The Age of Artificial Intelligence

Hummingbird CreativeTechnology

Marketing’s Use Of AI For A Better Customer Experience

When you hear the words “artificial intelligence”, do you think of Skynet or do you think of C3PO and R2D2 from Star Wars? While artificial intelligence isn’t quite what we’ve seen in SciFi films, it’s doing some pretty cool things for marketing.

What Exactly Is AI?

Artificial Intelligence, or AI, is a part of computer science that deals with building better, faster, more intelligent machines that can think– and respond– like people. Alan Turing developed the Turing test in 1950 as a way to test a machine’s ability to exhibit intelligent behavior. In this test, a human evaluator would judge how natural the conversations between a human and a machine sounded. The participants would be in separate rooms from each other and only the evaluator would know that one of them was a machine. The answers didn’t have to be correct, just human-like in nature. Part of what makes AI so intelligent is the proposed ability of machine learning. Think of the autocorrect on your phone. The more you type, the better it’s able to talk like you– it can start to learn that you’re actually talking about GDPR instead of trying to autocorrect to “grapes”. Specialized systems are in place to help artificial intelligence learn and improve with experience. Where artificial intelligence can really get freaky is when it gets into deep learning. This is a subset of the machine learning that’s comprised of an extremely large neural network, like a human brain, and a huge collection of algorithms that can mimic the human intelligence.

The Marriage Between Artificial Intelligence And Digital Marketing

Previously, marketers were wary to being AI into their marketing strategies. Even now, some are holding back. While people all over the Internet have been laughing at commercials and recipes written by bots, some digital marketers were second guessing their choices. But not all AI is like. AI takes a data-driven approach to marketing and marketers are all about the data, there’s no such thing as too much data for some. Platforms, like Albert or Marketo, store and collect data, analyze that data to understand customer patterns and develop automated systems and customer profiles to target certain markets. As AI learns and grows, and new algorithms are developed, computers will be tasked with increasingly bigger decisions. Artificial intelligence will soon be able to start analyzing behavior and customer profiles more closely to develop their own outreach strategies, write copy that speaks to customers and working with customers on purchasing decisions.

How AI Can Improve Digital Marketing

We’ve started to interact more with Artificial Intelligence than we realize. The Internet of Things (IoT), big data and even machine learning within your Netflix que are all touch points we have with AI. The benefits AI can have on digital marketing, especially as it’s in its infancy, are endless.   Personalized User Experience Facebook Chat Bots are part of AI that’s giving users a more personalized user experience. These bots are able to interact with users 24/7 in an almost human-like way. At IBM, candidates in the US can work with Watson, their new cognitive career advisor system. As Watson questions, like “Are there any computer engineering positions in Austin, Texas?”, and he’ll show you a listing of all computer engineering positions located in Austin, Texas. Chatbots are a great use of AI because they’re always there, no matter the business hours, and can retain customer data. This data retention makes the experience easier for your customers because they don’t have to repeat information after bouncing from representative to representative. It makes the entire customer experience more enjoyable. They can also handle multiple customer requests at a time and still treat each customer politely. Chatbots can also have the power to track any customer purchasing patterns allowing for a business to revamp and marketing strategies to increase sales. Predictive Marketing To correlate customer characteristics with anticipated behaviors, digital marketers have built statistical scorecards called “propensity models” to help identify prospective customers who are most likely to respond to an offer at any given time. With more predictive analytics, we can begin to extract better and more targeted information from the data to predict purchase trends and user behavior patterns. Google’s Display & Video 360 is a crucial tool to help define target audiences and campaign objected when working with AdWords. This tool uses AI to recommend strategies to achieve the desired goals. AI can sift through the piles of data to find the ideal customer or clients based on information that it already has, even going so far as predicting how hot or cold a lead is. Voice Optimization With the steady rise in voice searches, it’s becoming important that we optimize our SEO for natural language long-tailed voice queries. Before, we may type in the Google search bar “Justin Bieber age” because it’s easier, faster and more succinct. Now, with assistants on our phones like Siri, Google, Cortana and more, people are starting to use their voices for searches and the keywords are beginning to match our natural speech rhythms. Now, the search may sound more like “What is Justin Beiber’s age?”. Google actually found that around 70 percent of searches their Google Assistant receives consist of conversation language, not just targeted keywords. With the rise in dependence on voice searches, digital marketers should begin to optimize their pages to answer direct questions that start with “who”, “what”, “when”, “where”, “why” and “how”. Artificial intelligence might feel really creepy if you’re thinking of about Skynet. But, how cool would it be to have your own R2D2 helping you out around the house or a C3PO to answer questions for you? While AI hasn’t gotten that far yet, we can still use it to do some pretty neat things, make our customers happy and help our brands. AI-directed tools are becoming more and more common as we develop better algorithms, discover better uses and gain a better understand of what AI should (and should not) be used for.
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