What makes data good?

Data makes the world go round. It’s honestly pretty hard to understate how important it is to a sales department (not to mention the whole company, the economy…we can keep broadening the scope here).

Instead of relying on intuition, companies are leaning on data. It’s at the heart of all the big, important decisions that get made.  Accurate forecasting, business decisions, even team feedback — all of that relies on data. 

And that means your data’s gotta be good. 

Why does good data matter?

That’s a rhetorical question, right? 

But really, good data is the only kind of data you should be using. Maybe that’s a bold statement, but with so much riding on the quality of your data, you can’t afford to have unreliable information in the driver’s seat. 

Let’s step away from the 30,000 foot view of “data makes the world go round” and get a little more specific. Chances are, if you’re reading this (hi!), you’re in sales or marketing. 

So if you’re building out a newsletter audience or coming up with a prospecting list, you need data. Contact information, details about the companies your leads work for, information about the prospect themselves. 

If you rely on bad data to build out these essential pillars of your job, you’re going to have a hit on productivity and morale. 

Speaking of data, let’s look at some that proves our point here. A while ago we asked a whole bunch of sales professionals about their major challenges with sales outreach, and they all want better data. And there’s a couple of reasons why. 

30% said they want better data that will help them start personalized conversations. 22% want more accurate contact information so they know they can connect with their leads in the first place. 

And the after-effects of relying on bad data aren’t too great. Wrongly targeted outreach can lead to an ongoing loss of sales (52%) or reputational damage for your company (49%).

5 basic qualities of good data

All right, so we’ve said our piece about why you need good data (although let’s be real, we could go on and on). By now you’re probably wondering what makes data good in the first place. Here’s a quick primer. 

Accuracy

The definition for this is pretty straightforward: is the data correct? If your data isn’t error-free down to the last detail, then the insights and decisions that come from that data will have a problem or two (or more). 

When it come to keeping your data accurate, there are a few things you can do:

• Get data that’s accurate in the first place. This should be a no-brainer, but it’s easier said than done. Your most accurate prospect data is going to come from a reputable sales intelligence platform rather than purchased lists.
• Minimize manual data entry whenever you can. Unfortunately, human error plays a big part in creating inaccurate data. Use automated processes to connect your CRM and other sales tools and enrich your data whenever possible.
• Keep your data clean by regularly enriching it. Connect your CRM to an enrichment tool (like the one available via Lusha) to automate the process and make sure that everything in your database is still correct. 

Freshness

Speaking of regularly cleaned data, that brings us to this next point: good data is fresh and timely.

Even if your data was perfect when you got it, it’s not going to stay that way. B2B decays at a rate of about 2.1% of your database per month. That means after a year, that’s about a quarter of your database that’s no longer useful.

That means a couple of things.

1. Yet again, the importance of regular enrichment has become relevant. Make sure your database is full of fresh data by, well, refreshing it. Connect your CRM, whether it’s Salesforce or something else, to a tool like Lusha to keep feeding your database updates. 
2. If your database decays, that means the databases you use for prospecting decay too. When you’re looking for contacts in a B2B sales intelligence platform, you want to make sure that they’re continually updating. Take Lusha for example. Our database is constantly evolving and growing, with new data added daily based on what users search for. We also check and refresh data on a regular basis to make sure we’re only delivering the highest quality data.

Completeness

When you’re evaluating the quality of data, you have to ask: is everything that’s supposed to be here present? Just like you can’t make good decisions based on data that’s wrong, you also can’t make good decisions based on data that’s incomplete. 

What makes your data “complete” depends on what you’re using it for. Let’s put it this way: when your data is adequately complete, you’ve got the full picture and you have all the information you need to take the next steps. For example, if it’s data on prospect, then it needs to show at minimum all the data you need to engage with that prospect. 

Have you ever looked up a prospect who seemed perfect for you, only to find that there was no direct contact information? There’s nothing more frustrating than knowing you have to leave that opportunity hanging for lack of information. 

A reputable database with good data isn’t going to have empty contact profiles. The data should be complete – not just the person’s name and job title, but a way to get in touch so you can put that data to use. 

And – ahem – not to shamelessly plug ourselves here, buuuut we’ve got an emphasis on only including contact profiles that you can use. AKA, no incomplete data. 

Uniqueness

As much as we love good data, we only want to see it once. If you have data that overlaps, it can get real confusing real quick. 

Say, for instance, that you have two records for a John Smith at ACME Inc. They look like the same person, but each record has a different job title – or even worse, a different phone number. How do you know which one is right? Or how do you know that there aren’t coincidentally two people with the same name at the same company that are both in your CRM?

The answer is, unfortunately, that you don’t. So then you end up wasting precious time by trying to sort out which is the right one. 

According to Salesforce, 25% of the average CRM is duplicated data. That’s a whole quarter of your data that’s pretty much useless. 

One way to combat this is with data enrichment. CRM data enrichment is a hands-off, easy way to clean up that mess real quick. 

Compliance

Ok so you’ve got data that’s accurate, fresh, complete, and unique. Lest you forget, you’ve also got to make sure that, well, you’re allowed to have it and use it. Good data is data you can use, and that means that good data has to be compliant –  especially when it comes to prospect and customer data. 

If you’ve got information about people’s name, job, or contact details, then that’s personally identifiable information. That information is protected by legislation like the GDPR in Europe or CCPA in California. And those are just the biggest examples of legislation around data privacy. 

It’s a lot to keep track of, which is why it’s good to get your data from somewhere that’s already compliant. That way, you don’t have to sift through your data to figure out if you’re allowed to have it in the first place. 

Some sales intelligence tools will leave the burden of compliance on you. Don’t want to risk running afoul of GDPR? Then filter out all the European contacts. But if you want to sell to people in Europe, that’s not going to work. You want data that complies with GDPR, meaning those European contacts have been notified that they’re in a database and given their consent to keep their data there. 

In addition to being legal, that means those contacts are already aware that they might get contacted by someone like you, and are okay with it. That makes your cold calls just a little bit warmer. 

If you want a database chock-full of good data that’s fully compliant with GDPR and CCPA, you should give Lusha a spin. You can try us for free and see if we’ve got the kind of data you’re looking for. 

Key Takeaways

• Bad data can affect your sales productivity, company reputation, and team morale. 
• Good data is accurate, fresh, complete, unique, and compliant. 
• Lusha’s database is full of good data, and you can make your own CRM data better by using our data enrichment.