance in near real-time.
Executives and Decision-Makers
Leaders who want reliable, continuous insights to anticipate shifts in market conditions and make evidence-based strategic decisions.
Frequently Asked Questions
The recommended user is a data analyst with statistical knowledge and business understanding. After initial setup, your team defines refresh triggers and parameters. MASS Analytics can remain involved as needed to support recalibration or guidance.
It can run fully on MASS Analytics’ systems or in your environment. If implemented in-house, a data analyst typically manages the process with optional support from IT or other teams depending on setup.
A full model build takes 6–8 weeks depending on scope and data availability. After that, Always-On MMM refreshes key outputs in near real-time whenever new data is added.
Yes. The platform supports flexible and detailed reporting. Optimisation and forecasting outputs can be generated at the most relevant level — by region, channel, audience, creative, tactic, or placement — as long as the input data is available.
The automodel runs in the background, while the user interface (within Databricks) lets you monitor performance, configure refresh setups, and define triggers for running the model. Once new data is uploaded, the model refreshes outputs including coefficients, response curves, optimisation results, forecasting, and contribution reports automatically.
You can choose your preferred level of support. In a fully managed setup, a MASS Analytics data analyst oversees model runs, validates outputs, and guides recalibration if needed. Over time, your team can take over using our “Walk, Run, Fly” approach to ensure full in-house control.
Monitoring is a key step to ensure model accuracy. The algorithm can detect when a refresh is sufficient or when a rebuild is needed. Users receive alerts for anomalies and can access a statistical dashboard to review metrics like R², T-statistics, and coefficients to validate both statistical and business significance.
The model integrates media signals and other contextual information automatically. This ensures performance insights reveal not just correlations, but causation, helping you understand what drives results.