Case Study - 176% Boost in Google Reviews: How Our Automated System Drives Growth

Overview: Developing an Automated System to Boost Google Reviews and Streamline Management

PizzaForno approached us with the goal of increasing Google reviews across their 70+ pizza locations in North America. Our challenge was to develop and implement a tailored digital marketing strategy that not only streamlined the review process for consumers, but also optimized internal management capabilities. This strategy needed to enable their team to efficiently sort, filter, and manage all reviews through a single, user-friendly interface while also driving consumer engagement for the brand.

Understanding the Problem

PizzaForno was looking to boost Google Reviews across all its locations. Specifically, they needed a solution that would not only increase Google Reviews effectively, but also centralize their review management.

Why would they want this?

Firstly, 71% of potential consumers would not consider using a business with an average rating below three stars, according to this study.

If you think about it, would you want to go to a pizza restaurant with less then a 3 star Google rating?

So, the importance of not only maintaining but actively improving online ratings cannot be overstated—it's a key factor for attracting and retaining customers.

This helps give an idea as to why reviews are so important, especially for a pizza chain. If their Google reviews were under 3 stars, they would risk losing out on 71% of potential customers who discover them via Google.

So we had to ensure this didn't happen.

The challenge was not just about coming up with a solution for a single location; PizzaForno operates essentially as a "franchise" with over 70+ locations across North America. Therefore, we needed to tailor our strategy to be scalable and applicable across the entire fleet, ensuring uniformity in the review management process while accommodating the unique needs of individual locations.

For context, PizzaForno operates automated pizza vending machines, not traditional restaurant locations. Because these machines are fully automated with no on-site staff, conventional strategies like having a server ask for reviews or placing QR codes on tables are not applicable.

This unconventional business model required a different strategy to encourage customers to leave reviews after purchasing pizza.

Given the uniqueness of PizzaForno's automated pizza vending machines, we needed a method to collect customer data and accurately determine which location they visited. This information would allow us to tailor our digital marketing campaigns effectively, ensuring that follow-up requests for Google reviews are specific to each customer's experience at a particular machine.

Previously, PizzaForno’s customer contact lists via SMS and email only contained basic information like names and contact details, without any detailed tagging for effective segmentation. This limitation made it difficult to identify which specific vending machine a customer used, preventing us from sending them a tailored review link for the corresponding Google Business profile.

To efficiently generate Google reviews through our marketing campaigns, we needed to identify the specific machine each customer had used or was planning on using.

Thankfully, we did solve this data collection issue.

Another hurdle we had to keep in mind that our solution had to be scalable. As PizzaForno is in its growth phase, it was essential to create a system that their team could implement and utilize effectively for years to come.

Finally, lets get to the elephant in the room.

Only 66% of PizzaForno’s Google Business Profiles were verified, meaning the remaining 33% of locations were not even visible on Google. This problem arose because their machines are automated and unmanned, which complicated the typical Google verification process that usually involves sending a postcard to a physical location.

Addressing this issue was essential to ensure all locations could effectively gather reviews and enhance their online presence.

The Solution: A Comprehensive Digital Marketing Strategy and Review Automation System

In order to tackle this challenge head on, we designed a comprehensive plan that combined digital marketing and custom software development.

Here’s what we needed to do:

1. Bulk verify the Google Business Profiles

2. Optimize the profiles for reviews

   • Implement local SEO strategies

3. Get access to the Google Business Profile API

4. Update our location management tools

5. Develop a custom dashboard to manage reviews

   • Integrate with the Google Business Profile API

   • Aggregate data to display analytics

   • Integrate one-click AI-generated responses

6. Integrate review pop-ups on location pages

7. Create new data collection & tagging processes

8. Create automated email campaigns

9. Develop customer engagement surveys

With all that planned out, we began our efforts to implement a targeted marketing strategy for PizzaForno.

The first step was bulk verification of all Google Business profiles under the PizzaForno brand. Here's how we did it:

Google Bulk Verification

When our team started working with PizzaForno, only 66% of their Google Business Profiles were verified, which left a third of their profiles unlisted on Google. This was a significant issue for a chain with over 70 locations, as unverified profiles limited their online visibility (no one could leave a review even if they tried).

