AI and the era of smart marketing and customer service

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In 1957, when the first-ever movie based on a super-intelligent computer – ‘The Invisible Boy’ was released. A concept of having intelligent machines was nothing but just a figment of fiction. Less than a century later, today, intelligent machines or Artificial Intelligence is not just disrupting industries in unimaginable ways, every day; it has become a part of our day-to-day lives. There are almost 420 million searches happen through AI-based voice assistants, chatbots, recommendation engines are changing the way people shop, AI-powered driverless cars will soon become the new mode of transport. Prudent businesses know the potential of this technology and precisely why the AI market is set to grow at a rate of 52% by 2025.

But AI is not just transforming industries; it is also permeating business functions and is leading to efficient operations. Customer-facing functions like – marketing and customer service are one of the major beneficiaries of the AI revolution.

Here is how AI is boosting efficiency and impacting the marketing and customer service departments leading to higher growth and happier customers:

Marketing

AI can find multiple applications in the marketing function from search to customer engagement. Here are a few examples of how marketing is leveraging AI:

Improved search functions – technologies like Elastisearch are becoming mainstream in e-commerce by populating the best possible results for a search query. The distributed nature of Elasticsearch enables it to process large volumes of data in parallel, quickly finding the best matches for consumers’ queries.
Recommendation engines – Building a robust recommendation engine is a key aspect of creating a personalized user experience. Netflix is one of the best examples of how a recommendation engine works. More than 80 per cent of the TV shows people watch on Netflix are discovered through the platform’s recommendation system.
Customer segmentation is another aspect where AI is improving efficiency for marketing by learning from customer behaviour for e.g. Companies such as AgilOne are helping marketers to improve and optimize email and website communications, by analyzing, continually learning from user behavior.
– Recently IBM launched its new IBM Watson AI Marketing Suite that improves the marketing efforts by personalized targeting, improved programmatic buying insightful campaign analytics. The suite contains three AI-based solutions – IBM Watson Ads Omni, IBM Media Optimizer, and Predictive Audiences.

At Robosoft, we were a part of a project aimed at helping a leading US retailer based in Illinois, draw maximum ROI out of their marketing spends. The company relied on senior managers’ making marketing investment decisions based on past experiences with traditional marketing channels such as billboard and newspaper advertising. Even though there were massive amounts of data available for analysis, no data was utilized in determining the best channels to spend marketing dollars for maximum return on investment.

As a solution, a large scale machine learning system was developed to maximize Marketing Return on Investment (MROI) across all digital marketing channels. The system helped in
– Enhancing the company’s customer touch points’ data collection capabilities across all web & digital assets.
– Determining customers’ purchase behavior across digital channels.
– Recommending optimal allocation of marketing budget across all digital channels.

The company saw improved EROI across all digital channels, prediction model empowered marketing managers to make data-driven decisions and also helped in defining the in-depth content strategy to rank highly for the most relevant keywords.

Customer service and customer engagement

Artificial Intelligence is currently being deployed in customer service. According to Gartner, by 2020, 55% of all large enterprises will have deployed at least one bot or Chatbot.

Since chatbots can lead to faster but at times inefficient and machine-like customer responses, enterprises are using bots which can work in tandem with their human counterparts. One company that provides AI-augmented messaging is LivePerson, where simple questions can be handled directly by a bot, but as soon as the conversation becomes too complicated the bot can hand the conversation off to a human.

AI can also help in creating models to boost engagement with customers by improving internal processes. One of the largest pharmaceutical companies in Asia that conducts clinical trials based on various types of drugs that belong to Therapeutic Areas like Gastroenterology, Neurology, etc. wanted to ensure patients have access to a simplified explanation of the documentation given to patients during clinical trials. We were a part of a project for the client which was aimed at optimizing the process & time required in translation from Scientific to Simplified documents.

An AI based model was used to translate the documents to the desired language of choice. Additionally, a mobile app was built for the patients as an engagement platform for clinical trials which consisted of an AI-Chat bot that provides answers to user’s text/voice-based questions on-the-go. Resulting in patients being more willing to participate in the trial as they felt more in control of the clinical trial experience.

In conclusion:
Like any new technology AI also has its challenges like the cost of adoption, infrastructure requirements, specialists, etc. However, as technology advances, we will see more and more marketers adopting AI to understand their consumers, segmenting them and also improving the efficiency of their campaigns and engage with their customers.

**This article is an excerpt of the article – How Artificial Intelligence can lead to smarter and more efficient business processes.

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