80% of customer data is unstructured such as emails, phone calls, meetings, complaints, social comments, tweets etc. sandsiv+ VOC HUB offers automatic text mining solutions based on deep machine learning algorithms. Topic detection and sentiment analysis are available out of the box.
Distribute the right information, to the right people at the right time.
VOC HUB™ sends information in real-time to your CRM system such as salesforce.com, SAP Cloud, Microsoft Dynamics, and many others.
Oh, you don’t have a CRM yet? No worries! The VOC ACT! module can support the
Insights gathered through the Customer Intelligence process must immediately become actionable.
Avoid analysis paralysis and provide actionable insights to frontline people in real time.
At the same time, create a continuous customer intelligence feed to support your customer experience initiatives with strong evidence.
You cannot manage what you cannot measure.
sandsiv+ VOC HUB offers infinite numbers of custom dashboards.
Create and share with your organization important insights to support your customer experience initiatives. Cross tab Net Promoter Score, Customer Effort Score and many others with internal and external customer data and the results of the topic detection and sentiment analysis of verbatim feedback.
VoC Hub™ is the only truly agile, end-to-end AI-powered CXM platform that easily adapts to the complex customer experience management and analytics requirements of large organisations and it flexibly integrates with their IT ecosystems at relatively low cost of ownership.
Differently from many other VOC solutions, VoC Hub™ was built around a data lake (MongoDB) as core storage capability, that facilitates the co-location of data in various schemata and structural forms, which is used for various tasks including reporting, visualization, analytics and machine learning. Replication and synchronization with your data lake is easy through the built-in API.
Is a fully customizable customer feedback management (CFM) solution that can capture the Voice of the Customer across multiple channels, including SMS, IVR, email, web, digital channels, all in multiple languages and across multiple touch points. It allows collection of all types of feedback including direct, indirect and inferred.
It Is a deep machine learning text mining function with an easy to use interface to process all kinds of unstructured feedback and information to uncover key customer experience drivers.
It is an advanced ‘vector-based’ text classification and sentiment analysis engine that uses deep machine learning algorithms to accurately classify thousands of customer feedbacks, grouping specific content, business relevant categories as well as customer sentiment in a fraction of a second.
Customizable analytics and dashboarding solution that allows effective analysis and visualization of all the VOC and other customer data on VOC Hub™ in an intuitive, flexible, and fast way. Its extensive qualitative and quantitative analysis features turn the data into Customer Intelligence, to present it to the right people, in the right form, at the right time.
Support your close-the-loop process with an easy-to-use ticketing and cases reporting system. Manage your detractor by assigning and addressing the cases to the right people at the right time for the proper and correct follow-up action.
sandsiv+ IS BUILT AROUND THE CUSTOMER EXPERIENCE FRAMEWORK TO HELP BUSINESSES INCREASE CUSTOMER ACQUISITION AND RETENTION
This is the type of voice that most people imagine when they start talking about the voice of the customer. The direct VoC refers to any touchpoints whereby the customer expects the business to be listening, and very possibly is expecting some kind of response or reply. These touchpoints include dealing with support staff or a call centre directly, as well as less immediate forms of communication such as sending in a formal letter of complaint.
The indirect VoC refer to those instances whereby the customer is speaking about the business, but is not speaking directly to the business. Good examples of the kinds of channels that naturally carry the indirect voice of the customer are social networking sites (such as Facebook, LinkedIn, Twitter and Google+), email (between non-company related parties) and internet chat sessions.
The inferred VoC is the hardest of the three voices to understand. The inferred voice of the customer is extracted from historical VoC data using predictive analytics. Put simply, the inferred VoC is the prediction of what a customer would say in a definable circumstance. This prediction is arrived at by analysing warehoused VoC data.
Data visualisation is a general term that describes any effort to help people understand the significance of data by placing it in a visual context. Voice of the Customer patterns, trends and correlations that might go undetected in text-based data can be exposed and recognised easier with our data visualisation solution.
Natural language processing (NLP) is a subfield of computer science, information engineering, and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to process and analyse large amounts of natural language data.
The aim of Enterprise Improvement process is to help companies operating in all sectors and in any geographical area to do more with less and to reinvent themselves in order to increase market share in an increasingly competitive market.
sandsiv+ is more than a technology platform.
We are a rapidly-growing technology company that provides customer intelligence AI analytics solutions to companies worldwide.
Are you seriously considering your next steps in customer experience or in your net promoter score project?
Then it is time to talk to us.
SANDSIV SWITZERLAND LTD.
8005 – Zurich
Call us at +41 43 205 2132