The A to Z Of AI-Led Performance Management & OptimizationPyxis One
Performance management entails planning, execution, tracking, optimization, and analysis of a live campaign. To deliver a successful campaign, marketers need to consistently monitor several parameters and take appropriate actions to maximize ROI.Â
Not to forget, this monitor-and-act strategy has to be carried out across hundreds of campaigns. These actions could be on the campaign level, ad set level, or even on the ad level.Â
Generally, marketers perform campaign optimization manually 1-2 times a day, 3 times if the marketer is having a relatively light day. The reason for the lower frequency of optimization is because it requires an exhaustive analysis of funnel metrics for each targeting combination, creative, and campaign.Â
Marketers have to identify and analyze the reason for any underperforming ad set, and then come up with a strategy to overcome this inefficiency. Imagine doing this for hundreds of ad sets across multiple campaigns, each having its own targets and objectives. Phew, sounds impossible, right?Â
It is no surprise, then, that according to a Forrester research conducted in 2020, 57% of marketers are challenged with optimizing next-best-action marketing decisions.Â
How, then, can the optimization process itself be optimized?Â
An Efficient and Scalable Solution: AI-led Optimization
AI can work as a lifesaver for marketers. An answer to all their optimization-related questions that keep them perplexed 19 hours a day.Â
The Performance AI is an AI-led optimization system that can help marketers overcome their optimization-related challenges. The AI can generate media plans, monitor the funnel, optimize performance at a much quicker rate, and scale these operations. The Performance AI system optimizes 4 key efficiency factors. Each factor corresponds to a particular step in the campaign journey.Â
Planning is everything, it is the blueprint that maps whatâ€™s required for a campaign to hit and far supersede its targets. A realistic media plan that is based on historical data, competition, and market conditions is a foundation for building effective campaigns that contribute to the overall business plan.Â
The Performance AI system builds a predictive model of realistic campaign outcomes for different audience cohorts, for every channel. It recommends the optimal funnel metrics that can drive desired results at the lowest possible cost.Â
Precise targeting is one of the most important aspects of an effective campaign strategy. A highly optimized and monitored campaign is bound to fail if targeted at the wrong audience. Even a highly optimized AI-led campaign of baby products can prove fruitless if targeted at baby boomers.Â
Clearly knowing your target audience saves you thousands of dollars and precious time. Running a highly optimized campaign on the wrong set of audiences will only result in bad ROI. The need arises to constantly identify the right audience and update it regularly. This is where the audience efficiency kicks in.
Once the performance AI system has all the requisite data, it starts calibrating and identifying audience cohorts. Based on audience engagement, it provides feedback to the targeting AI which then modifies the audience. Targeting AI explores, evaluates, and exploits new audience segments thus including more potential customers.Â
Performance optimization is where the AI shines the brightest. To achieve maximum ROI, it constantly monitors and optimizes the funnel pulling in data from different sources including third-party analytics as well as the organizationâ€™s database. The AI monitors campaigns to ensure theyâ€™re on track with the media plan and meets the larger business objective. This is also carried out at an audience and creative level to optimize both of them based on scenarios.Â
This constant monitoring enables the system to exploit opportunities, and activate stop-loss gating to ensure that the campaigns are always at peak efficiency. AI also takes appropriate decisions in real-time and on a very high scale.Â
Complete Optimization – Creative Improvements:Â
True optimization doesnâ€™t end with mere performance optimization. Once you start understanding the components that are working, the underperforming components must be enhanced. This is the true essence of optimization.Â
Creatives are a great way to deliver an ad message in an inventive way. A compelling creative can increase conversions significantly. Performance optimization highlights the most resonating creatives that are working among different cohorts. This works as a compass for design teams to understand the most popular layouts, themes, and design patterns. In simple terms, you know which creatives are working the best, and use this information to design similar creatives.Â
Exploration and Exploitation:
The Performance AI works in 2 phases – the exploration phase and the Exploitation phase.Â Â
Once the campaign is up and running, Performance AI continuously monitors the funnel including but not restricting toÂ CTR, LPVR, CPP,Â and CVR. It increases the confidence score of actions which helps AI optimize any one of the above metrics, at the same time, change actions on poor performance. Based on the metrics, it continues to find new audiences, creatives, and optimization strategies to achieve scale at the desired cost. This is called the exploration phase. In the framework of reinforcement learning, the AI comes to a point where it is confident about permutations of actions that can optimize the campaign.Â
In the exploitation phase, the algorithm has learned the set of actions required to increase metrics like- reach percentage, frequency, impressions, CTR, link clicks, spends, LPV, CVR, and many more. It also identifies the cohorts lying in the sweet spot. These are the cohorts that are most likely to convert. This helps AI to manage targeting, campaign structure, and churn creative recommendations to scale, stabilize and exploit these cohorts. In this way, the AI can identify and manage hundreds of targeted cohorts which enables scale and cost-efficiency.Â
To add more robustness in terms of data, AI also learns from previous campaigns.Â
Based on the performance of previous campaigns, it recommends the most relevant set of creatives and targeting strategies that can ensure the success of future campaigns. Apart from highlighting the creatives that are performing well, the algorithm also highlights the underperforming creatives that might need a revamp in its design.
Performance AI explores and discovers new audience segments that the campaign can be targeted towards. To consolidate more audience segments, the AI also combines audience segments that are reacting similarly to different ad sets, allowing a single ad set to exploit a larger more relevant audience base. Based on the performance and engagement scores, AI can track the factors that are responsible for an underperforming ad set or ad.Â
A Scalable & Efficient Solution – AI-led Optimization
Performance AI, continuously monitors and learns in both, active and passive ways. The information gained through these learnings refines the algorithms thereby improving its performance. In AI lingo, it is called Reinforcement Learning. This reinforcement learning model can unceasingly learn from actions taken in different contextual environments, and then train itself to understand the ideal action to be performed in a specific situation. The core learning acquired by the AI system would then demand what type of action should be taken.
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