Seven Steps to Get Your Data Foundation in Order

Pietari Suvanto Feb 6, 2025

Data providers tend to oversimplify the data enrichment process.

Either they say, “Everything is possible,” but the moment the contract is signed, a custom solution built from the ground up is required. So, technically, they didn’t lie, but it leaves a lot of work to be done.

Or it’s a “plug-and-play” solution that is easy to implement—but then you quickly learn that it offers limited flexibility.

In this post, we will explain the work needed to enrich the data in your CRM. You will need to make many small decisions that will shape your business.

Note, even this process is quite simplified in order to keep this article in a more readable format.

Here is the 7-step process:

Define your company identifier
Match companies between the databases
Decide what to do with unmatched companies
Identify duplicates
Group structures
Map relevant data fields in the CRM
Decide how new companies are added

Step 1: Define Your Company Identifier

First things first. Let's define terms.

Match = Connect accounts from the source (Vainu) to the destination (CRM)

Map = Connect data fields from the source (Vainu) to the destination (CRM)

Enrich = Send data for the mapped fields of the matched accounts from the source (Vainu) to the destination (CRM)

With that out of the way, let's discuss something practical: What is a company?

This might sound trivial—but it isn’t. For your data integration project to succeed, you must choose a (consistent!) way of identifying companies in your database.

Here are three of the most typical ways of defining companies:

Option 1: Company Domains

Company domains (as in website addresses) have one big advantage: They're simple.

There is typically only one company for one domain, and you don’t need to consider, for example, any corporate structures that might complicate your CRM.

I am sure many have encountered the problem of sales reps claiming the same companies to themselves, even though there are multiple companies (for example, Vainu. io Software Oy and Vainu Finland Oy).

Option 2: Company Names

The advantage of using company names is that it's easy. For example, sales reps can manually type the company's name into the CRM and move on.

The problem with using company names is that some companies might have very similar names, such as Vainu Finland Oy and Vainu.io Software Oy, despite being separate entities.

It is also not rare to see an incorrect company name being used, such as Vainu Oy, which does not exist. In that case, what data would you enrich Vainu Oy with? Data from Vainu. io Software Oy or Vainu Finland Oy?

Option 3: Company Business IDs

Company Business IDs refer to a unique code given to a company by the local authorities when it is founded. They usually have a prefix to identify the country in which the company is registered, followed by an 8-digit string.

For example, Vainu. io Software Oy's Business ID is FI25578642, while Vainu Finland Oy's Business ID is FI28229966.

The advantage of using Business ID as a unique company identifier is that it is unique to each company, and all official data (at least in the Nordics) is collected using Business ID.

This unique company identifier also opens up a wealth of opportunities, such as corporate structures, group financials, balance sheets—you name it—to investigate further.

Another crucial advantage of using Business ID as your unique company identifier over other company ID definitions is its legal form. You can do business with a Business ID (send invoices, have it as a contractual party, etc.), but you cannot do the same with a domain (there is a Business ID behind every domain).

Step 2: Match Companies Between the Databases

The first step involved a lot of consideration, so thankfully, this second step is a little simpler—at least if you're a Vainu customer.

In Vainu, you can easily connect Vainu’s database and your CRM with our "plug-and-play" (but very flexible; more on that later!) Connectors.

Once you've established a connection, it'll run for a while (on autopilot), but after it has done its job, you can see how many companies it has been able to match between our database and your CRM. There are plenty of reasons why it might not have been able to match all companies—which is the topic of the next step!

Note: Our Nordic databases use Business ID as their unique company identifier, so if your CRM doesn't, that is likely a reason for a low match rate.

Step 3: Decide What To Do With Unmatched Companies

Why would there be unmatched companies? For one, databases sometimes use different types of unique company identifiers.

For example, our Nordic databases use Business IDs, meaning Vainu. io Software Oy's Business ID would be FI25578642. If Vainu. io Software Oy is not saved as FI25578642 in your CRM but as Vainu Oy, Vainu (Finland), Vainu Test, or any other name variation, the two will not match.

Here are two options for how to deal with the issue of unmatched companies:

Option 1: Ignore The Problem

We include this as an option because it technically is one, but we would not recommend it. It will result in a lot of erroneous data.

