Car Dealers: How to Humanise Your Review Responses When Using AI. Expert Tips

Using AI tools like ChatGPT to respond to customer reviews?

In this guide, we’ll show you how to instruct your AI review response tool (or ChatGPT) to write responses that sound like they were written by you.

Many car dealerships fall into the trap of using AI-generated responses to save time and improve their response rates.

But here’s the hard truth: customers can spot an AI-generated review reply from a mile away, and it can hurt their trust in your dealership.

In fact, a recent Bynder study found that 50% of consumers can detect AI-generated content.

A separate study by Markowitz, which focused on AI-generated reviews, revealed additional challenges.

The study found that AI text tends to be more analytical, overly emotional, and less readable than responses written by humans.

Why AI Review Responses Can Fail

Imagine leaving a heartfelt review about your car-buying experience and getting a lifeless, robotic reply.

Disappointing, right?

That’s how your customers feel when they receive overly formal, emotionless AI review responses.

Common AI review response pitfalls include

• Generic, formal language that lacks warmth
• Excessive repetition or overly complex sentences
• Responses that don’t match the tone or mood of the review

Why Human-Like AI Review Responses Matter

Even as AI advances, it often falls short of generating review responses that truly read like they were written by a human.

This gap can be addressed if the AI review response tool has been provided with custom instructions.

For car dealerships, getting review responses right is crucial for several reasons:

1. Building Trust and Authenticity: Customers expect authenticity in their interactions. A response that sounds robotic can feel insincere, eroding trust in your dealership.
2. Conveying Empathy: Reviews are inherently human. Whether a customer is praising or complaining, a well-worded, empathetic response strengthens the relationship.
3. Reflecting Brand Voice: Your dealership has its own personality and voice. Human-like responses help reinforce that identity and create a consistent customer experience.
4. Navigating Nuance: AI that can be custom-instructed to recognise tone and context will better address customer concerns, particularly in sensitive or complex reviews.

How to Train AI to Write Review Responses Like a Human

Here’s a step-by-step guide to custom-instructing your AI review response software to write responses like a human.

TIP 1: Use first-name pronouns

AI responses cannot replicate the emotional depth that characterises human writing.

Recognising these limitations allows you to develop strategies to bridge the gap.

Training your AI to use first-person pronouns is a simple way to make responses feel more personal and human-like, even though AI can’t truly experience emotion.

By mimicking emotional responses, AI can create more natural and engaging interactions.

Here’s how you can train your AI to use first-person pronouns effectively and mimic human-like empathy:

Train the AI to Use "I" Statements:

Instruct your AI to incorporate first-person language to create a personal touch and mimic human emotion.

Example prompts:

Train the AI to say:

"I apologise for your experience" or "I'm glad to hear you enjoyed the car-buying process."

These statements create a connection that feels more genuine.

Incorporate Personal Responsibility:

Guide your AI to show personal accountability, which can simulate human care and responsibility.

Example prompts:

Teach the AI to respond with:

"I will personally look into this matter" or "I appreciate you bringing this to our attention."

While the AI can’t feel personal concern, it can use phrases that make the interaction feel more thoughtful.

Train the AI to Mimic Empathy:

While AI doesn’t feel empathy, it can be programmed to recognise emotional cues in reviews and respond in ways that reflect understanding.

Example prompts:

Program the AI to respond to frustration with:

"I understand how frustrating this must have been for you" or "I can see why this would be disappointing."

This helps humanise AI review responses by mimicking empathy.

Simulate Personal Experiences (When Appropriate):

For positive reviews, train the AI to use a conversational tone by referencing fictional personal experiences.

Example prompts:

"I've driven this model myself and love it" or "I often recommend service plans to our customers."

Although these are fictional, they create a relatable, human-like response that fosters engagement.

Balance Singular and Plural Pronouns:

Teach your AI to alternate between "I" and "we" pronouns, as this reflects a natural conversational tone and responsibility-sharing.

Example prompts:

"I will ensure our team addresses this" or "We value your feedback, and I will share it with our management."

Avoid Overuse:

Ensure the AI doesn’t rely too heavily on "I" statements.

Vary sentence structures to maintain a natural flow.

