How Can AI Improve Customer Communications?

If you need convincing about the benefits of AI in the workplace, you’re not alone. Many people are unsure as to how it can help them. However, it’s quite likely you’ve already been part of a communication that used AI but were just not aware of it.

Think back to the last time you contacted Amazon about an item you’ve ordered or a delivery issue. Did the agent you spoke to manage to answer your query?

Most of you will answer ‘yes’ because Amazon is so highly focused on customer satisfaction. The speed and success of their customer interactions is achieved through leveraging customer data with AI. Artificial intelligence streamlines communications between a business and customers and improves the user experience.

Amazon’s customer base is massive, global and speaks a multitude of languages and yet its success rate in customer communications is unmatched.

A brief interaction with their chatbot is enough for Amazon to understand the best way to respond to the query. AI enables Amazon to be proactive and anticipate a user’s concerns. As soon as enough information is gathered an agent can take over the conversation by phone when required and is a step ahead in the resolution process.

Compare that experience to when you were passed from agent to agent trying to solve a problem at another company. Most other businesses funnel their customers into using outdated communication channels because they are connected to legacy customer platforms.

Compared to AI-driven systems legacy platforms are inefficient, adding unwanted additional time to interactions and often generating frustration in customers.

The ease of communicating with Amazon increases the likelihood that you will use them again, even when things go wrong. By contrast, a frustrating interaction with a business leaves a customer feeling less inclined to use them again. And when an interaction attempting to resolve a problem goes badly there is more chance of customers looking elsewhere for that product.

In fact, Walker Consulting predicts that customer experience will be the key differentiator in business by 2020, surpassing the importance of price or the product itself.

MORE CUSTOMERS USING DIGITAL COMMUNICATION CHANNELS

For many customers the phone is still their main form of communication and is the primary support tool for most businesses. This makes sourcing a cost-effective, high functioning telephony and UC solution business critical.

But the digital transformation means an increasing number of customers now also use digital support. Live chat, ticketing, knowledge base, social media and AI-powered chatbots are increasing in popularity and are the preferred channels for certain use cases.

The challenge is in choosing which channel to use and how to successfully incorporate them in your business.

Understanding who your customers are and their communication preferences will guide that decision.

However, AI is critical if the implementation of the new channel is to achieve its full potential. This is because every time a business communicates with a customer it’s an opportunity to enhance the relationship with them.

Personalisation is key. However, the only way to personalise communication at scale is by unifying customer data and using AI to present it in a coherent, actionable form.

Artificial intelligence can drive relevant, convenient and personalised communications at every point in the customer journey. As a result, businesses acquire new customers cost effectively.

Retaining customers over the long haul becomes easier as does realising more upselling opportunities which increases LTV (lifetime value). These improved interactions also reduce churn.

One exceptional ability of AI-driven business communication is to provide sentiment analysis about a conversation. The technology identifies customer mood to enable a business to provide highly personalised services. This type of information empowers agents and further analysis enriches subsequent conversations.

Sentiment analysis is not limited to customer conversations. Valuable insights are learned by analysing interactions between departments and even within teams.

Speech Analytics Analytics Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision-making. In the trading space, analytics are applied in a predictive manner in an attempt to forecast the price more accurately. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analy Analytics may be defined as the detection, analysis, and relay of consequential patterns in data. Analytics also seeks to explain or accurately reflect the relationship between data and effective decision-making. In the trading space, analytics are applied in a predictive manner in an attempt to forecast the price more accurately. This predictive model of analytics generally involves the analysis of historical price patterns that are used in an attempt to determine certain price outcomes. Analy Read this Term surface problem areas as well as reveal role-model agent behaviours. When combined with machine learning and natural language processing it can flag instances of non-compliance.

This helps quality assurance managers quickly zoom in on exactly what needs attention and is highly effective at identifying when an agent needs additional training.

DIFFERENCES BETWEEN LIVE CHAT KNOWLEDGE BASE AND TICKETING

When evaluating your communication infrastructure, it’s important to understand the benefits and role different channels can offer a business.

Live chat allows customers to connect with agents on demand to get answers to queries instantly via a website. With live chat a business can engage customers in real-time and quickly provide solutions.

According to a well-cited Aberdeen Group Report, companies that use live chat save 50% or more on support costs versus other methods. Agents can handle multiple chats simultaneously and there are better opportunities for organisations to use interaction logs for analysis and continuous improvement purposes.

Live chat helps to identify sales opportunities. AI-driven insights into browsing habits and customer personas help to create personalised interactions along the customer journey and identify upselling and cross selling opportunities.

Knowledge base is a self-help hub that is always available and can be used without the need to escalate to an agent. This is usually in the form of an FAQ or help guide and is compiled by collecting queries that occur most often and providing helpful responses.

Having well explained answers on demand frees up agents’ time which can be better used in more complex and challenging scenarios.

