Project description
New customer experience with CLARA superbot
Countless institutions and companies – from airlines to banks and wireless service providers – need to manage, monitor and process customer requests daily. They rely on call centres to manage this process, which is very time consuming and expensive. The Superbot is a conversation platform powered by Google algorithms and based on machine learning and artificial intelligence. Backed by high-data analytics, research, and self-learning, it can also manage virtually unlimited visitors. The EU-funded CLARA project aims to support the development of the CLARA Superbot platform, a proprietary technology of PREDICTIVA. It will use the speech-to-text feature to convert full audio recordings into text and analyse it automatically without losing detail. It’ll dramatically change the customer service experience.
Objective
Airlines, banks, electrical utilities, cable companies, wireless service providers and high-tech retailers rely on call centers to manage and response the massive amount of customer queries. However, there is a lack of detailed auditing from the brands to the contact centers to ensure the best customer engagement or it is only based on the manual and aleatory control of the calls.
In every Call Center it is necessary to monitor calls to verify that voice interactions with clients or leads conform to the guidelines and policies of quality established by the company. While calls are abundant in useful data, it’s impossible to manually evaluate and analyze each one given their staggering volume. In fact, only about 1% of customer call data is assessed in random quality evaluation processes. Since quality monitoring is done manually by listening to random calls and since it’s impossible to review all the calls, only a small percentage of the recorded calls is being evaluated and much important data is lost.
CLARA, is a Superbot capable of analyzing and interpret spontaneous conversations in real life conditions. CLARA is a proprietary technology of PREDICTIVA based on Deep Learning, a set of machine learning algorithms with multiple layers of nonlinear processing and learning representations of characteristics in each layer.
CLARA Super Bot Speech Analytics offers a better way to leverage customer call data. The tool transcribes all recorded calls in their entirety, then analyzes the interactions using advanced speech detection technology. Through datamining these transcriptions, it allows to discover actionable insights for improving brand - and won’t ever worry about missing a detail again.
CLARA offers a variety of must-have features to improve customer service experience. The Speech-to-Text feature automatically converts full audio recordings into text to easily identify root causes in customer interactions.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.2.3. - INDUSTRIAL LEADERSHIP - Innovation In SMEs
MAIN PROGRAMME
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H2020-EU.3. - PRIORITY 'Societal challenges
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H2020-EU.2.1. - INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
SME-2 - SME instrument phase 2
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-EIC-SMEInst-2018-2020
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
29602 MARBELLA
Spain
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.