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How do I use NLG and chatbots for eCommerce?

Ananya Azad
Aug 4
5-6 mins

Table of contents

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Natural language generation

Chatbots are causing the perfect storm. It's not just When (Now) but Where (everywhere) and How (in this article) that will shape the future as we learn to coexist with AI.

A study projects the global Natural language generation market was expected to reach $1.66 billion by 2023, growing at a CAGR of 25.3% from 2018 to 2023. Those projections stand nullified by the introduction of ChatGPT, which has taken over public imagination and is expected to reach a revenue of $1 Billion in 2024, further expanding and deepening the markets. 

Are you still living in an era unaware of the potential of chatbots? Or struggling to figure out how to use chatbots for your business?

If the answer is yes, then this blog is for you.

Here we dive into the concept of Natural language generation and how its cutting-edge technology can be used to boost eCommerce sales.

What is Natural Language Generation?

NLG stands for Natural Language Generation. It is a subfield of natural language processing (NLP) that focuses on the creation of natural language text or speech from structured data, such as a database, knowledge graph, or other forms of structured data.

NLG technology uses various techniques and algorithms to convert data into human-readable languages, such as templates, rule-based systems, machine learning models, and neural networks. NLG can be used in a wide range of applications, including chatbots, virtual assistants, automated report generation, emails, and content creation.

NLG technology is becoming increasingly advanced and accurate, making it an essential component in many industries. With the growth of big data and artificial intelligence, NLG has become an important tool for businesses to generate valuable insights and communicate with their customers more naturally and effectively.

How is Natural Language Generation used in Chatbots?

Chatbots are becoming increasingly popular as a tool for businesses to provide customer service and support. These software programs use Natural Language Processing (NLP) and machine learning techniques to interpret user input and generate responses conversationally. Natural Language Generation (NLG) is a key component of chatbot technology that enables chatbots to respond to user queries or requests with natural language responses that are tailored to the user's specific needs.

NLG allows chatbots to generate responses that are grammatically correct, relevant, and easy for the user to understand. This can be achieved using various techniques, including rule-based systems, template-based systems, and machine-learning models. With rule-based systems, predefined rules are used to generate responses, while template-based systems use pre-built templates to generate responses. Machine learning models, such as neural networks, learn from examples of human-generated text to generate responses that are more natural and contextually appropriate.

Hence, NLG plays a crucial role in chatbot technology by allowing chatbots to provide engaging and personalised conversations with users. By using NLG, chatbots can provide accurate and relevant information to users and help them complete tasks more efficiently. As chatbots continue to evolve, NLG is likely to become even more important in creating more human-like interactions between machines and humans.

How does Natural Language Generation work?

Natural Language Generation (NLG) is a technology that transforms structured data into natural language text using algorithms and computational linguistics. Here is a closer look at the four main steps of NLG:

1. Data Input

The NLG system takes structured data as input from various sources such as databases or spreadsheets. The data is then analysed to identify the key elements that need to be included in the generated text.

2. Content Planning

The system plans the content based on the input data and decides on the appropriate writing style, tone, and contextual information that needs to be conveyed.

3. Sentence Generation

NLG algorithms generate grammatically correct and semantically accurate sentences. These algorithms can be rule-based or use machine learning techniques such as neural networks.

4. Text Realisation

Finally, the NLG system selects the appropriate words, phrases, and sentence structures to create text that is fluent, coherent, and understandable. The generated sentences are then transformed into natural language text.

NLG technology is evolving and can automate tasks that require human-level language skills. In eCommerce, NLG is essential for creating personalised product recommendations, marketing messages, and content based on each customer's preferences and purchasing behaviour. NLG is also used to generate product descriptions that are informative, engaging, and easy to understand, which can help increase conversions and reduce product returns.

Moreover, NLG is used in chatbots to provide users with natural and engaging conversations. Chatbots can help customers find products, answer questions, and provide support, all while saving time and reducing costs for businesses. NLG is also used in customer service interactions to answer frequently asked questions, provide order status updates, and process returns and exchanges, which can help reduce wait times and improve customer satisfaction.

Why is Natural Language Generation important?

Natural Language Generation (NLG) has become an essential tool for eCommerce businesses looking to improve customer experience and drive sales. By leveraging NLG, businesses can create personalised product recommendations, automate customer service interactions, generate informative product descriptions, create engaging content, and enhance their chatbots' conversational capabilities. 

Here are some benefits of using Natural Language Generation in eCommerce:

1. Personalisation 

Natural Language Generation(NLG) can analyse customer data such as past purchases, search queries, and click-through rates to generate personalised product recommendations, marketing messages, and content. This approach can help businesses build stronger relationships with customers and improve customer satisfaction. Personalisation can also help increase sales and revenue by providing customers with relevant and targeted offers.

