AI in customer communication: tools, tricks, and best practices

Your goal was simple at first: get more calls, get more business. But then your business started growing,  the phone never stopped ringing, and those texts, emails, and voicemails began piling up.

The good news? AI customer communication tools can act as the always-on assistant your business needs.  They can speed up response times, take pressure off your team, and help you build better customer relationships. The results speak for themselves: 86% of small businesses say AI has made them more efficient, and one in three small business owners are prioritizing AI investments this year.

Is it time for your business to hop on the bandwagon?

Here’s everything you should know about using AI in customer communication.

4 ways AI can upgrade your customer communication

Here’s how AI is reshaping the way small businesses communicate:

1. Faster response times: One of the biggest benefits of AI is always being able to respond to customers. For example, you can use an AI voice agent to answer calls even while you’re out of the office. You can also set up workflows powered by Zapier and ChatGPT to send automatic email or text replies 24/7.
2. Better response quality. Speaking of tools like ChatGPT, you can use AI systems to make conversations flow more easily. With AI-generated text message responses, for example, you can help team members improve their tone, empathy, and consistency. You can also use tools like conversational AI to handle routine FAQs via chat. 
3. More time spent on high-impact work. No need to roll the dice on a virtual assistant. With AI agent bots and generative AI tools, your team can delegate time-consuming tasks such as creating action items after calls or tagging phone calls for important details and follow-ups. That way, you’re free to focus on higher-impact work — like building a better product or improving customer support.
4. Happier customers. The faster and more accurately you respond to customers, the happier they’ll be. But AI can do more than just speed up responses — it can help you proactively address customer needs. AI-powered call tags and sentiment analysis highlight key insights, helping you prevent frustrating experiences before they turn into lost revenue.

4 key AI tools that can transform customer communication

There are four types of AI tools you can use to build relationships with customers: AI assistants to answer quick questions, generative AI that creates content, real-time transcriptions and summaries to recap conversations, and sentiment analysis to uncover customers’ emotions at scale.

Here’s a closer look:

1. AI assistants for instant replies

You don’t always have time to pick up the phone — but AI assistants do. They can greet customers, collect key information, and provide basic answers so you don’t have to worry about conversations falling through the cracks.

For example, Next Realty implemented a website chatbot designed to act as a virtual broker. That way, they could collect contact information, answer questions, and chat with leads who dropped by their website after-hours (roughly 33% of potential customers). 

You can also set up AI assistants that reply to customers on your phone system. For instance, OpenPhone’s Sona can also handle calls automatically so you don’t have to drop everything to answer them.

You can use Sona to:

• Answer questions based on the knowledge you provide (like your business address, weekend hours, and mission statement)

Take a message with specific details you want to capture (name, number, preferred communication channels, etc.).

2. Generative AI for better messaging

Ever been stuck staring at a blinking cursor? Or typing the same messages over and over? AI-powered tools can take repetitive work off your plate so you can speed up, refine, and personalize customer responses at scale. 

A great example of this comes from Todd Harper, founder at Business Tech BFF. Todd uses a combination of Zapier and ChatGPT to write personalized follow-ups after a lead fills out a form on his website.

Here’s how it works:

• A lead fills out a work inquiry form on the website.
• In Zapier, the lead’s contact information is sent to OpenPhone, Google Drive, and Airtable.
• ChatGPT writes a personalized message based on information provided by the customer.
• The message goes to the CRM.
• The CRM generates an automated email workflow.
• The lead receives the AI message, a meeting booking link, and a quick disclosure saying it’s an AI-generated message.

You can also use generative AI tools to reply via text. With OpenPhone, you’ll get AI-suggested message responses on every plan. 

3. AI call transcripts and summaries for actionable insights

It’s not if but when you need to review past customer calls, whether for training new team members or customer service quality assurance. But we both know you don’t have time to listen to every call — which is where AI call transcripts and summaries come into play.

AI call transcripts convert audio into text so you can read conversations rather than listen to them. If you only need the SparkNotes, just browse through the call summary, which highlights key parts of the call and action items.

Transcripts and summaries keep team members on the same page without forcing them to listen to hours of calls. You can save even more time by turning key moments from conversations into shareable insights (think action items and important dates) so work gets done faster.

Here’s how Bookkeep & Prosper keeps their team aligned using OpenPhone’s call summaries and transcripts:

“The AI summary feature is a huge bonus for us because I can take that or the transcript itself right off the history and share it with my team and use it to create tasks. It’s the best feature they have.” – Conner Schryver, Founder of Bookkeep & Prosper

4. Sentiment analysis for smarter insights

Tracking customer sentiment is key to improving the customer experience. 

