Automation is a gamechanger in marketing — and we don’t use that word lightly. Well-crafted automation strategies accelerate processes, improve productivity and reduce costs. In real terms, automated marketing tactics translate to more leads, more conversions and more revenue.
Machine learning algorithms, which adapt and improve processes without the need for human input, take automation one step further. In simple terms, automated machine learning is the code-based equivalent of an autonomous vehicle. You prime your algorithm with input — ‘fuel’ and a ‘destination’, so to speak — and off it goes. Like GPS, AI predicts the most efficient way to get to a given destination.
Imagine if customer data platforms came with built-in machine learning algorithms. Even better: imagine if all customer journeys were honed to perfection via AI. Wouldn’t that be great?
We think so. That’s why we’re building our AI functionality for customer journeys.
Recently, we spoke with our resident machine learning expert, Karlo Sarin, and product manager Petra Bakker, to learn more about how the AI module will work, and why the module will be such an important addition to the Relay42 platform. In this article, we share the first part of the interview.
“Automated machine learning is no-code, no-data scientist machine learning model development, ” says Karlo Sarin, Machine Learning Engineer at Relay42.
Machine learning model development is expensive because machine learning models are difficult and tedious to build. Manual data analysis can take months; testing can push the timescale out even further, and not all ML models work outside the lab. Some don’t even work in the lab.
“At the beginning of the project, nobody knows if the ML model will be successful or not,” says Karlo, “because it can only be as good as the data you put into it. Failure is a completely valid academic output, so companies have to be prepared to spend a lot of resources and a lot of time on an unknown outcome.”
Automated machine learning, or AutoML, automates the machine learning development process. In practical terms, you tell your AutoML program what you want to predict, and the AutoML program generates a machine learning model for you. No coding, no data scientists.
With AutoML, the stakes are much lower. AutoML is much less expensive than human-led development, so when models don’t function as expected, they can be rewritten quickly and cost-effectively. Companies don’t need to have giant development budgets to take advantage of AutoML.
Customer data platforms (CDPs) like Relay42 eliminate data silos and help marketers create unique customer journeys, which guide consumers through the sales process. The better the data, the more effective the journey.
Without machine learning, marketers have to create and update customer journeys manually. They have to make educated guesses about which ads will be most effective for specific audiences, and they have to replace ads that don’t perform well with marketing messages that do. Meticulous journeys require a lot of human input and can be resource-intensive in the long term.
If they don’t have access to AutoML, marketers interested in implementing AI solutions have to create their own machine learning models. Most marketers don’t have the coding knowledge to create AI models by themselves, so they hire development teams. Model development is a lengthy process, and some models don’t perform well in the real world.
“We’re building the AI module to empower marketing teams. This module is easy to use and allows marketers to build their own AI-driven customer journeys,” says Petra.
You don’t have to know any code to use it, and you won’t have to invest any money in long-term development. Building a real-time customer journey with the Relay42 AI module is as simple as building a Lego model.
We genuinely believe that our new AI module will change the way you orchestrate journeys for the better. Get in touch to get a sneak peek at AI features, and to learn how Relay42 can help you take customer journey orchestration to the next level.