4 Use Cases of NLP in Marketing Automation

Elena Mia

Natural Language Processing (NLP), is a branch of Artificial Intelligence technology that assists computers to analyze, deduce, and influence human language. NLP infers many practices, including computational linguistics and computer science, in order to bridge computer understanding and human communication.

Role of NLP in Marketing Automation

In the Analytics era, there are ample KPIs and solutions to select from in order to evaluate your marketing information. One such technique is Natural Language Processing (NLP). NLP can help businesses to extract insights from large qualitative data sets like consumer inspirations, objectives, buying process, etc. Moreover, NLP can help businesses to vitalize marketing automation in a variety of methods as mentioned below:

  • Content Marketing

NLP in digital advertising, particularly content marketing, is acquiring incredible growth. It powers the type of content that marketers create and how they build it. NLP exactly helps businesses to understand user preferences, behavior, and what makes them click on certain content. Let’s look at two major use cases of NLP in content marketing:

1.      Identify trending topics–The NLP software implementation for your business helps marketers to run through diverse URLs to observe social media's driving force i.e. user conversations to identify what is trending.

2.      User sentiment analysis - Natural Language Processing algorithms examine social media posts, reviews & feedback, and also user-generated content to understand what users feel about a topic or product

Since content is the keystone of every digital marketing process, NLP can optimize the content through AI and ensure that it’s aligned with business objectives. You can compose many articles, but it will not benefit a company if it cannot be certainly found online. For this, businesses need to deploy the right marketing automation solutions that influence NLP and AI algorithms and ensure your content yields the best traffic possible.

  • Voice of Customer (VoC) Analytics

The “Voice of the Customer” (VoC) is essential for a user-centric marketing approach. If your business needs to consider multi-layered trends over a sensible time, a basic survey analysis tool isn’t adequate enough. Choosing a scalable Voice of Customer analytics tool is an ideal option to experience enhanced customizability and reporting.

A Voice of the Customer (VoC) analytics solution helps businesses to hear and listen to user opinions about their brand, services, and products. Voice of Customer solutions helps marketers to accumulate feedback and leverage it into actionable data and insights at large. To remain competitive in evaluating customer feedback, an NLP-assisted Voice of Customer solution is useful in analyzing unstructured data. At a rate of knots, NLP-driven Voice of Customer (VoC) analytics tools can evaluate databases and are efficient to grow customer lifecycle value and lower churn rate. This, of course, helps digital businesses with increased revenue and better organization of expenses. From troubleshooting customer onboarding to streamlining customer experiences, choose an integral NLP-supported Voice of Customer solution that improves the marketing automation process swiftly.

  • Targeted Lead Generation

Natural language processing solutions can support your business's marketing strategy, exclusively if you undertake a targeted method like Account-based Marketing (ABM). Using NLP tools, your marketing group can keep its finger on the pulse of user conversations regarding vital customers’ requests, disputes, and maybe even about your brand. The data that you collect from an NLP system can be automatically inputted inside a CRM system for salespeople to thoroughly observe customer sentiments, regrets, and complaints with the brand. This helps businesses to pitch tailored services based on user requirements and drive more lead generation.

If you’re a small to midsize business and you don’t have the luxury to implement marketing automation, An AI-powered CRM implementation will help you keep automated. Also, an AI-powered CRM allows your businesses to use Natural Language Processing (NLP) to access prompt data analytics and will help your team save efforts on monotonous, mundane tasks.

  • Sentiment Analysis

Sentiment analyses help businesses understand whether their data has a positive or negative approach among the audience. While there are several methods of executing sentiment analysis, some use cases include classifying the approach stated in a document or set of sentences in order to acquire a general opinion of user mood. In marketing, this can help understand how the audience responds to various communication methods. For instance, feedback generated from a chat platform may create a less positive approach than email feedback, since email feedback may denote that the user is convinced and interested in your services, whereas a chat system is mainly used by the audience for support requests or quick queries.

Wrapping Up

NLP use cases like those stated here can help you understand the knowledge of unstructured data sets and serve your current and potential users efficiently. However, before advancing in NLP, companies should precisely consider several aspects, like their business objectives, flexibility, and the scalability of integration. Thus, implementing NLP technology from the right marketing automation agency is effective to help your marketers analyze user content, extract practical insights and deliver extraordinary CX.

Elena Mia
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