Training guidance:

Program the AI to alternate between first-person pronouns and other phrasing to avoid repetition and ensure responses feel more natural.

By training your AI to simulate human-like responses through personal pronouns, you can bridge the gap between automation and personalisation, ensuring your customer interactions feel warm and genuine.

Benefits of Using First-Person Pronouns

1. Increased authenticity: First-person pronouns make responses feel more personal and genuine.

2. Human touch: They create the impression of a real person responding, rather than a generic corporate voice.

3. Emotional connection: "I" statements can convey empathy and personal responsibility more effectively.

4. Conversational tone: First-person language naturally leads to a more conversational and relatable style.

TIP 2: Train AI for Conversational Tone

When developing your AI review response system, focus on training it to generate replies with a conversational tone.

This approach creates more engaging and relatable interactions with customers.

Here's how to train your AI:

Informal Language: Teach the AI to use everyday phrases and contractions.

Train it to say:

"Thanks for sharing your thoughts!" instead of "We appreciate your feedback."

Rhetorical Questions: Program the AI to incorporate relevant questions that encourage dialogue.

Example training:

"How's your new car treating you? We'd love to hear more about it!"

Personal Pronouns: Instruct the AI to use "I" and "we" to create a sense of connection.

Train responses like: 

"I'm so glad you enjoyed your visit! It was great meeting you."

Conciseness: Train the AI to keep responses brief and to the point.

Example:

"I'm sorry about the wait. Let's sort this out for you."

Active Voice: Teach the AI to use active voice for more dynamic responses.

Train it to say:

"Our team really appreciates your feedback!" instead of "Your feedback was appreciated by our team."

By focusing on these elements during AI training, you'll create a system that generates more human-like, conversational review responses, enhancing customer engagement and trust.

TIP 3: Provide Context to Maintain Coherence

When training your AI to respond to reviews, focus on teaching it to provide relevant context.

This ensures responses are coherent and demonstrate a genuine understanding of the customer's experience.

Key aspects to train your AI:

Reference Specific Details: Teach the AI to mention car models, services, or staff members from the review.

Example:

"I'm glad the Hyundai Tucson exceeded your expectations! Its towing capacity is impressive."

Acknowledge Visit Type: Train the AI to differentiate between service (customer service) and service (car service).

Example: 

"Thank you for sharing your experience during your vehicle service. I am sorry to hear about the wait time and l will look into the issue."

Use Relevant Timeframes: Instruct the AI to mention visit timing when pertinent.

Example: 

"Since your visit last month, we've implemented a new customer service training program."

Connect to Previous Interactions: When applicable, teach the AI to reference prior visits or purchases.

Example: 

"It's great to see you back for your annual service. Your continued trust means a lot."

Address Seasonal Factors: Train the AI to mention relevant promotions or seasonal aspects.

Example:

"Many thanks once again for leaving a review. Can I take this opportunity to wish you and your family a Merry Christmas and a prosperous New Year?" 

By training your AI review response tool in these aspects, you'll create responses that are more personalised, relevant, and coherent, enhancing the overall quality of your AI review responses.

TIP 4: Use Natural Language Processing.

To make AI-generated review responses more human-like, focus on improving the AI's language understanding capabilities.

Here are key areas to consider:

Emotional Tone Recognition:

Train your AI to detect the customer's mood from their review.

Example: For a delighted customer, the AI might respond:

"I am happy to hear you're enjoying your Toyota Yaris.  Your excitement really comes through in your words."

Context understanding:

Teaching the AI to distinguish between similar words with different meanings 

• "Service" referring to customer service
• "Service" referring to vehicle maintenance or repair

Example:

Review:

"Great service, vehicle drives like new."

AI response: 

"It's great to know you were satisfied with your annual vehicle service. Our technicians work hard to ensure every car leaves our service centre in top condition."

Specific Detail Identification:

Help the AI recognise and use important details from the review.

Example: 

"It's great to hear you're happy with the spacious interior of the Hyundai Tucson and it meets your family's needs. It's no surprise it was voted Best Family SUV." 

By focusing on these areas, your AI can generate responses that feel more personalised and natural, showing customers that their specific feedback has been understood and valued.

This approach helps create a more human-like interaction, even when using AI to manage review responses.

