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Deep Learning Technology: How It Applies to Marketing

You’ve probably heard a lot about deep learning for marketing, but do you really understand the stuff? Brush up on the basics in this quick intro.

July 17, 2023 by Gaea Vilage
Deep Learning Technology: How It Applies to Marketing

Whether you realize it or not, you’re already using deep learning technology. It’s what allows smart speakers to understand human speech—and produce a lifelike facsimile of that speech. It helps Google’s search algorithm rank your web pages. It decides where your online ads show, and manages the bidding war that selects them.

In short, deep learning for marketing is already indispensable. But what is it, exactly? More importantly, how can you leverage this emerging tech to keep your sales funnel full to the brim? Keep reading to find out.

A Brief Introduction to Deep Learning for Marketers

To explain deep learning, we have to define a few related terms:

  • Artificial intelligence (AI) is a machine’s ability to think like a person, comprehending and/or responding to novel situations based on past experience.
  • Machine learning is one way to achieve AI. It involves training algorithms to categorize new data by exposing them to large existing datasets.
  • A deep neural network is machine-learning software that mimics the action of the human brain by passing data through a decentralized web of processors. Deep neural networks include an input layer, one or more “hidden” processing layers, and an output layer.

Deep learning, then, is a type of machine learning that uses deep neural networks to produce a narrow form of artificial intelligence. This is the computing power behind language translation software, facial recognition technology, driverless vehicles, voice assistants, and even the text-to-speech (TTS) voices that emerge from our smart speakers. Given its ability to automate tasks that used to require human intelligence, it’s no wonder that deep learning has become an essential tool for marketers.

Marketing, Deep Learning, & How They Intersect

Deep learning doesn’t just allow computers to do things that used to take a highly trained human. It also creates more lifelike interactions with digital systems. Here are a few ways these abilities can further your marketing efforts.

1. Personalized Messaging

Deep learning systems can analyze oceans of unstructured data about your customers—who they are, what they like, when they make purchases. That allows you to segment your audiences to the level of the individual, a marketing trend called “hyper-personalization.” When Netflix learns your Friday-night viewing habits and serves up content suggestions you actually appreciate, that’s hyper-personalization. If you have a system that predicts which offers to send to which customers at which times, there’s probably deep learning behind that analytics software.

2. Automated Customer Service

Customer experience is a crucial element of your overall marketing plan (some would argue it’s most important!) But maintaining an army of customer service specialists can quickly become cost-prohibitive. Deep learning allows you to deploy smart assistants, AI chatbots, and conversational interactive voice response (IVR) systems—call centers without the dreaded menus. These smart systems can solve customer problems 24/7, and it’s all thanks to deep learning technology.

3. Pay-Per-Click (PPC) Advertising

Deep learning advertising services—most famously from Facebook and Google—decide where to place online ads for the greatest user response. In fact, the whole PPC ecosystem is built on deep learning; the dominant business model for PPC ad exchanges relies on real-time bidding (RTB). This AI-powered technology uses data about websites and site visitors to determine the value of a given impression, auctioning it off to you (or a competitor with a higher bid!) in a split second.

4. Natural Language Understanding (NLU)

Remember those smart assistants and conversational IVR systems we mentioned? They use deep learning to understand natural human speech, allowing users to make a request in any number of ways. So instead of calling a traditional call center, your customer could ask a smart speaker to return a product. The voice assistant can instantly open your voice app and walk the customer through the return process, from making the request to downloading a shipping label. Deep learning and NLU allow software to recognize that “I’d like to make a return” and “Can I send my purchase back?” mean the same thing, so the burden of operation isn’t on the consumer.

5. Voice Branding

More than half of US adults own smart home devices or smart speakers. Nearly 30 percent of consumers surveyed said they’d prefer voice interaction with their mobile apps. In short, voice technology is trending upward. That creates a vital new channel for marketers. But in order to maintain brand consistency across voice platforms, you need a unique TTS voice that expresses your brand traits perfectly. Deep learning allows us to craft these lifelike TTS voices for brands and creators of all types.

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