Chatbots: a game changer for customer contact

The next few years, contact between people and organizations will more and more be taken care of by chatbots with human characteristics. At the moment, many organizations determine what role chatbots and artificial intelligence are about to play. In any way, the influence of chatbots on service, marketing and sales shall increase strongly in the upcoming period.

For quite some time we’ve already been aware that chatbots are incredibly popular. The number of worldwide search queries has raised in an explosive matter in the past few years, meanwhile bots have already existed for quite some time. The first chatbot’s name was ELIZA and developed between 1964 and 1966 by Joseph Weizenbaum. ELIZA was able to recognize keywords and could answer with standard answers. Technological developments have made the current chatbots smarter and more cost-efficient.

Alan Turing developed the Turing Test to determine how far a computer can pretend to be human. Chatbots and computer that aren’t recognized as such, passed the Turing Test.

Frank Smit, Chief Innovation Officer at Spotler Engage, tells us about the applications of the chatbots of these days. ‘’You can see a chatbot as virtual customer service employees. The bot ‘reads’ the message, determines the intention of the questioner and ensures a complete set of (customer) details. His job is then about done; the complete set of details are handed over to another employer.’’ Chatbots are the answer for the growing number of web care conversations within the digital customer contact channels as social media, messaging apps and live chat. Organizations are looking for increasingly smarter ways to take into account simple automated questions, without turning in customer satisfaction.

Chatbots support the web care expert in collecting the right information, as a type of virtual assistant. Within HEMA in cooperation with Spotler Engage, a smart bot was worked on. This bot is applicable to all direct message channels. The bot takes opening times of service locations into account and gives responses accordingly. The bot is able to recognize order numbers and other relevant customer details in the text. At the moment that this information is not available yet, then it collects the needed information of clients to finalize the response handling of the question. Service experts can then use this at once.

“The potential goal of a conversational chatbot is to make the process more efficient in order to decrease cost and raise customer satisfaction and employee satisfaction at once.” – FRANK SMIT, Spotler Engage

Chatbots have existed in many sizes and shapes. Think of smart chatbots, integrated in your web care tool and providing information for customer service employers. Bots can however apply another function, such as the smart response-assistant of business analyst. in any application used, bots always work goal-oriented. By asking the right questions, a bot helps the client to ultimately reach the preferred goal.

“Many parties think that chatbots only take care of handling questions faster on the live chat channel. But it is so much more, independent of the channel but also of the application. Not only answering questions but also helping out customers or selling products.” Frank Smit, CIO at Spotler Engage.

The input of chatbots is relevant for every organization with a focus on improving the online customer experience. Within both B2C and B2B organizations, bots are strongly influencing customer service, marketing sales and internal communication.

Better reachability, also outside opening times, is an important challenge for many organizations. Bots are not only useful with offering 24/7 support, but can also make information much faster available. Organizations with a complex information structure, such as municipalities and health organizations, can supply their target group with the right information. That lowers the work pressure of customer service eventually.

Another goal-oriented application of bots can be seen back in the world of banks. Putting together a decent savings plan is a complex and timewasting process. A chatbot can help potential savers directly to choose the right savings account, for example. Missing information can be requested directly and can be used to put together a personal offer. The conversation between bot and client can deliver handy insights by analyzing the customer need, response and result by using a monitoring system.

Intentions and entities
A smart bot works on the base of AI, short for Artificial Intelligence. Imagine that a consumer wants to order a pizza through a live chat on the website. A chatbot knows what information it needs to place the order and ask for the missing information. When all questions are answered, the chatbot gives green light for the order.

1. Does the consumer actually wants to place an order?
2. What size does the consumer want?
3. What combination (for instance ingredients) does the consumer want?
4. Where should the pizza be delivered?

Now you know what role a chatbots can fulfill, what objectives it can serve and how it works in the base, it is useful to know how chatbots are built. Spotler Engage believes strongly in the joining of force of machine learning and human insight. A chatbot is developed in 7 steps, in which it starts with defining the right tasks.

1. Determine the goal and the tasks of the chatbot
2. Develop dialogues
3. Train, train and train
4. Expand your chatbot by connecting it to external systems
5. Invest time in testing

1. Determine the goal and define tasks
It is of major importance to determine the right goal for the chatbot. Where do you want to put in the chatbot? What problems and challenges can a chatbot solve for your organization? Where can a chatbot help your customers better? Think of opening times, reporting meter measures or requesting of product information.

Three possible applications of a chatbot:

• As a support of a service agent, in which a service agent approves or disapproves suggestions
• As work preparer, whereby the chatbot already asks the client automatically for important information such as an e-mail address and/or a customer number
• A chatbot that takes care of service questions by itself

2. Develop dialogues
Before a chatbot can be presented to customers, it must learn to generate appropriate responses that meet the right tone of voice when communicating with customers. This is the basis for a uniform and authentic communication of your company to the outside world. Answers can be generated based on examples from the past. In this way, the stored conversations between customer service employees and customers serve as learning material for the chatbot. However, the chatbot should not only learn on the basis of historical data, but also by giving input yourself.

Another important point is the definition of business rules. Teach your chatbot where he can get information from, when he needs to access external systems and when he needs to request additional information from the customer. In other words: what is the bot allowed to do and what is it not allowed to do? Chatbots are currently becoming more intelligent and able to learn autonomously. But it’s important to set business rules to keep control.

3. Train, train and train
A chatbot must learn to understand what you mean. While in the past chatbots were mainly controlled by a script, nowadays bots can be made smarter using artificial intelligence and technology. This allows them to recognize the intention of the post (intention), but also to filter data from the message (entities), such as an email address or a customer number. In this way a bot can be trained to understand messages.

To train your chatbot, you can use your existing customer service system. To do this, categorize the existing customer inquiries and answers. In this way, you ‘feed’ the chatbot with various posts and various possible answers to which the customer could ask a question.

4. Expand your chatbot by connecting it to external systems
By adding external information systems, the chatbot learns to understand the customer better an addition with the CRM system enriches the service process and gives the bot more information for a proper handling of the questions. This increases the usability degree and ultimately the customer satisfaction level as well.

5. Invest time in testing
Test your chatbot continuously. Does it always work equally well? And if not, why is that? Can you feed him with more examples to improve his service? Regular tests will give you a better understanding how the chatbot performs. Take the time to take this step, because the success of your chatbot has a direct impact on customer satisfaction.

Start with a small application, so that what happens remains measurable. Work your way up step by step, to eventually for instance optimize customer service and increasing customer satisfaction. Do not underestimate the information and knowledge that is available internal!

“Many might still be getting used to the idea that chatbot is a part of customer service and web care does, but it is merely a ‘second industrial revolution’. Just as men thought that everyone is about to lose their job to machines in that time, that is how it is now with chatbots. “It may take a while, but then it becomes clear that the machine is not a replacement for human, but just an addition to a very useful tool.” – Frank Smit, CIO at Spotler Engage.

The right decisions in the development of a chatbot lead to a fundamental change for service, marketing and sales. Spotler Engage develops smart chatbots wit hand for organizations. The right input of AI within a controlled process of tasks, business rules and training results in bots that understand and help out the client better. Aside of that, the production costs of smart bots remain lower than when a bot of rule-based language recognition is developed. Machine learning and AI play a large role in guiding the customer through the customer journey and are not meant to automatize employees away.

A combination of chatbots and people is successful when people know of each other when tasks and actions are carried out. That is way Spotler Engage integrates chatbots within its own existing web care solution. This results in one dashboard for the settling of online customer service and web care, supported by bots as virtual assistance, work preparers of data analysts.