Data transformation in Supermetrics: 6 advanced use cases to level up your reporting

Just like how Super Mario gets his power from the Fire Flower, Supermetrics’ features, like custom fields and data blending, let you level up your reporting.

In part one of data transformation in Supermetrics, I discussed the most common use cases, such as converting currencies, managing data naming conventions, and calculating ROAS from different channels.

In this article, I'll walk you through six more use cases including:

• Analyze comment sentiment
• Creative analysis
• Summarize traffic sources
• Combine paid media with Salesforce data
• Combine paid media with ecommerce data
• Unify offline and online data

Use case 1: Analyze comment sentiment using AI text recognition

It can be tedious to manually analyze your community's sentiment, such as comments, reviews, or post reactions. It's labor-intensive and often inconsistent. AI sentiment analysis instantly evaluates the emotional tone of text—be it positive, neutral, or negative. Whether you’re analyzing social media posts or customer reviews, this tool provides a quick snapshot of audience sentiment. It’s also perfect for analyzing your competitor’s reviews, keeping you tabs on the feedback. This will help you:

• Analyze sentiment across thousands of posts or comments without added effort.
• Quickly spot negative feedback and address issues before they escalate
• Use positive sentiment trends to replicate successful campaigns.
• Free up team resources for strategic tasks rather than manual sentiment evaluation.

Here’s how to do it:

1. Log in to Supermetrics Hub.
2. Go to data transformations, click “new custom fields”.
3. Choose a data source you want to use.
4. Select dimension, select function, and choose the sentiment analysis.
5. Select a field from the source you want to transform.
6. Start reporting.

Use case 2: Label images using AI image recognition

Determining which ad creatives resonate best with your audience can feel like guesswork. Manually identifying patterns in large datasets is time-consuming and prone to human error.

AI image labeling automates the process of categorizing and analyzing visual content. By applying AI to your ad images, you can tag creatives with attributes like tone (“Light” or “Dark”) or composition (“people included” or “people excluded”) and quantify the results based on these attributes. This will give you actionable insights into what drives performance and better optimize your future campaign creatives:

• Analyze thousands of images in minutes instead of hours.
• AI applies labels uniformly, avoiding subjective judgments.
• Identify high-performing creative elements to focus resources on visuals that deliver the best results.
• Standardize creative analysis across multiple channels for holistic insights.

Here’s how to do it:

1. Log in to Supermetrics Hub.
2. Go to data transformations, click “new custom fields”.
3. Choose a data source you want to use.
4. Select dimension, select function, and choose the image labeling.
5. Select the Image URL field.
6. Create and go to the reporting tool.

Use case 3: Get a summary of your traffic sources

With data coming from multiple channels, it can be hard to quickly see where the audience is finding your site insights without spending hours in analytics tools and googling different sites.

Using AI, you can:

• Quickly understand what makes each traffic source unique.
• Avoid diving into granular data and instead get immediate insights.
• Use summaries to identify high-value sources for focused campaigns.
• Allocate budgets effectively based on a clear understanding of traffic quality.

Here’s how to do it:

1. Log in to Supermetrics Hub.
2. Go to data transformations, click “new custom fields”.
3. Choose a data source you want to use.
4. Select dimension and function and choose “transform with an AI prompt”.
5. Select the field you want to transform (e.g. in GA4 session source, first user source).
6. Put “Summarize source” with a short description.
7. Select the creativity level for the AI (with traffic sources, it can be balanced and controlled).

Use case 4: Combine paid media with Salesforce data

Data silos between platforms like Salesforce and ad channels make it hard to assess the true performance of campaigns. Without connecting cost data with conversion insights, marketers risk misallocating budgets to channels that don’t really convert or the cost per conversion is too high.

• With data blending, you can join datasets from different platforms, enable last-click attribution, and provide a unified view of campaign costs and conversions to calculate accurate cost per lead (CPL). You can Get a complete view of campaign effectiveness across platforms.
• Understand which campaigns drive the best ROI and allocate resources accordingly.
• Automate complex joins and transformations to ensure accurate results.
• Save analyst time by automating data integration workflows.

How to do this:

1. Create a union blend with your paid media platforms (such as Facebook Ads, Google Ads, TikTok Ads, Linkedin Ads)
2. Once you’re done, create another data blend, and choose “Join” as the blend type this time.
3. Select Salesforce, and your union blends to be part of the Join blend.
4. Choose leads, campaign names, and other needed metrics and dimensions from your salesforce account.
5. Then, choose the campaign name as the join key.
6. Move to the chosen reporting tool and start reporting

Use case 5: Combine paid media with Shopify data

For ecommerce businesses, understanding Return on Ad Spend (ROAS) is critical to optimizing ad campaigns and maximizing profitability. Without connecting paid media with ecommerce data in Shopify, you’re left with an incomplete picture of your campaigns’ true performance. This helps you:

• Connect ad spending to actual sales revenue to understand which campaigns deliver the best ROAS.
• Allocate your budget to campaigns and channels that consistently drive profitable results.
• Automatically blend Shopify and paid media data to eliminate manual data wrangling and reduce errors.
• Use insights to refine campaign targeting, creative, and bidding strategies for better results.

Here’s how to do so:

1. Create a union blend with your paid media platforms (such as Facebook Ads, Google Ads, TikTok Ads, Linkedin Ads).
2. Once that’s done, create another data blend and choose “Join” as the blend this time.
3. Select your paid media platforms, "Union" blend and Shopify.
4. Add all relevant metrics, especially campaign dimensions.
5. Join on campaign dimensions to see which campaigns bring the highest return on ad spend.
6. Go to your chosen reporting tool and start reporting.

Use case 6: Bring offline with online data together

Offline campaigns, such as TV commercials or print ads, generate significant brand awareness and engagement, but their impact can be difficult to measure in isolation. You’ll miss insights about how these channels influence online behavior without a way to connect this offline data with digital performance metrics.

Now, use data blending. You can upload offline media data, such as impressions, spending, or air times, and combine it with digital metrics from platforms like Google Analytics 4 or advertising tools. This creates a view of how offline campaigns drive online actions, such as website visits, form fills, or purchases. By doing so, you'll:

• Understand how offline media contributes to digital KPIs and overall customer journeys.
• Identify high-performing offline campaigns and justify their impact alongside digital efforts.
• Break down silos between offline and online teams by aligning metrics and reporting.
• Use data to fine-tune future offline and online campaigns for maximum impact.

How to do this

1. Browse or drag & drop files to import to Supermetrics and configure the import (support article)
2. Once data is imported, move on to data blending.
3. Create a union blend, choose your import as one of the sources, and then include your paid media sources in the mix.
4. See that your wanted fields are mapped, and include the ones missing from the blend.
5. Go to the chosen reporting tool and start reporting.

Over to you

And that’s six more ways you can explore and enrich your data with Supermetrics (combined with our part 1, it’s 13 use cases in total!). If you’re itching to test these features out, book a demo with our team.