Supercharge your Gsheets with AI

In startups, Googlesheets are often the very first version (V1) of most processes. From operations to Sales, to even Customer Service, many first steps begin with Googlesheets.

In general, the appeal of Googlesheets is undeniable, and rightly so. It is:

1. Free to Use: Googlesheets come with the added advantage of being completely free to use, making them an attractive choice for startups with budget constraints.
2. Provides Seamless Collaboration: Effortless sharing with teammates, and real-time collaboration.
3. Data Analysis Made Easy: Google sheet formula helps with almost all kinds of data analysis capabilities.
4. Scalability and Integration: As your startup grows, transferring Googlesheets content to other tools is a breeze. Further, integration with platforms like Salesforce or Zendesk allows one to scale and optimize effectively.
5. Automation: Probably one of the most important appeals of Google Sheets is automation.

With automation, the appeal of Google Sheets is multiplied.

Initially, automation would require coding skills. For instance, let’s say you have a customer database and want to send personalized email notifications to them based on specific criteria. For this, you would have to add a custom Javascript or Google apps script. These codes would fetch data from your sheet, process it, and then trigger email notifications. It required both technical expertise and time to develop and maintain.

Google Sheets always had this automation appeal, but it required resources to set up.

Now, for the same emailing tasks, we can simply use a plug-in such as Yet Another Mail Merge or Mail Merge with Attachments. These plug-ins allow users to connect Google Sheets with their email accounts, specify email templates with placeholders for personalized information, and trigger mass email sends based on criteria directly from the sheet. You don't need any coding knowledge to set this up, and with just a few clicks you are good to go.

Automation has been made very easy by incorporating these AI-powered add-ons and tools. Setup, in most cases, is cut down to just finding the right tools and getting started.

We want to make it even easier for you.

In this comprehensive deep dive, we will explore some of the most powerful AI tools available for Google Sheets, offering data analysis, automation, visualization, and more. With these tools, you can extract insights, streamline workflows, and make data-driven decisions efficiently.

1. AppSheet

Can you imagine creating mobile apps with your Google Sheets data? AppSheet allows you to do that.

AppSheet leverages artificial intelligence and machine learning to allow users to create tailored mobile and web applications with ease. It eliminates the need for traditional coding knowledge by providing a user-friendly interface that enables users to design applications using a drag-and-drop approach. By connecting directly to Google Sheets as a data source, it ensures that any changes made to the underlying spreadsheet automatically reflect in the application. This integration helps a lot with data management and ensures real-time updates.

Let's explore various use cases to understand this better:

a. Data Collection Apps: Suppose a company wants to collect data from field agents or customer feedback from multiple locations. AppSheet allows users to build data collection apps that enable field personnel to enter information directly into the app, which then syncs with the central Google Sheets spreadsheet. This guarantees data consistency and eliminates the need for manual data entry. The employees can do this on the go on the app instead of working on the Google sheet for each entry.

Or a retail company can develop a store inventory app using AppSheet, enabling store managers to update inventory levels, add new products, and track sales, all while automatically updating the central product database in Google Sheets.

b. Sales and Customer Relationship Management (CRM) Apps: AppSheet is ideal for creating sales and CRM applications. Sales representatives can access customer data, view purchase history, and log interactions, facilitating more personalized and effective communication. Furthermore, sales managers can use the app to track team performance and identify sales trends. If you want certain notifications or triggers, you can also build customization on the app for your own use case.

An example would be a real estate agency that can leverage AppSheet to build a CRM app that assists agents in managing leads, scheduling property viewings, and maintaining client communication. The app can be tailored to notify agents of critical follow-ups and deadlines.

Another noteworthy benefit of AppSheets is that applications created with them can work offline This is a significant advantage for certain business applications that are intended to be used in the field but without the certainty of having Internet access.

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2. Supermetrics

Can you imagine collaborating on all your marketing metrics without Google Sheets/Excel? Probably not. Supermetrics is like a genie + VA combined for all your marketing data needs.

Supermetrics is a data integration tool that empowers you to effortlessly gather, analyze, and visualize data from various sources, right within Google Sheets. Imagine you're a digital marketing manager responsible for monitoring and optimizing your company's online advertising campaigns across different platforms. With Supermetrics, you can seamlessly connect Google Sheets to major advertising platforms like Google Ads, Facebook Ads, and LinkedIn Ads.

For instance, let's say you want to monitor your Google Ads' performance and analyze key metrics like clicks, impressions, and conversion rates. Instead of manually exporting and importing data from Google Ads to Google Sheets, you can simply use Supermetrics. With a few clicks, you can set up a data connection between Google Sheets and Google Ads, selecting the specific metrics and dimensions you want to retrieve. Supermetrics will automatically fetch the data and populate your Google Sheets with the latest performance metrics, all in real-time.

It also helps you integrate data across platforms. Let's take another example. As a social media manager, you need to keep track of your company's social media performance across platforms like Facebook, Instagram, and Twitter. Instead of juggling multiple data sources and spreadsheets, you can integrate your social media data into Google Sheets, analyzing engagement metrics, post reach, and audience demographics, all in one centralized location. No manual exporting and importing of data; Supermetrics sets up data connections, fetching the latest performance metrics in real-time, right into your Google Sheets.

Across platforms, but also across different data sources. An example here would be if you're an SEO specialist, you can utilize Supermetrics to pull data from Google Analytics, Search Console, and other SEO tools directly into Google Sheets. This allows you to analyze website traffic, keyword rankings, and user behavior, providing valuable insights for optimizing your website's search engine performance.

This automation not only helps you save time but also customizes reports. Your data only makes sense when it is structured in a way that suits the use case. Supermetrics allows you to choose the metrics or data points that you want for each use and present reports accordingly.