The challenge stemmed from the fact that PizzaForno's locations are fully automated, with no onsite staff. This setup did not align with Google's standard verification process, which typically involves confirming a physical location through mail or staff interaction.

To resolve the verification issue, our team collaborated directly with Google representatives. We supplied the required documentation, systematically formatted the location data for all profiles, and did a few other things. This process ended with us securing verified Google Business accounts for the business groups we made. This ensured each location was now visible on Google.

Thanks to this process, the entire PizzaForno chain was now verified.

Most importantly, because we went through the rigorous process of getting our business groups "bulk verified," any new Google Business Profiles we create for the company are instantly verified on Google. This allows us to easily scale and add new locations without worrying about this roadblock any longer.

Google Business Profile Optimization

Once all we had all the locations verified and listed on Google, our team optimized each of the 70+ profiles.

This process involved a few main steps:

The first step was to incorporate SEO-optimized local keywords into each description. This approach helps inform Google's search engine about the listing's content.

Additionally, we needed to set up the correct categories across all locations, such as "pizza restaurant" and the subcategory "pizza takeaway." This categorization signals to Google exactly what the business is, helping it appear in local search queries like "pizza near me". For bulk verified accounts, it's a requirement that all categories match across the brand to maintain consistency and clarity for search engines.

We won't dive into all the little strategies we used, but we ensured each profile had updated menus, relevant pictures (if available), and other enhancements.

Overall, we filled out as much of the profile data as possible because, according to Google, comprehensive data completion is key to improving your local ranking.

Local SEO Enhancements

When we built the PizzaForno website, we developed custom landing pages for each of there 70+ locations as part of our comprehensive SEO strategy.

You can view the location finder we created here.

Now that we had these landing pages, we linked them to their corresponding Google Business Profiles to enhance local SEO.

By adding the related website URL to each profile, we helped these pages rank higher in Google's map pack, which provided additional organic traffic.

Maximizing our visibility in Google's map pack meant that when customers searched for related keywords, they were more likely to visit these pages. This increased traffic helped boost the number of reviews we received, creating a positive feedback loop that further improved local SEO efforts.

Through this snowball effect we accumulated more reviews, which helped improve our SEO. As our SEO improved, it enhanced the overall visibility of our pages, effectively attracting more customers, which then leave more reviews, and so on...

Google Business Profile API Integration

Once we had finally got all the profiles verified and optimized our next step was to integrate them into the custom dashboard we developed.

To facilitate this we submitted our access request form to Google and got approved to use their Business Profile APIs.

Once we obtained access to the Business Profile API it allowed us to:

• Display all reviews in one centralized location

• Respond directly to reviews from our dashboard interface

• Fetch all Google reviews programmatically

• Implement additional functionalities for enhanced management

In short, we could build some cool sh*t.

Custom Developed Admin Dashboard

Previously, we had designed and developed both the PizzaForno website and a custom admin dashboard to manage location data, and other information critical to their business operations.

We aimed to add new features to the dashboard to enhance our review campaign and create a scalable review management system for future use.

Here's what we added:

Location Management Tool

For some context, the admin dashboard we built for the PizzaForno team features a system that streamlines the addition and modification of internal PizzaForno location data.

This is used internally to track and manage all of the data associated with the PizzaForno fleet. This data is also used to generate the location pages on PizzaForno's website, with each of the 70+ locations having their own custom dedicated page.

We had previously developed a location management tool within the dashboard, which we then updated in order to store the Google Business Profile Review URL for each location. We included fields to add the GMB URL, GMB ID, and GMB Account ID (Google my Business, same thing as Google Business Profile).

This update allowed us to sync each location page on the website directly with its associated Google Business Profile. This streamlined the management of these URLs, making it easy for team members to add them and ensure consistency across their site.

Once a review URL was added, a visually engaging pop-up would appear on the corresponding page on the website. This would direct users to leave a review on the matching Google Business Profile.

Once we added this feature and implemented all the corresponding URLs, we instantly created over 70 new engaging pop-ups across all location pages on the site.

This means there are now 70+ additional opportunities for customers to be guided to leave reviews.

Even More Local SEO Optimization

Additionally, another benefit of these dedicated location pages is the enhancement of local SEO. As each page begins to rank for local search queries, the increased visibility boosts traffic. This in turn helps generate more reviews as each visitor to these pages is shown the review pop-up.

