How growing businesses use AI to analyze phone calls

Every call your business receives is full of useful information, like what customers are complaining about, why a deal stalled, or whether a rep handled a tough conversation well. 

But there are always so many fires to put out when you’re running a business. You probably don’t have time to analyze dozens of calls.

Adding AI to phone calls fixes that. Instead of manually reviewing recordings, you get instant summaries, searchable transcripts, and patterns. You can quickly see why your close rate dropped last quarter, or which support issue keeps coming up week after week. 

Eighty-three percent of small businesses already use AI at work. Over half of them do this to improve efficiency, and 40% to improve their decision-making. If you’re looking to modernize and stay ahead of the competition, this article outlines five key steps for using AI to analyze phone calls with Quo. And if you still need to get buy-in from your team, we’ll highlight several important reasons why AI call analysis is crucial for growing brands.

How does AI call analysis work?

AI call analysis uses a few core technologies to analyze customer interactions. Here’s how that plays out in practice:

1. AI uses real-time transcription. Using speech recognition technology, the tool converts speech to text. It accounts for accents, interruptions, and crosstalk.
2. AI reads the conversation for meaning. Using NLP, it analyzes tone, sentiment, and intent, picking up on frustration, buying signals, or unresolved issues.
3. The tool surfaces patterns across all your calls. Instead of one call at a time, AI compares across dozens or hundreds to spot recurring objections, complaints, or drop-off points.
4. Insights land where your team already works. Summaries, tags, and alerts flow into your phone system. When you integrate a phone solution like Quo with your CRM, Slack, or email, you’ll also see your AI call summaries there.

How to use AI to analyze phone calls with Quo this week

Ready to get ahead of the competition and stay there?

Here’s the step-by-step process to turn phone conversations into valuable customer insights.

Step 1: Get a phone system that supports AI call analysis

You could use standalone call recording AI tools like Otter or Rev AI. However, this will add extra work to your already full plate. You’d need to upload call recordings into the app, which becomes less scalable as your business’s call volume grows.

What about automating the upload with tools like Zapier? While this could save some time, it’d require adding yet another app to your expanding tech stack. Plus, if something goes wrong, manual troubleshooting could eat up your time.

A more efficient approach is to invest in a VoIP phone system like Quo. Quo automatically records calls and analyzes voice call sentiment with AI. You’ll find everything in the same conversation box, too. No need to switch between multiple tools. Just press record — or set it to auto-record — and you’re good to go.

Which brings us to the next point:

Step 2: Switch on call recordings and transcriptions

Before AI can do its thing, your calls need to be recorded and transcribed. 

There are two ways to record phone calls for your business: on-demand and automatically.

On-demand call recording is what it sounds like: tapping a button on your phone, computer, or tablet to capture specific parts of a call. Automatic call recording removes the manual effort. You don’t have to remember to turn it on. The tool records every call … well … automatically.

That’s what makes automatic call recording ideal for any busy business owner. If you’re using a VoIP system like Quo, you can turn on auto-recordings on the Business or Scale plans.

The next step is enabling AI-powered call summaries and transcripts. This creates searchable records for future reference. In Quo, our AI model transcribes audio, extracts key insights, and summarizes action items to help you prioritize next steps.

No more missed details or manual note-taking. You can stay fully present during calls and avoid the hassle of relistening later.

💡Related: How to legally record phone calls

Step 3: Enable your AI call analysis tools

Quo gives you two main AI call analytics methods: a direct integration with Claude and AI call tags.

Quo is the first business communication platform officially listed in Anthropic’s Claude Connectors Directory. With this connector, you can analyze multiple conversations at once and save hours every week. 

Ask Claude for what you need, just like you’d ask a team member. For example, “What were the most common reasons customers called last month?” You’ll get instant feedback you can work with to improve your business. More on this in the next step.

To connect with Claude, you need a Claude Pro or Team plan. Then:

1. Open Claude and go to Customize in the left sidebar.
2. Click Connect your apps. If you don’t see it on your screen, click on Connectors in the left sidebar.
3. Search for Quo and click Connect. 
4. On the next screen, click Allow.

