In today's increasingly competitive world, organizations need to do things differently, yet in a way that they stay relevant to customers. A major dimension of this is customer experience (CX) - the interaction between customers and organizations over the course of their continued relationship, eventually culminating into a purchase. Such a relationship includes attracting a customer, making them aware, and cultivating a transactional relationship with them, eventually leading to a purchase, use of a service, and advocacy for the organization by the customer.
A recent research by Gartner indicates that very soon, close to 89 percent of businesses will compete mainly on customer experience, making CX the differentiating factor for any business. With the advent of automation, implementing technologies like artificial intelligence (AI) and cloud in business processes will become imperative for companies to enhance their reach. Consider the following facts: Google's voice recognition technology now claims 98 percent accuracy and Facebook's DeepFace boasts a 97 percent success rate in facial recognition. These are all artificial intelligence (AI) technologies and they are all successful.
The question now is, 'how can organizations involve AI in CX?' To answer this, we need to first understand what exactly AI is (and no, it's not your typical, Hollywood Sci-Fi movie's AI that is ready to take over the Earth and overpower humans!). Artificial intelligence is in fact intelligence exhibited by a machine that evaluates its environmental factors to churn out actionable outcomes based on cognitive logic, in order to take decisions like a human. AI adds relevance to any intellectual task, and when this technique reaches mainstream-use, it is described as the 'AI effect.'
AI is everywhere and assisting millions of users daily in the most subtle way
Sounds too fancy to be true? Well, AI is actually involved in our day-to-day lives in various aspects like
activity recognition, which basically determines what a person is doing and based on the activity, decides what is the appropriate response / action that needs to be taken. Then there is natural language processing (NLP), in which the machine has the ability to recognize, interpret, and synthesize speech. An extension of this technology is the deep learning approach used by Google in RankBrain, which analyzes vast amounts of digital data in order to find relevance in content and queries. It can learn all sorts of useful tasks, like identifying photos, recognizing commands spoken into a smartphone, and accordingly respond to internet search queries. In terms of self service support, AI is used to create assisted customer care, wherein the interaction with customers is handled by machines. Chatterbots are another extension of this technology, where AI talks to humans over text chats. Siri, WeChat, IBM Watson, etc. are popular examples of this technology created over different platforms, which can additionally be embedded in websites and messaging applications. There are AI tools that are designed to augment human intelligence using an AI technique known as intelligence amplification.
Recent advances in AI and machine learning capabilities assure that AI can help improve customer experience significantly. There are several potential use cases for AI in the CX lifecycle that can be envisaged in the near future; such as:
Innovative marketing
1. Targeted advertisements and campaigns: Advertisements, which are the most basic form of marketing, can be optimized to be more targeted with the help of deep learning, by detecting trends in user behavior through internet content. Artificial intelligence will help increase the likelihood that a user will click on an ad and thus achieve better cost-per-acquisition for the organization.
2. Automated product pricing: With multiple products and different business factors that impact sales, estimating a cost-to-sales ratio -- commonly known as price elasticity -- can be difficult. AI can prove to be helpful here, with its ability to work out dynamic price optimization by analyzing pricing trends and environmental factors that affect sales.
3. Lead assistant bots: Sales leads assistance bots can be developed with AI to nurture your leads through constant interactions, at various touch points. The AI engine can be configured to generate leads based on various sources and also initiate a personalized email campaign or other media interaction for the targeted segment. The AI can then nurture the leads and hand them over to sales reps when such leads turn hot.
Accelerating sales
1. Complementary sales: AI can be used to upsell and cross-sell across product groups by providing potential customer recommendations with the help of AI-assisted analytics. The AI engine can analyze the information gathered from different sources, linking it to industry, purchase patterns, product types, etc. to suggest products to potential customers. Armed with information about different customer attributes, skillset of sales reps, and relationships with different types of customers, the engine can learn and recommend what combination of customers and sales reps yields the best results.
2. AI can recommend the most optimum territory coverage based on sales rep relationships, affinity, and strengths, alongside quotas based on industry statistics as well as historical sales.
3. With the help of social and digital platforms, AI technology can be used to enhance customer contact touch points. Different people have different preferences and adjusting your way of interacting with customers can help your business satisfy them better.
4. AI can also help in recognizing patterns and behaviors of customers to automatically generate action alerts. Additionally, by studying these patterns, AI can help recognize the most appropriate sales and service channels for a customer. AI-aided speech recognition could be used to spot key words and consequently trigger service enhancements.
6. AI can help businesses have effortless omnichannel engagement with customers across all channels, including phones, tablets, websites, etc. It can also guide sales reps to communicate with customers through the channel of their choice. This is not only a means of effective information, but also serves to elevate the quality of service and nurture better relationships with customers.
Powered with high-quality data, strong algorithms, and excellent computing power, AI is already paving the way for human brain-like behavior. Given the significant leaps in cloud technology, we can expect this space to witness some rapid innovation.
Critical Success factors of AI
It's clear that AI advancements and cognitive technologies will result in tangible results, such as upselling, increased loyalty, and cost savings. AI-driven customer experience can positively impact the bottom-line for a business and successfully make customers happy by:
Optimizing the selling and service time by inducing faster actions and decisions to satisfy customers who seek quicker responses
Providing better outcomes, be it via a resolution tailored to a customer's problem or faster diagnosis of an issue faced by the customer
Improving efficiency of operations and employees
Reducing labor costs through intelligent automation of service tasks, assignments, etc.
Greater scale of performing major tasks quickly that are otherwise too tedious to be performed manually.
Bringing innovations in products and services, such as improving customer service with personalized responses, and launching new approaches.
Rapid innovation is going to make AI a critical success factor in customer relationship management across various sectors. It will bridge the gap across digital, online, and offline channels, leading to improved efficiency, reduced costs, increased revenues and ultimately, a better and more connected customer service landscape.