TIP 5: Personalise with Specific Instructions 

Personalisation is a critical factor in making AI-generated reviews feel more human.

By providing specific instructions about your different customer types (branch, location, brands, sales or service customers), you can guide the AI to create more tailored and relatable responses.

Here's how to effectively implement this strategy for a car dealership:

Use Customer Names

• Always address the customer by their first name to create a personal touch.

Example:

"Hi Sarah, thank you for your kind words about our team!"

2. Handling Username-Only Reviews

• Train the AI to address reviews where only a username is available, adding a touch of context and personality to the response.

Example:

"Dear SpeedyDriver88 (great username, by the way!), I appreciate you taking the time to share your experience with us."

Personalise with Location-Specific Details

Example: 

"I'm pleased to hear you love your new Honda CR-V.  Make sure you take it for a Sunday drive to <popular scenic driving local road>"

Include Soft Upselling in Responses

Train the AI to subtly and randomly introduce upselling opportunities within responses, ensuring it doesn't appear in every review to avoid seeming forced or overly sales-focused.

Example:

"I'm thrilled you're enjoying your new Honda Civic. In case it was not mentioned, you may be interested in our Honda service plans." 

The more personalised the instructions, the more likely the AI is to produce review responses that resonate with your customers.

This approach helps create a sense of authenticity and connection typically associated with human-written review replies. 

TIP 6: Feed Your Tool with Your Writing Examples.

Many franchise directors and dealership owners prefer a hands-on approach, personally responding to customer reviews.

While this dedication to personal touch is commendable, it's often not sustainable in the long run, especially as the volume of reviews grows.

Fortunately, there's a way to maintain that personal touch while leveraging the efficiency of AI: training your AI review response tool to write in your own style.

This process teaches the AI to speak your language, using your unique voice and expressions.

By feeding the AI with examples of your writing, you can create a powerful system that generates personalised, high-quality responses that closely mimic your unique voice and approach.

This strategy offers the best of both worlds: the efficiency and scalability of AI combined with the authenticity and personal touch of your own writing style.

It allows you to maintain consistency in your brand voice across all customer interactions, even as you handle a growing number of reviews.

Here's how you can do it: 

• Collect Samples: Gather samples of your own writing or select pieces that capture the tone and style you want your AI to emulate.
• Train the AI: Use these samples to train your AI tool, guiding it to understand and replicate the nuances of your writing style.
• Mimic the Style: Instruct the AI to mimic the style and structure of these examples in its responses.

Remember, the quality of these training samples directly impacts the quality of the AI review responses.

So, be selective and ensure that the samples you use are well-written and representative of the style you want to achieve.

This technique can significantly improve your AI review response tool's ability to mimic human-like writing, making responses sound more natural and less robotic.

TIP 7: Inject Personality into AI 

Teach your AI to add personality to review responses, making them more authentic and engaging. Here's how:

Develop a Brand Voice Guide

Create a document outlining your dealership's unique voice.

Include tone, key phrases, humour guidelines, and banned words.

Example: Train AI to say, 

"We're not just your local Toyota dealership - we're part of the [Town Name] community!"

Use Conversational Language

Instruct AI to use relaxed, natural language.

Example:

Instead of "We appreciate your patronage," train AI to say, "Thanks for choosing us - it means a lot!"

Incorporate Local Flavour

Teach AI to reference local events, landmarks, or colloquialisms.

Example: 

"Your new Mazda MX5 is perfect for a drive down [Local Road] or a trip to [Local Hotspot]!"

Add Appropriate Humour

Train AI to include light-hearted comments for positive reviews.

Example: 

"Glad you're loving your new car! Just remember, it doesn't come with a speeding ticket exemption!"

Use Emojis Sparingly

Instruct AI to incorporate relevant emojis for warmth, but avoid overuse.

Never use emojis in responses to negative reviews.

By training your AI in these aspects, you'll create responses that feel more human, strengthen customer connections, and differentiate your dealership from competitors.

Tip 8: Work with the AI to improve Review Responses.

Creating human-like AI review responses isn’t a one-and-done process. It requires ongoing refinement and adjustment.

This is where you can work with your AI review response software.

By consistently reviewing and providing feedback on AI-generated responses, you can guide the tool to produce more human-like replies over time.

