CommerceIQ proudly introduces its enhanced Retail Media Management (RMM) platform with a flexible goal-based optimization that uses Rules and AI to enhance e-commerce advertising management with precision and efficiency.
Why is AI Goal Optimizer Needed?
The need for robust ad optimization tools arises as brands have different objectives ranging from Share of Voice (SoV) , advertising performance focused Return on Ad Spend (RoAS) to Incremental Return on Ad Spend (iRoAS) and Net New Sales for different product lines and business.
Setting, managing and seamlessly optimizing goals across retailers and category levels is a challenging task as majority of retailer advertising platforms either do not provide this capability or they provide it in a limited version.
Creating and maintaining a rule-based optimization system is a complex process as even for a mid-size advertising account with a single goal one needs to define multiple rules for a combination of different brands, sub-brands, product lines, campaign types and targeting types. Further more, as metrics evolve over time, these rules become outdated pretty quickly and need regular updates to be incorporated.
Lastly, most of the optimization capabilities of retailer platforms and tools are focused on driving Return on Ad Spend (RoAS) and that often leads to cannibalization of organic sales by investing ad dollars on high traffic branded keywords or keywords with high organic presence as this does not affect overall sales and profitability of the business. Customers seek for a solution that drives overall incrementality and growth with the same ad spend.
How CommerceIQ’s AI Goal Optimizer solves this?
Completely customizable goal setup, tracking and optimization
The platform offers a flexible methodology to create budgets through retailer categorization or internal categorization (including campaign taxonomy) enabling users to define varying goals for different product lines, digital shelves, campaigns and optimize these.
Users can also select a combination of 2 categorizations to allocate budgets and goals and create reports on them.
Dual Modes Optimization: AI-Driven or Rule-Based Optimization
CIQ's AI Goal Optimizer combines AI-Driven Algorithmic Optimization with Rule-Based Optimization for users to get the best outcomes.
CIQ's AI Goal Optimizer continuously optimizes bids and budgets across thousands of keywords and campaigns using custom built ML models tailored for your advertising account.
Furthermore, for customers who prefer greater control, its 1-click campaign optimization rule setup with auto-refresh capabilities sets up carefully curated and customized optimization rules for each brands, sub-brands, product lines, campaign types and targeting types within minutes and provides scale to execute millions of automated actions every day.
These rules are refreshed automatically and do not require any user input once defined.
Users can use both systems, bringing focus and better control for critical product lines thus enabling efficient and effective optimization for rest of the business.
Harmonizing Conflicting Systems for Operational Efficiency
Working with multiple systems simultaneously like; rule-based automations, day parting, and algorithmic optimizations often lead to operational inefficiencies.
AI Goal Optimizer harmonizes these conflicting systems, providing a cohesive and streamlined approach to advertising.
Comprehensive Reporting and Insights
The platform acts as a single source of truth across sales, digital shelf, advertising, supply chain and market share for multiple retail channels.
Once the setup is finished, users can track their budget pacing from our reporting widgets, curated to help track the pacing and performance against the defined goals.
With our proactive alerting mechanisms in place, customers are alerted of any deviations from their set plan through a series of notifications, thus helping them act with the right actions as required.