Natural language processing (NLP) is an immensely exciting technology. NLP covers how computers and human language interact, looking at how to program computers to process and analyze natural language data. From a marketing perspective, NLP is the process of using a computer to analyze and interpret large amounts of data that involve language. NLP can help your chief experience officer and business owners make smart decisions. It can even help with the translation experience through machine translation online, with various types of machine translation services available. Below, we’ll go into three trends that will help with marketing.
NLP Data Analysis and Marketing: Helping Business Owners Make Smart Decisions
NLP has many applications for marketing. Primarily, as we touched on above, it helps marketers analyze larger amounts of conversational data.
In practice, NLP can help with topic extraction, as a major use. This involves using NLP to look for common themes or topics from a data set, often pulled from sources like surveys or company forums. It helps marketers determine what an audience is thinking about. They can then tailor their marketing messages or even products to meet those needs.
As an example, let’s say a marketer for a clothing company analyzed the feedback from surveys about which types of clothing people were looking for. The data showed that many people were talking about having trouble finding comfortable workout clothes. The company could then tailor some of its product lines for workout clothing or come up with content marketing strategies detailing the best clothing items for different types of exercise.
NLP can also help marketers determine which communication methods produce better feedback. For instance, a company may get a sentiment analysis from a chat system or email response, which is determining how negative or positive responses are. Using this data, the company can figure out how to tweak messages or use communication methods that the target demographic is most comfortable with.
Marketers also use NLP to analyze certain terms or keywords to gain insights into which audiences are most relevant and which keywords work for SEO techniques.
Post-Editing Machine Translation
One industry that is being affected by NLP in a major way is the translation sector. As computers become increasingly sophisticated at analyzing and replicating human language, machine translation software has become a key part of the industry’s offering. How accurate is machine translation? That’s an interesting question. It’s not as accurate word-for-word as human translation, but you can certainly get the gist of a document when needed.
Where is machine translation used? Really, anywhere that multiple other languages are spoken, and choppy translation here and there isn’t the end of the world. Many online retailers and travel industry businesses use machine translation routinely.
But machine translation isn’t quite there yet. In fact, it’s still at the point where translation agencies offer post-editing machine translation services to make up for the difference in quality between machine and human translation. Language services provider Tomedes posted recently about offering services where the goal is to fix up poor text that resulted from machine translation. You provide the machine translation document and the original document to the translator, and they bring it back up to standard. Often, translation services can provide post-editing machine translation with a fairly quick turnaround, as many people realize they need the service at the last minute when machine translation lets them down.
What does this have to do with your marketing strategy? Well, if you plan to expand into a foreign market, you will have to work translating the text into your strategy. You might do it aided by machine translation as a first pass. But use human translation services to edit the copy to professional standards. You can find translation services through local keyword searches, like translation services UK, as an example.
One service machine translation can’t provide is localization. This process makes sure the layout looks good from a human perspective and that the message itself stays culturally sensitive. As impressive as NLP is getting, it still can’t tell when certain references are offensive in a new culture.
Dialogue Systems and Machine Translation
Another exciting new area for NLP and marketers is the use of chatbots or (more formally) dialogue systems. Chatbots aren’t going anywhere, as the global chatbot market was set to reach $1.25 billion by 2025.
Chatbots often have more direct applications to customer service, where people can type in questions or get automated help with billing. However, they’re still relevant to marketers.
Many marketers use chatbots to assess which questions are most pertinent to consumers. Those asking less pertinent questions can be routed elsewhere, and marketers can better assist prospects and lead them to a sale.
As an example, people might use a chatbot to ask about billing issues. The website and chatbot could then be set up to direct people to billing assistance or prompts. Meanwhile, if people are asking about a certain product, the chatbot could then be set up to link people to sales pages or sales employees, leading to an easier way to connect the sales team with prospects. As such, a chatbot can be an important part of a modern marketing communication strategy.
NLP is an exciting frontier for business. The NLP market is expected to grow to $41 billion by 2025. By making use of it now, you can keep your business competitive in the coming years.
