M&A deal sourcing: Practical Tips & Tricks

If you work in an M&A role, and you need to source deals, this blog will give you practical tips on how to save time and get a higher level of completeness.
M&A deal sourcing, or M&A deal origination, means identifying companies to invest in or to acquire. For this article, we are assuming that you want to source private companies, as opposed to listed companies.
Deal sourcing is quite a labor-intensive process. Good preparation and a couple of tools can save you a lot of work. You want to avoid labor-intensive work on companies that do not make it to your shortlist. You can avoid spending time on these companies by i) not making the longlist any longer than necessary with a small enough scope and ii) by rejecting companies on the easiest criteria first, before you start assessing criteria that are more time-consuming.
Start with defining your M&A deal sourcing scope by creating criteria for your search project. Ideally, you select criteria that you can easily filter companies on, as this is the quickest way to exclude irrelevant companies. Typical values that are often available in most databases are geography, size (sales, FTE, funding) or a defined industry segment (like an industry code).
For companies that you find outside any company database, obtaining these values can still cost you a bit of time, unless you know how to enrich the profiles of the companies you find with the necessary information. We will explain more about enrichment in the next paragraphs.
We recommend you to set up a taxonomy (or set of breakdowns/categorizations) before you start searching. This is a bit more work, but categorizing your company set this way helps you in several ways:
Example ways to break down your longlist can be by part of the value chain, production process, technology used, type of solution, business model type, and much more. Try to make your tags MECE (stands for “mutually exclusive and collectively exhaustive” a phrase coined by McKinsey that encourages you to make sure that each part of the breakdown does not overlap with other parts and that all the parts together should contain all possible options). If you find MECE breakdowns difficult, you can always use ChatGPT to give you a first version of a MECE breakdown.
Now that you have prepared your set-up, you can start with your first mission: find all the companies that are potentially relevant. At Venture IQ, we call this the “build” phase. You want to enrich the companies you find with as much information as you can, to allow you to dismiss companies quickly.
When you start searching for companies, use the taxonomy you have created in the previous step to systematically search all areas of your scope. There are many sources where you can find companies.
When you gather all these companies in a spreadsheet, we recommend you to at least add all the names and the URLs of each company and to clean up all the double entries based on their URLs.
Most of the sources you pay for will provide you some basic data for all companies, like for example a one-liner, FTE and the country of origin, but from other sources you might just get the name of the company or the hostname (URL). The hostname is the first thing you should try to obtain for all the companies. It allows you to quickly check out the website, but more importantly, for the enrichment step, it will help you use tools to enrich your Excel sheet.
If you have access to tools like Orbis, you can bulk search all your companies in Orbis and export all the profiles
There are a lot of steps mentioned above that Catalist, Venture IQ’s deal sourcing platform Catalist can automate for you:
Catalist allows you to quickly build your set of potentially relevant companies for your longlist by letting you scrape websites, extract companies from online databases like Github, a patent database or subsidy databases, upload files or google companies in bulk.
In Catalist every company gets auto enriched with Crunchbase, Patents, Github and Twitter. On top of that, you can also enrich companies with LinkedIn company profile data. In addition, Catalist auto-enriches every company profile also with the website text (translated into English). This allows you to search and auto-tag (automated data gathering) companies in your dataset, even if they are not part of any other source.
If you are interested in Catalist and want to learn more about it, get it in touch and book an introduction meeting.
Happy deal sourcing!