Another @$#% Ton of AI Use Cases for Call Tracking

Living up to our title choice, the conversational AI use cases were too plentiful for just one post. In part two, we’re digging deeper into how AI call tracking isn’t just another excuse to hop on the artificial intelligence bandwagon, but a significantly useful engine to extract insights from your conversations. 

Use AI for Analyzing Phone Calls

When you give a conversational AI tool, like our AskAI, a transcription to work with, the opportunities for analysis are as endless as your imagination. Sure, there’s some easy stuff to knock out first. But, with a little old-fashioned human brainstorming, you can start automating even small things to make a huge impact. 

Basic Analysis

Let’s start where most do with conversation intelligence: getting a snapshot of what the call was about. If you’ve ever taken sales or customer calls, you know there’s a wide range of possibilities for how that conversation can go. You might still need to talk to the person on the other end of the line, but let AI analyze it when you hang up.

1. Quick summary – Transcriptions are incredible sources of insights, but reading through an entire eight-minute sales call just to find out they thought they were already customers isn’t fun. Instead, have AI generate a concise summary. No more guessing which calls are worth listening to.
2. Sentiment – Your sales team is constantly having lengthy phone calls with leads. These are all considered successes—which could be a mistake if those leads are spending the whole call mad, confused, and swearing. Even a basic positive, negative, or neutral sentiment tag can go a long way to add context to calls. 
3. Keywords – If there are specific words or phrases customers say that signal to your team they are an ideal fit customer, it sure would be nice to know which calls reference those keywords! 
4. Next best action – When it comes to the next step towards closing a deal, your team has great instincts, but AI can provide a great second opinion. Based on sentiment and context, what’s the best next action? 

Sales Coaching

What’s the point of analyzing sales calls in the first place? To get better! You listen and review the good calls to replicate success. You also listen and review the terrible, crash and burn, calls to avoid making the same mistakes again. How does conversational AI help the sales coaching process? 

5. Script accuracy – Is your sales team going rogue? Have AI analyze how closely they’re sticking to the script. Nudge your team back in line, or find out you should throw out the script altogether. 
6. Promotions – Discounts and promos work best when customers actually know about them. So if your promo isn’t generating the kind of sales you forecasted, perhaps they’ve been forgotten by your team. Tailor your keyword spotting use case, similar to script accuracy, to signal if the agent mentions the free upgrade promo. 
7. Empathy – Closing deals takes more than scripts and discounts. The best teams tap into human feelings. And what better way to quantify how human your team is being than by having AI assign an empathy score? 
8. Establish timeline – You’ve got the next best step from the basic analysis above, but did the salesperson help clarify the buying timeline? It’s an important question for many sales teams, “when are you looking to make a decision.” Your friendly AI can get you both the answer from the conversation and how well your salesperson did getting those details. 

What Else can AI do with Calls?

9. Customer satisfaction – Take a pinch of sentiment analysis and add a scoop of script accuracy to build a customer satisfaction outcome. Was the customer happy? Did the representative actively listen and provide helpful feedback?  
10. Targeting clarity – Call tracking’s whole thing is matching calls to their advertising source. But if you have an ad campaign running for product A and you keep getting calls about product B? Something’s off with your audience targeting. Does the content of the conversation match the advertising source? AskAI.
11. Call preparedness – Marketing’s job? Prepare leads for their conversation with Sales. They should know basics like price and features before calling. Did they do their job? Or is Sales spending half of the call repeating basic answers? 
12. Upgrade opportunities – Wouldn’t it be nice if there was a way to flag when a customer is signaling they’d be a good candidate for an upgrade? It would be. And can be done with a custom AI prompt. 

Analysis at Scale

Analyzing one call is a perfect way to learn about that one customer. That one sales rep. Analyzing hundreds of calls? Thousands of calls? A great way to learn about your entire customer base, team performance, and trends in your space. Conversational AI outputs rolled up into account-level reports is a whole new game.

13. Help desk issue trends – What’s the product that’s been blowing up your helpline? Maybe it’s not one feature, but a category that your ticketing system might not catch as a trend, but it comes through in the voice of your customers.
14. Customer preferences – We like to think everyone follows the same customer journey, but it’s just not true. Are there indications of how to better serve your customers in the reporting? Are they asking for fewer phone calls and more opportunities to chat, to text? 
15. Macro impact (economic uncertainty) – Notice a trend of more and more customers asking about discounts and lowering their bills? It might not be a coincidence, it could be the economy. Use those AI signals to get ahead of big changes. 
16. Competitive trends – If you’re tracking competitor mentions in your conversations (and you should!) you can catch the ebbs and flows of their customer sentiment and deploy campaigns to take advantage. 

Taking Action on Analysis

Call tracking is designed to give sales and marketing teams actionable insights. Not just fluffy data. The actions you can take are as endless as the analysis itself. But here’s a taste of what kinds of stuff can you do with all of this AI call tracking output:

Email summary of Zoom call to new customer 

There are more useful ways to use Zoom recordings apart from saying “I’ll review it later” and never following through. You know you should send a follow-up email after a customer call. But there’s never enough time to do everything you want. But, since you’re a good customer rep, you outlined some next steps during your call. You helped troubleshoot some issues. And you maybe gave them some new things to try. Just like a phone call, AI can generate a summary of your conversation, bullet points and all, to send over right after your call ends. 

Send a review request to customers most likely willing to leave you a positive review

There’s been a renewed focus on not just adding new customers, but keeping your current customers happy. With sentiment analysis and customer satisfaction tags, you can find opportunities to fix problems but, just as importantly, you can leverage good service moments to transform customers into advocates. Practically, your AI tags your calls as review candidates. Your call tracking software integrates with your CRM. And your CRM shoots off a personalized email with a review request to those customers likely to leave a glowing review. 

Enhance your sales and buyer enablement

You’ve used your transcriptions and AI to pull out keywords and phrases. And you’ve set up some qualitative insights about buyer preparedness. Combine the two and you’ve got a way to look at knowledge gaps in the selling process. What are the frequently asked questions (FAQs) of your least prepared prospects? Send those to your content team to answer in blog posts, demo videos, or nurture drips. If there are FAQs more relevant to prospects further in their buying process, make sure your sales team has PDFs, decks, and interactive tools available to send to buying teams. 

Human Creativity Drives Conversational Intelligence AI

There are way more than 16 use cases for AI in call tracking and even more than the 32 when you combine this with part one of this blog on Search Engine Journal. As you start down your own path of using AI to fuel new marketing and sales insights, just keep in mind that the best questions to ask AI are the ones that you can use, and make sense for your team’s goals. Don’t build your prompts on what might seem cool. Build them around getting to know your customers better. 

Don’t miss out on deeper customer insights. See how CallTrackingMetrics has built AI right into our platform to amplify the already robust data we provide for every call, text, chat, and Zoom recording.