The image below showcases the organic search traffic across the location pages, which together generated over 14,500 clicks and more than 615,000 impressions in just 7 months.

Building a Review Management Dashboard

Using our newly obtained access to the Business Profile API, we developed our "Google Review Management Dashboard".

This interface allows users to view reviews from every PizzaForno location on a single page. With dozens of locations, it became a massive time saver, providing a clear overview of the online engagement and feedback we were receiving.

We added search functionality within the interface to help sort and display reviews based on specific locations, keywords, phrases, and more, making review management even more efficient.

Additionally, we implemented filters to sort reviews based on rating, location, date, and other criteria. This feature helps the team manage customer engagement and support more effectively in their daily operations.

The most significant boost to daily operations provided by this review management tool was the ability to respond to reviews directly from the dashboard. This is what we call our "AI Auto-Response System".

AI-Integrated Auto-Response Review System

Inside the review management tool, we integrated a feature using the OpenAI API, which includes a button to generate AI-crafted responses tailored to individual customer reviews.

To make this work correctly, a custom AI assistant was developed to ensure that the responses matched the company's tone, aligned with our specified response criteria, and were trained on the business's specific needs.

This integration, tailored to our exact instructions, streamlines workflows and significantly reduces response times. By providing the team with tools to:

1. Respond to all reviews in one place

2. Craft personalized responses using AI with a single click

3. Publish responses directly to the Google Business Profile

It greatly enhances both employee efficiency and customer engagement. These responses are published directly to the corresponding Google Business profile through the Business Profile API.

The "icing on the cake" was the addition of a button to generate a $5 off code, which could be included in responses to customers who had a negative experiences. This feature helped turn potential negative feedback into positive customer interactions.

At first glance, this may not seem difficult to implement, but it required a lot of custom development and integrations. We documented the entire process in our other case study: 1800% Increase in Email Signups: Streamlining Code Distribution and Data Collection Processes

Google Review Analytics Dashboard

Another key feature of the review management system we built was the integration of Google Review analytics into a user-friendly interface.

These analytics helped visualize trends and track the effectiveness of our campaigns, providing the team with valuable insights for ongoing improvement. Plus, they looked cool.

To make this work, we aggregated Google Business Profile data from all locations using the Business Profile API.

We then displayed the Google Review analytics through a modern user interface, allowing users to sort reviews by location, time, ratings, and other criteria.

This intuitive user interface helps visualize trends across all locations, giving the team deeper insights into current operations and aiding in more informed business decision-making.

The screenshot below was taken after the campaign was implemented, making it a great visual to showcase the success of the strategy we developed.

Automated Email Campaigns

At this point, we had verified and optimized all Google Business Profiles, added pop-ups on each location page with their corresponding review URL, and built a dashboard to manage all reviews in one place. These actions alone were already boosting review rates and making internal processes more efficient.

But...

We knew we could drive even more reviews through tailored email campaigns.

However, there was one issue:

We didn’t know which locations customers had visited. In other words, we lacked a way to segment them by location in order to send them the specific review URL for the location they visited.

When a customer purchases a pizza at the machine, we don’t have much information about them. We don't know their name, phone number, or email... In other words, nothing.

So how could we email them for a review?

This is how:

Data Layers, Audience Fields, and Merge Tags

To solve this, we integrated email pop-ups and embedded forms on each location page, added QR codes to the machines' 32" digital screens via video format, and implemented custom signup forms on the website.

When a customer submitted their email through one of these forms, their contact information was tagged with specific data layers. In this case, the Google Review URL corresponding to the location they visited was added to their contact details.

This allowed us to capture customer information and follow up for reviews.

We covered this in depth in our Email Signup Case Study. If you'd like to know more about how we did it, feel free to check it out!

But in short, these data layers function as dynamic repositories that capture and organize user interactions on the website—like page visits and form submissions—before sending this structured data to MailChimp.

To automate and personalize the email campaigns, we connected to the MailChimp API, allowing us to programmatically update contact lists and manage tags based on the data layers.

Here are the audience fields and merge tags we used, with "GMB" as the field that captured the Google Review URL:

Utilizing these data layers, we created automated email sequences with custom merge tags that dynamically inserted the Google review link from the customer's profile, corresponding to the location they chose or signed up from.

