Many business experts expressed their concern that cold calling may have lost its charm. But suddenly, AI integrated cold calling increased the average engagement rate from 2.3 to 2.7% !!
Well, the reason is simple, intelligent AI tools are making cold calling exceptionally precise. When these direct cold calls hit the exact pain points with the help of AI, conversion possibility increases significantly.
This blog will cover how and where to use AI for cold calling. It will also discuss how AI integrated cold calls are performing significantly better than manual ones.
What is AI Integrated Cold Calling & How It Works?
AI integrated cold calling means when a cold calling service is integrated with AI to enhance its capacity. This type of cold calling uses NLP and machine learning to massive amounts of previous user data to increase performance.
In an AI supported cold call, human agents initiate the call and AI works as a supporting tool. Prior to making the call, AI helps to find and score leads, collect contact numbers and address. AI agents cleverly identify business buying patterns, cycle and committee members. This key insight helps with script development and making strategic offers.
During a call, a highly capable AI model has the capacity to support an agent with data and information proactively. It means, using voice recognition and LLM, it can automatically show key data to agents that prospects are requesting. This saves precious time needed for manual data searching during call.
In post cold calls, AI helps cold callers to store and keep notes from the calls. Beside this, AI is massively helpful with lead nurturing. Because it can cleverly monitor prospect’s social and virtual footprint and notify agents when to act.
Difference Between AI Cold Calling and AI-Integrated Cold Calling
AI cold calling means when an AI makes the calls to prospects. On the contrary, in AI integrated cold calling an human agent makes the calls, but AI works as a supporting tool.
AI calling agents do the same work like a human agent does. But it can initiate multiple calls at the same time.
Reddit user Minnesotamad12 describes in a post that doing 600 calls by human agents is not just time consuming, it’s costly and difficult to manage.
On the other hand, AI agents can make those calls in a few seconds.
How and Where to Use AI for Cold Calling?
AI integrated cold calling makes an agent more insightful, engaging and effective. Here are the areas where AI can be used for cold calling.
AI Powered Cold Calling for List Building
List building companies use your ideal customer profile (ICP) to research, identify and then qualify them as leads manually. When businesses do this manually it takes a lot of time and resources. But integrating AI to build a list not just saves time, it reduces the cost too.
AI uses public data to identify and develop a list. For example, it collects contact information, location, business reports and ideas about business operations from google maps, websites and public reviews. Then it smartly compares these with your ICP and gradually develops the list.
ATSCoupe described in reddit that AI can generate a significant amount of leads compared to human agents within a timeframe. It’s because humans need to do manual research. Manually analyzing business reports, reviews and public engagement takes time to conduct.
It takes a human agent 15-60 minutes to qualify one lead. On the other hand AI can do the same task in one second.
Lead Quantification With AI Integrated Cold Calling
After you build a list of leads, the next step is to determine which of them have higher intent and which have lower. To evaluate position, lead qualification service providing companies uses these frameworks.
- BANT (budget, authority, need, time)
- SQL (Sales qualified leads)
- MQL (Marketing Qualified Leads)
- CHAMP (Challenges, Authority, Money, Prioritization)
Similar to list building, when done manually this process takes a lot of time to conclude. On the contrary, with proper and detailed instructions AI can do multiple lead qualifications in seconds.
AI models use primary and secondary frameworks to analyze leads scores even more accurately.
Reddit user aytekin shared his experience on how he developed and used an AI to qualify leads. Here are the steps he described. It will help you to use AI for cold calling too.
- Define what makes a high-quality lead before starting the automation process. It gives you key instructions needed to train your AI agent.
- Train your AI agent to ask the right questions from the key insights you gained in step one. This ensures that your AI agents are generating qualified leads accurately.
- Set a clear benchmark and lead scoring framework. It helps your AI agent to qualify leads under categories like high medium and low intent.
- Randomly select leads and do manual qualification. It gives you an idea about how accurately your AI agent is performing.
Insightful Outreach & Solid Openings With the Help of AI
Openings are the most crucial part of a cold calling. Prospects decide in 3 seconds whether to continue the call or not.
Rather than a generic opening, starting the conversation with a hook or a key pain point leads to longer conversations. AI significantly helps to find out these pain points in real time.
