How does Salesfolks source its data on Salespeople?

Great question! We get this question asked often.

First off, we like to make it very clear: SALESFOLKS DOES NOT SCRAPE LINKEDIN. While it may be tempting to look at LinkedIn as a natural resource for intelligence on Salespeople (because it is) we do not pull our data from LinkedIn. While you can find salespeople there, it is a rather shallow source of data. Because LinkedIn wasn't specifically designed for salespeople or the people who hire salespeople, the profiles of salespeople tend to be missing key decision-making information such as years of sales subject matter expertise, total sales dollars contributed during their career (production), soft sales skills and more. So, it's very hard to tell if the salesperson would be a good fit. Not to mention the fact there are thousands of recruiters on LinkedIn messaging every salesperson they can find, and that creates tons of noise to cut through.

Salesfolks has three primary sources of data on salespeople:

1. Signups - thousands and thousands of salespeople have signed up for Salesfolks
2. Data Syndication - a form of data sharing cooperative
3. Licensing - we augment our data from third-party sources

Data Syndication

Data Syndication is a proprietary data sharing co-op. Data sources have opted into sharing their data and warrant that their data is fully compliant with global data privacy regulations. Some data sources are provided as a one time dump, others are refreshed each time a new data build is completed. The data sources come from a variety of verticals including HR Tech, Identity/Anti-Fraud, Martech, and others.

Public Data Sources

Our public data sources help us shore up areas where our data syndication sources are not providing enough information. These sources include open-sourced datasets, publicly available and free-use government filings, and others. This data is also globally compliant and fair use.

Source Validation and Accuracy

Before a source is added to our data builds it goes through multiple steps of validation. We check aggregate information across each source, ensure accurate cardinality between fields, and hand-check large samples of every single source before it is added to the build. We take extensive measures to prevent false linkages that could adversely affect our product.

Compliance

Data sources are evaluated from a compliance standpoint before being integrated into the dataset. The evaluation criteria includes review of permissions and how clear the consent is, as well as additional context around how the data is obtained. We offer opt-outs that any individual in the world can use. For any privacy or compliance questions, feel free to email [email protected].

Data Build Process

Taking in data from many different sources means complicated problems including standardization, de-duplication, and time stamping data. Here we discuss many of these core product questions in detail.

• Standardization - Standardization comes in two forms, ensuring general formatting standards and canonicalizing data. Salesfolks lowercases all data and strips leading and trailing whitespace. This ensures normalization across all our data sources since raw data comes in a variety of capitalization formats. We also strip any leading or trailing punctuation that we have deemed non-essential. Secondly, many of our fields are canonicalized into standardized values. For some fields, such as majors/minors this allows for standardized output and queryability; for other fields our canonicalized data provides extra information (schools, companies, and locations all are enhanced by our canonicalization techniques).
• De-Duplication - We de-duplicate our data using both deterministic and probabilistic methods that all stem from a blocking/matching logic. We group records on similar values "keys" such as a common email, common name, etc and then compare all records within a "blocking group" to verify if they are in fact a match. This process is extremely strict as our primary goal is to avoid false positive merges. Our general philosophy is that false positive merges have significantly more detrimental effects than missing out on a potential match of two largely different values. This philosophy helps define our datasets, ensuring we don't provide duplicate salespeople in a data pull, but that we return as much information as we can confidently provide for any given input. Rather than feed all this data, we provide the known or most probable piece of data.
• Quality Assurance - At the tail end of each quarterly data build several weeks are spent doing quality assurance on our data. Our Q/A involves hand checking, running aggregations, and significant unit testing to ensure we have not decreased the quality of data in any way. Occasionally this allows us to remedy issues before we release our data to production, but often the primary focus is to ensure we can communicate to our customers what our objectives for our quarterly improvement were and how we achieved them. We are also doing real-time improvement to data when users (salespeople) append our data through self-curation. That is, they add to the data we have on them by improving their profile.
• Time-Sensitive Data- Our goal is to ensure we have all data related to a salesperson that we can possibly have. This includes historic work experience, locations, emails, social media profiles, etc... Some of these fields (such as email or location) are useful for outreach. Others, such as historic work locations are useful for modeling. All of these data points are valuable for matching out of date data and providing newer, more useful, information.

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FREQUENTLY ASKED QUESTIONS:

Does Salesfolks validate emails?

Due to the sheer amount of profiles and emails we have it would be unfeasible to validate all of them on a timely basis to ensure accuracy. However, all salespeople who are active users of Salesfolks have validated their email address and phone number.

How many candidates can I get for the sales role I'm hiring for?

That depends on many factors, including whether it's an employee/employer market, how broad or narrow your candidate search criteria, whether the job is location-specific or remote, competitive compensation and upside opportunity for the role, etc. Salesfolks is agnostic to candidate pipeline size. We do not make minimum or maximum candidate guarantees. Instead, we take your Sales Job Posting that you publish with us and market it through our community and marketplace, as well as outbound messages to potential candidates. In addition, you may choose to identify and reach out to candidates directly using our tools or yours.

Are the salespeople here the same or different as the resources I use today? E.g. career sites, data resources, and LinkedIn

The simple answer is BOTH. You will find candidates with Salesfolks you will find nowhere else. You are also likely to find candidates via LinkedIn that you might find via Salesfolks as well. The good news is that technological advances in data and machine learning have undergone amazing changes of late that make finding and engaging with these potential sales hires much easier and more effective. Using data aggregation techniques, Salesfolks has access to proprietary information on millions of salespeople. If properly leveraged, this can help sales leadership, recruiters, and hiring managers find talented salespeople based on their sales skills, years of experience, subject matter expertise, and more. Salesfolks analyzes the data and turns it into profiles for each sales professional, with details and contact information. Then we let sales leaders, recruiters and hiring managers search and review the profiles and reach out these folks. Because Salesfolks makes use of mountains of "implicit" sales activity data, it solves the problem of finding salespeople who are not searching for jobs, not present in job boards, resume databases, and hard-to-discover on LinkedIn due to their thin profiles. Moreover, many of these profiles have personal email addresses and/or phone numbers, which are so, so much better for engaging candidates. Your open, click and response rates using Salesfolks can be as much as 3-5x better than generic InMail outreach. And while the raw statistics tell the story, the hundreds of companies using Salesfolks for sales hires tells the story even better.

Questions? Email Us!

[email protected]