LivePerson is probably best known for its real-time text chat feature on many e-commerce sites that connects vendors with customers to support sales and service requests. These chats help vendors increase the conversion of website visits into sales – at the same time improving profits, lifting customer satisfaction, and reducing costs.
Over the last several years, LivePerson has been transforming itself from a reactive to an active and now, a proactive platform that is leveraging text analytics and natural language processing (NLP) that helps with pushing offers and coupons to prospective buyers in order to reduce cart abandonment.
While the conversion rates via desktop or laptop clients are relatively high, cart abandonment when dealing with mobile purchases is still a big challenge. In the middle of 2012, LivePerson acquired Look.io that had a software solution that enabled mobile users a very similar real-time connection with the vendor.
As Dr. Ellis shared with Neuralytix, some of the challenge of improved customer experience lies in the operations of most vendors. Live chat and voice support are often funded by different internal organizations that leads to disparity between service levels delivered via different media.
Combining text analytics and NLP together creates a consistent level of understanding of the conversations that take place independent of media. It also creates the ability to generate a knowledge base that can be used to improve machine understanding and automation that helps to reduce human intervention that leads to a more predictable, repeatable outcome.
Using advanced analytical techniques that go beyond traditional statistical, algorithmic approaches to numeric-based problems is one of the most exciting opportunities available from the affordability and capabilities of Big Data.
Like all Big Data activities, the pursuit of competitive advantage is paramount. What LivePerson is able to demonstrate with its technologies is that Big Data benefits are synergistic – LivePerson’s customers and its customer’s customers are both able to benefit from the analytics and outcomes of Big Data. Improving LivePerson’s customer responsiveness from reactive through active to proactive results in better individualization, targeting and upgrading of the end-customer’s experience and by extension, that same end-customer’s propensity to express loyalty through increased spending.
For LivePerson, the ability to observe the activities of around 9,000 global customers and their interactions with their customers brings some very interesting opportunities. With so many customer interactions, LivePerson can develop recommendation engines and generate predictive analyses that provides its customers with more accurate and fulfilling connections.
There seems to be a change in the engagement model with a longer term expectation that there will be convergence between chat and voice which will benefit LivePerson.