Augmented agent: the customer relationship of the future?

These days, companies are deploying considerable resources to excel in customer experience. They are increasingly using artificial intelligence (AI) to manage their customer interactions, and this trend is accelerating. One of the most innovative solutions is the "augmented agent".

The promise? To be able to combine human skills with AI efficiency to improve customer service effectiveness ✨

AI is not the solution to all your ills 👀

With the advent of new technologies and recent advances in artificial intelligence, companies are facing new challenges. To modernize and meet their customers' expectations, they must..:

      • 🎲 Adapt their processes and working methods. Digitization often implies changes in the way people work and communicate. Customer service teams need to adapt to these changes to be efficient and productive.

      • 🤯 Manage the complexity of omnichannelity, which can complicate customer interactions due to the number of channels available (e-mail, chat, social networks, ...). Companies need to be able to guarantee a consistent experience of equivalent quality across all channels.

      • 🔒 Ensuring data security. Digitization is leading to an increase in data and infrastructure security risks. Companies need to implement robust security measures and keep them constantly evolving to avoid losing the trust of their customers.

      • 🧞 Find the right tools. There are many, and they're often very uneven. Companies need to find the tools best suited to their needs, budget and existing infrastructure to deliver on their customer experience promises.

      • 💪🏼 Train employees, as the digitization of processes and methods can create new training needs. Mastering new tools and work processes is the key to guaranteeing the best possible agent productivity. Investing in human resources training ensures that they are always able to meet customer needs. Artificial intelligence promises to play a decisive role in enhancing agents' skills. But it will also make it easier for them to adapt to increasingly rapid change.

    In short, digitizing a customer service department offers many advantages, but also represents a major challenge for companies.

    To succeed in this transition, companies must be ready to adapt to new work processes, manage the complexity of customer interactions, guarantee data security, find the right tools and train their staff.

    AI, like many other innovations, makes it possible to achieve certain objectives, as long as it is used in a favorable context and correctly positioned.

    The augmented agent: trend or utopia? 🤔

    This is the promise of AI. Enabling companies to embrace galloping digitalization by facilitating transformations over short cycles.

    The transformation of the customer service agent profession has been underway for several years. All the signs point to an evolution in the role of agents, and above all to greater complementarity between humans and AI. In fact, according to a study by Gartner, companies that use chatbots and other forms of AI for customer service see a 25% increase in customer satisfaction.

    However, customer satisfaction is even higher when AI is used in combination with human agents. Customer satisfaction increases by an average of 35%. This is the case for companies using tolk. ai solutions such as Aéroport de Marseille Provence, Régie des Eaux d'Azur, Agorastore and FMA Assurances.

    The benefits of AI in customer service agent productivity 💪🏼

    The use of AI in customer relationship centers can also increase agent productivity.

    According to a study by Salesforce, 72% of customer service agents say that AI allows them to focus on more complex tasks, but get rid of repetitive ones. But AI can also help reduce agent training time, which can take up to six months.

    How? By automating certain repetitive tasks, providing them with crucial information at the right time, or generating precise answers from immense unstructured knowledge bases.

    This is the innovation behind tolk.ai's Genii. Able to learn several thousand pages of unstructured knowledge (pdf, word, website, excel, ...), Genii answers all its users' questions from the data it has been trained with(the beta is available, sign up 👀).

    This highly innovative technology promises to further reduce response times. But also to improve the customer experience. It also marks the beginning of a new complementarity between agents on the one hand, and artificial intelligence on the other. The latter will shorten improvement cycles and facilitate agent training. In the medium term, this will improve job satisfaction and reduce internal turnover 🙌🏼

    AI is not miraculous but practical ✨

    Aside from the media excitement surrounding the latest innovations in artificial intelligence, it's important to understand that artificial intelligences are only useful when they are correctly positioned, fed with relevant data and calibrated to intervene in a defined context.

    To maximize the benefits of human-AI collaboration, companies need to provide agents with tools designed for their specific needs. And feed them with data that is consistent, clean and as structured as possible.

    According to a survey conducted by Accenture, 61% of customer service agents feel that the tools they use are not suited to their work. This can lead to a reduction in productivity, job satisfaction and customer service quality. The FOD triptych (Training, Tools, Data) is central to the success of an AI implementation project dedicated to agents.

    Let's take the example of the latest generative AIs, more specifically LLM models, of which GPT-4 is the most talked-about at the moment.

    Thesegenerative AI models may seem highly efficient and hyper-performant, almost magical. In reality, they are very useful for certain tasks. But it's important to understand their limitations in certain situations. In the case of a company wishing to improve the productivity of its customer service or automate a large proportion of its interactions, there are dangers. These so-called "generalist" models have not assimilated the business knowledge required for such use. It is therefore necessary to rely on adapted tools and models, trained on the company's data and "fine-tuned" to meet its requirements.

    The augmented agent is still in its infancy...

    In conclusion, the augmented agent is a trend that is gaining popularity in corporate customer relations centers, thanks to its benefits in terms of customer satisfaction and productivity.

    Nevertheless, to make the most of it, companies need to provide agents with tools designed for their specific needs and AI powered by corporate data, to guarantee a quality customer experience and build loyalty among their customer service agents.

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