This setup enabled us to send targeted emails with the exact Google Business Review URL for the location the customer visited, ensuring that reviews were accurate and location-specific.

This feature not only prevented misplaced reviews from individuals who had never visited those locations but also simplified the customer experience, allowing them to easily navigate directly from the email to the correct Google Business profile to leave a review.

Since launching this email campaign, we've sent 8,680 emails asking customers for reviews. While that seems like a lot, we acquired nearly 5,000 new email contacts. The total number of clicks was 431, resulting in a 5.0% click-through rate (CTR). For a pizza chain in the restaurant and venue industry, a CTR of 5.0% is considered very strong.

The typical CTR for the restaurant sector is 1.58% according to Mailchimp. As our campaign is over 200% more than that, we can infer that the content is engaging and effectively driving interactions.

Image via the Mailchimps email metrics tool:

Although, we did underperform on the unsubscribe rate, primarily due to the nature of the campaign (sign up to get a $5 code). Once they received the code, 1.2% of users chose to unsubscribe.

Customer Feedback & Engagement Survey

In addition to sending automated emails requesting reviews from customers, we also integrated a custom form on our website to proactively address any potential negative experiences.

By clicking on 4 or 5 stars in the email we sent, customers were immediately directed to the Google Business Profile to leave a review. However, if they clicked 1, 2, or 3 stars, they were redirected to a custom survey we built to help us understand why their experience wasn't ideal.

This helped us resolve issues before they could impact overall customer satisfaction.

Here is the review email the customer would receive:

Under the "good" and "great" buttons, we included a custom merge tag with the link to the corresponding Google Business Profile.

But under the "bad," "poor," or "okay" buttons, we inserted a link to a survey on our website. This allowed us to gather more detailed feedback and address their concerns directly.

We anticipated that some users might misclick or explore the email out of curiosity, potentially leading to customers who intended to leave a positive review getting lost and ending up on our feedback survey instead of the Google Business page.

To address this, we created even more tags.

If a customer initially gave a low rating on the email but later submitted a 4 or 5-star rating on our survey, we applied a custom tag connected to a specific data layer and updated their contact details on Mailchimp. We also applied the same tagging approach if the customer submitted a 1, 2, or 3-star rating on our survey.

Based on our website survey, customers would be tagged as either "high_rating" or "low_rating."

This action automatically enrolled them in a follow-up email campaign we created. If they were tagged with "high_rating," they received an email inviting them to submit a review at a later time. If they were tagged with "low_rating," they received a different email apologizing for their experience.

Here’s how one of the high-rating retargeting emails in that sequence looked:

Here is how the low-rating retargeting email looked:

This approach ensured that we not only maximized opportunities for positive reviews but also addressed negative experiences effectively, improving our customer service and loyalty.

Project Summary

Our team developed and implemented a comprehensive digital marketing strategy to enhance and manage Google Reviews for PizzaForno. This strategy included bulk verification and optimization of all Google Business Profiles, the creation of custom data layers for advanced tracking, and the integration of automated email campaigns. We also designed and deployed custom web development solutions for location-based review pop-ups and built a user-friendly dashboard for managing Google Reviews across PizzaForno’s 70+ locations.

The Product: What We Developed

The Google review dashboard integration was crafted with:

Client Testimonial

The Results: A Streamlined Google Review Management System

Initially, there were multiple hurdles we had to overcome and figure out. But, we successfully addressed each one and made the strategy work effectively.

The custom-built review management system enabled the team to efficiently manage, track, and respond to reviews from a single dashboard. This automation streamlined their business operations, improved overall productivity and freed up valuable time for other priorities.

Through our custom email pop-ups, local SEO efforts, and additional web development techniques, we were able to boost organic traffic and enhance visibility across all locations.

Finally, by leveraging custom data tracking and automated email funnels, we were able to effectively communicate with customers and request reviews—something that was previously not possible.

This tailored digital marketing strategy and software development work for PizzaForno resulted in significant improvements in online engagement and review generation.

Here are the results:

In the end, this comprehensive approach resulted in a significant 176% increase in Google Reviews. As of writing this case study, the average Google rating across North America is 4.06, not bad! Even more impressive, the streamlined system we implemented saved the team over 8 hours a week, translating to more than 40 hours a month.