6 Ways to Automate Your Pricing Data (Without Code!)

Pricing data gives businesses insight into many crucial parts of their processes. Depending on what you collect, you can track market trends, observe direct competitors’ behavior, or purchase stock at optimal prices. But before data becomes actionable insight, it has to be cleaned, organized, and viewed in a readable format.

The good news: not all of this has to be done by hand. You can use automation to prepare your data for use.

If you’re looking for creative ways to save time in your data management and analysis processes, you’ve come to the right place. We’ll take you through a few pricing data automation ideas that could save you valuable time each day.

What Can I Automate?

The first step of automating any process is understanding your purpose. As you consider pricing data, you might ask yourself questions like:

• What are some decisions that will be influenced by this data?
• What specific aspects of pricing data management are consuming the most time?
• What tasks could benefit the most from automation?
• What tools and apps are involved in the processes I want to automate?
• Who needs access to this information?

You should also consider limitations like data predictability, frequency, and accessibility.

When you have a clear idea of what you want to accomplish with your pricing data, it’s much easier to identify tasks that can be automated.

Ideas for Automating Your Pricing Data

Every business has unique data needs, meaning there is no one-size-fits-all automation solution. But if you’re looking to streamline pricing data management and reduce manual effort, here are a few ideas to get you started:

1 - Connect Your Sourced Data to a Cloud Database

A fairly simple way to automate many data management processes is sending information directly to a cloud database as it’s acquired. This saves time and ensures you’re always working with the most up-to-date data.

Automatic database updates are especially beneficial when utilizing automated collection methods such as web scraping. Data in a structured format can easily be sent to apps like Airtable, Google Sheets, or Baserow using APIs or workflow integration apps such as Zapier.

Many spreadsheet-database hybrids offer the capability to directly connect to a data source or trigger automated data uploads, which is usually a more efficient option than manually uploading data in CSV format.

2 - Clean Messy Data For Improved Viewing

Data inconsistencies are common when you’re working with multiple sources, making analysis and presentation challenging. Scraped data often requires tweaking before use. Depending on how it is structured, it can be excessive, incomplete, or poorly organized.

Fortunately, you can clean data in mass using the built-in tools in Browserbear, Zapier, or your database of choice.

Using Database Formulas, Filters, and Scripts

Formulas, filters, and scripts are common features in spreadsheet and database management softwares. You can use them to clean up your pricing data in so many ways, such as extracting specific parts of a string, deleting duplicate entries, changing number, capitalization, and date formats, and filtering entries to reveal items that fit your specifications.

Each app has its own syntax, so it can take quite some time to set up the formulas and filters you need. But when you see columns and columns of data organizing itself into the best format for your use, the effort is well worth it.

Using Zapier

Formatter by Zapier is a tool built to help you manipulate data in a Zapier workflow before sending it to the next step. With it, you can reformat currencies, turn arrays into strings, and split strings to remove unnecessary data.

This tool is a fantastic way to transform pricing data automatically—especially if you’re already using it in a Zap. Formatter is able to refine number, text, and date / time data and prepare it for further actions. It also allows you to perform several different utility actions that give you more control over your automations.

Browserbear Custom Feeds

Browserbear’s data transformation feature is an easy way to clean data in the very same automation that extracts it from the source. This reduces the amount of manipulation needed in other automated usage steps, which can increase the efficiency of your workflow.

Formatting data with Browserbear can involve many types of transformations, including splitting text, finding and replacing characters, and changing capitalization format.

These built-in data scrubbing features are ideal for web scraping use cases where you need to transform output slightly before applying it to your final product or storing it in a database. You can stack multiple transformations on top of each other until the custom output is exactly what you need.

3 - Set Up Automated Alerts

Access to updated pricing data allows you to take advantage of timing. Manually monitoring your database for updated pricing from scraped data can lead to missed opportunities or overlooked risks. Fortunately, there’s a solution.

Automated alerts eliminate the need for constant manual checks, and instead prompt you when something important has taken place or action is required. They might be used to alert you when:

• A product has been discounted
• A product’s price is within a certain range
• A product’s category has been changed

And as an added bonus, they’re generally quite easy to set up.

With Airtable, for example, setting up a view that filters for certain requirements can be done in a matter of minutes.

All that’s left to do is to set up an automation that notifies you when a new record matches conditions or enters a view.

Then, you can receive alerts from the convenience of your inbox:

Many spreadsheet and database apps have built-in monitoring features that integrate with Slack, Gmail, and other communication tools to alert you when a certain condition is met. Even if your app of choice doesn’t have this feature, you might be able to set notifications up with a Zap instead.

4 - Incorporate Visualization

Rows and rows of data don’t always give you a look the broader perspective. Fortunately, you can use dashboards, charts, timelines, and other techniques to visualize your data.

Airtable has Interfaces, which you can use to visualize selected ranges of data in various ways to build a dashboard.

Google Sheets has a variety of chart types and timelines, and you can use open-ended references to include new data as it is added.

If built-in options aren’t meeting your needs, you can also create more complex graphics by integrating other tools into your workflow. For example, you can connect your database to Bannerbear to visualize crypto pricing data.

The most important thing to keep in mind while automating pricing data visualization is to set processes up to include the most recent data. This might be by using open-ended references, consolidated data views, or automations that add new data to the active data range.

5 - Compile Regular Reports

Occasional alerts can be helpful when you’re monitoring specific, time-sensitive pricing data points, but they can quickly become overwhelming if you have a lot to track. In such cases, automated reports can save you time and energy.

Instead of checking your data every time something comes up, you can provide yourself and your team with reports conveniently delivered to your inbox.

The reports you automate can be as simple or as complex as you’d like. It might be automated Slack messages updating you of the latest pricing trends…

…or a lengthy compilation of data points sent as an email attachment.

These reports are best for updates that aren’t time-sensitive, and they’re fantastic for keeping team members in the loop.

6 - Use AI to Streamline Workflows

Incorporating artificial intelligence into your pricing strategies can help your business gain valuable insights, optimize pricing decisions, and stay agile in fast-paced market environments. You can use technology like OpenAI to build GPTs (Generative Pre-trained Transformers) trained on your data to assist in various pricing-related areas, such as:

• Price optimization
• Market analysis
• Dynamic pricing
• Demand forecasting

While it’s possible to build AI into the backend of many databases, some also have built-in features that make setup much easier. Airtable, for example, has an affordable AI feature that can be used to analyze information, extract insights, and analyze opportunities.

Notion also offers an AI feature to help find and organize data, create actionable lists, summarize insights, and more. You can integrate these tasks into automated workflows to further streamline your processes.

If you want to incorporate AI into your pricing strategies, check if your chosen database has the necessary features. If not, you might still be able to utilize third-party apps to connect without the need to develop an integration from scratch.

Streamlining Pricing Strategies with Automation

Tracking pricing information and developing actionable insights often involve endless amounts of data. That’s what makes it an ideal candidate for automation.

Business owners, product managers, and market analysts can save valuable time by setting up processes to collect and optimize data. Identifying tasks that can be automated and creating a workflow is a beneficial time investment for those working with pricing information.