Dec 01, 2020 10 technologies to transform customer experience in 2021
There is no shortage of customer experience technologies that organizations can use to improve contact center agent skills and, by extension, customer experience. But budgets are finite and executive demands can often be urgent.
Customer experience and IT leaders are in the hot seat for identifying business cases and selecting the best technologies for these transformation initiatives. AI-enabled capabilities are at the forefront of the technology plans, and 71.6% of organizations are now using or planning to use AI for their customer engagement initiatives. That’s an increase of 60.5% since 2018.
How to boost customer satisfaction
As part of their digital transformation projects, organizations are using or planning to use the following technologies or adopt the following best practices to improve customer experience:
1. Digital channels. For years, voice and email were the primary — and sometimes the only — interaction channels available to deliver customer service. Now, the customer journey can include any number of additional channels, including text messaging, web chat, video, social media and in-app messaging for those using mobile devices. On average, companies offer 6.6 channels, up from 5 in 2019. Among the newer digital channels, organizations use social media and text messaging the most.
2. Omnichannel capabilities. Many customer experience leaders are being proactive by delivering a variety of interaction options, but problems arise when they don’t integrate the channels. That’s where omnichannel capabilities come in. Though only 27.8% of research participants adopted omnichannel in 2020, another 22.5% plan to do so in 2021.
Omnichannel service improves the customer experience; without it, the customer journey is fragmented. It is important for current and historical customer data to pass from channel to channel, so agents don’t have to ask customers to repeat information they already provided.
3. Agent analytics. These tools provide KPIs on contact center agents, along with analysis of their performance using AI-enabled capabilities such as natural language processing or sentiment analysis. The data and analysis help supervisors coach agents, and the tools themselves can provide self-training techniques backed by data. In 2020, when many agents went to work from home offices, agent analytics was the top AI-enabled capability in use.
4. Personalization. Customers prefer personalized interactions, and artificial intelligence can help deliver that. Businesses, for example, can implement a machine-learning knowledge base such as Zendesk and interact with customers based on their preferences. Personalization applications can dictate whether companies call, text or email customers — and whether that changes based on the topic, time of day or day of the week.
5. Intelligent routing. To deliver the highest level of customer service, it’s imperative to route calls or chats to the best possible agent at that moment for that customer. AI-based intelligent routing enables decisions about where to send a call or chat to the agent with the highest likelihood of resolving the issue with a five-star rating. A knowledge base considers issues such as how customers rated their last interactions and with whom, which agents are available with the same qualities as those that they previously rated, and predictions about why the customer may be calling or texting.
6. Language translation. As companies continue to expand globally, the ability to perform real-time language translation — using software such as CirrusTranslate — during any type of interaction addresses customer needs and also expands the capabilities of agents who may not speak multiple languages.
7. Customer chatbots. Self-service is growing considerably. In 2020, 36% of transactions used self-service, up from 28% in 2019. By the end of 2021, research participants expect that figure to reach 43%. Going hand-in-hand with successful self-service are AI-enabled chatbots — virtual assistants — which can guide customers through a knowledge base to find answers. They can also conduct simple transactions or escalate interactions to a live agent.
8. Real-time voice transcription. By enabling real-time voice transcription — using software such as Google Cloud Contact Center AI — agents can save the time they normally take during and after a call to take notes. The transcription engine captures the entire call, and by recognizing certain keywords, it can note specific items that require action or attention. After the interaction, the company can send the transcript to customers so they also have a record of the call.
9. Sentiment analysis. Capturing customer sentiment — with software such as NICE Enlighten — is important for both immediate actions and historical analysis of customers, agents or situations. For example, if sentiment analysis detects voice tones or all capital letters during a webchat, it can create a screen pop-up telling the agent to escalate to a supervisor to address an immediate issue. Or supervisors can view historical or trending reports to see if certain agents are generating more positive or negative sentiment — and why.
10. Natural language processing. Going hand-in-hand with sentiment analysis, NLP engines “listen” to voice or text streams and act based on what customers or agents are saying. For example, NLP may hear words that indicate the customer is a good candidate for a new product, then deliver a screen pop-up that shows the product and links to its description.
For links to related articles and additional charts, please see full post here.