This article originally appeared as part of Demand Gen Report’s “The 2017 State of Database Quality” special report, published in August 2017. Be sure to download the report if you haven’t seen it.

In recent years, some third-party data providers that traditionally focused on selling contact data to sales teams began expanding their positioning and aggressively marketing their offerings as “data cleansing” solutions for marketing teams.

That begs the question, “Can I simply buy some data from a data provider and have a clean marketing database?” The short answer is…no, not unless you really narrowly define what it means to “clean” your data.

Technically, what those third-party data providers are doing is matching a field in your database, like an email address, with their database, and then either overwriting your data with theirs, creating additional custom fields to duplicate your standard ones and filling those in, or just filling in missing values in your standard fields with theirs.

Third party data providers play a valuable role in providing valid direct dial information and in identifying new contacts that fit your buyer personas at a target company. Few sophisticated marketing teams can get by without at least one data vendor, with many studies, including the 2017 Openprise B2B Data Market Industry Report,  showing that the most satisfied marketing teams subscribe to multiple providers. This seems like a simple and elegant solution to cleaning up dirty data, but third-party data alone usually can’t clean up a dirty database for more sophisticated marketers. Here’s why:

You Have to Match to Make a Difference

The first challenge is getting a match. In regions and industries with high turnover (e.g., B2B Demand Generation professionals in High Tech in Silicon Valley), match rates can be as low as 30%. That means that the vast majority of your leads, contacts, and accounts won’t be any cleaner than when you started. Many data providers aren’t able to identify that an email address like “bob.smith@toyota.com” is in the “automotive” industry if that email address isn’t in the provider’s database, even though the provider knows that the domain, “Toyota.com” is from an automobile manufacturer.

You Need Normalized Data

You could address the match issue by working with multiple data providers, and many marketing teams do, but that approach exacerbates a second issue – data normalization (i.e., standardization). Each data provider may have its own set of field values for key fields like Industry, Job Function, and Job Level, which are critical in most marketers’ segmentation strategies. Field event organizers, webcast promoters, and syndicated content providers all have their own values as well. For example, in Marketing roles, different data providers may classify a PR professional as in “PR,” “Public Relations,” “PR/AR,, “Marketing Communications,”or “MarComm.” Using multiple providers doesn’t solve the normalization issue, and it can actually make the problem worse. Also, most marketers will want their field values standardized to what makes sense for their unique business, not what any one data provider uses.

A marketing database that isn’t normalized severely limits a marketer’s ability to do effective segmentation, personalization, or lead scoring.

You Need to Dump Your Duplicates

A critical element of data cleansing is identifying and merging data from duplicate leads and contacts. Having duplicates in your marketing and sales automation applications can sabotage your lead scoring, attribution, and lead routing. Buying more data won’t provide you with the logic and tools to both identify duplicate records and automatically clean up those dupes by merging data in a consistent way. For marketers with over half million records, manually tackling this task isn’t a practical option, and outsourcing this to an offshore firm almost always delivers inconsistent results.

You Need Unified Data Across Your Systems

Since most marketers have several applications in their MarTech stack that are integrated together, such as sales and marketing automation tools, account-based marketing, and predictive applications, most companies also suffer from data unification issues.  Common fields in these systems are often not in sync, causing even dirtier data.  Unfortunately, a data provider can’t help with this issue.

Clean Up All Your Salesforce.com Structures, Not Just Your Lead Records

Salespeople get compensated for selling, not for good data hygiene. That’s one of the root causes of duplicate leads, as well as leads that aren’t converted to contacts, and orphan contacts that aren’t associated with accounts and opportunities. To understand how every campaign affects the pipeline and generates revenue, all of this needs to be perfect, but rarely is. Unfortunately, no data provider can help you with these issues because they are specific to your database.

Data providers also aren’t able to clean critical fields that are important to marketing and sales, including lead source, campaign membership, lead and account ownership, and campaign membership. These fields are critical for understanding campaign attribution and lead routing.

So, can sophisticated marketers expect a third-party data provider to clean up their database? Probably not. Third-party data providers can help, but savvy marketers will want to deploy a data orchestration or data hygiene solution like Openprise that understands the underlying structures of their marketing and sales automation solutions, as well as engage with data providers.

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