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Updated August 22, 2022You’re reading an excerpt of Founding Sales: The Early-Stage Go-To-Market Handbook, a book by Pete Kazanjy. The most in-depth, tactical handbook ever written for early-stage B2B sales, it distills early sales first principles and teaches the skills required, from being a founder selling to being an early salesperson and a sales leader. Purchase the book to support the author and the ad-free Holloway reading experience. You get instant digital access, commentary and future updates, and a high-quality PDF download.
Remember your sales narrative, which was based on hypotheses about how your offering solves the pain points of potential customers? Parts of your ideal customer profile were defined there. But now, instead of expressing this in a narrative format, you want to boil it down to abstracted characteristics. You want to get to the point that you can rattle off a set of metadata characteristics that describe the relative level of attractiveness of a prospect.
exampleIn TalentBin’s case, this would be something like, “This account has five technical recruiters and twenty open technical hires, including iOS, Java, and Android roles, and uses LinkedIn Recruiter.” What are the characteristics in there? First, we have the existence of technical recruiters—without at least one recruiter or sourcer to actively use the tool, customers are unlikely to have success. Passive-candidate recruiting is too time-consuming and challenging to be done on the side by an HR generalist or a hiring manager. The fact that there are five recruiters indicates that this is a juicier-looking account, where there is an opportunity to sell up to five seats of TalentBin. And when it comes to business pain, there’s a lot: 20 engineering hires is a tall order. Even better, iOS, Java, and Android roles are the kind that TalentBin does particularly well at compared to LinkedIn (versus, say, .NET or C#). Lastly, if we can figure out whether the account has multiple seats of LinkedIn Recruiter—a market alternative to TalentBin—we’ll know how much they’re willing to spend on passive-recruiting tooling to make those five recruiters more effective. If they all have seats, we know that there’s around ~$50K of budget already allocated for LinkedIn Recruiter, which we can take a bite of.
exampleIn the case of Immediately, makers of a really cool sales-focused mobile email client and CRM tool for Gmail and Salesforce, it might look something like, “This account uses Gmail, Salesforce, and Marketo. They have fifty sales reps scattered across the United States, selling software that costs on average ~$50K. And it looks like the Vice President of Sales has a Sales Operations Manager reporting to her.” What are the characteristics Immediately is looking for? Well, as of 2015, the software needs Gmail and Salesforce to work. So if an organization doesn’t use Salesforce and Gmail, the conversation is dead in the water. Those are required characteristics. This account also uses Marketo, which indicates a level of sophistication within the sales and marketing organization, and a willingness to pay for expensive tooling that accelerates revenue acquisition. There are 50 reps, each of whom represents a potential user, so this seems like a potentially valuable opportunity.
Moreover, because the reps are spread all over the U.S.—rather than co-located in a single area, indicating a call center—it would seem that these are outside sales reps. And outside sales reps are less frequently in front of a laptop, which makes a compelling sales-first mobile email client and CRM all the more important for them. Beyond that, the software this prospect sells is expensive; incremental wins are very valuable to them. A solution like Immediately, which helps reps handle more deals and avoid dropped balls while mobile, is all the more important when each of those potential dropped balls represents ~$50K of revenue. Lastly, because someone is managing sales operations, we know there is someone who is specifically charged with making those 50 sales reps more effective and for maintaining a clean and effective CRM. He will likely be very interested in something that not only makes those reps more effective, but also helps him with the pain point of getting 50 distributed professionals to enter information into the CRM to help with data cleanliness, forecasting, and so forth.
Take a quick second to think about what your qualifying characteristics could look like.
Also importantly, while we’ll be talking about a number of tools below that support this prospecting effort, over time tools may change; the core concept of identifying prospects based on their outward facing characteristics remains the same and is key to success here.
When it comes to looking for potential accounts, you can start with people or you can start with companies, and you need to figure out what the right approach is for your solution. You’ll look in different places for this information depending on whether you’re talking about contacts (people) or accounts (companies), and depending on the kind of characteristics you’re assessing.