Here’s a simple process you can follow:

1. Generate review replies using your AI review response tool
2. Review the output carefully
3. Identify areas that sound artificial or robotic
4. Provide specific feedback on how to improve these responses
5. Use this feedback to adjust the AI’s parameters or prompts
6. Generate new responses and repeat the process

This iterative approach allows you to gradually fine-tune AI-generated responses, making it increasingly indistinguishable from human-written replies. 

Tip 9: Use Adverbs Sparingly 

Overuse of adverbs can make AI-generated responses feel unnatural.

Here's how to train your AI to use them more effectively:

Limit Adverb Usage

Teach AI to use adverbs only when they add significant value

Example: Instead of;

"We truly appreciate your feedback," train AI to say "We appreciate your feedback"

Use Stronger Verbs

Instruct AI to replace adverb-verb combinations with more precise verbs

Example: Rather than 

"We sincerely apologise," train AI to say "We regret any inconvenience caused."

Identify Commonly Overused Adverbs

Train AI to recognise and avoid overusing adverbs like:

• Truly
• Sincerely
• Extremely
• Highly

Enhance Message Without Redundancy

Teach AI to use adverbs selectively to enhance the message, not make it redundant

Example: Instead of; 

"We are extremely sorry," train AI to say "We apologise for the delay and are working to resolve it."

By training your AI to be more selective with adverbs, you'll create responses that sound more natural and human-like, improving the overall quality of your customer interactions.

Tip 10: Use Natural Word Pairings 

Teach your AI to use word combinations that sound natural to human ears.

This will make responses more fluent and authentic.

Here's how:

Provide Collocation Examples

Train AI with common automotive collocations.

Example: 

"Trade-in Value," "fuel efficiency," "smooth handling"

Replace Awkward Combinations

Instruct AI to use natural phrases instead of stilted ones.

Example: Use;

"We'll look into this issue" rather than "We'll investigate this problem"

Use Industry-Specific Collocations

Teach AI common phrases used in car dealerships.

Example: "Schedule a service," "trade-in value," "extended warranty"

Incorporate Everyday Language

Train AI to use casual, natural-sounding phrases.

Example: 

"Thanks for dropping by" instead of "We appreciate your visit"

Review and Refine

Regularly check AI responses and update training to improve collocation use.

By training your AI to use natural collocations, you'll create responses that flow more smoothly and sound more human-like, enhancing the overall quality of your customer interactions.

Tip 11: Employ Fine-Tuning Techniques.

Fine-tuning is a process that involves training your AI review response tool on a specific dataset that reflects the writing style you want to achieve.

While it requires a bit more technical expertise, fine-tuning can significantly improve your AI's ability to generate human-like review responses.

Here's how to approach it:

Gather Quality Examples

• Collect high-quality, human-written review responses that reflect your desired style.
• Include responses to various types of reviews (positive, negative, neutral).

Create a Training Dataset

• Organise these examples into a structured dataset.
• Include a variety of scenarios and response types.

Train the AI Model

• Use your dataset to fine-tune the AI model.
• This helps the AI learn the nuances of your preferred writing style.

Test and Refine

• After fine-tuning, test the AI's output on new reviews.
• Analyse the responses and identify areas for improvement.

Iterate and Improve

• Based on test results, adjust your training data or fine-tuning parameters.
• Repeat the process to continuously enhance the AI's performance.

Monitor and Update

• Regularly review the AI's responses to ensure they maintain quality.
• Update the training data periodically to keep the AI current with your evolving brand voice.

By employing these fine-tuning techniques, you can train your AI review response software to closely mimic human writing, enhancing the authenticity and effectiveness of your responses. 

Case Study

Conclusion

Humanising your AI review responses is essential for maintaining trust and fostering better relationships with your customers and positively influencing your prospects. 

By training your AI with the right techniques—such as using personal pronouns, adopting a conversational tone, and providing specific context—you can create responses that feel personal, empathetic, and genuine.

Humanising your AI review responses does more than just make the original reviewer feel heard.

They show prospective customers you're engaged, attentive, and genuinely concerned about customer feedback.

With the right approach, AI can become a powerful tool in your dealership’s reputation management strategy—helping you scale your responses without sacrificing quality.