There are many ways Artificial Intelligence (“AI”) will automate media planning and media buying workflow. Here are 7 use cases with clear benefits that are possible with today’s AI.
AI is More Than ChatGPT
With the current popularity of ChatGPT, many first think of transformer-based large language models (LLMs) when they think of AI. This includes Open AI’s GPTs, Llama, Gemini, Claude, Cohere, Mistral, and other foundation models.
It’s important to remember there are many other forms of Artificial Intelligence. Just a glance at the Glasswing AI Palette gives you a good sense of the diversity. There are many tools in the AI toolbox. It’s important to pick the right tool for the right job.
With that in mind, let’s dive into seven opportunities for AI to automate media planning and media buying workflows.
1. Summarize into a Media Brief
Sometimes the lead up to the kickoff of an advertising campaign is messy.
A flurry of media concepts are discussed: goals, audience insights, market research, media mix, media sources, etc. These concepts may be scattered throughout emails, spreadsheets, presentations, videos, transcripts, and other documents.
When it’s time to kick off the media planning process, it’s important to distill all of this into a concise media brief to direct the efforts of the media team.
AI can summarize key points into a structured media brief. This can include trends, competitive analysis, and audience segmentation, with the AI generating a ready-to-use media brief for media planners.
Useful AI Tools:
- Large Language Models
- Natural Language Processing (NLP)
- Summarization algorithms
2. Create Media Strategy
Data is everywhere. With this over-abundance of data, it’s hard to glean insights and distill in into a strategy.
AI can create more precise, data-driven media strategies by analyzing historical campaign data, audience behavior, and current market conditions. This enables media strategies based on current trends, versus rehashing old strategies that may have become obsolete.
AI can help media planners identify the most effective channels, timing, and content for campaigns.
By processing vast amounts of past performance data, AI can predict which strategies are most likely to succeed in each context. This enables media planners to optimize budgets, reach, and frequency more effectively.
Useful AI Tools:
- Machine Learning (ML)
- Predictive Analytics
3. Source Media Placements
When considering ad placements for your media plan, there are dozens of media channels to choose from. Within each channel, there are virtually infinite placement options. But your budget is limited. How do you choose placements to get the biggest bang for your buck?
AI can streamline the process of identifying and selecting media placements. It can suggest the best publishers, platforms, or channels based on market behavior and past performance.
Using AI-driven platforms, media planners can input campaign goals and audience profiles, and the system will automatically recommend or even buy media placements that align with the campaign’s goals. AI can also dynamically adjust placements based on real-time performance data.
Useful AI Tools:
- Recommendation Engines
- Programmatic Advertising Algorithms
4. Optimize Pricing and Bidding
When buying advertising placements, you want to feel like you’re getting good value. You don’t want to get ripped off.
Because advertising is dynamic and highly negotiated, setting prices is a major challenge no matter how you do it. It’s a challenge when you are buying a batch of advertising the old way through an insertion order. It’s also a challenge when buying impressions one at a time through real-time bidding and programmatic advertising.
AI can significantly enhance the process of setting prices by making pricing decisions more dynamic, data-driven, and responsive to market conditions.
Useful AI Tools:
- Machine Learning for Predictive Analytics
- Reinforcement Learning
- Artificial Neural Networks
- Programmatic Advertising Algorithms
5. Automate Ad Ops
According to the 2024 Marketing Technology Landscape Supergraphic, there are 14,106 marketing technology (or “martech”) products available. It seems like this number will continue to expand. In fact, the 2024 landscape has 27.8% more products than 2023! 👀
When you get the green light to execute your media plan, the next step is to activate the placements on all the marketing and advertising technologies involved with your media plan. This is where advertising operations – or “Ad Ops” – enters the picture.
AI can be used to automate Ad Ops tasks such as ad trafficking, bid adjustments, A/B testing setup, and tracking pixels across platforms. It saves time and eliminates errors.
This allows ad ops teams to focus on higher-level strategic tasks rather than getting bogged down in repetitive, manual workflows.
Useful AI tools and related technologies:
- Application Programming Interfaces (APIs)
- Machine Learning
- Robotic Process Automation (RPA)
- Large Language Models enabled with Tool Calling
6. Automate Optimizations
Unlike traditional forms of broadcast advertising, digital advertising provides real-time performance data and the ability to adjust placements while in flight. This is a blessing for those looking to optimize their advertising. However, this can be a curse for those tasks with identifying and making these optimizations.
AI can continuously monitor campaign performance. It can recommend or automatically make optimizations, such as adjusting bids, reallocating budgets, or shifting creative elements to maximize performance.
This enables campaigns to constantly improve without requiring constant manual intervention.
Useful AI and related technologies:
- Real-Time Data Processing
- Machine Learning
- Programmatic Advertising Algorithms
7. Automate Reconciliations
One of the often overlooked, but most laborious tasks in media buying is vendor bill reconciliation. When you receive a bill from an advertising vendor, you can’t just pay it. As a steward of the media budget, you first need to reconcile the bill to ensure the vendor delivered as promised. There are many aspects to “as promised” – dates, quantities, prices, audiences, creative, etc.
AI tools can automatically pull data from unstructured invoices, ad servers, media plans, insertion orders, and other sources to reconcile invoices against actual campaign delivery.
Useful AI and related technologies:
- Optical Character Recognition (OCR)
- Large language models enabled with Structured Output
- Data Matching Algorithms
- Robotic Process Automation (RPA)
How to Prepare for AI Future
We are just scratching the surface of the possibilities for AI in media planning and media buying. There are many other applications possible with today’s technology. And there will be many more in the future.
The best way to prepare yourself is to:
- Get Smart – Learn about AI and the applications of AI. This can be as simple as watching YouTube videos or as elaborate as a degree or certification. Even a small amount of education will put you ahead of most of your peers.
- Clean Up Your Data – There’s an old saying in software, “garbage in, garbage out.” This is especially true with AI. In order to train your AI models the right way, You need a pipeline of good, clean data. Before you invest heavily in AI, you should invest in your data pipeline.
- Upgrade Your Technology Stack – One of the most powerful uses of AI will be intelligent agents who can analyze data, glean insights, make decisions, and take action. The last part of “take action” is contingent on the availability of APIs. If you’re operating on an archaic system hidden behind a firewall with limited ability to integrate with other systems, now is the time to review and upgrade your technology stack to an AI first stack.
Taking these steps will prepare you for an AI future. Nobody knows where AI will be five years from now. However, it’s clear that education, data, and technology will prepare you for this future no matter where it leads.
The post 7 Opportunities for AI in Media Planning and Media Buying first appeared on Bionic Advertising Systems.