SentiSquareCX SIGNED
Qualitative Jump in Customer Experience: Omnichannel Impact of Distributional Semantics
Total Cost €
0EC-Contrib. €
0Partnership
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0SentiSquareCX project word cloud
Explore the words cloud of the SentiSquareCX project. It provides you a very rough idea of what is the project "SentiSquareCX" about.
Project "SentiSquareCX" data sheet
The following table provides information about the project.
| Coordinator |
SENTISQUARE SRO
Organization address contact info |
| Coordinator Country | Czech Republic [CZ] |
| Total cost | 71˙429 € |
| EC max contribution | 50˙000 € (70%) |
| Programme |
1. H2020-EU.3. (PRIORITY 'Societal challenges) 2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs) 3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies) |
| Code Call | H2020-SMEInst-2018-2020-1 |
| Funding Scheme | SME-1 |
| Starting year | 2019 |
| Duration (year-month-day) | from 2019-06-01 to 2019-11-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | SENTISQUARE SRO | CZ (PLZEN) | coordinator | 50˙000.00 |
Map
Project objective
Understanding customer voice is fundamental in building products, services and customer facing processes. Although companies have abundance of data, they still lack insight. According to Gartner, fewer than 10% of companies have a 360° customer view, and only 5% are able to use it to systemically grow their businesses. The reason is that listening to customers has been difficult and technologies available either arduous to use, non-scalable or providing skewed interpretation of the data collected. To meet the needs of data intensive industries and deliver cost-effective NLP, we offer our AI-based, self-learning solution for any text. It is language agnostic, applicable thus to any language without limitations and even in multi-language datasets. Compared to alternatives, where search content is predefined (pre-tagged), our disruptive technology genuinely reflects the actual meaning of text, not being limited by lexicons or biased by content predefinition. The unique qualitative advantage of our engine stems from our research in Distributional Semantics. This approach enables the vectorial representation of word meaning. Every word is associated with a vector which reflects the contextual (distributional) information across a text dataset. Vectorial representation allows us to quantify the similarity between meanings. On this basis, our algorithms are employed to automatically discover hidden patterns. We realize that most data in organizations is about customer engagement. For this reason, we want to offer the portfolio of products covering the entire multichannel 360° view: providing AI-powered analytics from insights, through inbound communication assistance, to contact center process automation to semantic segmentation. Private and public organizations, with large volumes of daily communication or large base of customers are our main target segments, representing substantial business opportunity across industries and geographies.
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The information about "SENTISQUARECX" are provided by the European Opendata Portal: CORDIS opendata.