The Bots are Coming! Will They Save Customer Service?


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Today’s customers are impatient. They want to — and have the right to — get answers to their questions and concerns about a company’s products and services without being in the need to perform lengthy searches or to dig around. This holds true for pre-purchase questions as well as to post-purchase questions.

Enabling this is an important part of good customer service. And good, or better yet, excellent, customer service is one of the core drivers of a positive customer experience.

But how does a typical service flow look like, from the customer’s point of view?


I have an issue. Hmmm, let’s Google this. Maybe there is a solution on the web, or in their community? Bummer, nothing. Do they have self-service, or can I search the web site? Ahh, here, something comes up! Oh, dear, that is not quite what I look for. Is there a chat? No? Ok, then let’s call them…

There are scores of studies confirming that customers want their time valued and that they will abandon online purchases if their questions are not answered quickly and easily, or that they will stop doing business with a company altogether because of bad experiences, sometimes even after a single bad experience, e.g. a shocking 89 per cent according the 2011 Rightnow Customer Experience Report; or 62 per cent according to the 2015 Parature Global Customer Service Report. On a more positive note, Forrester Research finds in their 2016 report on The Future of Customer Service that 73 per cent of customers consider valuing their time as the most important way to provide good service.

At the same time, customers are starting off with search and self-service, while talking with a service agent on the phone is still vastly popular. A non-representative poll that was conducted during a webinar that I recently attended also confirmed this.


Source: What Should Your Business Be Thinking About to Grow BIG in 2017?

The number of customers turning to chat after self-service fails is steadily increasing and has reached 65 per cent already in 2015, up from 38 per cent in 2009, according to Consumer Technographic Lifestyle Data 2009 – 2015.

So, as per the scenario above, customers first try to educate themselves before contacting a company via phone, chat or mail.

It is the Customer’s Way – or No Way

As I have written before, an important part of providing good service is being available to help the customers on their preferred channels, at the time of their choosing, and at their pace.

Theirs, not the company’s!

This includes that a customer, who initiates a conversation, or engaging in a conversation that is initiated by a company, may not respond in a while, or chooses to continue using another device, or both. On the other side a customer will not accept the company being unresponsive or losing information she already gave during handovers between different service agents. Customers expect the company to remember information about them – when it suits them, not only the company.

The conversation between a company and a customer is both, asynchronous and asymmetric. Just it is no more asymmetric in favor of the company, but in favor of the customer instead. And the company needs to deal with it.

The way to do this is an integrated, intelligent, and efficient service offering that helps customers getting to the information that they want, at their pace. Efficient, integrated and intelligent are the key words here. The chat equivalent of holding music is not an option. Scaling the call center infinitely isn’t either.

Then how to achieve or maintain positive customer experiences in service engagements?

What Does it Mean?

The customers’ choice to increasingly prefer self-service over assisted services and then proceeding at their own pace is a huge opportunity for businesses.

It allows them to build communities and enable service automation via bots, with both being backed by a learning system. Knowledge contributed by human agents trains the bots, which in turn free them to do the hard work and support them in the ongoing solution finding process. Communities and their body of knowledge help reducing the number of calls to the call center altogether and bots help call center agents to scale beyond one conversation at a time.


At the core of the technical part of the solution are knowledge bases, machine learning and bots. Service agents obviously still need to be well trained, perhaps more than ever, as they will get an increasingly higher share of difficult to answer questions. Routine matters need to be taken care of by the machine.

In 2017 we can take it as a given that chatbots will become mainstream in service solutions. As covered by Gil Press, Forrester Research’s recent AI technology radar has placed virtual agents, machine learning platforms, robotic process automation and text analytics/NLP into the growth stage of their life cycle. Speech recognition and semantic technologies are out of the baby throes while natural language generation is still emergent. All these technologies are relevant.

The future of assisted customer service clearly sees bot-supported interactions with the bots being the first point of contact of assisted service. The bots gather — or already have access to — relevant contextual information coming from the customers’ current and previous interactions with the company. They then, based upon the available data and information, and the internal knowledge base plus other sources, e.g. communities, determine answers for the simpler questions, and seamlessly hand over the too difficult ones to human operators.

And they learn from the proceedings of the ongoing conversation.

Making it Work

Putting all this together there are four main courses of action that business leaders need to pursue to gain both, effectiveness and efficiency in customer service, thus creating lasting positive customer experiences:

1. Think of creating a community. Not every company is big enough or has sufficient resources, but a community is a strong helper when it comes to self-service – and self-service is clearly on the rise.

2. Consider the knowledge base, covering internal as well as external (community) knowledge, a very high priority. Data and information needs to be attributed and converted to knowledge so that external (Google, Bing, etc.) as well as internal search engines can find relevant information and put it to the top of the result list. This is a learning system utilizing an intelligent agent that learns from the queries and their results. This system will also help the call center agents. Knowledge management is absolutely the foundation for self-service as well as well as assisted support.

3. Strongly consider chatbots that use contextual information and act as a first line of interaction, both in customer initiated as well as company initiated interactions. Minimally they keep the customer engaged and do a seamless handover to a human agent. This does not only help the customer, but the agent, too, as she is prepared and can dig right into the problem. As the chatbots are supported by a learning system the problems they solve can become increasingly complex. Additionally the bots do support the agent with their ability of continuously suggesting good solutions based on the knowledge base, suggesting tags for new articles, etc.

4. Human agents need to be well-trained, as the first level service will increasingly be taken care of by automation. Focus on effectiveness, not efficiency. The chatbots will benefit from the knowledge they create as their search patterns and recommendations become learning material for the bots.

Thomas Wieberneit

Thomas helps organisations of different industries and sizes to unlock their potential through digital transformation initiatives using a Think Big - Act Small approach. He is a long standing CRM practitioner, covering sales, marketing, service, collaboration, customer engagement and -experience. Coming from the technology side Thomas has the ability to translate business needs into technology solutions that add value. In his successful leadership positions and consulting engagements he has initiated, designed and implemented transformational change and delivered mission critical systems.


  1. Some really interesting thoughts! Would love to see this play out in reality – have you got any examples/case studies of companies using bots for customer support? What issues did they run into, and were they able to measure an increase in customer happiness and retention?

  2. There are multiple really helpful use cases available for AI Chatbot+Human integration, where up to 90% of the traffic was handled by the Chatbot.
    I did one similar project a few years ago, the key there was that the best results were measured in environments with relative simple Q&A’s (eg NAP change, product upgrade, send brochure); I question if there are any examples of AI handling really complex, multi-input use cases (eg outage analysis). Tend to think we’re still in the “little AI” phase. Certainly promising, but for me not the end of the physical customer care agent, yet.

  3. Helena, thanks for your comment and question. I do think that we are very much talking about an emerging market. Down here in NZ I do know of two proof of concept implementations, one geared a bit to tracking and tracing of deliveries, accessing an OLTP-like system, and another one answering questions based upon a knowledge base. In Australia is a big live governmental implementation that even uses Natural Language Generation. Some contacts in helpdesk software for smaller companies tell me that they see not much demand but that they are anticipating a rise, preparing to build a solution. A fairly big retailer (well, for the ANZ scale) tells me that bot-support for their call center is not on their priority list at the moment. But then, knowing them, their priorities can shift fairly fast …

    Putting a vendor name here (and no, I am not paid by them 😉 ) – I know that Microsoft has a bot that connects to Dynamics CRM and is capable of e.g. creating cases right out of the box.


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