One of the biggest advantages of Supermetrics is its simplicity. You don't need to be a data expert or a programmer to use it effectively. Its user-friendly interface allows anyone to set up data connections and automate data refreshing with ease. Moreover, you can create customized reports and dashboards that suit your specific needs, making data analysis a breeze.

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3. Sheets AI

Sheets AI is an add-on that enhances data analysis capabilities within Google Sheets. Imagine you're a sales manager, and you need to analyze a large dataset of sales transactions to identify trends and patterns. With Sheets AI, you can easily gain deeper insights without complex data manipulation.

How? Let's say you have a dataset containing sales figures for different products across various regions and time periods. Using Sheets AI's "Insights" feature, you can quickly identify the top-selling products, best-performing regions, and peak sales periods. This automated analysis saves you a lot of time.

It is more than just basic insights. For instance, for financial analysis, you often need to perform complex calculations and forecast future stats. Sheets AI's "Predictions" feature enables you to build accurate forecasts based on historical data.

Further, Sheets AI's "Segmentation" feature can also be super valuable. For instance,  you can segment your customer data based on demographics, behavior, or other variables to identify target audiences for specific campaigns or promotions. This data segmentation simplifies your marketing efforts, leading to better customer engagement and improved campaign performance.

Sheets AI also offers advanced data visualization with its "Charts" feature. Instead of spending hours creating visualizations, you can now generate interactive charts and graphs directly within Google Sheets.

Once again, you don't need to be a data scientist or a programming expert to take advantage of its powerful features. The add-on's intuitive interface and step-by-step guides ensure that anyone, regardless of their technical background, can leverage its capabilities effectively. It is a text-to-command kind of interface.  You can explain the tool in simple English what you would want, and voila! it produces the command for you.

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4. Simple ML

Simple ML is a free and open-source Google Sheets add-on that makes it easy to use machine learning without knowing any coding or machine learning expertise. It is designed for beginners and provides a simple interface for tasks such as predicting missing values, spotting anomalies, and clustering data.

Let’s understand with an example. Say there is a startup that sells online courses. It could use Simple ML to predict which students are most likely to churn.

The startup would need to provide Simple ML data about its students. This data could include things like the students' demographics, their progress in the courses, and their interactions with the course material. Once Simple ML has the data, it will use it to train a model. The model will learn the factors that are most likely to lead to students churning. For example, the model might learn that students who are more likely to churn are those who are not progressing in the course or who are not interacting with the course material. You could then use this data to reduce churn by sending them motivation or reminders.

With simple ML, it is easy to train the algorithms as per your need with some simple steps.

Here are some more use cases to understand the potential of simple ML:

1. Customer segmentation: With Simple ML, startups can segment customers based on their data, allowing them to target marketing efforts effectively. For instance, a clothing startup could use Simple ML to segment customers based on their clothing preferences, demographics, and purchase history.
2. Product recommendations: Simple ML enables startups to recommend products to customers based on their data, boosting sales. For example, an online bookstore could utilize Simple ML to suggest books based on customers' purchase history and ratings. This recommendation increases the user experience of the user and creates higher conversion. You can integrate this data and recommendations directly on your site.
3. Fraud detection: Startups providing financial services can use Simple ML to detect fraudulent transactions, safeguarding customers from financial loss. By analyzing transaction data, such as amount, IP address, and location, Simple ML helps identify potential fraud.
4. Image classification: With Simple ML, startups can classify images, aiding users in identifying objects. For example, a plant identification app startup could use Simple ML to classify images of plants based on features like color, shape, and size.

The use cases of simple ML are as wide as your imagination. You can use the tool to elevate any of your existing data and automate a lot of your processes.

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5. Promptloop

PromptLoop is an AI-powered tool that helps users transform, extract, or summarize text data in Google Sheets. It provides a variety of features that can be used to improve the accuracy and performance of data analysis in Google Sheets.

For example, you could use PromptLoop to extract text from web pages, PDFs, or images, and then summarize the text to identify the key points.

Let's explore how prompt loop enables users:

• Text transformation: PromptLoop can transform text data in a variety of ways. For example, it can convert text to different formats, remove punctuation, or extract specific information from text. This can be useful for startups that need to clean up or manipulate text data.
• Text extraction: PromptLoop can extract text data from a variety of sources. For example, it can extract text from web pages, PDFs, or images. This can be useful for startups that need to collect data from external sources.
• Text summarization: PromptLoop can summarize text data in a variety of ways. For example, it can create a short summary of a text passage, or it can identify the key points of a text. This can be useful for startups that need to quickly understand large amounts of text data.

Let’s understand this better with some use cases:

• Developing new products and services: PromptLoop can be used to develop new products and services. For example, a startup could use PromptLoop to extract text from customer reviews, and then summarize the text to identify the key pain points that customers are experiencing. This could help the startup to develop new products or services that address these pain points.
• Recruiting talent: PromptLoop can be used to recruit talent. For example, a startup could use PromptLoop to extract text from resumes, and then summarize the text to identify the key skills and experience that candidates have. This could help the startup to find the best candidates for open positions.
• Customer support: PromptLoop can be used to improve customer support. For example, a startup could use PromptLoop to extract text from customer tickets, and then summarize the text to identify the key issues that customers are experiencing. This could help the startup to provide better support to its customers.

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Data management is an ongoing challenge for many companies, especially startups with resource constraints. Often, the right data is not available, or it cannot be extracted in a usable format. Even if you have the right data, it is not in the best format to be able to make the correct decisions. With these challenges, automation or enhancing the use of data takes a back seat.

These AI tools not only help you manage data but also elevate the data collected in-house. With simple steps and the right tools, your data management and use are taken to the next level. Further, you can create much better experiences using your company data for both your users and your employees.

Let us know how you used these plug-ins in your daily operations.