Artificial Intelligence Chat Is Evolving Faster Than IVR

Nov 11, 2016

Although it doesn’t feel like all that long ago, way back in the 90s one of the most important factors to a call center’s success was the ability to route a customer to the right support agent with the IVR (Interactive Voice Response). Countless hours were spent identifying the most efficient call routing patterns and expert agent capabilities to ensure that your request reached the right person quickly. This technology is still widely used today and there are still teams in the largest companies programming IVR systems to accomplish pretty much the same goal.

As the standard for customer support evolved there have been many attempts to improve the function and the customer experience associated with IVRs to reduce hold times and provide more relevant support faster. Even today some companies will use their IVR system as a way to keep a customer on hold, rather than provide a solution, when agents are inundated with calls.

For those of us who’ve worked in the voice industry for some time, we’ve seen first-hand the attempts to accomplish a customer’s need before reaching an agent. First there was expert agent routing that delivered your call to the agent most qualified to help you. Then came advances in voice recognition, which today has evolved to be a very effective tool to increase containment rates and deflect calls from reaching a live agent. My two favorite examples of the power of voice recognition are Cox Communications and Capital One, two examples of great voice recognition and routing.

Our memory, however, is short. It wasn’t so long ago that we were all pulling our hair out punching digits into the phone or constantly repeating “agent”, “Agent”, “AGENT”, AGENT!!!!!”.

Whether it was a limit of computational power or the sheer cost of developing and implementing advanced call center technology, it took decades for phone systems to be able to front end the customer support process as efficiently as they do today. Thankfully we all survived to see it without boiling over from the hypertension usually associated with calling with a customer service department.

Bad customer experience is definitely not the case with Chat Artificial Intelligence (Chat AI). While we seem to hear about the shortcomings of Chat AI like the disconnected conversations and the robotic like responses, these experiences are usually the product of Chatbots with limited AI functionality or early stage deployments. The increases in both computational power and the massive advancements in machine learning are driving excellent customer experiences that improve over time.

When was the last time you heard of technology actually performing better, on its own, without a ton of additional development work or continuous updates? Well, that’s the case with Artificial Intelligence. Like a person, the more experience it has interacting with customers and information, the better it performs with little need to be manually improved or fine-tuned.

Today, AI Chat can be used to answer a large majority of customer requests and because Artificial Intelligence learns as it is used, customers prefer to interact through AI chat to avoid all of the frustrations commonly associated with calling a contact center agent.

Interested in reading more? Check out our other blogs:

AI: Our Only Weapon Against Climate Change?

Artificial Intelligence, more commonly referred to as simply AI, has been, since it’s early days, changing our lives in many ways. AI has become one of the greatest inventions of the human mind. When thinking of AI, we do not normally associate AI as being involved in helping farmers grow more crops to feed the exponentially growing population, or helping develop cancer treatment, or even keeping kids safe from trafficking and abuse by finding improper online activities. Instead we think of computers to phones, to self-driving cars and robots. However AI doesn’t just power the gadgets that we have grown so accustomed to in our daily lives, but it is increasingly being used to help solve impending social challenges.

One of these impending social issues is the quite literally hot topic – global warming. The challenges of global warming are growing by the day, as its impacts are becoming more severe and harder to manage. Melting ice caps, severe sever weather changes, extinction of species, are just a few of the consequences of the manmade climate change that is plaguing our world today. Despite widespread acceptance and awareness, the rate at which the world is embracing positive change is unfortunately not fast enough.

Fortunately there are many large companies that are setting an example by using AI to develop new ways in which to battle global warming. In fact, it seems as though AI is the only solution we have. It is helping us not only track and our present data, but also analyze our past data so that we can make informed decisions about the future. One such example is the use of AI to collect large amounts of data on land, animals, weather, ecosystems, etc… and organize it, so that scientists and governments can then determine what needs to be done, and the most cost effective ways to engage conservation methods.

We are quite surely seeing more and more AI initiatives being undertaken to help create a more eco-friendly world.

In order to reduce human influence on nature, increasing levels of human interference with natural processes are required” (Harvard University)

Whatever the downfalls of AI may be, its ability to help us against destroying our planet is perhaps its most important trait – because as hard as it may be to accept, our planet is dying and AI can help us prevent that.

Social selling. Difference between Facebook and Twitter

There are obviously some key differences between Facebook and Twitter that make them appealing to different people as well as businesses. If possible, businesses should try to leverage both networks in their marketing and sales efforts.

But marketing approaches for each network differ. Consequently social selling approaches differ as well. Here are some major differences of the two networks that impact sales strategy:

- Twitter lets all the accounts commingle, Facebook makes a definite distinction between business and personal. This can be an issue because a business page cannot proactively connect with individuals with personal profiles. Individuals have to first like a business page and still the business can’t reach out to them directly unless they message first. This is not the case with Twitter, as anyone can follow pretty much anyone.

- Facebook preferred way to market products and promote online sales can be compared to a showroom. The prospects can see the product and purchase it through some other channel, however engagement (with prospects) is limited to friends and followers. Hence growing the number of friends and followers becomes a critical task on Facebook. Twitter does not offer promotional capabilities but engagement activity is not limited to followers. The engagement on Twitter is therefore more straightforward and can lead to direct sales.

- Facebook user data is typically open to friends or followers. Twitter data is typically open to the entire world.

- Twitter is fast (minutes). Facebook is slower (hours and days).

- Twitter is more about building a brand identity. Facebook is more about business relationships.

To summarize, a direct timely engagement could be a good strategy on Twitter. In a typical scenario a user tweets that she needs a taxi or asks where to dine tonight. A taxi company or a relevant restaurant engages in a conversation and secures a customer. It is an efficient approach with immediate ROI.

On Facebook a good strategy is to grow and educate a community of followers. Facebook is excellent for promotional campaigns. This is a longer-term strategy with effects not visible until after several months.