Unified Measurement for a Complete View of Your Marketing
In a cross-device, cross-channel world, measurement only increases in complexity. Multi-Touch Attribution (MTA) is not enough to answer the demanding questions marketers face. While granular, MTA only provides a partial view of marketing without accounting for factors like offline activities, baseline sales, and external factors. That’s where Unified Measurement comes in.
Unified Measurement (sometimes referred to as UMIA) leverages Marketing Mix Modeling (MMM) and MTA to bring together aggregate full-business models, and user-level models for a customer view. The result is a holistic view with consistent data and incrementality, delivering a unified version of the truth.
This approach enables the marketer to identify and adapt to performance drivers, from marketplace changes to channel optimization. Unified Measurement can also add nuance by offering a clearer picture of how multiple factors interact and remove the biases inherent with siloed approaches.
Increase Your Company’s Adaptability
Unified Measurement enables marketers to uncover deeper understanding of their marketing and business. With this knowledge clients can adapt strategies that consider each step of a customer’s journey, as well as direct, indirect and environmental factor. Whether accounting for seasonal changes, consumer sentiment, media spend changes or anything that could contribute to the success of the business, being adaptive requires a unified approach.
A Unified Truth Drives Results
Unified Measurement techniques can help you:
- Make better data-driven budget decisions: Take the guesswork out of spending allocations
- Increase accuracy and confidence: With a holistic view with consistent data you can develop strategies to drive better results
- Adapt to fluctuations: You can’t control everything. Unified Measurement helps you understand everything affecting your business from the weather to the business climate.
Adaptive – Every Business is Different
Unified Measurement is an adaptive solution, and can look different based on goals, data availability. Three example use cases from our own experience demonstrate the point:
|USE CASE 1||USE CASE 2||USE CASE 3|
|Industry||Retail||Financial Services||Consumer Goods|
|Business Goal||Drive topline sales||Drive customer acquisition and retention||Grow the stagnant category, improve branding and market share|
|Data||Robust store selling data, limited customer and e-Commerce data||Robust customer level data, integrated online & offline activity and sales||Syndicated sales data, household panel, brand equity, in –depth capture of online & offline marketing|
|Key Performance Indicators||Daily & seasonal sales particularly in season||New customer acquisition, churn rate||Category growth, market share, Brand Equity|
|Adaptive Solution||Mix with MTA: Marketing Mix for holistic business view, MTA for digital deep dive (given data limitations focused on website store locator visits)||Integrated Mix & MTA: Integrated Marketing Mix and MTA for new acquisitions, Independent Churn Model, Customer Journey Analysis||Segmentation, Mix with MTA: Buyer segmentation, cross-brand Marketing Mix, Econometric model for brand equity, MTA for digital deep dive|
|Results||34% ROI improvement on $83 million in marketing spend||+12% in new customers, 5% reduction in churn rate||Identified segments & marketing to spur category growth, initial results show positive momentum|
While all the above cases leverage econometric and probabilistic models as well as experimental design for in-market validation and optimization algorithms, the choice and mixture of these techniques are adapted to best meet the business goals.
Every company is different and has its own challenges. What works for one business will not necessarily work for another. The rapidly changing and multi-touch world of marketing meeting outside competitive, economic and market forces necessitates a robust and adaptive solution – to address both the challenges of today’s marketplace and the unknowns of tomorrow.