The True Cost of Clean Investment Sales Data: A Breakdown

As a salesperson or a sales leader, you have one enemy greater than all the others. Sure, rejections are part of the job, but this is worse than a simple rejection. 

It’s something that stops you from doing your job well, or, sometimes, doing your job at all. 

What is it? You probably already know: stale, outdated data

Stale data causes you to waste valuable time chasing down contact information and finding the right people to call on. Instead of having a full database of leads you can take action against, you have to hunt down emails and job titles on LinkedIn, firm websites, wherever you can. 

We’ve written before about the cost that this can have for your opportunities and for your sales team, and while morale is incredibly important, clean data can be just as important. 

But, clean data also comes at a cost. Which is why, in this article, we’re breaking down what it would cost for a firm to hire a full-time data research analyst to keep your data as clean and up-to-date as possible. 

Of course, a full-time role is not the only option here. You can also choose to invest in a database that updates itself on a daily, consistent basis. But which is worth your investment?

By the end of the article, you’ll have an answer to that question, as well as an understanding of exactly what it would cost for either choice. But don’t worry, we’re not here to tell you that our database, Dakota Marketplace, is the one and only solution to your problems — though we think it’s a good one. 

Instead, you’ll have a clear understanding of all your options. 

To start, we’ll break down the three defined areas of cost when it comes to hiring a data research analyst for your firm. 

The three defined areas of costs

    1. Personnel to maintain existing data. This includes anything and everything from updating emails, phone numbers, job changes, new hires and exits to prospect and customer firms; maintaining the key information on each account: what they buy/don’t buy, and staying updated on recent updates and news on each account, just to name a few. 

    2. Personnel to add new data. The lifeblood of any sales organization is the “new.” Finding the “new” means locating new prospects to sell your products or services to. To do this effectively, dedicated team members are needed to continually find new accounts and contacts for your sales team to call on and build relationships with. 

    3. Various software and tools. Even with an in-house staff, you’ll need to equip them with the software and tools they need to ensure that all the data is clean. For example, these tools can include platforms like: Seamless, Neverbounce, Emailable, Rocketreach, LinkedIn Sales Navigator, among others. All of these tools come at a cost and should be calculated into your overall spending for data maintenance. 

How much does it cost to add personnel to maintain existing data?

This cost will vary based on the size of your database and how much data is within it. Once you know that number, you can estimate that one Data Research Analyst is needed per every 15-20K contacts in your database.

The estimated cost for a new data team member (all-in with benefits and associated employment costs) is approximately $100,000.

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How much does it cost to add personnel to find new opportunity data?

At least one data team member should be dedicated to “finding the new” at any organization. If your firm is attempting to access new channels, new geographies, etc., more new data team members could be needed depending on the scope and goals of the sales team. 

As stated above, the estimated cost for a new data team member (all-in with benefits and associated employment costs) is approximately $100,000.

How much do you need to budget for data cleansing software tools?

Additional software tools and licenses can cost anywhere from $25-30K per year or more depending on the size of your team. 

Additionally, it should be noted that in addition to software, other costs may arise as well, such as:

  • CRM licenses for each data team member

  • Professional LinkedIn tools to help track employment changes (new hires, terminations, role changes) at your prospects and customers

  • One or more email tools to test existing emails addresses to identify bounced emails and to identify new email addresses where needed

  • Website change detection software to identify when prospects or customers or other necessary information on variety of websites has changed

Next, we’ll run through some examples based on database size, and help outline the estimated cost for each. 

How many data team members do you need, and what will it cost?

In this section, we’ll break down how many employees you’ll need depending on the size of your dataset, and add in additional costs such as software and other tools. These costs are estimates based on Dakota’s on research, internal team, and can of course vary by firm and needs. 

Example database: 35K contacts, normal effort to identify new prospects, and software tools:

    • 2 professionals for existing data: $200K

    • 1 professional for new data:$100K

    • Software tools: $30K

  • Total estimated annual cost $330K

Example database: 50K contacts, effort to enter new channels with existing products:

    • 3 professionals for existing data: $300K

    • 2 professionals for new data: $200K

    • Software tools: $30K

  • Total estimated annual cost- $530K

These costs, which can be anything from $330,000 to $530,000 per year, show that maintaining clean and accurate data is a critical investment, but it is a big investment.

Is there any other way to keep your data updated?

The numbers above can seem overwhelming and huge, we know. But, all is not lost. While it’s imperative that your data stays fresh and accurate, you don’t necessarily need to employ an entire data team yourself. 

In fact, many firms don’t have the resources or the budget to do this, and have turned to outside institutional investor databases to provide that clean and accurate data for them. 

While a database can come at a cost as well, it’s a fraction of what it would take to hire and retain an in-house data team. 

An institutional investor database can cost anywhere from $5,000 to over $30,000 per year, depending on the needs of your firm. 

There are plenty of considerations and questions you should ask before you invest in a platform, including the number of new leads you’re looking for, the budget allotted, channel focus, and more. 

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Is an institutional investor database right for your firm?

Again, this all depends on your individual needs, and factors such as outcomes, budgets, and the size of the dataset all come into play here. 

There are dozens of institutional investor databases on the market, including Preqin, RIA Database, Discovery Data, and more. To find out more about the top-selling database on the market, we encourage you to check out our Institutional Investor Database Buyer’s Guide. 

Of course, we’d be doing ourselves a disservice if we did not mention our own database, Dakota Marketplace. We’ll jump into that next.

What is Dakota Marketplace? 

Dakota Marketplace is our own institutional investor database with over 10k accounts and 30k contacts. The platform is updated daily by our team of in-house data experts, as well as an investment sales team that is out in the field using the data every day. 

A subscription to Dakota Marketplace is $13,500 per year, and $1,000 for each additional user license.

In addition to just accounts and contacts, though, Dakota Marketplace also includes:

  • Institutional searches

  • Public plan minutes

  • Public pension investments

  • Field consultant information

  • Manager presentations

  • Fee studies

  • Access to a library of Dakota Live! Call content 

So, which option is best for your firm?

Now that you know the approximate costs associated with hiring a data team and buying an institutional investor database, it’s time to make some decisions. 

Either way, it’s a huge investment. And while we think clean data is an absolutely critical component of building a strong sales team, we also know it comes at a high cost. 

If you…

  • Have a small team and a small dataset

  • Are growing rapidly

  • Are expanding your team

  • Want to see exactly what goes into your database every day 

Then an in-house data management team might be the best fit for your firm. 

However, if you…

  • Have too much data 

  • Want to focus on selling rather than data maintenance

  • Are just starting out

  • Are working with a smaller budget

  • Want the certainty that all of your contact data will be reviewed on a daily and weekly basis

Then an institutional investor database is the best fit for your firm. 

If you’re ready to find out more about Dakota Marketplace, take the next step by requesting a free trial with the team below. 

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Written By: Gui Costin, Founder, CEO

Gui Costin is the Founder and CEO of Dakota.


The leading intelligence platform on institutional and RIA data