Artificial intelligence (AI) is a force multiplier, allowing organizations to do more with less. Northbeam was founded with AI baked into its DNA; its team of in-house academics and AI experts built Northbeam to wield the power of machine learning, attribution modeling, and statistical analysis to help marketers achieve their most ambitious goals.
By using Northbeam as your marketing team's source of truth, you're not only using AI by extension - you're making AI the backbone of your marketing processes.
So, how exactly does Northbeam use AI?
Let’s differentiate between different types of AI.
AI is an umbrella term that refers to the ability of a computer to think, act, and/or learn like a human. AI has many different applications, like machine learning (ML), generative AI, natural language processing (NLP), and large language models (LLMs) to name a few.
ML is a form of AI that learns over time and is able to use algorithms trained on data to create new models — even new AIs! — to perform a variety of complex tasks. It is the powerhouse of AI applications. Using a strong ML model is like putting a supercharged engine in your car, whereas generative AI is more akin to giving your car a fancy paint job.
Northbeam uses ML to analyze trillions of data points and come to conclusions about your performance with a superhuman degree of speed and accuracy. Its ML models are built to deliver next generation ad attribution and forecasting so you can make the best decisions possible.
Marketing attribution is the process of measuring and quantifying the individual impact of all of your campaigns on a desired outcome. If your desired outcome is a completed checkout, attribution helps you understand the effect of every activity a customer did before they finished their purchase. If your desired outcome is lead generation, proper attribution can show you which campaigns contributed to a lead ultimately converting on your website.
If you can get attribution right — if you can understand the exact impact of each touch on the buyer’s journey — then you can get your budgeting and spend right. The simple truth is that if you don’t know how your campaigns are performing and contributing to your bottom line, you can’t truly optimize your spend.
Northbeam’s proprietary ML models do the dirty work of attribution for you. They analyze first party data across thousands of parameters and assign a percentage attribution to each campaign or touch along a buyer’s journey.
Because Northbeam feeds its models with direct first party data, they are not susceptible to reporting bugs or changes in privacy settings.
“Our technology is very resilient to the current privacy landscape and we’ve built out offerings like MMM+ that are future-proof,” said Josh Rad, Principal Technical Product Manager at Northbeam.
“We don’t rely on third party cookies or tracking, which makes me confident in the quality, accuracy, and compliance of the data that comes into our system,” said Dan Huang, Chief Technology Officer at Northbeam.
Northbeam doesn’t look at activity in a vacuum. Its models combine data across platforms and channels to present a unified picture of your ad attribution so you can make informed spending decisions with the help of powerful AI.
“If you look at click-through data on other platforms, you see lots of purchases and only one touchpoint — you know in most cases the person did not simply type in the name of the website to make a purchase," Huang said.
"We use probabilistic machine learning models to predict and infer where that purchase actually came from based on each brand’s own historical data and performance."
“It’s a very customized model based on the brand’s true customer data,” Josh said. “Our machine learning is reducing the amount of traffic that other platforms or tools will say is direct, but actually isn’t.”
You heard them: Northbeam's machine learning fills in the naturally-occurring gaps you see in other ad attribution datasets.
Super-accurate ad attribution is already a boon, but what if you could forecast how different channels would continue to perform in the future? ML is especially suited for this type of task: intaking trillions of data points and using them to model or predict future impact.
“We can forecast your attribution windows based on your historical information,” Huang said. “A click today might generate revenue in the next thirty days, right? And that is valuable information if you want to know how your campaigns are performing now or will continue to perform in the future without actually having to wait thirty days to get that data.”
Northbeam’s ML can go beyond real-time to deliver dynamic forecasting at your fingertips. You can run simulations on the Northbeam platform and see how channels would perform at different spending levels. This lets you predict when diminishing returns may occur and optimize your ad spend for maximum ROI.
The best part is that Northbeam’s ML gets better over time: a hallmark of strong AI. As it learns your unique data and channel performance, its predictions and attributions become more fine-tuned, delivering more and more value with each use.
“No one can give you 100% ground truth. If someone tells you they can, they’re being misleading. We intentionally don’t train our model on your entire historical dataset because we want to validate and see if we can match the non-trained historical data. This tests the performance of our methodology, and our accuracy against ground truth,” Huang said. “This is called ‘backtesting.’”
But perhaps the actual best part is that you don’t need to be an AI expert like Dan or Josh to use Northbeam. Its platform’s backend is built on a foundation of industry-leading AI and its frontend is built with you in mind, so anyone on your team can get instant value with ease.