What is Deep Learning & Marketing Technology? Definition, How It Works, Best Practices, and Benefits of Deep Learning & Marketing Technology

Definition of Deep Learning & Marketing Technology

Deep learning refers to the algorithm-based machine learning techniques that are used to process data. The inspiration for deep learning comes from the human brain which is comprised of neural networks. Deep learning technology uses multiple layers – just like the neural networks in our brain – between input and output to model high level extractions in data.

Put simply, deep learning is about getting software to do what our brains do naturally. Deep learning technology is highly effective at dealing with large volumes of data making it extremely attractive to companies to day – who use vast amounts of data.

Marketing technology is the set of tools and software solutions used by marketing and sales people to do their jobs. The traditionally separate areas on deep learning and marketing technology have become somewhat intertwined recently as artificial intelligence tools that leverage deep learning techniques have become one of the hottest topics in marketing today. Be it customer lists, customer call data, competitive intelligence, social media activity, website visitor information, or the lead database, marketers are inundated with data. As a result, deep learning and marketing technology solutions can be hugely beneficial to companies who are trying to make sense of all the data they are faced with.

How Does Deep Learning & Marketing Technology Work?

Data is the biggest asset companies have. The problem is figuring out the best way to use this data. To put the sheer volume of data into perspective, it is worth remembering a quote from former Google CEO Eric Schmidt who explained that every two days we now create as much information as we did from the dawn of civilization up until 2003.

Deep learning and marketing technology can help companies find insights within their data. It is no longer humanly possible for any data scientist to manually work through the various data points and sources used in the modern organization. Instead, deep learning and marketing technology hold the key and companies are incorporating these technologies into their sales and marketing organizations. Research has shown that 44% of B2C marketing teams are now using big data analytics to drive productivity – and with a number of free data analytics courses on the web, there’s no excuse not to learn how to leverage big data.

Examples of Deep Learning & Marketing Technology

One obvious example of how deep learning and marketing technology can be used is in call centers. Call centers are at the very forefront of the customer relationship. Call conversation data contains really important information on customer needs not to mention added insights like competitive intelligence, industry pain points, and solution use case examples.

However, with larger companies making thousands of calls every week, it is not really feasible to apply any manual techniques here to glean insights. One deep learning and marketing technology solution that can add a lot of value here is interaction analytics. By combining recorded call data with interaction analytics, you get 100% call coverage as well as identifying key conversation patterns and phrases associated with successful calls. By pinpointing key trends in your call center data, you can learn more about both your customers and your own agents.

Once you know which behaviors and phrases are leading to successful outcomes, you can start to leverage these best practices, as well as insights from the experts, and share around your organization. It might be to help your underperforming agents get up to the level of your top performers or you might want to share the messaging proven to work with your marketing team as they look to hone their materials.

Benefits of Deep Learning & Marketing Technology

There is a range of benefits associated with deep learning and marketing technology.

  • Scalable: Deep learning solutions can be exposed to terabytes of data and essentially teach themselves the correct outcomes. Older technologies such as those reliant on rule-based logic would not be able to scale with the volume of data companies create and leverage today.
  • Pattern Recognition: Deep learning is highly effective at recognizing patterns within datasets. In doing so, deep learning and marketing technology tools can highlight key business insights separating the signal from the noise. As we have shown with the call center example above, deep learning solutions are able to highlight patterns within the data like keywords and phrases used to bring the call to a successful outcome.
  • Create a More Targeted Customer Experience: By highlighting key customer needs, deep learning and marketing technology solutions can help you deliver a more targeted customer experience.
  • Quickly Resolve Customer Pain Points: Deep learning tools provide you with valuable insights into customer pain points allowing you to develop a swift response. One example might be that your competitors had launched a campaign targeting a lot of your customers. By analyzing 100% of your calls and measuring interaction analytics, you would quickly become aware of the issue and have time to launch a counter measure.

Further Reading on Deep Learning & Marketing Technology
A Beginner’s Guide to Deep Learning and Artificial Intelligence for Marketers
What Marketers Need to Know About Deep Learning and Google
How artificial intelligence will revolutionise marketers’ lives