Next, set up your AI call tags. This AI communication tool makes it easy to prioritize specific calls. It does that by managing and tracking customer sentiment and call content.  For example, it can automatically flag calls where a customer is upset as “negative sentiment.” It can also categorize calls where the person is asking for an appointment as “Booking inquiry.”  You can configure the tags to flag calls however you’d like.

Here’s how to set up call tagging on Quo:

1. Click Settings in the left-hand menu.
2. Select Phone Numbers under Workspace settings.
3. Choose the phone number you want to configure.
4. Click Automations.
5. Scroll to the Call assistant section.
6. Find Add tags to calls and click Enable.
7. Toggle on Enable AI call tags on the next page.

Now the AI handles the tagging process automatically. Quo already gives you predefined tags to get you started. You can edit, disable, or delete these at any time. If you want to set your own, click on Add tag, name it, and optionally add a description to help AI apply your tags.

Here are some examples of AI tags you could define:

• Dissatisfied customer or negative sentiment 
• Satisfied customer or positive sentiment
• Billing issue
• Escalation needed
• New customer 
• Booking request 
• Follow-up needed 
• Quote needed 

Step 4: Take action based on smart insights

Once your tools are set up, here’s how to get the most out of them. First up, Claude. Here are a few ways to put it to work:

• Find out why you’re losing deals. “Fetch the calls tied to [my business phone number], along with the most recent text conversations from that same number from the last 30 days. From there, identify the main reason leads choose to not move forward with us.”
• Spot missed upsell opportunities. “Pull the last 20 call transcripts on [my business phone number]. Did any caller mention something they needed — a different service, an add-on, a second job — that we didn’t follow up on?”
• Flag leads that need following up. “Pull all messages on [my business phone number] in the last seven days and flag any new leads that haven’t received a reply yet.”
• Find out where your customers are coming from. “Pull conversations from the last 30 days on [my business phone number]. Share the top three answers for how customers heard about us.”
• Catch sales call coaching opportunities without listening to every call. “Pull call transcripts for [rep name] from the last 30 days. Are they still struggling with [specific issue], or has it improved since we last spoke on [date]?”

⚡Find more prompts and ways to use Claude in our guide to Claude prompts.

Deep-dive analyses are great for uncovering the full picture. But sometimes, you just need a quick read on how things are going. Use AI call tags for this. 

You can quickly filter and find important calls using call views. This dashboard lets you filter calls by tag, teammate, or date. That way, you can identify objections, feature requests, and call drivers at a glance, and follow up with specific leads as needed.

By opening call views and filtering by rep, you can also review their most common call tags and summary items. That makes it easier to find coachable customer service moments or celebrate wins.

Step 5: Automate follow-ups and optimize workflows

Apart from simply analyzing calls, you can use AI tools to make post-call work easier.

For example, you can:

• Use integrations to auto-log transcripts and call details in your CRM. This is a great way to help support and sales teams stay aligned and create a single source of truth for everyone to reference.
• Schedule recurring analyses with Claude. Instead of running the same prompts manually, you can set Claude to run analyses on a set frequency. It can also deliver results straight to your inbox or a Slack channel so your whole team stays in the loop without anyone having to go looking for it.
• Send batch follow-ups. Claude can draft and send texts at scale. Try something like: “Pull my messages from the last seven days on [my business phone number]. For anyone I haven’t heard back from, draft a short, friendly follow-up text.“
• Turn calls into tasks without switching tools. With Quo Tasks, you can create a follow-up action — a callback, a quote, a booked appointment — directly from any call or text conversation. Assign it to a teammate, set a due date, and mark it done when it’s handled, right inside Quo. No one loses context in the handoff because the task stays linked to the original call or text it came from

Why analyze phone calls using AI?

Still not convinced AI call analysis is worth it?

Here are a few more ways it benefits small businesses:

Save hours of manual work

According to Adecco Group’s annual Global Workforce of the Future survey, AI saves workers one hour a day on average. A fifth of the workers surveyed said it saved them as much as two hours a day. And 5% of workers said it saves them between three and four hours.

