October 31, 2022

Is Conversational AI The Next Best Thing In Cold Calling?

Conversational AI is changing the way businesses communicate with customers. Find out how conversational AI might just be the next best thing for cold calling.

Ivan Serrano

Reading time: 5 minutes

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.

What is 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:

Machine learning involves building software with algorithms that improve through repeated use. When applied in the cold calling process, machine learning can recognize patterns in data. These patterns could help understand customers’ responses to a specific sales script.
Natural language processing (NLP) is about modeling and interpreting human language. Automatic speech recognition (ASR) enables humans to converse with a computer interface. Both NLP and ASR help people communicate with a computer or software program.

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:

Virtual agents or talk bots: Can help agents with repeatable tasks. These tasks include password help or product recommendations. One of the most popular talk bots is Apple’s Siri. In telemarketing, talk bots help answer account queries or follow up on potential leads.
Chatbots: Can offer customer chat help through three channels — email, messaging, and voice.
Short Message Service (SMS) bots: Can generate and send the appropriate text message. These bots use information from the company database. For example, Facebook Messenger’s bot sends users prompt notifications.

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.

How does conversational AI change the cold calling process?

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.

Helps find, identify, and nurture potential leads

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.

Improves sales calls

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:

Companies can produce effective cold calling techniques from call logs

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.

Companies can shorten lengthy onboarding with conversational AI

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.

It can offer an excellent customer experience

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.

Assists in monitoring and coaching sales teams

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.

Whjy you should consider adding conversational AI to cold calling processes

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:

What stages in the cold calling process can I improve to increase productivity? Gauging productivity means looking at high success rates, qualifying leads, checking faster sales cycles, and finding well-trained agents.
In terms of finding new leads, can we do better? Can we generate new leads at optimum levels and avoid missing sales opportunities?
How can we improve engagement between our sales teams and leads? Do we have data showing the performance of teams cold calling with conversational AI? How about the performance of those calling without AI?
What does a conversational AI-power call center look like? Does the company have the team and technology to realize this vision?

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 is the future of cold calling

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.

Ivan Serrano

Ivan Serrano is an enthusiastic writer who enjoys learning whatever he can about business development and growth hacking. He also enjoys sharing his knowledge of technology and how it can improve business communications on an international level.

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