For example during building a list you collected data according to the prospect’s current situation. But when you start dialing, their decision making timeframe or buying cycle have changed.
In this situation, if you have an active AI system, it will update all the information. And when you are making the calls, you have updated insights to make the pitch.
When you have updated data collected by AI from news, business report or other public domain you can make the start like this :
Agent: Mia, How are you! Heard you just bought another restaurant.
Mia (Prospect): Yeah… How do you know? Who are you?
Agent: Well I’m Jim. I saw your partner Lucas’s post yesterday and thought you might need a VA (virtual assistant) to support your operation.
Mia: Yeah.. I guess so…
Agent: Do you have any plan how you will arrange this?
Mia: Not really..
This opening signals the prospect that you are familiar and connected with them in some way. And in the overall process AI support you with real time insights
AI Helps You to Conduct Personalized Nurturing
Lead nurturing is the process that starts with your cold calls. Top performing calling agencies have started to use AI to enhance lead nurturing with engaging personalized messages.
The goal is simple, make the buying cycle shorter and increase the conversion rate. Cold calling works best when it is used to warm up lead with a consultative message rather than direct sales pitch.
For every lead, pain points and requirements are different, so do the nurturing messages. When AI is integrated with the nurturing process it gives the agent real time insights of prospects requirements, needs and paint points.
When you sound more consultative rather than salesy, it helps to build trust. These insights gathered by AI in real-time support telemarketing team to help to optimize MQLs to SQLs ( marketing to sales qualified leads) more sufficiently.
For example, previously you called Mia and just talked about her VA requirement. For nurturing the conversation looks like this:
Agent: Hi Mia, congratulations on your fabulous opening week.
Mia: Thank you.
Agent: You got 4 starts in the first week. But I can see some reviews asking you to make the booking system more smooth, what happened there?
Mia: Well due to the rush we face some management related issues.
Agent: Yeah I guess too, Look mia, I might have a solution for this….
Mia: What?
Now with manual nurturing with fixed CRM data, observing these changing pain points is time consuming and costly. But AI can notify you of these changes in real time and with zero costs.
Analyzing the Funnel Conversion Rates and Overall Performance
Cold calling success for appointment setting to lead generation, relies on how efficient your conversion process is. When you integrate AI with lead nurturing, it automatically enhances the funnel conversion process. Then it helps to maintain a benchmark and KPI for agents.
When you have an AI integrated system, it gives you insights of
- Which agents have most conversion rate
- In which time period connection rate is most
- Contact list accurately and connection rate
- Which agents have more idle time
- Script validation and relevance
- Objection analysis and mitigation techniques
- Agent talk to listen ratio
- Cost Per Qualified Lead (CPQL)
- ICP shift detection
These are almost all the aspects related to a cold calling operation. And when you implement AI to do these tasks, it cuts short management overhead and other costs.
Nurturing and funnel conversion are interrelated. Better nurturing means faster conversion. Faster conversion reduces CPA (cost per acquisition) which directly influences profit margin.
We discussed in the previous two sections how real time insight and pain points make Mia from a cold lead to high intent leads. This faster conversion was fully backed by AI gathered data.
Follow Ups and Re-engaging Old Leads
AI can be implemented as a constant monitoring tool. It can notify changes to reps’ situations in real time. For cold calling and telemarketing campaigns, calling the prospect with the right time makes all the difference.
That’s why follow ups are crucial. When you get these changes, call the leads for a solution, it automatically makes them more interested in you. Which you can see in Mia and Agents conversation in the personalized nurturing section.
Follow-ups help you convert the lead from TOFU to BOFU. Because you remain well-known to your prospects.
Similarly, older less interested leads often become high intent leads. If you have an AI system that monitors these changes too, you can establish further communication to them as well.
Final Thoughts
Cold calling effectiveness isn’t finished, rather it has been reborn with the help of AI. Cold calling is now more accurate and less costly thanks when you integrate it with AI tools.
When you use AI to support your cold calls operation in areas like, lead generation, lead scoring, performance analysis to monitor overall operation, it automatically reduces cost and increases conversion rate.
However, AI isn’t ready yet to make the cold calls. Rather, using it as a tool to support agents’ tasks is providing better results.
