Analytics, AI/ML

NLG and Its Business Impact Across Industries

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NLG and its Business Impact across Industries

 

Artificial intelligence has redefined the way businesses operate and communicate with consumers. The ability to use technology to identify, process, and use structured and unstructured data for better results is an appealing proposition for all businesses. For instance, personalization has always been labeled as a unique factor with which companies can succeed in any industry.

According to a report by McKinsey, personalization can drive better results for an organization by influencing consumer behavior. The study further observed that organizations that grow faster than their competitors drive 40% more revenue from personalization than their slow-moving counterparts.

In the traditional business ecosystem, the main challenge with personalization was the ability to execute it at scale. As personalization used to require human intervention, the limited availability of talent made it difficult for businesses to use personalization at scale. To address this challenge, organizations turned to technology and found a solution in natural language generation (NLG).

The generative AI function of NLG makes it possible for businesses to create various forms of content and personalize them for different target audiences. NLG uses AI capabilities to empower systems to develop human-like responses by identifying, storing, and processing structured and unstructured information.

According to a report, the global natural language generation industry is expected to grow at a CAGE of 13.5% during 2020-2027 to reach $1.4 billion.

What is Natural Language Generation (NLG)?

NLG is part of artificial intelligence's natural language processing (NLP) capabilities. It is related to processing information from various sources, such as written text and IVR voice texts, and converting them into structured data that can be used and understood by a system.

NLP also includes other functions like natural language understanding (NLU). NLU is mainly used to understand human language and decode a collection of words and phrases. NLU also overcomes the challenges of syntax, mispronunciation, and slang.

NLG takes assistance from NLP and NLU to develop a human-like language that fits the context and matches a human's sound. A very common example of NLG would be how Siri dictates driving instructions to the user.

How does Natural Language Generation work?

NLG is mainly used to develop a language that various business functions, like marketing, customer service, etc., can use. NLG is primarily responsible for creating a natural and context-fit language that can be personalized by a business and deployed at scale. NLG process especially involves four stages as explained below::

Data pre-processing

The AI system mainly cleans and sets up the available data in the first stage. This stage is also used to filter out the data based on the final objective of the business.

Data Understanding

After the data has been set up, the system moves to understand the available information. Using a machine learning framework, NLG understands the relationship between the input and expected output data.

Content Planning

This stage is used to identify which content will be used to create the final output and in what order. It is the stage where the NLG system has the headroom to be creative, much like a human writer, and decide how the available information can be presented to the end user.

Natural language generation

In the last stage, the NLG framework aims to generate natural-sounding language and text and put the final result in the suitable format. It can be a report, email, or chatbot conversation.

The business impact of Natural Language Generation

NLG can provide a positive business impact in a variety of ways. Here are some of the possible use cases of NLG in business operations:

Hyper-personalization at scale

NLG systems are designed to generate text and language tailor-made per individual customers' requirements. Some of the most famous examples of hyper-personalization using NLG systems include conversational AI, voice assistants, and chatbots that efficiently respond to customer queries.

Improves conversion rates

NLG output usually helps to improve the conversion rates in a business. It can be more clicks, more sales, or more subscriptions. The fact of the matter is NLG can be used to improve conversion rates across a variety of campaigns. Brands like Orange and Michaels have achieved better results with NLG.

Improves customer engagement

NLG technology is essential in improving customer engagement and providing the correct information to consumers at the right time. The NLG tools empower a business to resolve customer issues at a fast pace and direct customers to the right resources that help to improve customer engagement rates.

Several e-commerce brands use NLG solutions to increase customer engagement.

Better customer retention and loyalty

The ability to provide personalized, relevant content improves the level of trust and loyalty among customers. At the same time, NLG is also critical in retaining customers by providing the correct information to individual customers. With NLG systems in place, it is easier for online businesses to cross-sell, up-sell, and create a base of repeat customers becomes much easier when a company can develop a set of loyal and engaged customers.

Lower operational costs

NLG helps automate several aspects of business operations that lower operational costs. By reducing manual interventions in customer service, employee workflows, and marketing functions, NLG helps improve efficiency and productivity for an organization.

