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..:
🎲 Adapter leurs processes et leurs méthodes de travail.
La digitalisation implique souvent des changements dans la façon de travailler et les méthodes de communication. Les équipes de service client doivent s’adapter à ces changements pour être efficaces et productives.
🤯 Gérer la complexité de l’omnicanalité.
Cela peut complexifier les interactions clients en raison du nombre de canaux disponibles (e-mail, chat, réseaux sociaux, …). Les entreprises doivent être en mesure de garantir une expérience cohérente et de qualité équivalente sur tous les canaux.
🔒 Assurer la sécurité des données.
La digitalisation entraîne une augmentation des risques pour la sécurité des données et des infrastructures. Les entreprises doivent mettre en place des mesures de sécurité robustes et les faire évoluer en permanence pour ne pas perdre la confiance de leurs clients.
🧞 Trouver les bons outils.
Ils sont nombreux et souvent très inégaux. Les entreprises doivent trouver les outils les mieux adaptés à leurs besoins, à leur budget et à leur infrastructure existante pour tenir leurs promesses en terme d’expérience client.
💪🏼 Former les employés.
La digitalisation des process et des méthodes peut créer de nouveaux besoins de formation. La maîtrise des nouveaux outils et processes de travail est la clef pour garantir la meilleure productivité des agents. Investir dans la formation des ressources humaines permet de s’assurer qu’elles sont toujours capables de répondre aux besoins des clients. L’intelligence artificielle promet de jouer un rôle déterminent dans la montée en compétences des agents. Mais aussi de faciliter leur adaptation aux changements toujours plus rapides.
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.