While live chat and knowledge base can quickly solve customer problems, they also require an unquantified commitment of user/agent time. However, there are some queries that don’t need an asap response which is when ticketing or email is preferred.

These communications can be mined to reveal actionable detail like pain points. This information can drive improvements in product development or new features.

Using AI to track these interactions reveals activity patterns to determine customer risk thresholds and identify at-risk clients. By closely monitoring these interactions AI identifies the patterns where customers are likely to discontinue and help to reduce churn.

THE POWER OF SOCIAL MEDIA AND AI-CHATBOTS

Social media’s importance as an engagement channel increases in relation to the age of your customers. Microsoft research in 2016 revealed that most millennials believe social media is a useful channel for customer service as opposed to only 27% of Baby Boomers.

Its effectiveness for getting issues resolved is via the ability to ‘go public’ on unsatisfactory issues by leveraging public opinion.

While many organisations mostly use social media as a ‘megaphone’ to broadcast marketing messages, they ignore the important ‘microphone’ aspect for handling queries.

An imbalanced approach where a business fails to respond to issues on a social media channel results in a decline in customer support by as much as 50%.

However, given its popularity organisations must be available through at least one social media channel.

AI-powered chatbots capture customer data and context to deliver better communications and customer experiences. The use of conversational AI offers a responsiveness that mirrors having a normal conversation. It creates a relationship with the user by drawing context from data collected.

Chatbots also reduce website bounce rate – marketing’s equivalent metric to churn. By interacting with customers directly the user is engaged for longer and increases the consideration rate.

The AI systems learn from data collected through sales transactions, customer service tickets, live chat, emails, and phone call recordings in addition to the chatbot interactions.

The chatbot solution is a 24/7 gateway that is highly effective at addressing user frustrations when reaching out to a company. Human inconsistency has less of an impact and the scale of customer interactions is virtually limitless.

While each of these digital channels have their own compelling merits, integration is the only way to provide agents with a personalised view of every customer. The ability to communicate as a one-on-one relationship increases possibilities to sell and serve more effectively.

MORE INTEGRATION GIVES MORE AI-DRIVEN INSIGHTS

The value in these various communications channels is determined by the ability to analyse the data they produce about customers. However, customer data needs to become actionable to realise its true value. AI turns customer data into actionable insights.

However, if the goal of the company is to deliver Amazon like customer experience it requires integrating all the company’s data, connecting every communication channel and business applications through a single AI-driven platform.

Customer facing employees need to access this data and insights whenever needed. Amazon identified that customers base their opinion of a company on their latest interaction. Therefore, employee consistency and their ability to answer questions and resolve issues is essential.

Integrating communications data with CRM data and other business app data gives a business a truly holistic picture and empowers agents when presented in a single screen.

Account insights regarding deposits and withdrawals as well as payment insights in relation to transactions can be analysed with email and marketing campaign insights. Every interaction can be analysed to predict where a problem might occur. This also includes customer paths recording as they navigate a website, actions logs, profile logs and KYC/AML logs.

The more customer data analysis, the more capable a business is to make good decisions. This ability arches across the entire business and through every layer of a company. An employee is armed with complete customer context and able to resolve an issue on the first call. An executive planning business strategy using analysis of sales and communications data is equally empowered to make the best decisions.

A SOLUTION FOR EVERY BUSINESS

Legacy customer platforms that can’t integrate with modern CRMs or other business applications are never going to be able to achieve Amazon-like customer responsiveness.

To achieve this the customer platform needs to offer easy integration with common communication channels, as well as APIs that allow integration with other business applications.

An AI-driven customer platform makes actionable business insights accessible to companies of every size, even those who don’t have the IT resources to create custom integrations.

Cloud-based solutions are designed to unify business functions. When combined with AI to Leverage Leverage In financial trading, leverage is a loan supplied by a broker, which facilitates a trader in being able to control a relatively large amount of money with a significantly lesser initial investment. Leverage therefore allows traders to make a much greater return on investment compared to trading without any leverage. Traders seek to make a profit from movements in financial markets, such as stocks and currencies.Trading without any leverage would greatly diminish the potential rewards, so traders In financial trading, leverage is a loan supplied by a broker, which facilitates a trader in being able to control a relatively large amount of money with a significantly lesser initial investment. Leverage therefore allows traders to make a much greater return on investment compared to trading without any leverage. Traders seek to make a profit from movements in financial markets, such as stocks and currencies.Trading without any leverage would greatly diminish the potential rewards, so traders Read this Term customer data a business can see all analytics through a single interface and access a complete customer history on demand.

These insights empower employees with the ability to address customer interactions successfully at the first point of contact – whichever communication channel the customer prefers to use.

The business can also identify trends in individual customers and offer personalised interactions as well as in the entire customer base to ultimately make optimal business decisions.