April 14th, 2017 | by

Your sales team is doing double duty: They’re selling to the leads delivered by your marketing department—and they’re de facto researchers. Very, very expensive researchers.

Even if you’re already purchasing sales intelligence data (most of us are), sales teams still spend over half of their day scouring LinkedIn, Twitter accounts, and forging through forests of phone trees for correct phone numbers and email addresses. According to a CSO Insights survey, 82% of sales teams feel challenged by the amount of data available and the time it takes to research a prospect before making a call.

Using your gated marketing content to collect names and email addresses is always a great way to collect information; however, marketing’s budget and reach is limited, contact data collected decays over time, and it’s not always safe to assume user-generated data is accurate in the first place.

How many of us have a second (or third or fourth) “throw-away” email account just for gated content like yours? You don’t need to get caught making a hasty back-door exit from a first date gone tragically wrong to offer up a fake phone number.

According to a CSO Insights survey, 82% of sales teams feel challenged by the amount of data available and the time it takes to research a prospect before making a call.

Acquiring enough qualified net new names at the top of the funnel to hit pipeline and bookings targets is a real issue for most marketing departments, and a recurring headache for CMOs and CGOs. Even the most creative data-collection methods of the marketing department are no match for time and human nature.

Perhaps the bigger challenge is what to do with account and contact data after you’ve collected it or purchased it. How do you know who to engage first?

You need good clean, verified data, and actionable insights that help you score, rank and prioritize accounts and contacts for follow-up – especially for an effective account-based marketing (ABM) strategy. It’s not just about targeting accounts, it’s about targeting the best-fit accounts with a high propensity to buy now. Without verified data and deep intelligence, sales reps spin cycles on accounts that would never buy your services.

When it comes to acquiring highly accurate and actionable intelligence there are really only three options – and they all require using humans to gather and verify data: You can (1) use existing resources, such as a sales team to conduct the research, (2) build a research team to gather data, or (3) buy it from a data provider. Let’s explore the cost of these three options.

Option 1: Use Existing Resources

Let’s get this out of the way first: One of the real benefits of accurate sales intelligence, regardless of source, is giving back time to your sales reps to do what they do best: sell.

Whether you buy a list or create one using in-house resources, sales teams should spend their time selling – not hunting down phone numbers and guessing at different email address permutations.

Because the sales team engages with prospects and customers daily, it makes sense that they might update contacts as they encounter outdated or incomplete information. Through their direct contact with prospects and customers they have access to insights that others do not.

Occasionally sales reps learn about personnel changes within a company, they uncover new opportunities, learn about new contacts, and collect new phone numbers. Should sales update and add this sales intelligence data? Yes.

Should they actively research and source sales intelligence? No.

Sales Teams Shouldn’t be Frontline Researchers

Sales teams are an expensive way to gather and qualify data – not only in terms of an hourly rate, but in opportunity cost. Sales reps are not hired for their research skill. They are not motivated by collecting data and they are not compensated on it. Every minute they spend gathering and validating data is a minute spent not selling.

DiscoverOrg CEO Henry Shuck puts it succinctly: “Hiring expensive, top sales talent to sift through crap is just plain stupid. ‘Let me spend my time cleaning up your data!’ … said no sales rep, ever.”

If your sales team is well-compensated outside of commission, they’re paid too much to scour the internet all day. And if the sales team’s compensation comes mostly from commission, they’re not getting paid enough to scour the web all day, resulting in low morale and high turnover.

We can all agree that, no matter where your data is coming from, sales teams shouldn’t be the first line of defense for sourcing data. But someone has to do it. Generation and qualification of quality leads remains a major concern.

Option 2: Build a Research Team to Gather Data & Intelligence

But how about hiring a research person, or team, dedicated to researching quality leads for your sales team? Main benefits of in-house researchers is returning time to sales teams, and specialization of research, among others.

Cost of Hiring a Research Team

Let’s look at the cost of hiring three researchers:

Researchers: 3
Fully loaded cost per hour (each): $18.00
Cost per hour: $54.00
Hours per week: 35
Cost per week: $1,890.00
Cost per month: $7,560.00

Lead output per researcher/day 20
Qualified leads per researcher/week 100
Output per researcher/month 400
Total leads per month 1200
Total cost per lead $6.30

This doesn’t include the cost of training researchers, management and oversight, or overhead. Even so, $6.30 per qualified lead is a fair price for companies who are motivated to initiate it.

Option 3: Rent a research team

A third option to consider is a hybrid solution of using a third-party research team to do the legwork of finding, vetting, and refreshing leads. This frees your sales team to focus on one thing: selling. Building revenue. Driving growth.

DiscoverOrg employs over 250 researchers, most of them in-house, constantly contributing to a comprehensive database of MQLs. The depth and volume of sales intelligence that is sourced by the research team is comprehensive, and the features offer nimble navigation.

The data is constantly being refreshed – every piece of data, 90 days – so the 30% rate of data decay is mitigated. Most important, human-verified data is remarkably accurate; a 90% rate of accuracy is contractually guaranteed.

That translates directly to dollars.

Just look at this recent blind A/B test of DiscoverOrg data compared to that of a major competitor showed that the increased accuracy of DiscoverOrg’s data resulted in 2 times more contacts reached, 300% more meetings booked, and half the number of gatekeepers … all with 70% fewer dials per meeting booked.

If your marketing team can free the sales team from wasted calls and cycles, redundant efforts, and improperly routed leads, you improve the trustworthiness of MQLs, and all numbers go up.

Identifying the best way to deliver MQL to sales is a complicated matrix for any marketing team, but it is possible to calculate clear ROI. With cost, efficiency, and accuracy in mind, check out our offering.

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Katie Bullard
About the author

Katie Bullard

As Chief Growth Officer (CGO), Katie brings 15 years of marketing, product, and strategy experience in global, high-growth technology businesses to her role at DiscoverOrg. She has a bachelor’s and masters degree from the University of Virginia.