How to Identify Leads for Your Startup
Last Updated: By TRUiC Team
You’ve started your business-to-business (B2B) startup. You have some inbound customers, but you want to find more. This requires some lead identification and lead sourcing. In other words, it is time to get familiar with finding leads and their contact information.
We will discuss how to identify your leads and where to source your leads, so your team can make an informed decision on where you want to hunt for those leads and find the best leads for your startup.
Lead Identification 101
Lead identification starts by parsing leads into two categories;
- business-to-customer (B2C) leads
- business-to-business (B2B) leads
In this article, we will only be discussing identifying B2B leads, including business-to-business-to-customer (B2B2C) (e.g., ecommerce software such as Shopify, BigCommerce, etc.) and business-to-business-to-business (B2B2B) (e.g., CRM software such as HubSpot Salesforce, Monday, etc.).
B2B leads are typically parsed into segments:
- Company or account data
- Individual personal data
When combined, these two segments make up the ideal customer profile (ICP) that marketers and sales leaders use to search for leads.
For usual B2B companies, the data they collect or want to collect is data on the company and account would be these basic categories:
- State or province
- Employee count
- Annual revenue
Additionally, employee count and annual revenue data are typically grouped for easier data analysis. For example, a company may identify that target prospects in the small and medium business category (SMB) are companies with one to 200 employees.
Additionally, companies will include other company-related data that is related to their sales.
A B2B selling a sales enablement platform may have different points they would triangulate on. For example, a company that helps sales representatives with a ton of products or stock-keeping units (SKUs), such as Bigtincan, will try to collect the number of products companies sell. In this case, a company with 500 employees that sells three products would be an SMB prospect, whereas a manufacturer representative that has only 20 employees but represents hundreds of products would be an enterprise prospect.
Another sales enablement company may not care for the number of SKUs being sold; however, the number of outside field sales representatives may be the key metric of importance.
Yet another example would be a company selling medical devices to medical facilities. In this case, the employee count and annual revenue would be meaningless, and industry data redundant; the number of beds, however, would be the most important account data relevant to the sale. In this case, Definitive Healthcare would be one of the best sources with that available data.
Thus, understanding what a company sells and how they sell it will more adequately determine the company and account data that they would be interested in collecting.
Individual Persona Data
For usual B2B companies, the data they collect on the personnel working within the company would be, in order of importance:
- Business email
- Cell phone
- Direct phone
- LinkedIn profile
The key aspect here is that regardless of the type of B2B sale a company is involved in, they will collect the same information, with the key differentiators being the way that a company selects doing its outreach.
Parsing the Title
As an individual's title can be quite inconsistent depending on the individual, company, and industry, it is important to parse the title so it can be normalized to search a lead sourcing database. The first step in parsing a title is breaking it into several different parts:
Seniority is the most important part of a title and will supersede most other information.
Think of it: if you are selling IT security products and want to reach the Director of Engineering Operations, even at a larger company, a VP of Sales will very likely know a reasonable high-level contact in engineering, despite not being remotely close to that division. Similarly, a sales manager, marketing manager, or accounting executive will be less likely to have a relationship that can be exploited.
Unlike other title segments, seniority is the easiest to parse. Best practices for parsing or binning when structuring unstructured data is to separate as much as possible and then condense.
- Below M
C, V, D, and M stand for chief, vice, director, and manager, respectively.
Often there are prefixes to seniority titles such as an “executive” vice president or “senior” manager; however, these prefixes don’t matter. These types of prefixes have more to do with the length of time someone has been in their company or their salary rating. If you are building a robust organizational chart, they may matter; however, in all other cases, not so much, so why make things more complicated?
This leads to the second part of a title to be parsed.
The area is defined as the part of the company individual works in:
This type of segmentation is also typically straightforward to parse. However, like all data, it sometimes gets complicated. If you have a chief revenue officer, there may not be a specific “revenue” department; it is usually marketing and sales, or they may be in charge of an analytics department.
Similarly, consider “VP of Sales and Marketing” or “Director of Accounting and Finance” — each of these combination titles may make you take pause and cause an existential quandary.
Interestingly, the final part of the title to be parsed is one that can either help drill down and focus prospecting efforts or, in some cases, be completely ignored.
For example, take an IT manager of SharePoint. Using the above rubric, the seniority segment would be “Manager,” “IT” the area segment, and “SharePoint” the role.
At a large company, there may be numerous IT managers, many of whom may manage completely different areas; thus, if you are selling something that would help SharePoint, knowing the role is very important.
Here, again, you may encounter some edge cases where you find a multidisciplinary person who occupies several roles at the company. Again the best practice, as described above, is determining which one of the roles is the best fit and using that one, or creating two fields with a primary and secondary role.
Understanding who your leads are is a huge step for any B2B company. Being able to parse those leads into the right type of companies, accounts, and personas ensures that you and your team will have a good handle on exactly who your ICP is. Once you have identified your ICPs, and there will be several, you can then go off to a lead source provider and query for the best leads.
Next, we will delve into the different types of lead providers — and the industries they fit — and help you figure out which one is best for you and your team.
What is lead generation?
Lead generation is the process of finding leads so that you may target them with your marketing and sales efforts.
What is a lead broker/data provider?
Lead brokers and data providers are services where you can either enhance your current lead database or find news leads.
Why do I need a lead generation tool?
You may need a lead generation tool if you like to grow your business outside of a referral or channel program.
What is the best lead generation tool?
The best lead generation tool is one that provides you and your team with the right contacts with the most relevant contact information. If you are sending business-to-business emails, a platform that can scrap and enhance information from LinkedIn will suffice. If you were looking for cellphone numbers, that type of data broker might not be the one for you.
About the Author: Mark Shalinsky, Ph.D., found his way from the bench to the startup world as a science editor for the Journal of Visualized Experiments (JoVE.com). As an editor, he discovered a talent for cold calling. After a successful tenure at JoVE.com, Dr. Shalinsky joined Duo Security as the fifth employee and first sales hire, growing the inside sales and sales operations teams there. After four years and a $2.35 billion exit to Cisco, Mark joined Rusty Bishop at FatStax again with the mandate to build out the sales operations and inside sales team. Within two and half years and more than quintupling of revenue, FatStax was acquired by the largest and publicly traded sales enablement company, BigTinCan. With that exit, Mark was recruited to, again, build out sales operations and inside sales at DryvIQ. After two years of sustained growth, Mark left and started Data Sales Science, a fractional sales operations consulting and sales enablement VAR. Dr. Shalinsky has recently joined TRUiC as the VP of Revenue Operations, where he also writes about his experiences in startups and how technology can help startups in their sales and marketing efforts.