2. Customer Service

By utilising Natural Language Processing to comprehend and address customer inquiries, NLG can automate customer support interactions. This can help lessen human agents' workload, accelerate response times, and enhance the overall experience for consumers. Automated customer service can also assist companies in reducing costs associated with customer service staffing.

3. Product Descriptions

eCommerce businesses can use Natural Language Generation(NLG) to create product descriptions that are optimised for search engines and product discovery. By including relevant keywords and phrases, businesses can increase visibility and attract more potential customers to their eCommerce site. NLG can also help reduce product returns by providing customers with clear and accurate information about products.

4. Content Creation

Content that is tailored to specific target audiences can be made using Natural Language Generation (NLG). By analysing customer data, NLG can generate content that is more relevant, engaging, and informative, which can help increase customer loyalty and retention. Relevant content can also drive traffic to eCommerce sites and improve search engine rankings.

5. Chatbots

Natural Language Generation(NLG) is also used to make chatbots more intelligent and responsive. By leveraging machine learning algorithms, chatbots can provide personalised recommendations, troubleshoot customer issues, and even place orders on behalf of customers, all without human intervention. This can help businesses improve customer satisfaction, reduce response times, and increase sales by providing customers with a more efficient and personalised shopping experience.

What are the top 7 use cases of Natural Language Generation in eCommerce?

Here are the top 7 use cases of how Natural Language Generation can be used in eCommerce:

1. Personalised Product Recommendations

NLG has the ability to analyse customer information, such as purchase history, browsing patterns, and preferences, to generate tailored product suggestions. Showing customers products they are more likely to purchase can aid eCommerce companies in growing their sales. The customer experience is also improved by personalised product recommendations, which present customers with more pertinent and practical product ideas.

2. Product Descriptions and Reviews

NLG can generate product descriptions and reviews that are engaging, informative, and relevant to customers' needs. This can help eCommerce businesses improve their product pages and increase conversion rates. NLG can analyse product features and benefits and generate descriptions highlighting the most relevant information. NLG can also generate reviews specific to the product, including its quality, value, and usability.

3. Order Confirmation and Shipping Updates

Order confirmation messages and shipping updates can be created by NLG in a straightforward and concise manner. Better customer communication and a reduction in customer support workload can benefit eCommerce companies. Customers can receive customized order confirmation messages and shipping updates from NLG, who can create and send them automatically. This gives them access to real-time order information.

4. Customer Service Chatbots

NLG can power chatbots that can assist customers with their queries and issues. This can help eCommerce businesses provide 24/7 customer support and reduce customer service costs. NLG-powered chatbots can handle routine customer services queries, such as order status and shipping information, freeing up customer service representatives to focus on more complex customer issues.

5. Content Marketing

NLG can create blog posts, articles, and other content that is informative and engaging. This can help eCommerce businesses improve their content marketing efforts and attract more customers. NLG can analyse customer data, industry trends, and other relevant information to generate content specific to the eCommerce business and its customers.

6. Product and Inventory Reporting

NLG has the ability to produce summaries on product and inventory data that are simple to read and analyse. This can help eCommerce companies manage their inventories more effectively and predict their sales more accurately. When generating reports that demonstrate which products are selling well, which products are not selling well, and when to reorder products, NLG can analyse inventory data.

7. Fraud Detection and Prevention

To identify and avoid fraud, NLG can analyze client data. This can assist eCommerce companies in lowering fraudulent deals and safeguarding the personal and financial data of their clients. To identify suspicious behavior and stop fraudulent transactions, NLG can analyze customer transaction data, including purchase history and location.

In conclusion, Natural Language Generation can help eCommerce businesses improve their customer experience, increase efficiency, and drive sales. By leveraging NLG technology, eCommerce businesses can gain a competitive edge and stay ahead of the curve.

How do I use NLG and chatbots for eCommerce?

To use NLG and chatbots for eCommerce, follow these steps:

Determine the purpose of the chatbot and NLG.

Decide what you want to accomplish by using these tools in your eCommerce business, whether it is to improve customer experience, automate repetitive tasks, or increase sales.

Choose a chatbot platform. 

There are many chatbot platforms available, so choose one that fits your needs and budget. 

Define your chatbot's personality and tone

Decide how your chatbot will interact with your customers and what tone it will use. Ensure the personality and tone are consistent with your brand and target audience.

Develop conversational content

Use NLG to develop conversational content that is engaging and personalised to your customers. This can include product recommendations, promotions, and answers to frequently asked questions.

Integrate chatbots and NLG into your eCommerce tools and systems

Ensure that your chatbot and NLG are integrated with your eCommerce platform, website, and other tools and systems.

Test and refine your chatbot and NLG

Test your chatbot and NLG with real customers and use the data to refine them. Make sure your chatbot and NLG are providing value to your customers and are improving your eCommerce business.


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Ananya Azad

Ananya is a content writer at Engati with an interest in psychology and literature. Ananya enjoys ghostwriting and brand stories that elevate others in innovative ways.

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