Artificial intelligence technology is being employed across many industries in countless ways, and the agency world is no exception. Marketers and advertisers have been using AI and machine learning tools to automate and elevate campaigns for years now. As ML capabilities increase, so too do the applications for leveraging them to reach consumers.
Here, members of Forbes Agency Council share impactful ways agencies are leveraging ML advertising tools. Read on to learn about a variety of innovative ways agency pros are using ML to better reach consumers and attract more targeted audiences.
Members pictured from left to right.
Photos courtesy of the individual members.1. Pinpointing And Highlighting Marketing Opportunities
We leverage machine learning as our “data microscope” to pinpoint and highlight marketing opportunities. By analyzing the data of previous marketing responses and customers, you can obtain visible “sweet spots” to enhance your future marketing targets. The results are decreased ad-spend waste, increased engagements and optimization of the overall campaign budget. - Chris Gutierrez, LeadJig
2. Optimizing Across High Volumes Of Audience Segments
We use ML to optimize across high volumes of audience segments, beyond what I would or could assign to my team. Data is only as valuable as what you do with it, and it is important to structure your tests to provide you with the right, isolated findings. Leveraging machine learning in advertising is my favorite use of AI to maximize conversions—to reach the right audiences, at the right time, in the right location, with the right placement. - Jason Fishman, Digital Niche Agency (DNA)
3. Determining Baselines For Campaign Data And Success Metrics
Machine learning is key in advanced marketing analytics. First, you determine baselines for data and success metrics for a campaign with data scientists and analysts. Then, when the campaign is effectively running, machine learning can help take over data sets and support core marketing plans. - Jessica Hawthorne-Castro, Hawthorne LLC
4. Targeting Beyond Demographics And Behaviors
Machine learning is definitely useful for targeting; I’m talking about more than just demographic and behavioral settings. An algorithm has the capability to learn from your existing ad sets, targeting and segments to recommend related audiences that you can expand your campaign to. This helps to implement the funnel approach within advertising campaigns, strategically expanding their reach and making them a lot more effective. - Vanhishikha Bhargava, Contensify
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5. Curating Personalized Messages And Timed Touchpoints
Using machine learning tools to connect with customers and prospects is changing the landscape of marketing. As we collect more data, ML is using it to curate personalized messages and perfectly timed touchpoints. Leads are converting faster with less experimentation (read: fewer prospects are slipping through the cracks). - Marc Hardgrove, The HOTH
6. Tracking And Monitoring Ad Performance
Machine learning ad tools are valuable resources for tracking and monitoring your ad performance. This technology will regularly collect data about your ads to determine how well they are performing, and it will recommend that you pause and replace ads that have underperformed. This helps to ensure you are not wasting your advertising budget on efforts that are not driving traffic and conversions. - Adam Binder, Creative Click Media
7. Making Decisions About Content Creation
An extraordinarily innovative and impactful way agencies are leveraging AI and ML tools is for making decisions about content creation. There are some fantastic tools out there, such as Cortex.io and others, that help make data-driven decisions on what content to use, what content to create and what content will convert better. Instead of relying on humans, let the algorithms decide! - Krishan Arora, The Arora Project
8. Monitoring And Personalizing Emails
Email personalization is surging, but it is very time-consuming. Using machine learning to drive email monitoring—in combination with contact and business firmographic data—brands can save time and go beyond contact name and business name personalization to include content relevant to industry needs, adjust images or color schemes, or optimize subject lines and calls to action to increase conversions. - Paula Chiocchi, Outward Media, Inc.
9. Scaling Creative Testing, Optimization And Experimentation
ML is helpful for scaling creative testing, optimization and experimentation because it greatly improves the efficiency of media dollars spent. This is particularly true in search marketing. It’s about the creative, not the keywords. You’ll see this impact continue to grow. The platforms—especially Google—have made a lot of headway here. - Gyi Tsakalakis, AttorneySync & EPL Digital
10. Expediting Influencer Research And Eliminating Guesswork
When it comes to marketing campaigns, working with the right social media influencers is key. We use specialized tools that have machine learning capabilities to identify compatible influencers, detect fake followers and assess engagement rates on their profiles. This helps us expedite our research and eliminate the guesswork of finding the right partner. - Fernando Beltran, Identika LLC
11. Predicting Audience Impressions And Engagement
Machine learning can be leveraged to predict audience impressions and engagement more accurately than experts. For example, it’s traditionally been difficult to attribute outcomes for key performance indicators to product placement. By using AI, brands are now able to predict what programming is going to be successful even before it airs and move forward with authentic integrations of storytelling directly into content. - Ricky Ray Butler, BEN
12. Building Strategies, Initiatives And Solutions At Scale
As an agency, AI tools or platforms with machine learning capabilities enable us to build strategies, initiatives and solutions at scale. As technology, data and consumers evolve, we want the solutions that we provide for our clients to constantly adapt and be optimized along with them, and deep learning through AI and ML allows us to do that in a very efficient way. - Maria Orozova, MODintelechy
13. Providing Better Engagement, Personalization And Targeting Opportunities
Machine learning tools can help agencies better engage customers, personalize content and provide better targeting opportunities. We know that data is at the heart of implementing ad campaigns that reach the right audience at the right time. That is not to say that AI is flawless, nor that humans are obsolete. Automation drives progress, but it is just a tool that—in the right hands—can lead to success. - Nataliya Andreychuk, Viseven
14. Automating Scaling And UTM Tracking And Attribution
Machine learning advertising tools have pros and cons. Some massive wins in the space include automated scaling, UTM tracking and attribution, as well as tracking a customer’s entire buying journey. Machine learning has greatly impacted the automation and cleaning up of marketers’ day-to-day task lists; it’s a great tool to drive better results and save time. - Drew Urquhart, Banch Marketing
