Managing and optimizing retail media and commerce data is becoming increasingly complex for brands and agencies.
With data coming from multiple sources and accounts, integrating and structuring this information can be challenging. This fragmentation leads to critical analytics, reporting, and optimization hurdles.
Mimbi offers an end-to-end data platform aimed at simplifying retail media data management for brands and agencies to:
- Reduce time spent on manual reporting and data wrangling
- Centralize data from disparate sources into a single platform
- Build custom dashboards and visualizations for stakeholders
- Gain insights from marketing data across channels
A key capability is mimbi’s “Segment” feature, which allows users to restructure their data according to customizable parameters. This provides unified, structured data that can be integrated into workflows for enhanced insights.
In this guide, we’ll explore the power of segmentation, walk through using mimbi’s feature, provide advanced strategies, discuss integration opportunities, best practices, case studies and more.
Follow along to see how segmentation can help your business capitalize on retail media growth opportunities.
Understanding the power of segmentation
Data segmentation is the process of filtering and combining data based on defined parameters, such as product attributes, time periods, regions etc. Segmentation creates unified datasets tailored to specific business needs.
Structured, segmented data unlocks opportunities in measurement and activation. It enables apples-to-apples comparison, drives actionable insights through reporting/analytics, powers AI/ML initiatives and facilitates efficient system integrations.
With segmentation, brands can analyze performance by product line, market campaign type or other attributes like product categories. Agencies can segment data by client brand for tailored optimization.
Setting the stage — initial setup
To start, sign up for a mimbi account at mimbi.io. After logging in, connect your data sources such as Amazon or analytics platforms.
Once data is imported, the fields will be available for segmentation.
In your mimbi account, navigate to the “Segment” page.
Here you’ll find tools to filter, combine and restructure your data like:
- Filter data by specific field values
- Feature for validating accuracy of segments
Creating your first data segment
Let’s walk through creating a segment focusing on a specific brand. First, define your goal — in this case, analyzing UK sales for skin care products of a specific brand.
In the segment builder, choose your data source. Select the “Brand” field.
Apply filters and name your segment.
Preview the segment data to validate accuracy. Make any adjustments needed. Finally, save the segment.
You can combine filters, aggregators and other tools for deeper insights:
- Multiple filters to narrow product, region etc.
- Concatenate fields to merge attributes
Integrating segments into your workflow
Export segmented data as CSVs or connect to business intelligence, data visualization tools, or data warehouses. Data can also be exposed through a dedicated API. Schedule automatic segment exports to ensure your dashboards stay up-to-date.
Best practices and tips
Creating segments is a fantastic way to restructure external data according to your own needs and standards. The possibilities are endless and we are already surprised by the creativity of mimbi users.
Here are some best practices to get you started with segments:
- Keep segments organized for ease of use.
- Name segments intuitively based on the included criteria.
- Update filters/aggregators periodically to reflect new priorities.
A tip is to really think out of the box, you may set yourself some constraints like your previous Amazon ad campaign structure or your internal data structure, but the mimbi platform gives you back control and allows you to start with your own needs and not the platform's rules.
Do you want to see how data segmentation can benefit your business?
Get started with mimbi today and reach out for a demo!
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