If you’ve been reading up on the latest advances in marketing technology, or any technology for that matter, you’ve likely seen the following terms quite frequently:
- Machine Learning
- Artificial Intelligence
But do you know the differences between them? And more importantly, do you know how these technologies can help improve the performance of your marketing?
I think the best way to understand these terms is not just rely solely on their technical definitions but also look at use cases for them in your marketing.
Intelligence in Technology
Intelligence in technology is essentially applying solutions to known, repetitive problems based on data that’s structured and easy-to-model to reduce manual work.
Imagine you’re a marketer for a fictitious company named Digital Phone Network (DPN), a leader in telecommunications with over 25 million customers. DPN just launched a new smartphone on its network but then discovered a mistake in the activation guide and wants customers who contact support to quickly get the latest instructions to fix it.
To accomplish this, the company sets up an automated chat support tool with a goal of resolving 90% of cases using logical workflows and communicating content that’s likely to lead to successful case closure.
This Intelligence in Technology solution is possible because the chat support software is integrated with a central digital asset management solution, so DPN customer service reps can easily update all related chat workflows then swap assets to facilitate the automated solution. Yet to the customer, the support experience seemingly feels like talking to a real human.
Machine Learning at its most basic is when advanced data analytics practitioners use algorithms (e.g., specialized math models created to evolve and adapt in a way that they become more accurate the more they’re used) to take in data, calculate an outcome, and then determine the most logical next step.
Now let’s step back to before DPN launched this marketing campaign and evaluate the launch preparation. DPN is an enterprise company with a large marketing team that handles huge amounts of content creation needs for its global launches. This company does thousands of projects every year.
Rather than hire lots of project managers, DPN has an advanced marketing operations solution that uses machine learning to route projects to the right resources based on range of different attributes including expected skills needed, availability or resources or teams given other project requests, and the actual performance metrics of the pieces in market. The key here is that the more data that comes in about marketing results, the ability of resources to deliver on-time given existing tasks, or other parameters, the more the model can better route projects to the appropriate resources.
Building on the machine learning concept above, Artificial Intelligence (AI) is the higher level, broader category that seeks to enable machines to do critical thinking that is normally done manually. An easy way to think about this is by going step by step through some of your more tactical day-to-day tasks and then imagine a computer doing those exact steps but to perfection every time and without getting distracted or tired.
To maximize the investment of all its marketing projects, DPN uses AI to automatically tag, or categorize, each individual piece of its content. DPN’s AI solution is able to look at virtually any type of content (pictures, video, etc.) and automatically tag it with various unique identifiers much more quickly than a team of humans ever could and with greater accuracy.
The tags then feed the search capability of DPN’s digital asset management system. This has the dual outcome of enabling DPN to better manage new request costs while also improving the findability and re-use of existing assets.
These are just a few examples of how Machine Learning, AI and Intelligence can help improve your marketing activities.
Interested in learning more? Watch our on demand webinar, “Optimizing AI for Marketing” What’s the future and what’s just hype?” to learn real-life case studies where AI is driving meaningful business impact and how you can take advantage of this emerging technology.