Live chat is becoming an increasingly important part of the customer support experience. But in many cases, the service customers receive via live chat is siloed from service they get via other channels and not targeted to their specific needs.
Customer experience technology provider 7 aims to make live chat support “smarter” by offering a cross-channel platform called 7 Assist that ties live chat to predictive analytics and dynamic changes in consumer behavior.
“People still use three or more channels to contact a company for customer service,” said Brooks Crichlow, VP of Product Marketing for 7, during a recent phone briefing with CMSWire. “None are optimal. A customer may have different needs at different times. For example, they may be on the go and use mobile. They won’t use the channel the company hopes they will use or steers them toward.”
Whatever customer service channel they choose, Crichlow said people “want to assume someone is always there to help them.” He attributes this attitude to consumers learning from experiences they have had on social media platforms such as Facebook and FourSquare, as well as on e-commerce sites such as Amazon.com. “Consumers want a contextual experience that takes advantage of the connection to the Internet most of us walk around with every day.”
According to Crichlow, the typical live chat text pipe “totally falls down and hasn’t changed in 10 years.” To rectify this situation, 7 connects its live chat support application to a “smart” platform that analyzes both structured and unstructured data and looks at customer behavior throughout their buying journey and across contact channels to help determine why a customer is visiting a site, what they are looking for and whether they would like to be contacted by a chat agent.
“As a rule, chat support systems don’t know why a customer is on a site,” said 7 Chief Marketing Officer Kathy Juve. “We use a data model to predict why the customer is on the site and only send a chat invite when we think they need help. We can also rotate them to specific agents based on intuiting their needs, which leads to higher conversion rates.”
Other benefits of 24 Assist, according to Juve, are that it mines 100% of all chat interactions instead of sampling a percentage of chats like most competing applications, enabling “machine learning” to improve customer service, and that it offers a Facebook-like user interface that agents find convenient.
Oracle Enables Cloud-based Chat Engagement
7 is not the only chat solution provider attempting to make chat-based customer service “smarter.” Oracle is attempting to enable more proactive customer service by integrating the Oracle RightNow Chat Cloud Service with the Oracle Engagement Engine Cloud Service as part of its new Oracle RightNow CX Cloud Service release. As part of the upgraded Oracle RightNow Chat Cloud Service integration, RightNow CX Cloud Service users can leverage more than 70 built-in rule conditions from the Engagement Engine Cloud Service. These conditions enable granular control of customer engagement, launching service agent chats based on specific customer behavioral and profile characteristics.
In addition, a “click-to-call” feature allows customers to automatically switch to phone-based support from a chat or Web browsing session, availability controls enable companies to manage chat volume based on internal agent availability and analytics offer metrics to measure agent and channel performance. Other new features include a set of developer tools and improved administrative capabilities.
Live Chat Especially Suits Service Industries
As explained in a posting on allBusiness, live chat customer support can be especially valuable for service industry participants. “As an online interactive service, real-time chat can deliver the personal touch that service-oriented businesses like real estate and auto sales require,” states the article. “When done right, online chat can benefit an auto sales or real estate website several ways.”
These ways include bringing the human touch to the online interaction (such as an auto dealer offering a customer specific information about a car model they were currently browsing), providing instant answers and feedback to customer questions and actions, engaging visitors when they most need help (such as if they are spending a long time on an online loan application) and identifying and targeting top customers.