You’ve got a few options, depending on the medium:

• Text sentiment analysis tools. After you import text data, you receive a list of keywords and insights into customer sentiment. This can help you spot negative trends that need to be addressed, like customers sharing negative feedback about a new product. Text analysis tools can also help you pinpoint emotions in surveys, emails, and more.
• Social media analysis tools. These scrape customer data across all your social media channels — think Facebook, Instagram, and LinkedIn — to collect information about how customers feel. Some tools identify trending keywords and brand hashtags so you can spot opportunities and concerns before they go viral (like when an influencer mentions your brand). 
• Voice sentiment analysis tools. With call recording AI tools, you can capture conversions and pull out insights at scale. OpenPhone’s call tags, for example, use machine learning and natural language processing to categorize calls based on specific topics or emotions you specify (like ‘Billing issue’ or ‘Frustrated customer’). These can help you analyze customer feedback and improve your product and service based on patterns you notice.

Here’s how 512 Hosting uses voice sentiment analysis to organize their customer interactions:

“Being part of the Call Tags beta program, I’ve seen firsthand how much easier it makes organizing and tracking customer interactions. The AI automatically tags calls, saving me time and letting me focus on what really matters. I can quickly find key conversations, spot trends, and keep everything organized without the hassle. It’s been a game-changer for staying on top of customer needs!” – Will Swan, Founder and CEO of 512 Hosting

3 challenges of AI in customer communication (and how to solve them)

AI has big benefits, but there can be issues if you choose the wrong tool.

You’ll have to consider:

1. High costs: Some AI tools have steep monthly fees. For example, sentiment analysis tools like SentiSum can cost upwards of $3,000 per month. If budget is a concern, start with AI solutions that offer flexible pricing and AI capabilities — including those with usage-based models (APIs) or tiered plans (like OpenPhone).
2. Steep learning curves. Not all AI tools can be used right out of the box. Some require onboarding or in-house IT resources. Google’s NLP API, for example, requires in-depth coding or a data analyst. If you’re a small business, you should choose no- or low-code AI tools with intuitive user interfaces, pre-built workflows, and automation templates.
3. Customer trust concerns. Automated customer communication has its place, but most people prefer human interactions. Sixty-four percent of customers would prefer you didn’t use artificial intelligence in customer service, which means AI should enhance — not replace — your human support. Consider using AI to handle repetitive inquiries or simple tasks rather than complex conversations.

5 best practices for using AI in the customer experience

Here are five proven tips for using artificial intelligence with customers:

1. Properly train your AI

AI is only as good as the data it learns from, which is why it’s important to have a solid knowledge base first. Before launching an AI assistant for phone or chat, it would be wise to collect key business information (like pricing and answers to FAQs) so it can be easily uploaded to your tools.

Not sure how to build up your knowledge base? Try using AI to do the heavy lifting for you. OpenPhone’s call tags can help you identify common call drivers, track how customers feel after interactions, and take note of common complaints that need to be addressed.

You can also try experimenting with different AI prompts to see which questions or phrases give optimal results. You can store these prompts in a centralized tool so everyone on your team has access.

2. Integrate AI into your tech stack

You want AI technology to bring your tools together — not create more information silos. That’s why it’s a good idea to look for AI tools that connect with your CRM, communication platforms, and other pieces of your tech stack.

An integrated AI also saves your team time since they don’t have to manually switch between apps. And think about what it can do for the customer journey: you can easily follow a trail of context as they leave messages in your phone system, email inbox, and beyond.

3. Choose AI tools that are easy to use

Keep your eyes peeled for user-friendly AI tools that don’t require onboarding or advanced coding knowledge. That way, everyone on your team can leverage AI immediately and start splitting responsibility for incoming customer queries. 

4. Track success metrics

AI tools are an investment, so set clear KPIs. This could be something like first response time for your support team, customer satisfaction scores after a customer goes through self-service workflows, or first call resolution rates for your customer service team.

5. Ensure AI tools meet privacy and security standards

Most (but not all) AI tools offer privacy and data security. That said, it’s a good idea to do your homework and make sure they meet your needs — especially if you’re in a sensitive industry like healthcare.

When you’re researching tools, be sure to check for privacy information on the company’s website. Can’t find anything? Reach out to the sales team for specifics or consider a more transparent provider.

Start using AI in customer communication with OpenPhone

AI tools can help you streamline customer conversations so you can focus on what really matters: building meaningful relationships. This means no more wasting time on repetitive tasks or questioning your life choices every time the phone rings.

But keep in mind that picking the right tools matters — and investing in quality ones will give you better results. An AI-powered phone system like OpenPhone can help you get started with easy-to-use tools like call routing, call views, call tags, transcripts, and shared inboxes.

Sign up today for a seven-day free trial and start using AI tools in OpenPhone.

P.S. Want a closer look at use cases? Read our guide to AI in customer service.