Conversational Data Intelligence drives innovation and customer acquisition
Re:infer helps telecommunications companies extract crucial insight from their unstructured communications data, boosting efficiency and customer loyalty.
Telcos lack insight into the causes of customer dissatisfaction and process inefficiency
Telcos know they need an innovative approach to keep up with customer demands for new kinds of content, while also delivering competitive coverage and performance.
However, transformation starts with data. Telcos preside over masses of unstructured communications data they are unable to understand or exploit. Until they overcome this challenge, operators will continue to miss out on the insight they need to innovate forward.
Re:infer turns any message into structured actionable data, enhancing visibility, driving innovation and enabling automation
In customer experience, Re:infer reveals the value in every conversation. From customer calls and emails to chat support and forums, every customer touchpoint is understood, analysed and actioned at scale.
In operations, Re:infer provides visibility into thousands of manual and grey processes that run between the shared service centre and the business.
Tight integrations with enterprise automation tools like Robotic Process Automation allow Re:infer to bridge the gap between requests expressed in natural language and actions downstream.
Telcos use Re:infer to understand their communications, drive process efficiency and customer loyalty
- Discover the actions and behaviours behind customer loyalty
- Identify the drivers of failure and value demand
- Bring visibility to the drivers of churn
- Uncover actionable insights that drive personalisation and promotions
Cognitive contact centre
- Analyse customer calls to detect root cause drivers of customer pain
- Compare the performance of customer service agents
- Uncover hidden relationships between product, experience and loyalty
- Discover and quantify all manual processes
- Detect root-cause of exceptions and process, systems and people failure
- Identify opportunities for automation and self-service
- Make all communications data structured and actionable in the wider IT real-estate (RPA, CRM, CMS, SCV, ERP)
- Deliver straight-through processing of requests
- Optimise change initiatives
“When I joined Farfetch I was totally cynical about text analytics. Re:infer has really changed my mind on that. The power of taking detailed qualitative feedback data and quantifying it is really special. Re:infer has definitely been good value for Farfetch.”
“With requests coming in through multi-channels, unstructured comms is a huge part of day to day life at Deutsche Bank. With that backdrop, how do we respond quickly to clients? How can we help clients facilitate payments and transactions? Being able to navigate and create structure out of unstructured data makes it easier to respond to our customers, faster.”
“The enterprise is built on communications. It should be no surprise that, to digitally transform, NLP is not just a nice-to-have, it is a must-have, which is why our partnership with Re:infer is so important to us and our clients. Re:infer's deep learning platform allows us to unpick customer intents and unlock understanding in unstructured processes across the business.”
The Re:infer platform truly follows the low-code/no-code mantra with rapid models created in hours by process SMEs, not data scientists. Re:infer is at the cutting edge of the Intelligent Automation spectrum.
"Re:Infer enables us to have a more data-driven approach, giving us the chance to digitise qualitative customer feedback, and even to embrace the so-far ignored silent majority of customers. As a CX leader, I feel much more empowered when our analysis is linked to revenue."
Re:infer enables us to hear every customer and plays a critical role in our customer-centricity strategy. With Re:infer we can continually improve our product, service and support to meet the demands of our customers.
“Re:infer's AI platform lets us understand what our customers tell us – at scale. Ultimately it helps us make better product decisions.”
“We were able to capture years of the bank’s domain knowledge essentially overnight.”