How Sophisticated is Your Customer Service Strategy?

Take Stock of Where You Are

Honest and frequent evaluation is one of the most important aspects of any leader’s job — particularly in the customer service industry. In a rapidly evolving communication ecosystem, it’s important to regularly assess how satisfactory your service is. Whereas ten years ago, simply having email-based support put one at the forefront of customer service, today’s consumers expect messaging-based self-service options, lightning-fast responses, and seamless interactions.

Meeting, much less exceeding, these customer expectations has proved challenging for many companies. Phone support with reasonable wait times is simply not scalable, and too costly for companies to maintain as agents can only handle one phone call at a time. With only traditional support options available, ticket backlog will increase while customer satisfaction likewise decreases. Yet, most companies have not yet solved this problem; according to a recent Helpshift survey, over 50 percent of consumers give American customer service a “C” rating or below.

To help you achieve an “A” rating, this evaluation is designed to assess your current customer service strategy and help you progress with actionable next steps.

How Robust Is Your Knowledge Management?

  1. I think we have some FAQs somewhere on our site
  2. We have knowledge articles for our most common queries, but they don’t deflect many tickets
  3. We have a robust knowledge base system and chatbots that suggest appropriate articles based on keywords in their question
  4. I think we have some FAQs somewhere on our site

The New World of Customer Service Automation

AI and Bots are Easy to Access if You Know Where to Look

It’s An AI World, We’re Just Living In It

Think about what you’ve done today: did you check the weather? Ask Siri to call your mom? Read the news? Scroll through Facebook? Listen to Spotify playlists? Check your email? Watch Netflix?

If your answer is yes to any of the above, you’ve used AI today.

AI is all around us, so woven into the fabric of our lives that we don’t even realize it’s there. From predictive algorithms (used for predicting the weather or suggesting Netflix shows), to NLP (used by Siri and various chatbots), to machine learning (used for Facebook feeds and Google search), AI has become so commonplace that most of us use it upwards of 10 times per day, without even noticing. The reality is AI doesn’t only refer to sentient robots; it refers to intelligent machines that can learn, teach themselves, and process information in real-time. And these machines are everywhere.

In most industries, AI has also been incorporated into enterprise solutions. For instance, Geico uses decision-tree bots with limited NLP to help users buy the right insurance for their needs — without ever interacting with a human. DeepMind’s recent development of a retinal scan that can predict cardiovascular risk is a highly complex example of auto-classification. Netflix bought “House of Cards” without ever even seeing the pilot — the decision to invest in the show was based exclusively on predictive analytics that used data points including plot theme, viewership trends, director metrics, and the political climate. AI is even used in logistics and delivery systems to allow organizations to schedule work orders based on resource availability, inventory, and timeline.

Strategic Moves to Mobile App Success

AI and Bots are Easy to Access if You Know Where to Look

It’s An AI World, We’re Just Living In It

Think about what you’ve done today: did you check the weather? Ask Siri to call your mom? Read the news? Scroll through Facebook? Listen to Spotify playlists? Check your email? Watch Netflix?

If your answer is yes to any of the above, you’ve used AI today.

AI is all around us, so woven into the fabric of our lives that we don’t even realize it’s there. From predictive algorithms (used for predicting the weather or suggesting Netflix shows), to NLP (used by Siri and various chatbots), to machine learning (used for Facebook feeds and Google search), AI has become so commonplace that most of us use it upwards of 10 times per day, without even noticing. The reality is AI doesn’t only refer to sentient robots; it refers to intelligent machines that can learn, teach themselves, and process information in real-time. And these machines are everywhere.

In most industries, AI has also been incorporated into enterprise solutions. For instance, Geico uses decision-tree bots with limited NLP to help users buy the right insurance for their needs — without ever interacting with a human. DeepMind’s recent development of a retinal scan that can predict cardiovascular risk is a highly complex example of auto-classification. Netflix bought “House of Cards” without ever even seeing the pilot — the decision to invest in the show was based exclusively on predictive analytics that used data points including plot theme, viewership trends, director metrics, and the political climate. AI is even used in logistics and delivery systems to allow organizations to schedule work orders based on resource availability, inventory, and timeline.

Strategic Moves to Beating Mobile Churn

AI and Bots are Easy to Access if You Know Where to Look

It’s An AI World, We’re Just Living In It

Think about what you’ve done today: did you check the weather? Ask Siri to call your mom? Read the news? Scroll through Facebook? Listen to Spotify playlists? Check your email? Watch Netflix?

If your answer is yes to any of the above, you’ve used AI today.

AI is all around us, so woven into the fabric of our lives that we don’t even realize it’s there. From predictive algorithms (used for predicting the weather or suggesting Netflix shows), to NLP (used by Siri and various chatbots), to machine learning (used for Facebook feeds and Google search), AI has become so commonplace that most of us use it upwards of 10 times per day, without even noticing. The reality is AI doesn’t only refer to sentient robots; it refers to intelligent machines that can learn, teach themselves, and process information in real-time. And these machines are everywhere.

In most industries, AI has also been incorporated into enterprise solutions. For instance, Geico uses decision-tree bots with limited NLP to help users buy the right insurance for their needs — without ever interacting with a human. DeepMind’s recent development of a retinal scan that can predict cardiovascular risk is a highly complex example of auto-classification. Netflix bought “House of Cards” without ever even seeing the pilot — the decision to invest in the show was based exclusively on predictive analytics that used data points including plot theme, viewership trends, director metrics, and the political climate. AI is even used in logistics and delivery systems to allow organizations to schedule work orders based on resource availability, inventory, and timeline.