Ecommerce aggregators accelerate when data moves freely

Ecommerce aggregators accelerate when data moves freely

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Automate complex, custom data workflows

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Operationalizing large datasets while selling on marketplaces like Amazon, Walmart, and eBay takes a lot of time and resources. Brand Managers have access to tons of data and valuable insights into the competitive landscape, and they need to be able to operationalize and act on that data in a structured and repeatable way (especially when it's trapped in a data warehouse).

Read on to learn how Parabola makes it easy to standardize process and reporting, making data accessible to operators and enabling teams to understand their growth levers.

Maximizing the value of your data warehouse 

The valuable data your team needs to make decisions likely exists in a data warehouse or siloed sales channels, however it’s often extremely difficult to turn millions of records into actionable reports in real time. Especially when there are never enough tech resources to build that custom Snowflake report or new internal tool.

Parabola allows you to turn data trapped in your data warehouse into real-time custom reports without waiting on an engineering backlog.

A Parabola Flow for calculating sales forecasts, pulling inventory from multiple data sources, and finding net available quantity and months to depletion.

Search term analysis

With tools like Datahawk, Junglescout, and others, you have access to a lot of valuable keyword data, but it can be difficult to get actionable insights from huge amounts of data across siloed sources. In Parabola, you can extract and aggregate this data to make it easy to access and understand. You can also notify your team about keyword performance in real time. This way, you can adjust your spend and make decisions to increase conversion in a timely way.

Learn how you can use AI in Parabola to identify high-performing keywords and generate new keyword suggestions based on the highest performing ones.

If you’re only interested in monitoring a certain number of keywords for each product, you can filter and trim data before sending reports to your team. By automating reports in Parabola, you can spend more time managing the things that matter and less time on the things that don’t.

Here’s an example of a Parabola Flow that could pull inventory data from multiple sources, filter by search volume, and send a report via email and Slack:

A Parabola Flow for pulling inventory data from multiple sources, filtering by search volume, and sending a report via email and Slack.

Preparing for acquisition

When you acquire a new brand, you acquire a whole new dataset and all of the problems and nuances that come with it. Standardizing this data, understanding parent-child product relationships, inventory reconciliation, and brand velocity become top of mind.

In Parabola, you can share, copy, and replicate pre-built logic that’s already used for brands in your portfolio, creating workflow consistency across brands. This makes it more efficient for your team to onboard new brands and reduce data debt. And because account-specific operating silos are torn down and processes are standardized, you can do it without increasing headcount.

To see how Parabola can help you streamline data processes across brands, set up a time for us to show you how it works:

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