Verified

This page describes 'verified' as a concept, which is applicable when it comes to lead data or disputed meeting outcomes, and goes hand in hand with the concepts of 'purported' and 'data decay'.

Definition(s)

• Verified refers to some Purported fact or data appearing to be true, and subsequently being definitively verified as accurate or inaccurate.

• In the context of sales and Leads, here are some examples:

  • To verify that an email address is working, you send an email and see that the email you sent has not bounced.

    • The email bounces, so you have Verified that the data is inaccurate.

  • To verify that a person is still working at the company, you check their linkedin profile, and see that the person does not have the company listed in their profile.

    • Their linkedin job history shows that they left the company 5 years ago, so you have Verified that the person is no longer at the company. Straightforward, right?

Why verification is hard

Verification is more difficult than appears on the surface. Even in the examples above, consider two additional facts and how they change things:

• The email bounced, not because the recipient's email address is fake or mistyped, but because the email address you sent the email from was misconfigured, and so the recipient's email service provider rejected the email.

  • In this case, the bounce message, or bounce reason, might reveal that the email bounced not because the prospect's email address is inaccurate, but because of an issue on your end!

• In the linkedin example, it turns out that the person was rehired to the company 2 months ago, but they've just been busy and haven't updated their linkedin profile.

  • In this case, your verification process generally works 90% of the time, but 10% of the time, this kind of scenario might happen.

Verification is about confidence intervals

Have you ever been asked, 'How sure are you about this?' And you have to give some ballpark estimate about how your gut feels about your claim? Verification works similarly. Verification comes with confidence intervals.

Why verified is an important concept

When it comes to Leads data, not all data is perfect or accurate.

• When Leadsare added to Lead Pools via Lead Ingestions, the information you see, like: first name, job title, email, phone number, etc are all purportedly accurate, but not necessarily verifiably accurate.

How purported and verified work together as concepts

There's a Russian proverb, доверяй, но проверяй which translates to trust, but verify.

Verifiedis another concept that goes hand in hand with the concept of Purported, and typically looks like this:

Example of Purported and Verified Working Together

• You see a phone number associated with a contact in your Lists. This is a Purported phone number, but not yet a Verified phone number (because you haven't called it yet)

• You call the phone number, and you hear a 'this number is not in service' automated response on the other line.

  • By calling the phone number, you have Verified this Purported data, and unfortunately it has been Verified as inaccurate.

  • You disposition the lead's phone number as 'bad data' or something similar, or you disqualify the phone number.

By dispositioning the lead properly, you've helped our system improve the quality of the data.

Example #1 of How Purported but not Verified facts can impact Meeting Outcomes

• You scheduled a meeting

• One of the Qualification Criteria is that the business is doing over $5M in annualized revenue

• You looked at the Purported revenue for the account in the Account Details page, and you see a $5M number

• You didn't necessarily verify the revenue on the call because it would have been awkward

• It didn't occur to you to quickly google search or research the company to see if you can soft verify the revenue

• The meeting outcome comes back as Not Qualified

• The Account Executive provides a recording of the conversation, where they Verified the Purported revenue of the company

By choosing not to verify the purported revenue data, you decrease the likelihood of a Qualified meeting outcome.

But, maybe you would have lost the meeting if you'd been a stickler for verification and lowered the prospect's interest level because you were asking too many questions. There's always a tradeoff.

Good sales reps will know how to ask these types of qualification/verification ways in ways that aren't robotic/come off as natural.

Strategic use of humor, or spreading out the timing of qualification questions organically throughout the conversation, can help you get the best of both worlds.

Example #2 of How Purported but not Verified facts can impact Meeting Outcomes

Purported and Verified applies in contexts besides just lead data accuracy. Here's another example.

• You scheduled a meeting

• The Purported meeting outcome comes back as a No Show without any useful or specific context from the meeting taker

• You decide to verify the No Show by calling the lead and asking how the meeting went. This is generally good practice - good sales reps always follow up and are focused on building relationships. Checking in is a form of relationship building

• The lead says they waited 10 minutes on the call but nobody showed up.

• You submit a meeting dispute and you get your payout.

By choosing to verify the purported no show, you changed a Qualified meeting outcome.