Beam.City Inc. is a unified advertising automation platform that uses artificial intelligence to help companies improve paid ad performance on the top social media networks, all in one simple interface.
The company promises increased ad performance using automatic learning and can save users hundreds of hours usually spent on research and labor and maximize ROI. Sounds pretty cool, right?
We spoke with Beam.City’s Founder and CEO Zeze Peters to learn more about how this solution uses AI in advertising.
In a single sentence or statement, describe your company.
AI meets Mailchimp for ads. Beam.City helps clients affordably and quickly acquire customers with AI-powered ads on millions of sites.
How does your company use artificial intelligence in its products?
We use AI to do automatic ads setup, monitoring, learning and optimization pattern recognition. We also use AI to create predictive datasets for targeting personas based on where they live and work in Canada and the US.
What are the primary marketing use cases for your AI-powered solutions?
We help clients attract customers affordably and quickly with brand ads, transactional ads, app installs, website visits and surveys.
What makes your AI-powered solution smarter than traditional approaches and products?
Beam.City automatically cuts out most setup, all monitoring and all optimization tasks completely for multiple ad networks. Our solution also learns about who ideal customers are at the location level down to the zip code. Our platform also has statistical insights you cannot get natively from Google, Facebook or any other platform.
Are there any minimum requirements for marketers to get value out of your AI-powered technology? (e.g. data, list size, etc.)
No. The platform can automatically learn or users can import and improve their results within days.
Who are your ideal customers in terms of company size and industries?
Consumer electronics and tech companies.
What do you see as the limitations of AI as it exists today?
Most applications use the wrong combination of AI and statistics to solve problems, creating huge data fragility issues and a low to moderate level of accuracy. The accuracy you see depends on the data models used and most architects are no good at data architecture.
What do you see as the future potential of AI in marketing?
We will use AI to create pre-emptive ads that are triggered just before clients are ready to even conduct a search.
Any other thoughts on AI in marketing, or advice for marketers who are just starting with AI?
Marketers have to try different AI tools and they need to lean towards tools that give them serious performance improvements on most channels.
Paul Roetzer is founder and CEO of Marketing AI Institute. He is the author of Marketing Artificial Intelligence (Matt Holt Books, 2022) The Marketing Performance Blueprint (Wiley, 2014) and The Marketing Agency Blueprint (Wiley, 2012); and creator of the Marketing AI Conference (MAICON).