What would you do with that extra hour you’re not manually reviewing call recordings or taking notes? Spend more time engaging with customers and coworkers? Flesh out that next big idea for growing your business? End the day earlier and enjoy a nice stroll outside?

With conversation intelligence tools, you can instantly convert conversations into text and get a detailed summary of action items for after-call work or follow-up emails. That way, you can spend less time doing busy work and more time on tasks that are meaningful to you.

Surface the issues your team can’t see yet

Unless you have a full-time analyst on your team, there are likely issues you might be missing. A great way to proactively identify red flags that could become issues later on is to have AI analyze your call data. Data analytics is actually the most common reason small businesses use AI.

Here are a few things you can have Claude look for:

Identify customer needs faster

Fifty-eight percent of customers are willing to pay more for better customer service. The first step to delivering it is understanding what they actually need.  Rather than guessing, you can use sentiment analysis tools to find and address their issues. This will help you build stronger customer relationships and reduce churn risks.

Try asking Claude something like:

Validate your marketing spend

How do you know if your best customers are coming from that Google Ad you put up last week or from your flyers? If you’re running multiple marketing channels and need to know which one is worth it and which you should cut, you can use AI call analysis to find out.

With Quo, you can set up multiple dedicated business numbers for each marketing channel in minutes. Then ask Claude which number you’re having the best conversations with. Try asking:

Develop your team 

You don’t have time to listen to dozens of customer call recordings every day. AI does. You can use AI to analyze phone calls to improve coaching, onboarding, and performance across support, sales, and operations. 

Start with AI call tags. Filter for calls with negative sentiment and listen back or read the transcript to understand what went wrong. From there, you can leave feedback directly in the conversation thread or bring it to your next team meeting.

You can also use Quo’s Tasks feature to assign follow-ups and coaching action items to the right teammate, with clear due dates and context, like: “Review June 10th’s call recording with Max before next 1:1.”

For a broader view across your team, Claude can surface patterns you’d never catch call by call:

Limitations of AI call analysis 

AI-powered call analysis can be valuable, but choosing the wrong tool can lead to serious issues for your business. Here are a few important limitations to keep in mind:

1. Data privacy risks

AI call analysis comes with legal responsibilities at a few levels.

First, recording. Many US states require all parties on a call to consent to being recorded before it starts. This applies regardless of whether you’re using AI. It’s a baseline requirement before any analysis can happen.

Second, data handling. Once calls are transcribed and processed, regulations like the CCPA govern how that personal data can be stored, accessed, and used. Some states are also beginning to address AI specifically. Texas, for example, has introduced requirements around AI-driven data processing and consumer notifications.

Privacy laws vary by state and are evolving quickly. Always consult a legal professional to understand the specific requirements that apply to your business and location.

When choosing a tool, look for:

• Communication and data encryption 
• Transparent data policies 
• Documented compliance with relevant privacy standards 

You can find out more about Quo’s dedication to privacy in our security and compliance documentation. 

2. Misinterpretation of nuance and sentiment

AI can struggle to detect sarcasm, slang, or emotional tone, which can lead to misleading insights without human oversight. You should always have a human double-check AI-generated content and reports. 

3. Accuracy depends on audio quality

Transcript accuracy depends on the AI model and on real-world conditions. Examples include background noise, audio quality, microphone setup, and acoustics. It’s important to choose a tool with high-quality audio and use VoIP headsets to help mitigate these issues. 

Start analyzing calls with AI using Quo today

Every call your business receives is a data point. The five steps above give you a system for using that data without having to carve out more hours you don’t have.

From the Business plan, Quo’s call recording and transcripts automatically capture every conversation. You can then connect Claude to have it surface patterns across your entire call history. Scale users can also set up AI call tags to organize calls in real time. 

Finally, Sona can handle calls around the clock, and integrations push data straight to your CRM, Slack, and more. You can use AI to analyze phone calls, and the whole system runs with very little upkeep, starting at $23 per user per month. Test Quo’s AI tools with your team by signing up for a seven-day free trial.

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