Learn how to improve customer satisfaction and create added-value using Google Contact Center AI
Read about the key outcomes of the webinar on March 30th presented by
Matthieu Myszak – Data Consulting Director, Artefact and Julien Tribout – Sales Lead Google Contact Center AI

In today’s competitive business environment, customer experience is becoming a key differentiator for organizations well aware that it is more cost-effective to keep an existing customer than acquiring a new one and that a disgruntled customer well-handled can be turned into an advocate for your brand.

The recent advancements in technology and artificial intelligence can be applied to your own customer interactions and be a tremendous support to help your organization profit from productivity gains, improve customer retention and create additional revenue.

Having your customers talk to a robot can seem out of a scifi novel. But actually, it is already a reality for hundreds of millions of customers that have regular interactions with interfaces powered by artificial intelligence.

Ultimately, the goal of an optimal integration is to have customers talk like they usually do when interacting with a conversational agent that can analyse their sentiment, provide useful information, and answer recurrent standard requests as well as complex issues. Also, the virtual robot can pass on the caller to a human agent when needed. Beyond this conversational agent, Machine Learning technologies record the interaction for further improvement in setting new and sophisticated protocols of problem solving.

1) The main advantages of using artificial intelligence for call centers

What differentiates customer service boils down to the quality of the relationships and the overall user experience. In that regard, AI can be a useful tool helping organizations achieve unmet customer expectations.

An artificial intelligence-powered customer center is a crucial asset for three reasons:

  • reduce operating costs (via automatisation, reduction of average handle time)

  • improve the quality of the service and the customer satisfaction (via an increased reactivity and availability)

  • offer opportunities for cross-selling and upselling customers

The revolution of conversational technologies has already begun. Today, internet users are becoming more and more familiar with voice commands and chatbot interactions thanks to natural language understanding capabilities (NLP) wired into mainstream digital products, such as Google Voice Search, Google Assistant or Google Home.

According to a recent Gartner study, by 2023, 70% of consumers will prefer to interact with a vocal interface than a real person and 40% of all customer interaction will be fully automated.

2) How does it work

Google Cloud has been developing virtual assistants capabilities for years and has created a product that can be used for business purposes.

Artificial intelligence is not always meant to replace humans as it can be utilized to augment real agents. Thanks to the robot, call center operators can concentrate on complex and higher value situations and be freed from small, repetitive and low-value tasks. The chatbot is also critical in providing assistance to the operator. In certain situations, maintaining a human contact is key.

With the support of artificial intelligence, the customer service agent becomes an “augmented agent”, meaning that the virtual assistant listens to calls in real-time and provides contextual assistance letting the human stay focused on the conversation and expressing empathy towards the customer.

3) Concrete business cases showing tangible benefits in improving customer satisfaction

Businesses of all sorts could benefit on both sides from a positive impact by powering their customer service with artificial intelligence:

  • For call service operators
    Improve efficiency and focus, reduce churn, provide opportunities to upsell and cross-sell

  • For customers
    Improve user experience with a customer service available 24/7 with no waiting time, accelerate retention and customer loyalty

“If a customer asks for the status of his order, the virtual assistant has to provide the right request and give the correct information.”

4) Seamless integration into your legacy system

For optimal performance, the Google Contact Center AI must be integrated into the call center workflow, work with the existing databases and documentation (via APIs) and the front desk interfaces.

Organizations need to bring a multidisciplinary team to achieve this project according to their needs and their own IT architecture.

Before being set up, a chatbot needs to be fed with customer interaction data. The bot needs to be trained by listening and analyzing past customer interactions. That will enable the virtual assistant to be able to provide value immediately with high levels of customer satisfaction. Existing data can be emails, chat messages or voice calls. The data will help train the model according to the customer journey and the expected optimisations.

“If we have to manage use cases of a client from the banking industry, we will not train the AI tool the same way that if it was for an ecommerce brand, for example.”

It can take from one up to three months to integrate the artificial intelligence solution into an existing customer service depending on the number and the complexity of use cases, and number of integration points to access.

“Deploying a virtual agent for an insurance company that can automatically file a damage claim is more complex for example than if you are asking for the status of your order on a ecommerce website.”

In the event that a business doesn’t have any data to analyze or precise use cases to aim for, it is possible to implement a working solution by asking each caller a prompt such as “Could you please tell us the reason for your call ?” and then letting them access the traditional customer experience journey. By analyzing the initial answer and the human agents’ interactions, the artificial intelligence will get trained to quality future interactions.

5) Why rely on a partner

Before taking the task of implementing a virtual assistant solution into your architecture, it could be useful to bring in an experienced partner that could assist you in the different steps of the project and help you maximise value.

Artefact has been helping clients, in various industries, turbocharge their call centers with artificial intelligence. We provide assistance in different ways:

  • identification and prioritization of use cases

  • setup and training of artificial intelligence solutions

  • development of integrations to collect relevant data

Our company has extensive experience working with both partners and service providers from the digital, data and artificial intelligence industries. Artefact’s method is centered on featured teams, composed of members with complementary skills, from business analysts to data scientists and software engineers, that can help projects come to life.

Our company has extensive experience working with both partners and service providers from the digital, data and artificial intelligence industries. Artefact’s method is centered on featured teams, composed of members with complementary skills, from business analysts to data scientists and software engineers, that can help projects come to life.

“We don’t usually think of adding a UX Designer to feature teams but this role is important, as it helps give a personality to the virtual agent that reveals your unique brand image”

Setting up a bot that is both well-embedded into your data architecture and provides usefulness to consumers is a goal that can take some effort but can be reached when organizations make it a customer experience priority.


An artificial intelligence, such as Google Contact Center AI, integrated into the data architecture of your customer service will supercharge your customer experience.

The machine learning capabilities and recordings of interactions provide a constant feedback loop that helps the performance of the virtual assistant and the use cases that can be addressed.

The right partner for an artificial intelligence project can help organizations smooth out the definition and implementation phases and achieve immediate performance and business gains, while providing useful industry benchmarks and key learnings from previous experiences.

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