This tutorial will show you how to use the Similar Companies and Lookalike Cluster filters within Target.
Similar Companies
You can add multiple companies to use as a reference and we show you similar companies. The work behind the scene is done by AI.
How it works:
The AI evaluates core business characteristics — like industry and operations.
There will be equally many similar companies for each input company (so not all results are similar to, say, just the first company).
Adding more input companies will at a certain point no longer increase the number of results, but may change the composition.
Please note that using filters other than the Regional filter with the Similar Companies filter may unintentionally reduce the number of results to a low amount due to the way the filter works internally.
2. Cluster Lookalikes (Company List Segmentation)
The Cluster Lookalike filter works a little differently when it comes to what information it uses to find new companies. Instead of starting with a diverse set of companies, it begins with a group of companies that are already quite similar – think of them as belonging to the same "cluster."
Because the filter starts with this pre-selected, similar group, the new companies it suggests will also likely fit within that same cluster. You can expect them to share the key characteristics of the initial group.
It's important to know that even though the starting point is different, how the filter actually determines if one company is similar to another is exactly the same as our Similar Companies filter above. The underlying comparison process – what the system looks at to decide if companies are alike – remains consistent across both filters.
To add the filter, first navigate to Cluster Lookalikes and click on AI Tools.
Click on the blue Start button under Company List Segmentation:
Then choose the company list you would like to use.
Confirm your choice by clicking on Start analysis.
The Dealfront AI then analyses all companies on the selected list and locates them in the digital space. Physical space is usually measured within three axes, however, Target uses 80 axes, allowing for a very high level of analysis of the companies and their characteristics.
The AI imitates the human brain and implicitly compares information such as business areas, industry assignments, and employee numbers. In doing so, it creates so-called “company clusters” and assigns companies to these clusters. “Company clusters” are groupings of companies that are topically very closely related to one another.
In the tool you can see a graphic representation of these clusters:
Please note: Larger company lists allow for more individual analyses, leading to additional queries.
You may now choose a cluster for which you want to find similar companies.
If you move your mouse over a cluster, you can see keywords that have been assigned to that particular cluster and that give you an overview of the cluster content.
📌 Pro Tip: Use these keywords for future queries!
Move your mouse over a cluster and click on it to show a list of the companies allocated to that specific cluster. You can remove individual companies by clicking on the trash can symbol at the right side of a company listing.
The “similarity of companies in a cluster” slider at the bottom left allows you to set the degree of similarity in the cluster analysis. If you want companies within a cluster to be very similar to one another, the analysis will generate more clusters that are smaller. Conversely, if you opt for a broader degree of similarity, you will get bigger clusters, but the companies contained therein might be more diverse.
Click on the blue Show similar companies button at the bottom right to receive a new results list based on the selected cluster.
📌 Pro Tip: We recommend creating separate queries for each individual cluster.
In simple terms:
Similar Companies: Starts with one or more companies and finds others that are similar to those individual companies.
Cluster Lookalike: Starts with a group of similar companies and finds more that are like that specific group.
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Questions, comments, feedback? Please let us know by contacting our support team via the chat or by sending us an email at support@dealfront.com.
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