It’s big and it’s clever.
TELECOMMUNICATIONS, ARTIFICAL INTELLIGENCE AND BIG DATA
Connex One have aligned with modern advances in technology to engineer a solution which positively impacts on the way people interact with one another on a global level.
Connex One provides a comprehensive data analytics module to enhance future customer engagement. Armed with data- mined intelligence, businesses can better understand and engage with their customers. Throughout the user journey, through the multimedia layer and modules, data is automatically generated.
The Connex One platform offers:
- Data Insights
- Data Reports
- Gender Insights
- Location Insights
- Age Insights
- Historical Charts
Connex One provides a data warehouse for clients to house all of their customer data. The data warehouse is elastic and can hold millions of data records and transactions without impacting performance. Data can be imported or extracted via API feeds, SQL, Web Services or via manual import or export.
Example Sources of Data:
- Online Websites
- 3rd Party API feeds
- CRM systems
- Inbound Live Chat / SMS / Voice and Email
data per second
90% of all data that
exists today was
created in the last
Connex One provides an API feed which can identify, sort, process and receive inbound data. All of which are then organised into files within the Connex One platform.
The API is fully secure and can facilitate multiple feeds at the same time.
Connex One also provides a control API that allows clients to access the communication platform and data level from remote platforms such as back office CRMs.
All data within the Connex One platform provides useful insights via a friendly interface. Being informed allows our clients to make better decisions on how the data can be utilised to maximise performance and data penetration.
Example usage of Data Insights:
- Review and maximise geographical performance
- Review and maximise gender performance
- Review and maximise age performance
- Review and maximise snapshot analysis against previous weeks, months
- Review, maximise and limit upward / downward trends
Data can be archived from the system based on rules or logic to maintain an active and relevant data set to maximise performance. Data archives can still be accessed, extracted and reported upon for MI Purposes.
Examples of Data Archive:
- Move data which is no longer used to a separate storage area for retention
- Store data which may be required for regulatory compliance
- Retain data which may be analysed for data insights to understand past performance
- To keep the live data bases lightweight and maximise performance
Our customers can create rules to organise/assign data into lists, campaigns or teams as it Flows through the system.. The data becomes more refined and organised over time.
The Data Waterfall strategy can be outcome or time based.
Uses of Data Analytics:
- To move a data record from one department to another
- To penetrate uncontacted data on new channels
- To create new data from existing data records for cross selling or marketing purposes
- To distribute Data evenly between Sales Operatives