How do various business functions use Natural Language Generation?

Businesses use NLG in four essential functions - marketing, digital adoption, and customer service. Here is how the various business functions use NLG:

How does Marketing use NLG?

The marketing department of any business uses NLG to automate the content generation and improve conversions at various customer touchpoints in the buyer journey. From the initial awareness stage to the post-purchase engagement, NLG can help automate the customer journey to consistently deliver a superior customer experience.

Use of NLG in digital adoption

NLG helps the customer move from traditional workflows to digital channels. By creating convenient and easy-to-use experiences, a business can deliver a personalized digital experience for a business. As a result, a company can use NLG to create uniform content across multiple touchpoints and accelerate customers' digital adoption.

How NLG drives customer experience?

Using NLG in customer service can prove to be critical when handling increasing consumer demands and resolving customer issues. NLG can play a crucial role in delivering a superior customer experience consistently. NLG can reduce customer support calls to a business by providing natural-sounding responses to customer questions or requests. 

How do various industries use NLG?

Businesses across various industries use NLG capabilities to design a personalized experience for customers at scale to improve customer experience across the board. Here are some of the examples of significant industry players using NLG to develop a customized experience for their customers:

Finance

Areas like banking and finance have been using NLG to simplify complicated financial reports and other materials like regulatory filings, suspicious activity reports, and executive summaries to improve customer experience. The data-guided language can help improve the onboarding rates of customer onboarding in the banking and finance industry.

For instance, BNP Paribas Securities used NLG to create a simplified executive summary of the Management Information Services Book that runs over 100 pages. The executive summary captures essential information like income, corporate actions, assets under management, and settlement.

Use Cases of NLG in Finance

Retail

The retail industry has been using NLG capabilities for creating product descriptions for e-commerce businesses. At the same time, it also uses NLG to personalize communication with customers conducted over email, SMS, web, and chatbots.

Michaels, North America's most prominent art and craft retail chain, used NLG to personalize communication across emails and websites. The business registered a 25% jump in its CTR. At the same time, it also helped to improve engagement in its SMS campaigns by 41%.

Use Cases of NLG in Retail

Insurance

The insurance industry has been using NLG to improve engagement among prospective customers and increase sales. NLG can also provide customer-specific underwriting and actionable claims data.

For instance, a significant player in the insurance industry used NLG to create more engaging language on their quotes page. It helped improve the number of hot leads the business was generating and increased sales by 17%.

Healthcare

Healthcare is another area in which NLG can bring meaningful change. Healthcare companies can use NLG systems to come up with material like health summaries and customer-friendly educational material. For instance, customers can be supplied with summary sheets that are easy to understand.

Humana Inc., an American health insurance company based in Louisville, Kentucky, used NLG to send personalized flu-reminder emails to its customers. By adding a personalized emotional element to its communication, Humana improved its email open rates to 31% from 20%.

Use Cases of NLG in Healthcare

Telecom

The telecom industry has been using NLG to improve communication with customers. Customers need to be aware of their usage patterns to avoid overuse charges. NLG systems help telecom companies keep customers aware of the usage pattern in an engaging way. At the same time, NLG is a powerful medium to upsell and cross-sell customers.

Orange used NLG to determine the best semantic choices to improve email conversions. With the use of NLG, Orange improved its email open rates by 40%, read rates by 300%, and registered strong growth in product orders.

Travel

The travel industry has been using the NLG capabilities in the planning, booking, during-the-trip, and post-trip communication with customers. NLG integration helps achieve a personalized communication strategy that can be used across channels and platforms.

Using NLG also makes it easier for companies to compare and seamlessly add various upgrades to the booking plan.

Conclusion

NLG can support each business function with attractive value addition. As it can create the available information into a compelling narrative, NLG can provide a consistently superior experience for an organization.

Apart from improving the customer experience, NLG can play an active role in driving conversions for a business. With the addition of NLG in business strategy, an organization can see the benefits of using artificial intelligence for day-to-day tasks and achieve better results.

To read more insightful content, visit the Cogent Infotech website.

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