Option 2: Export All Accounts From the Source

This will be a very time-consuming project and require a lot of manual work, as you'll need to ensure all accounts currently in your CRM are either deleted or matched to a valid Business ID or other unique company identifier used by the company data provider you're working with. Still, it will ultimately lead to the best outcome for your data foundation.

If Vainu happens to be your chosen company data provider, then you're in luck since we've created a feature that will help cut down the manual work to be done. More specifically, our export shows, for example, the likeliest match between the accounts in your database and ours.

However, if this is not a data project you're interested in doing in-house, you can use our experts or one of our partners to do this for you.

When you have all the relevant companies in your CRM matched to a Business ID, you can import that data to CRM to enrich the companies' data. After you run the match function again in Vainu, you will get all the relevant companies matched. The rest that do not match are not relevant.

If you match only some of the companies, it will create a lot of unnecessary duplicates!

Step 4: Identify Duplicates

As you have manually matched the remaining companies, the outcome is most likely that there will be duplicates. Thankfully, these can be merged using your CRM's merge functions.

Step 5: Group Structure

When all the data is matched, it’s time to consider another important aspect of company data: Group structure. Let’s use Vainu as an example.

Vainu’s company structure is as follows

Vainu. io Software Oy owns 100% of Vainu Finland Oy, Vainu Sweden AB, and Vainu Norway AS.

Whether you're interested in the parent company, the subsidiaries, or both depends on your product and sales process. For example, it's unlikely that a company will use different CRMs in each country, so if you're a CRM vendor, you'll mostly be interested in the parent company. However, each entity will likely handle food services individually, so it might make sense to look into the subsidiaries as unique buying units.

It's not uncommon for a CRM to contain both parent and subsidiary companies. In this case, you have three options:

Choose to have no group structures. This means you'd have parent and subsidiary companies as individual companies.
Choose to only have parent companies. This means you merge all subsidiaries with their parent companies in CRM.
- This is best for when you see a company as a single unit. The buying center is the parent company (Vainu. io Software Oy).
Choose to have group structures. This means keeping the parent and subsidiary companies as individual companies but structuring the data so that it is clear that they all belong to the same group.
- This is best for when the company is seen as having multiple buying units (Vainu Finland Oy, Vainu Sweden AB, Vainu Norway AS).

Non-Operational Owner

Here is a fictional example: A private equity company named Hungry and Eager Investments owns 60% of Vainu. io Software Oy.

In this situation, Vainu's parent company would, on paper, be the private equity fund. However, it's unlikely that they would be making the day-to-day decisions.

We've developed a "highest operational owner" data point to address this. This data point refers to the company that owns the largest share of another company while also making decisions on operational, non-board-related matters.

Step 6: Map Relevant Data Fields in the CRM

Now, you are at the stage where you have matched the accounts, eliminated unnecessary companies, merged the duplicates, and figured out the corporate trees. Great job! You’ve done quite a feat. The sad thing is that nothing visible is out there yet. But the peak of an iceberg is approaching!

So let’s dig into it. Now, you should map the data fields.

First, decide what data you want to keep updated and into which fields. It should be quite easy to use Vainu’s Connector. Read more here. After the mapping, decide how the new data points are updated.

Step 7: Decide How New Companies Are Added

When a new company meets the criteria of one of your target groups, you need to decide whether you also want that company to be available in your CRM. Here are two options for making that happen:

Automate new company creation in CRM. Use our trigger functionality to ensure that all companies are automatically found in your CRM as soon as they meet your predefined criteria.

Send manually. Use this option if you want to be precise about which companies are in your CRM. You can also exclude companies that are already in your CRM—making it much easier. (We are working on a feature to exclude all companies that belong to the group structure.)

Final thoughts

In conclusion, navigating the data enrichment process is akin to assembling a complex puzzle. Each step, from defining your company identifier to deciding how new companies are added, requires careful consideration and strategic decision-making. By leveraging the right tools and methodologies, you can transform your CRM into a powerhouse of accurate and actionable insights. Remember, the key to success lies in the details—ensuring that every piece of data is meticulously matched, mapped, and enriched. As you refine your approach, you'll not only enhance your data quality but also empower your business to make informed decisions that drive growth and innovation.