December 27, 2017 Search Marketing

In a world where the holy grail of marketing is to understand what customers want, natural language processing (NLP) is the missing piece to help get you there. Marketers preparing for the future of search should be exploring how NLP can give them a competitive advantage when it comes to selecting keywords and optimizing their Google AdWords ROI.

Natural language processing (NLP) is a field that lies at the intersection of computer science and linguistics and uses computers to process and analyze large amounts of human (natural) language that would otherwise be intractable for humans to manually examine. NLP seeks to understand the actual content and concepts of language and plays a large role in the advancement of artificial intelligence (AI), given that language is a significant part of humans’ intelligence. Below are four numbers that speak to the importance of NLP for marketers and how it can help you win the Google AdWords game.

32 zettabytes (32 trillion GB)

Big data is a veteran on the analytics stage — but just how big are we talking? According to an IDC Digital Universe study, worldwide digital data will reach 32 zettabytes (ZB) by the year 2020. Even more interesting is the fact that 80-85% of that data is unstructured, referring to data without a formatted structure. Unstructured data is largely comprised of any form of human language-based data, such as emails, text messages, Twitter or phone call conversations.

Humans are creating unstructured data at a staggering rate and the importance of leveraging this data for marketing improvements cannot be overstated. The best AdWords campaigns use keywords that resonate with a customer’s needs and wants. What better way than to analyze the text related to what they are talking about in their everyday lives? This is the type of data that is being underutilized due to a lack in the technical capabilities necessary to process text-based data. NLP experts at DialogTech are uniquely positioned to analyze any type of unstructured data using the latest innovations in NLP techniques and methodologies. In this way, they can provide actionable insights concerning what their clients’ target demographics are talking about and translate that into improved marketing strategies based on data, not guesses.

$2.42 billion

$2.42 billion is a significant number that represents the expected worth of the global AI market in 2017; and that number is expected to continue to grow exponentially. AI is a hot topic in the marketing world with machine learning (ML) becoming a common household term. While ML and AI are becoming pervasive, using these techniques on unstructured or text-based data is not. In general, people are jumping on the bandwagon of ML and AI deep learning without first understanding their data and the features that represent it. Trying to use AI to improve AdWords campaign performance without using NLP is like trying to use a boat on land: you can do it, but you won’t get very far.

DialogTech is keenly aware of the power of NLP and its importance in the marketing industry and has made it our mission to use NLP, in conjunction with ML and AI, to improve clients’ marketing capabilities. Our call classification offering, Dialog Analytics, takes expert knowledge of call content and features and offers customers a way to meaningfully filter calls for deeper insight into phone conversations. The eight million calls that have been automatically classified this year speak to the significance of this offering for DialogTech’s clients.

Interested in learning how to drive more calls and customers with AI?

Check Out The Webinar →

20,000-35,000 words

The average English language speaker has a vocabulary of 20,000-35,000 words. This makes using the right keywords in a marketing ad particularly important. However, this can be as difficult as finding a needle in a haystack: you can either begin sorting one by one and hope it’s not at the bottom, or you can get a magnet. Which would you rather do? NLP is a big step forward toward taking the guesswork out of choosing keywords.

NLP opens the door for marketers to expand their repertoire of keywords to include how specific words relate to the actual language people use in real-world settings. This means being able to assign a quantifiable value to each keyword that represents its relatedness to customers’ actual language and the things they are talking about on a daily basis. DialogTech leverages NLP to shrink that haystack to a manageable size, greatly increasing the odds of success.

20 keywords

When it comes to AdWords, good marketers know it’s easy for poor ad campaign decisions to result in lost revenue. But when you’re supposed to choose only 20 keywords for a given ad group to maximize your conversions, the possibility for missteps is high. Many marketers make the mistake of using their personal creativity or intuition to make these critical choices instead of letting their untapped historical data influence future directions. Some questions you should be asking yourself as a marketer:

  • Do the keywords resonate positively with the target demographic?
  • How similar are my keywords to the language people use in their everyday lives?
  • Are there similar, more applicable, keywords that would more closely align themselves with what people talk about?
  • What type of language is used on my most promising leads’ phone calls?

These are not questions a marketer should attempt to answer without data science augmented by NLP. DialogTech offers this data and ensuring our clients stay ahead of the competition. 

Natural language processing is no longer reserved for the Googles and Microsofts of the world. Marketing groups across the country are recognizing its power and the potential boost for their processes. But getting the right people to help you reach those goals is the key. DialogTech knows this and takes the guesswork out of finding those people. Let us leverage innovative NLP techniques to answer your most important questions.

We would love to discuss with you our AI and machine-learning capabilities, as well as share what our data science team can do to ensure you’re having great conversations with your customers.

Interested in learning how to drive more calls and customers with AI?

Check Out The Webinar →
About the author:

Amber McKenzie

Data Scientist , DialogTech

Amber “Doc Am” McKenzie is a data scientist at DialogTech. With a masters degree in linguistics and a Ph.D. in computer science, she has over 8 years experience in data science and natural language processing (NLP). Her professional interests include NLP, machine learning, predictive modeling, and big data technologies. When she does get a spare moment outside of work, she enjoys reading, board games, dabbling with Arduinos and Raspberry Pis, and photography.

See more posts by Amber McKenzie

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