For account sourcing based on people who work for a given organization, it’s really tough to beat LinkedIn—specifically their premium talent solutions. Much of the time, prospect identification will hinge on job title, and LinkedIn is pretty much the best place to find that information. Before LinkedIn, resume databases and contact databases like Salesforce’s Data.com and Dun and Bradstreet were the go-tos, but they all suffer from being out-of-date and incomplete. Right now, LinkedIn is your best bet. There are industries whose professionals are less likely to be on LinkedIn, and that can present more of a challenge; in those cases, you may have to revert to more traditional sources. But for the purposes of finding 50–100 prospects, I would be very surprised if LinkedIn didn’t handle this for you.
Source: LinkedIn
Do you sell an analytics tool that only someone with a title that includes “analytics” would use? LinkedIn is helpful for identifying those people, and thus the companies they work for.
Remember, though, that when you think about your ideal customer profile, you should be thinking about the organization you’re selling to. While you may approach account sourcing by looking for the job titles you need, you shouldn’t be focused on targeting a particular person or people just yet. Unless you’re in a situation where there is literally no difference between the individual and the organization that is purchasing the solution (an organization of one, or an individual within a larger organization buying the solution on his own), your ideal customer is still an account. That account will certainly include key people (recruiters, sales reps, sales ops staff, data scientists, and so on), and you’ll eventually be seeking out the right point of contact, or multiple points of contact and decision-makers, to engage with. But your customer profile is the description of an organization.
As for account sourcing based on the characteristics of the company itself, because companies have a tendency to stick around longer than individuals stay in a specific role, information latency is less of an issue. LinkedIn is still a great resource here, in that you can find accounts based on the number of people in a specific role at those organizations. But there are a host of other providers as well. More traditional ones include Dun and Bradstreet, Hoover’s, and Salesforce’s Data.com, which are well suited to account sourcing based on size, geography, and industry, with DiscoverOrg and ZoomInfo being more modern variants of these. For small-business account sourcing, Yelp can be a great place to go looking for local businesses, bucketed by industry, along with contact information (but generally lacking the specific point of contact you would seek to engage with). Other helpful data sources for small and local businesses include Radius and InfoUSA’s Salesgenie. A pure Google Maps search can work here as well. You can often use products you compete with for account sourcing too. If you’re selling into restaurants, OpenTable’s index is a great way to find restaurants that care about revenue management, and GrubHub and Seamless are great places to find restaurants that care about delivery. If you’re selling into doctors’ offices, Healthgrades, Doximity, and even state license databases are good places to look.
Moreover, some of these data sources can tell you if the prospect is paying for technology and services. The profile of a small business that is paying for Yelp business services looks visually different than one for a business that’s not, showing you that they’re paying for the service. And willingness to pay for marketing services can be a helpful signifier in prioritizing a given business as a prospect.
For example, using Yelp we get 16K dentists in Orange County to target:
Source: Yelp
And with Google Maps, we find auto repair shops in San Francisco to target:
Source: Google Maps
More modern account-sourcing services reveal the technologies that run on an organization’s website, which can be indicative of their business pains and willingness to pay for solutions. An organization that has a Salesforce Web-to-Lead form on its homepage clearly pays for CRM and could be a fit for a solution that extends Salesforce or replaces it. An organization that runs Optimizely on its website might be a target for a solution that makes better A/B testing software. BuiltWith, Datanyze, Datafox, SimilarWeb, HGData, and Wappalyzer are examples of this type of account-sourcing service. There are also those that rely on self-reported information, like DiscoverOrg, Siftery, and RainKing, which can be helpful if the technology that is installed isn’t visible to web crawling. And then there are services like Spiceworks that provides free network-monitoring software and allows marketers access to see which accounts use what type of solutions for marketing purposes.
Using Datanyze to find accounts that use Salesforce and Gmail, in the sweet spot of 100–250 staff, we get the below results.
Source: Datanyze
exampleYou can also use hiring information for account sourcing. This is most directly applicable when your solution is also hiring-related. The number of open hires listed on an organization’s website would be a good leading demand indicator for a SaaS solution that reduces time to onboard new employees, or a leading indicator of willingness to pay for recruitment-branding services like LifeGuides or Glassdoor. The type of open roles can also be revealing. If an organization is hiring for engineering staff, that indicates demand for a recruiting agency or candidate database that focuses on engineering. You can even tell if they’re a current customer of companies that provide these solutions. If you’re looking at Indeed, Glassdoor, Monster, or LinkedIn for hiring information, you can often see if the prospect has a paid account or just the free version based on the appearance of the company’s profile.
