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5 use cases your data quality solution must address

When it comes to data enrichment and data quality tools, there are numbers of use cases you should be almost expecting the vendors to be able to address. While many of the features can be helpful for your organization, only a few of them can really impact your B2B sales and marketing productivity. In this blog post, we’ve outlined the key features your data quality and data enrichment solution must have.

1) Automated data enrichment based on email domain or website address

This is by far the most popular use case for B2B organizations – your lead registration forms capture lead information which then gets into your marketing automation platform (Marketo, SalesForce Pardot, etc.) and CRM (SalesForce, Hubspot, Intercom, etc.) where the leads are being distributed among the salespeople based on the lead routing rules. As marketing or sales operations leader, your goal is to ensure that the data you’re pushing through is accurate since the sales productivity falls down dramatically as soon as your sales reps start spending their time crawling through the bad data.

Sales productivity drops as soon as sales reps start dealing with bad data

The automated data enrichment is a must-have feature that helps you obtain critical business information such as Company Name, HQ location, Number of Employees, Annual Revenue and others based on lead’s email domain or website address. Also, what you should expect is a flawless integration with either your marketing automation or CRM platforms of choice, so that by the time leads get to your sales team, all the right information about the business they represent is already in place.

2) Business email validation

On a scale of one to ten, how would you rate the importance of having a legit business email address for doing business with or marketing to a B2B customer? Most of the B2B marketing and sales leaders consider this data point as by far the most critical. But why would prospects be open to share their business email addresses? Don’t they already have enough vendors chasing them? Right, nobody really wants to provide accurate information unless there’s a mature need. Therefore, your goal is to be able to identify prospects who provided accurate business addresses and score them higher than those who didn’t.

The email validation tool should be either the add-on or simply part of any modern data quality solution. Armed with proper email validation technology, you can easily distinguish bad leads from good leads and automatically disqualify prospects with 10-minute, junk and fake emails.

3) Company name lookup based on website address

There for sure will be cases when your prospect data is incomplete and you need a scalable (automated) way of finding company name from website domain information. One example could be Account-Based Marketing tools that almost require company name information for better targeting. Another use case is when your events team gets back from a trade show in Europe (say hello to GDPR), and the company information is missing for the list of the attendees. At small scale you could probably get around assigning a small data quality project to one of your marketers or sales operations guys to go through the list manually, but at larger scales this is totally unmanageable.

The company name look is now a standard feature that will help you convert domain name into company name very precisely. In fact, you should be expecting the precision to be at around 80%.

You should be expecting about 80% match rate on company name information from your data quality vendor

4) Phone validation

If your registration forms collect phone number as a mandatory field, you need to think about a way to identify whether the phone number provided looks accurate or not. The phone validation technology compares the phone number to the overall lead profile and checks the format and indicates whether it believes that the phone number is correct or not.

Some of the use cases and examples:

  • You’ve got a lead from Peru, but he put a German phone number in a correct format – the phone validation tool will classify it as a phone number of “medium” quality;
  • You’ve got a lead from US who put “123123123” as their phone number, the phone validation software will classify it as “low” quality;
  • You’ve got a lead from the U.S. with a U.S. phone number in a correct format, the phone validation feature will assess the quality as “good”.

5) GDPR compliance

When it comes to data quality and data enrichment tools and processes, you’ve got to be sure that your partner is GDPR compliant by design. What does “GDPR compliance by design” mean? It means that your data quality solutions provider doesn’t have anything to do with the personal information of your customers and prospects. From the data quality perspective, enriching personal information makes very little sense since on average, people are changing jobs every 2-3 years. Instead, if you’re dealing with businesses as clients, your enrichment efforts should be focused on obtaining as much information about it as possible. Any vendor that provides personal information about your customers and prospects based on let’s say email domain, is exposing you to tremendous risk or a lawsuit since regulations such as GDPR prohibit such practices.

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