Understanding Primer’s AiTD: the next evolution in digital adverting
Understanding Primer’s AiTD: the next evolution in digital adverting
Today’s programmatic advertising ecosystem is more fragmented than ever, causing inefficiencies from pre-campaign planning through to post-launch optimization and reporting.
The original purpose of programmatic ad tech was to allow advertisers to manage digital advertising campaigns at scale across inventory and publishers. However, as the number of platforms in the ecosystem grew, so did the fragmentation. DSPs and other platforms began limiting their owned inventory or data exclusively to their platform (known as walled-garden inventory/data), thereby increasing the complexities of managing campaigns across all the different systems, channels, and inventory sources.
Primer’s AiTD is designed to simplify the programmatic landscape by leveraging custom A.I./machine learning to deploy campaigns through our unique meta-DSP software, streamlining the execution, management, and optimization of digital advertising campaigns.
What is a DSP?
DSPs (demand-side platforms) originated as a system to simplify the programmatic landscape, allowing advertisers to purchase and manage ad inventory across various ad exchanges, networks, and supply-side platforms (SSPs) programmatically.
This amalgamation of technology, paired with the development of agency trading desks, created transaction efficiencies and enabled the advent of advanced audience targeting and digital measurement/attribution.
Key Features of Traditional DSPs:
- Programmatic ad buying
- Audience targeting and segmentation
- Real-time bidding (RTB)
- Campaign tracking and optimization
Over time, the segmentation of these DSPs created a divide, where walled-garden inventory and data were limited to specific platforms, reducing campaign reach and performance efficiencies. Agencies and advertisers increasingly required multiple DSPs, data sources, and measurement providers to ensure effective campaign execution.
What is a meta-DSP?
A meta-DSP is the next iteration of advertising technology, designed to aggregate multiple DSPs, buying platforms, and other advertising technologies into a centralized interface.
Unlike traditional DSPs, which are limited to one specific algorithm, a meta-DSP can optimize campaign performance toward the most efficient channels and inventory. To maximize campaign reach and performance, a meta-DSP has access to activate campaigns across the walled-garden inventories of various DSPs, as well as test head-to-head performance of various tactics, channels, and KPIs across DSPs via cumulative automated reporting.
How meta-DSPs work
Aggregating multiple DSPs: A meta-DSP connects to various DSPs and ad exchanges via APIs (application programming interfaces). By pooling data from multiple platforms, it provides a comprehensive view of ad inventory and audience data.
Data integration and optimization: The meta-DSP takes in large volumes of data from different ad sources, analyzing more than traditional impressions, clicks, conversions, and engagement metrics. By analyzing this data, the meta-DSP can recommend the best-performing channels, tactics, and inventory to allocate ad budgets for maximum ROI.
User Experience: Marketers typically interact with a meta-DSP through a user-friendly dashboard that consolidates all the relevant metrics, campaign settings, and insights throughout the ecosystem.
Evolution of an Artificial Intelligent Trading Desk (AiTD)
Primer developed a revolutionary AiTD platform using global-first API connections to various DSPs and ad tech software. This meta-DSP is powered by our proprietary A.I. trading model, which simplifies the setup, deployment, management, and optimization of digital advertising campaigns.
The A.I. machine model is powered by years of historical managed-media campaigns that ran across DSPs, channels, inventory, and KPIs. This model is customizable and designed to learn and adjust to manual optimizations and individual agency best practices, thereby helping amplify the unique approach each agency takes to programmatic campaign management.
Key benefits of AiTD
Cross-platform integration: AiTD provides the ability to seamlessly integrate with multiple DSPs and advertising networks, giving advertisers access to the widest range of ad inventory and data. This integration of data can improve campaign efficiency, enabling advertisers to optimize bids, target more precisely, and reduce wasteful ad spend.
Consolidated reporting, analytics, and billing: Instead of logging into multiple DSPs to pull performance data, a meta-DSP offers consolidated reporting, making it easier for marketers to track KPIs, measure success across channels, and adjust strategies in real time.
AI-enhanced campaign management: Using years of historical performance data, our AI enhances campaign planning to ensure campaigns are set up to support the specific audience, objectives, and inventory requirements. Our AI-optimized recommendation engine ensures campaigns are actively managed towards multiple KPIs and success metrics.
Improved efficiency and performance: Primer’s AiTD leverages data from multiple sources to offer more robust audience targeting. This integration of data can improve campaign efficiency, enabling advertisers to optimize bids, target more precisely, and reduce wasteful ad spend.
AiTD vs traditional DSP
Scope and reach: Traditional DSPs typically focus on specific channels (e.g., display, social, or search), whereas a meta-DSP brings together a broader range of media types and platforms, offering a more holistic approach to digital advertising.
Complexity: Managing multiple DSPs can be challenging for large brands with campaigns running across various digital touchpoints. Meta-DSPs solve this problem by acting as an umbrella solution to streamline operations and reduce the burden on advertising teams.
Real-time optimization: Traditional DSPs provide real-time bidding and optimization within a single ecosystem, but a meta-DSP takes this a step further by enabling cross-platform optimization, leading to more efficient ad spend allocation, while still supporting multiple objectives.
Use cases and examples of AiTD
Example 1:
Cross-channel campaigns: A brand running a media channel mix of display, video (OLV), CTV, and audio can use AiTD to centralize and manage this campaign in one place. The brand can optimize its budgets, bids, and targeting strategies across multiple KPIs simultaneously.
Example 2:
Split DSP testing: A brand looking to see which DSP and ad exchanges are most effective at driving return-on-ad-spend (ROAS) while balancing inventory spend commitments. AiTD allows the brand to test which DSP is more effective at running specific inventory deals (e.g., PMP/PG) while supporting a primary KPI, and still allows additional DSPs to be added seamlessly for further testing.
Challenges and considerations
Unified tracking and measurement: For AiTD to effectively measure performance across various DSPs and self-serve tools, it must also leverage an ad server. The ad server reports (in addition to DSP reporting) provides a single source of truth on deduplicated conversions (via various attribution models) and holistic reporting for metrics like reach and frequency.
Integration with existing tech stack: AiTD has been developed to integrate with existing tech stacks, offering a customizable experience that works with different DSP seats, inventory deals, and flexible reporting outputs to integrate with existing reporting tools.
Cost and complexity: While meta-DSPs offer a wealth of capabilities, their complexity might require additional training and support to leverage their full potential. With AiTD, we leverage AI-trained machine models to assist in campaign creation and management, thereby simplifying the tool and maximizing efficiencies.
Conclusion
AiTD represents the next evolution in digital advertising, offering advertisers a powerful tool to manage, optimize, and scale campaigns across a wide range of channels and platforms. By simplifying the ad tech landscape and centralizing campaign management, it provides both efficiency and effectiveness.
As digital advertising continues to evolve, marketers must stay ahead of the curve. Exploring AiTD could be a game-changer for those looking to enhance their ad strategies by ensuring AI is at the forefront of planning, programmatic execution, and optimization.
