Reducing operation costs without compromising the quality of services is a smart move. Yet, lowering costs is challenging without drawbacks in service delivery or customers’ expectations. For cold calling, this challenge might soon dissipate.
By 2026, contact centers are expected to gain $80 billion in savings from reduced labor costs. Experts predict conversational artificial intelligence (AI) will power telemarketing teams with automated calls.
Uninterested or undecided prospects will find themselves discussing their needs with conversational AI. This article provides a deep dive into the telemarketing capabilities of conversational AI.
A conversational AI platform is more than just getting quicker responses to customer questions. It works by producing cold calls that sound like they’re coming from humans. This outcome is possible through these technologies:
The key differentiator of conversational AI is its ability to learn and adapt. Compared to traditional chatbots or cold calling software, conversational AI can deep dive, screen through vast data, and identify patterns.
Conversational AI can learn human speech and interactions. Since it can predict potential outcomes, the technology can recommend the best responses.
Moreover, conversational AI is efficient at retaining new information. This feature is great for customers who would need to wait for a callback when the agent doesn’t have data. Common examples of conversational AI include:
Do not confuse conversational AI with traditional or rule-based chatbots. Early chatbots rely on keywords, but conversational AI uses deep learning. People have different ways of asking questions; conversational AI gets this. Rule-based chatbots would need training to understand these nuances in questions.
Besides telemarketing, conversational AI is present in healthcare, real estate, airlines, restaurants, and travel.
Conversational AI handles simultaneous queries without compromising the quality of service. Its capabilities allow companies to make the most of their dataset.
Conversational AI is transforming the cold calling process, allowing contact centers to compete better. The technology is helping sales agents get successful cold calls, automate repetitive tasks, and generate savings through new leads. Additionally, conversation AI can assist teams in improving call quality.
The following are some of the other ways conversational AI is changing the cold calling process today.
Generating leads has always been a challenge for many. Conversational AI helps companies bridge this gap using data from existing customers. The technology screens through hundreds of leads, finding ones with the potential to become potential customers. This approach ensures better conversion rates.
This AI technology can also avoid wasting time and resources. Sometimes a sales agent pursues a potential customer who doesn’t qualify as a lead. But conversational AI only selects leads who meet the customer’s requirements.
Once the cold calling starts, the system records the lead’s responses. Before a follow-up, the automated cold calling system reviews these recorded calls. Conversational AI uses insight to offer auto-suggested responses to the agent. These features can help turn uninterested and unsure leads into interested customers.
To nurture potential leads, conversational AI leverages its NLP capabilities. It allows sales teams to assess their customers’ positive, negative, or neutral sentiments.
Conversational AI has improved so much over the years. Now, it can detect many facets of human conversations, such as pauses, repetition, and tones, and help preserve data integrity.
In particular, talk bots have speech-to-text features that are useful for logging calls. It can also introduce improvements in sales calls through these aspects:
Sales teams can gather insights or details from a successful cold call. Then they can incorporate them into the sales process.
The technology also allows sales teams to understand their leads’ needs or pain points. Conversational AI identifies different approaches that would work best for the specific lead.
The technology can learn new changes in the cold calling script or sales process. Conversational AI uses it in calls to potential customers.
In some applications, conversational AI can use inventory information. It can guide sales teams in implementing pricing strategies.
Some calls can be difficult, especially when made at the wrong time or when it’s least convenient for the customer. Time and emotional labor can add stress for agents, which in turn, impacts the call.
Talk bots and chatbots do not feel emotions. It can maintain a consistent tone, which consumers may find reassuring.
So, conversational AI can turn a potential issue into a positive customer experience and gain better conversion rates for the company.
Conversational AI has practical applications in monitoring calls and coaching sales teams. The latter is important in helping agents be at par with industry standards.
Besides, even the best salesperson requires training from time to time.
A sales team needs to have a complete training module that must cover real cold call experiences and reflect actual talk time.
An accurate training module can be helpful for new agents struggling to hit their quotas. Conversational AI makes this possible through real-time monitoring and call recording.
Conversational AI filters through these call logs and live calls. It finds effective cold calling tips that are useful for training. Teams can use conversational AI to listen to ongoing calls and do sales exercises.
With conversational AI, the trainer doesn’t need to read many call logs to find the best sales practices.
Coaching works through auto-generated suggestions provided by conversational AI to the sales agent.
Furthermore, AI technology can run a sentiment analysis before or during the call. The results of this analysis can be useful for customizing a sales script, so it can best fit the mood and needs of the lead.
During the COVID-19 pandemic, conversational AI addressed the gap created by agent shortages. In a world rebuilding itself, it won’t do good to throw away the positive insights provided by conversational AI.
Instead, companies should take a deeper look at their cold calling processes. They can use these questions to guide their analysis:
In 2020, the AI market revenues worldwide peaked at $296.7 billion. AI software drove this increase from three segments: software, hardware, and services.
Today, about 1.6% of interactions use AI, but a 2026 prediction sees a boost — with one in ten agent interactions being automated.
The ongoing growth of the AI market speaks volumes about its innovation. Companies and customers can expect more from conversational AI in the coming years.
Conversational AI can drive the current cold-calling process to a level many have yet to explore. The technology also champions support for other areas of customer service, such as accepting support tickets and handling client issues.
With many companies now reimagining cold calling, the journey with conversational AI is only the beginning.
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