When it comes to processing data and generating algorithms, machines are faster and more efficient than humans. As machine learning tools become more prevalent, digital agencies may find themselves attempting to directly compete against machine learning power by hand.
Rather than going head-on with machine learning, it’s better to find ways to use it to your agency’s advantage. Machine learning is a programming tool designed to create complex algorithms outside the scope of normal human capacity. This frees the humans involved to focus on creative interpretations and solutions, rather than worrying about crunching the numbers on advanced algorithms.
In this article, you’ll first learn a little about what machine learning actually is. Then we’ll show you how your agency can use this technology to avoid directly competing against machines in the future. Let’s get started!
What is machine learning?
Machine learning examines existing data, and identifies algorithms to make predictions and decisions using new, similar data in the future. For example, Google Search uses machine learning to identify user behaviors that indicate certain links are more valuable than others.
While these types of algorithms are possible for humans to create with relatively simple data, machine learning takes it to the next level. Since the computations are run by machines, it is possible to analyze and create algorithms for huge amounts of data and influential variables.
To elaborate on our Google example, a search engine can observe sequential searches to better refine the most recently requested results. This allows for contextual searching, where the search engine teaches itself based on searches rather than needing to be explicitly given an answer for every situation. For instance, a user might search for “the first president of the united states,” followed by “what was his birthday.” From these two pieces of data, Google can automatically make an educated guess that the searcher wants to know George Washington’s birthday.
The key here is that machine learning allows the search engine to observe successful searches in the past, and better predict what users are searching for in the future without direct developer intervention. Of course, this is just one of many examples of machine learning in action. This technology is growing increasingly popular in the mainstream, as its advantages become more clear and the tools required become increasingly accessible.
Avoid directly competing with machines
Since digital services revolve around the use of data, they offer the perfect opportunity to use machine learning. In fact, many digital agencies may soon find that competitors are offering better services at lower prices, all thanks to machine learning.
Fortunately, your digital agency can start using machine learning on its own, instead of attempting to go head-to-head with these new, automated services using old-fashioned systems. Here’s how you can begin this process today.
1. Understand the benefits of machine learning
Machine learning is becoming invaluable to digital agencies, as it enables automated, deep personalization within existing services. Plus, it can open the doors to brand new business opportunities!
Automation, particularly automated personalization, can save a company a lot of manpower while still improving its output. This allows the business to focus on more creative solutions for clients, delivering higher-quality work customized for each situation and based on quantifiable data.
To take advantage of this technology in your own agency, you’ll need to scrutinize your services. Look for places where your data processing follows patterns that could be predicted, and where personalization could improve a product or service’s output. After all, machine learning can process and interpret data at a deeper level than a human team can. If you want to benefit from this fact, you’ll need to find ways that machine learning frees up resources and adds value where it would be impractical for a human to do the same.
2. Become familiar with machine learning tools
Machine learning can be difficult to understand when you are new to the concept. To better grasp how it can be useful to your agency, it’s a smart idea to study examples of machine learning that are already in use.
Google Search, Facebook’s News Feed, and Netflix’s recommendation engine are all strong examples of machine learning. Google uses the technology to create algorithms that return highly accurate, quality search results. Facebook, on the other hand, uses it to create a custom news feed based on who you follow, your interests, and your past comments, likes, and shares. Finally, Netflix is constantly adjusting its recommendations based on users’ viewing habits.
These may sound like unremarkable elements at first, but each is at the core of the corresponding business’ strategy and is the foundation for its future success. Since the incoming data received by these types of companies is always changing, they need to have the necessary tools to adapt to new feedback in real-time and stay competitive.
If you want to do the same within your own agency, spend some time finding more companies who use machine learning, and study how the technology impacts their businesses. If you’re interested in the technical aspects, you can learn more by following popular machine learning publications put out by the likes of Google and Facebook. If you prefer strategy, blogs like ours are your best bet.
Otherwise, keep your eye on the news and research every use of machine learning you can find. The more you learn, the easier it will be to understand how to design your own system – one that will be invaluable for simplifying internal processes and creating new, stronger services for clients.
3. Think creatively with data
Data, and lots of it, is critical for successful machine learning programs. Machine learning relies on having data to analyze, interpret, and apply to create algorithms that make sense of incoming data. For example, Google Search fields 3.5 billion searches daily, while Facebook sees 4.75 billion pieces of content shared every day. Netflix is constantly helping its users binge watch their new favorite show, and identifying why they chose each one.
All of these services started out as something much simpler. Google was a directory of links, Facebook was a way to share short statuses, and Netflix delivered DVDs on demand. However, by collecting and analyzing user data, they were all able to create entirely new products that catered to each of their users’ needs. Without the ability to track and use the data available to them, these companies could never have built the powerful machine learning tools that helped them become so successful today.
If you plan to apply machine learning to your agency’s services, you will need to have a lot of data on hand. Start with the data your agency already collects, such as traffic analytics and customer surveys. Then take a look at that information, and brainstorm with your team the types of questions you might be able to answer using it. That’s the core of machine learning. If you find there are pieces of data missing that would help you to better answer the important questions, it’s time to begin collecting that data for the future.
Use machine learning to your advantage
If not taken into consideration, machine learning is likely to become a direct competitor for digital agencies. Rather than being intimidated by this possibility, digital agencies can use machine learning to their advantage and focus on the new creative challenges it presents.
You can discover how to use machine learning within your own agency in three ways:
- Understand the function of machine learning, in order to properly introduce it within your agency.
- Become familiar with examples of existing machine learning technology, so you can better imagine its potential applications.
- Think creatively with data, and begin collecting any relevant information that can be used for future machine learning projects.