Data Management Best Practices and More with RingLead CEO Chris Hickey

While the Big data hype has certainly given way to things like blockchain and AI, harnessing the power of data is becoming a competitive advantage for new companies every day. Even though we are constantly building data models at TriFin, we wanted to speak with someone that is in the trenches advising companies on data management best practices every day.

RingLead is one of the leading data management solutions boasting clients like Oracle, Capital One, and the NYSE. I sat down with Chris Hickey, RingLead’s CEO, to get his perspective on data management best practices, things every company can do today to improve their data quality, and most importantly, what the real value of quality data is.

I think you’re really going to enjoy this conversation (and probably share it with your management team) because Chris is a wealth of knowledge. If you want to be the first to read part two of this conversation where we talk with Chris about the exact strategies they’re using to 4x their company this year, be sure to subscribe to our newsletter.

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Can you introduce yourself and let us know what RingLead does?

My name is Chris Hickey, CEO of RingLead. At RingLead, we provide quality data married with sales intelligence to help people grow their Revenue. We are a revenue generator for companies through quality data and sales intelligence.

What is data management, and what are some data management best practices?

Data management varies by company and best practices but the best practices of data management all start with a plan. What is your plan to manage your data right, who owns that, and do you have an executive sponsor to do best practices right?

#1 – Start With a Plan

So the number one thing is to get the plan right, get the outcome(or goal) right, get the owner, and make sure you have an executive to sponsor you. [This is important] because it takes an executive to move data best practices through an organization whether you are an SMB, a commercial, or an enterprise. Your company needs to have a mandate that data is part of your DNA.

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#2 – A Tool to Keep Your Data Clean

Best practices with our DMS Product is, we always tell people to have a duplicate prevention strategy. Is your data clean, and what does clean mean? [By clean, we mean] – are there duplicates in your data and are those duplicates causing compliance issues?

So the first thing is that compliance is a big deal right now. When you look at Europe for GDPR, there’s a new law being launched that you have to have compliant data.

I’ll give you a simple example. Some phone numbers are on do not call lists that you have to be compliant with.

Also, ensuring that when people unsubscribe from an email address, they unsubscribe from one section of your database. But, [having clean data] means they’re all linked and there are no duplicates to make sure that an unsubscribe process hits all data at once.

The second part of having clean data is normalizing the data. Does IBM come in as International Business Machines, and then next week it’s showing up as IBM? Does everybody have the same titles, the same normalized fields, the same standardized fields?

So, Chris Hickey is always spelled the same way. IBM is always spelled the same way.

Having data that is clean by preventing dupes and normalizing the data is very, very important and not easy.  Those are the two things, right off the bat, that we preach.

[It gets even harder because] data comes from different sources. DMS products are implemented in Salesforce to allow them to prevent duplicates, clean and normalize titles, and settle everything up on a regular basis. All with an automated engine that allows you to set rules for keeping your data in check.

In your mind, what is the most important thing companies need to be doing to better manage their data?

Best practice number one is you have to have a tool that allows you to clean your data, improve the quality, and normalize and standardize. For us, that is DMS cleanse. So, you have to pick a tool, but a tool is a tool, right?

Editor’s note: you don’t need to pay for a product per se. You could build your own toolset, or maintain your database manually if you’re on a small enough scale. But nonetheless, manually formatting data is a pain, and building tools is expensive.

Back to Chris: Then you have to figure out – okay, you have contacts that are in different databases or different orgs so what practice, what are your rules that you want to match data on?

Do you want to match it by email address, do you want to match it by company name? Those are [2 of many] ideas committees have about best practices to do that.

Then the other is just a quick scan of your database. [This is where tools help] – what if I could scan your database and say look, based on our rules, we found this many duplicates in your database and here they are. So [it’s important] to do a health check of your database to identify if you have a problem to begin with.

If we say – look, you’ve got 10,000 duplicates in Salesforce – that’s costing your company $1.50 per duplicate, on average, through lost productivity, improper communications on email, your prospects are being emailed like they’re your customers, and your customers are being emailed like they’re your prospects. People are confused, they’re unsubscribing, you’ve got chaos. 

Note: This has the potential to dramatically increase the cost of Salesforce for your company. Because of this, we highly recommend choosing a tool to keep your data clean.

You just touched on this with the cost of bad data, but why should people care about having clean data, and data management best practices in place?

For Sales and Marketing:

Let’s do one together. Where do most people get their leads today? Their website. You give them an ebook, you give them a demo. 99% of the world gets leads off a form on a website. Companies are spending thousands and thousands and millions of dollars with Google to buy keywords.

Here I am, I want to buy the keyword cleanse, duplicate prevention, etc. So how much does that keyword cost? 140 dollars a click. Okay, [so I decide] I’m going to spend half a million dollars there this year. And where do you drive them to? The website of course – you want them to fill out the form that they’re interested and raise their hand.

If you ask for 10 pieces of information, they’re not going to fill it out. [We haven’t talked about this yet] but with our enrichment product, you can fill out just an email address and we instantly source the company you work for. On 50% of them, we know their cell #, on 40% we know your demographic data. I know your LinkedIn profile, your company, and more.

Editor’s Note: You can think of ‘enriching’ your data as part of your rules for matching data. If you use an enrichment database, all of the data will already be aligned to specific standards. You can adopt those standards into your own workflow and set them as ‘rules’ for your data-cleansing processes and toolsets.

Back to Chris: So now with all the right data – we’re routing leads to the right sales reps, they’re getting the information on the fly, and they’re writing effectively – which means you’re growing your business just by enriching, cleaning, appending, and routing leads effectively with information that’s critical to the sales cycle.

For Marketing:

[Without clean data] your whole marketing strategy is off. Think about this – what we’re always looking for is, if I close 10 deals today, what vertical were they closed in?

Let’s do one together. I close 100 deals, and I want to know how many were with technology companies that are growing at this rate. How many were technology companies growing at another rate? So I can start to build a profile on my customers and start saying: Are there any more that look like this in the database?

That’s setting up your marketing plan. [You’re using this data to tailor your messaging, target your ads, and a lot budget to different verticals]

When it comes to best practices if you don’t have rich data that’s clean, because you can have a duplicate, [you could be targeting the wrong company]. I could show that IBM is coming from this location, but we’re working IBM from another location, they’re not merged as one IBM.

Note: This also applies to sales, because companies often map territories to different reps. You don’t want two different reps working to close IBM because there are two disparate IBM contacts. That’s not only a waste of resources but a point of tension within your organization.

Back to Chris: Your company wants to know, IBM is merged as one location and they have all of these different site locations that fit into one larger persona. So without cleaning your data, you can’t set up your user acquisition strategy properly.

Because you learn from your wins, right? You learn which verticals are growing and then you try to replicate more in that vertical. So incorrect data leads to identifying the wrong verticals, which throws off your whole strategy.

Are You Excited to Make Better Use of Your Data?

Following data management best practices is definitely not an easy task. You have sales reps skipping fields, marketers collecting poorly formatted data, and most people don’t really understand why this data is so important anyway. After speaking with Chris, it’s clear that having clean, standardized data can be a major competitive advantage for your business.

If you want to hear how Chris’s team is using data-driven sales and marketing to 4x their business this year, we talk all about it in the second half of our conversation. We will break it down for you in an article that we’re making within the next few weeks. If you want to be the first to read it (you really don’t want to miss this one) be sure to subscribe to our newsletter.