Conversational IVR interprets customer feedback using natural language processing and automatic speech recognition, commonly in response to a customer support request.
While verbal IVR has been available for over two decades, new advances in AI have expanded the possibilities for straightforward, natural, and important phone-based speech. However, new technologies generally comes with exaggerated statements about efficiency.
We’ll dispel some of the popular myths in this manual and demonstrate the proven benefits of linguistic IVR.
Verbal IVR: 5 authentic advantages
You’ve probably had the experience of navigating through a maze of IVR voice causes before calling a customer support line only to have to resolve the issue in the end. Luckily, verbal IVR breaks this period with organic, dialogue-based interactions.
Using verbal IVR to simplify customer support, in this article, are some of the main advantages.
1. Reduced guest navigation
Traditional IVR systems rely on tedious menu prompts, asking callers to” Press one for sales, two for support …” to direct their needs.
Callers can usually find through no more than four menus levels before deciding to opt out of speaking with an agent, according to research. This flowing tracking most often leads to misrouted demands, duplicate calls, and abandoned assistance interactions.
Conversational IVR avoids these complicated pitfalls by allowing clients to communicate requests in conversation using normal language.
Instead of navigating recipes, buyers simply ask their concerns. With fewer transfers and less stress, the visitor gets to the appropriate solution sooner, whether it’s checking an order position or requesting a refund.
This reduced tracking not only makes things simpler for the visitor, but it also makes asset allocation in the background more efficient to keep your call center running smoothly.
2. Feels more healthy for the consumer
Most traditional IVRs come pre-built with automated support sequences that gradually point users in the direction of the appropriate support agents, as if wading through confusing menu trees was n’t enough. Although these default settings physically accomplish the desired result, they lack the individualization necessary to raise your customer service’s standard level.
Conversational IVR uses natural language processing and automatic speech recognition to create healthy, portrayed interfaces.
Clients you speak their requests as though they were speaking to a live person rather than push buttons to the appropriate support representative. Until the customer’s help request is resolved, the IVR communicates with the customer.
This human-mimicking speech keeps conversations going nicely by responding to questions with the appropriate context rather than just the click of a button.
By removing these structural list barriers and replacing them with smart, human-like talk, your customers will feel heard and cared for.
3. Greater productivity through technology
You wo n’t have to worry about responding to frequently asked support questions or queries with conversational IVR again.
For inquiries like” What’s my account harmony”? or” When will my order dispatch”? Without agent assistance, it will immediately interpret the request and gather the necessary information to solve it.
Your support staff can concentrate on higher-level, more complex relationships while reducing the repetitive task of handling these automated calls.
Better still, natural language versions get better over time. When the IVR method learns how to answer your most frequently asked questions, over 50 % of your outbound call volume can be completely automated.
4. Personalization determined based on visitor report
If the potent machines alone were n’t enough to persuade you that linguistic IVR is far superior to traditional IVR, the plugins will undoubtedly do the same.
By integrating an Voip program with your CRM, solution stock information, ERP platforms, and more, IVR can get the most current data to provide callers appropriate, personal responses.
Your automated phone system can use these back-end integrations to retrieve customer-requestive information like order statuses, account details, shipping dates, and other useful information.
Callers are shown that they are more than just another number by this personalization.
For example, when asking about order status, conversational IVR can reference the specific product purchased, shipping destination, and estimated delivery window based on integrated order records.
5. Understands complex questions
Traditional IVR systems fall short when callers ask complex questions, need clarification on answers, or expect personalized responses. These systems simply were n’t designed with this level of customization in mind.
But by applying natural language processing, neural networks, and machine learning, conversational IVR can interpret intricate, nuanced inquiries across multiple topics. The difference is huge.
Conversational IVR can easily handle these nuances, whether a customer requests to modify an already existing order and check loyalty points or attempts to book travel while mentioning previous trips.
These systems can also change the context of answers in back-and-forth dialogue without losing any of the context or getting frustrated.
By studying customer transcript data from all recorded customer calls, conversational IVR will get better at understanding multi-intent requests, analyzing customer sentiment, and resolving support requests through intuitive, smart dialogue.
4 exaggerations about conversational IVR
While conversational IVR promises to revolutionize customer support experiences, that does n’t mean it has endless capabilities with zero downsides. We’ll disprove some of the arguments made about conversational IVR and highlight areas where it might require more time for your support teams, as opposed to reducing their time.
1. Conversational IVR is simple to set up.
Some conversational IVR vendors boast quick, simplified deployments. However, it takes more than just installing basic software to create an intelligent IVR system that is customized for your team’s needs.
Significant upfront development is required to properly interpret customer intent. Conversational IVR systems must analyze call transcripts, identify common queries and topics, label them as “intents”, and map IVR dialogue flows before anything goes live.
Even if you could make it live without all of that, it will only lead to a potentially worse customer support experience than one provided by a traditional IVR system.
Integration challenges add deployment delays, too. If you want to pull in real-time data to assist your customers, your conversational IVR system needs to integrate with contact center infrastructure like ACDs, CRMs for customer data, payment systems, inventory databases, and more.
Setting up these integrations takes time for end-to-end testing before they can be scaled up.
And while the long-term gains of conversational IVR far outweigh the costs, organizations should expect several months of development, testing, and fine-tuning before these systems can deliver a positive ROI.
In other words, there are no shortcuts to improved customer support.
2. It has 24/7 human-level conversational ability
Some conversational IVR vendors boast seamless, human-like interactions. Even the most advanced natural language systems struggle to understand and replicate everyday human speech.
Without any lived experience or cultural awareness, IVRs often misinterpret slang, sarcasm, niche references, and requests that require emotional intelligence.
Modern neural networks can identify intent and entities with accuracy in some situations, but they frequently fall short in those situations where intricate personalization is necessary. For example, while humans can easily context switch between topics, IVRs rely on rigid dialogue trees.
AI augmentation is great for assisting support agents, but it is n’t meant to replace them. Years have passed since any assurances of complete, scalable automation have been made.
3. It has near-universal self-service containment rates
Some conversational IVR vendors may imply that nearly all caller needs are addressable without human assistance, but this is hardly, if ever, the case.
Conversational IVR’s reported higher containment rates than those of traditional IVR systems in the real world. While this is impressive, it’s nowhere close to end-to-end customer support automation.
Instead, contact centers should be designed for a balance of automation paired with staff augmentation. This hybrid approach is ultimately the best way to balance managing costs, expectations, and customer experience.
4. You’ll get immediate cost savings
Implementing conversational IVR systems seems to be fairly straightforward in terms of ROI. Less involvement from support agents results in lower operating costs, right?
While it’s plausible, this is almost never true in practice. Before its automation can lower operating costs, it takes months to create a roll-out-ready system. Call drivers, define conversational flows, train natural language models, and then integrate these dialogues across backend systems require a lot of upfront effort.
These build costs range from content licensing fees to development teams fine tuning speech recognition and call routing, as you might have already guessed. Your containment rates will suffer significantly if the design and testing are n’t done right before the launch.
Conversational IVR still requires ongoing maintenance to address changes to call drivers over time, even after it has been operational. Conversational IVR systems only begin to show their true potential with ongoing content enhancements.
Planning for customer support’s future
Callers can get answers much more quickly using conversational IVR systems without having to speak with a live agent. However, the technology still has limitations when tackling complex queries, and it may take a while before the system is operational and can begin routing customer calls.
Generally speaking, customer service should be handled in a hybrid way. Implementing a conversational IVR system is a good first step if you want to increase your customer support from good to great.
