How Can AI (and Machine Learning) Add Value to Your Brand?

welocalize April 16, 2021

Artificial intelligence (AI) is a huge business. Worldwide spending on cognitive and AI systems will reach US$57.6 billion in 2021, according to IDC. A study by Markets and Markets reports that the global AI market could reach a market value of US$190 billion by 2025.

There’s no doubt that AI is increasingly becoming mainstream. It is changing the way we interact with brands. Customer experience consultancy Servion predicts AI will power 95% of all customer interactions by 2025. No wonder companies are throwing a lot of money into AI.

There, however, is the problem.

The McKinsey Global Survey on artificial intelligence reveals only 22% of respondents attributed more than 5% of their enterprise-wide earnings before interest and taxes to their use of AI, while 48% reported less than 5%. It’s not that AI delivered little value, but most organizations are not yet able to maximize its potential.

The lesson: Don’t invest in AI for AI’s sake.

Linking AI to Business Outcomes

Before jumping on the AI bandwagon, be clear about what you’re trying to achieve with your AI-led initiatives. It’s important that you link them to business outcomes. Are you after higher revenue? Better customer support? Improved customer experience? Lower operating costs?

Next, identify use cases that will help achieve these outcomes. While you can adopt AI for every business function, the most common applications are in service operations and sales and marketing.

Service Operations

AI can contribute to a more seamless and personalized customer experience by analyzing and predicting consumer behavior. You can use AI to deliver customer care 24/7. For instance, deploy AI-enabled chatbots to understand and respond to customer queries instantly.

Sales and Marketing

Use AI in sales and e-commerce for product recommendations, purchase predictions, dynamic pricing, personalization, customer segmentation, and fraud detection. For marketing, programmatic advertising and cognitive advertising use algorithms for ad targeting and optimized real-time bidding. In addition, AI can create, personalize, and optimize global ad copy and creatives. Content marketing can use AI for personalized news feeds, automatically generated content, content curation, social semantics and sentiment analysis, and language recognition – all in multiple languages.

The Role of AI in Language and Localization Strategy

For global brands, AI will play a crucial role in their language strategy. The use of neural machine translation (NMT), natural language processing (NLP), and machine learning (ML), all subsets of AI, will continue to transform localization and translation in many ways.

Through AI, companies can unlock the potential of their large multilingual datasets. And they can go to global markets faster.

For one, language technologies such as NMT speeds up the process and lowers the costs of translation. No human translator can beat a machine in translating vast amounts of content and also identifying languages. Whether for gisting purposes or content destined for post-editing by human translation, AI enables more scalability and scope. NMT, a form of deep learning, lets MT engines train themselves. It uses an artificial neural network similar to how our brains work.

Some NMT can miss nuances and context in language and misunderstand slang and colloquial words. That is where NLP comes in. With NLP interpreting the meaning and intent of the text, machines can better understand how humans speak, think, and feel.

Localization, in other words, is better achieved and enabled with AI. And while human translators and linguists are still required to edit and review MT, AI certainly makes their jobs a lot easier and faster.

AI in Action

There are many ways to use AI to boost the brand value of global brands.

Language Translation

Breaking into new markets, particularly where another language is used, requires translation and localization. This applies to your content assets such as websites, apps, and social media accounts. Deploying NMT models allows you to go to market faster at a lower cost.

Multilingual Chatbots

An AI-enabled chatbot that can converse like a human agent is a powerful customer service tool. A multilingual chatbot that not only detects a foreign language but also understands cultural context will do wonders for your brand.

Text Analysis

You can use AI to monitor multilingual user-generated chat (UGC) to give product feedback, address complaints, combat fake news, and more. It automatically analyzes thousands of websites, social media platforms, and forums in different languages.

Sentiment Analysis

AI can also help guard your brand reputation. Use it to analyze high-volume content such as social media posts and product reviews. Sentiment analysis identifies emotions in text and classifies opinions as positive, negative, or neutral. You can monitor what your customers feel about your brand and respond accordingly.

The Power of Localized AI Training AI

It takes a huge amount of effort and investment to execute your AI-led initiatives. You can partner with an AI-enabled language service provider like Welocalize to transform your data. We blend human intelligence and machine automation to create, annotate, and augment high-quality training data for machine learning and AI initiatives.

Whether you need to create a multilingual chatbot that can respond to customers worldwide or improve the content relevance of search queries based on text, voice, or images, Welocalize can help you unlock the potential of your multilingual training data. Contact us to learn more.

You may also like to read:

White Paper: Your Guide to Conversational AI

White Paper: Global CX & Customer Support Through Two Lenses: Localization & Conversational AI