Because Twitter has a featured review, and a list of Jobs You May Like, you know that they pay for Glassdoor.
Source: Glassdoor
Thanks to their Careers page, we know that Yelp is hiring lots of engineers.
Source: Yelp
The kinds of people an organization has hired in the past can also be helpful. Even if an organization is not currently hiring for data scientists, if they previously had a posting up for that role, it’s likely an organization that employs data scientists. So if you sell a solution that makes data scientists more successful and efficient, you know, at a minimum, that the account likely has data scientists in-house and might be interested in your solution. Providers of hiring information include services like WANTED Analytics, or even just job boards like Indeed, Monster, Glassdoor, and LinkedIn.
Below you can see companies hiring data scientists in the United States, per WANTED Analytics.
Source: WANTED Analytics
If you sell to organizations that employ data scientists, these accounts would be good ones to address.
While these services will often be able to show you the single piece of information that you’re looking for—like whether an organization uses Salesforce or not—other times you can use them for finding information that is correlated with the actual demand signifier you’re looking for. Organizations often replace the default Salesforce lead capture form with specialized marketing automation lead capture forms from Marketo or Eloqua. And while the existence of a Marketo form on an organization’s website isn’t 100% correlated with Salesforce use, it’s usually a pretty good leading indicator. And it shows that the company is willing to pay for a more evolved solution.
Remember, you aren’t wedded to one data source when you’re fleshing out ideal customer accounts and contacts.
exampleIf you were Immediately, makers of that really cool sales-focused mobile email client and CRM tool, you might use BuiltWith or Datanyze to find organizations that use Salesforce and Gmail. Then, if you wanted to know how many salespeople there are in each of those organizations, you might run a title search on LinkedIn for “Account” or “Sales” (catching people with titles like Account Executive, Sales Consultant, Sales Director, Account Manager, and so on) to get that demand magnitude information. And that’s before you would turn to finding the individual contacts you would like to engage, which are likely to be on LinkedIn.
We can see there are around a dozen recruiters at New Relic—so say we sourced New Relic as an account based on their Glassdoor company page and wanted to see how many potential users there were; we now know they have a goodly amount of recruiters.
Source: LinkedIn
However, while you might use multiple data sources to flesh out the demand characteristics of accounts that you’ve already found, using multiple sources to drive sourcing is typically a bad idea. If you can reliably find promising new accounts with a specific source (such as Datanyze or LinkedIn or Yelp), and there is a good quantity of them, you’re kidding yourself if you are trying to get much more out of other sources, at least to start. Usually this is a sign of overactive prospecting more than anything else. Feel free to iterate and see if there is a more effective tool for account sourcing, but don’t pretend that prospecting across things like Twitter and Meetup and Facebook is actually anything more than poor discipline.
Finally, a cautionary note. There are also lots of marketing list providers, but I typically take a pretty dim view of those. They’re generally extremely out-of-date compared to information on LinkedIn, and they’re generally poorly modeled. They typically include very sparse metadata outside of name, title, contact information, and lightweight company geography, size, and industry information. So your targeting will be poor. Moreover, you don’t want to waste your time calling numbers that go to nowhere and emailing email addresses that no longer exist. And for now, since you’re just looking to get your first hundred targets, you can do it manually—not to mention that manual prospecting is a very good exercise to go through to get a more concrete sense of what these accounts and individuals look like. As you go, you may discover that a characteristic you thought was important actually isn’t, or discover another characteristic that is even more important for sourcing or qualifying potential prospects. So stay away from lists.
Just because a given characteristic isn’t outwardly discoverable doesn’t mean that you shouldn’t include it in your ideal customer profile. It could still be extremely important in determining whether or not your solution is relevant for a prospect.
exampleWith TalentBin, whether an organization used passive-candidate recruiting databases, like LinkedIn Recruiter, was a fantastic indicator of whether TalentBin could help them with their recruiting efforts. The problem was, that information was not publicly available. There were correlating pieces of information: if an organization paid for a premium LinkedIn Company Page, or had job postings on LinkedIn’s job search engine (by paying for a job slot), and also had recruiters in-house, they usually had one or more LinkedIn Recruiter seats. Still, we couldn’t definitively identify this characteristic from publicly available information—but it was an important one to include in our ideal customer profile.
So, if a characteristic isn’t identifiable, how will you ever be able to get the information you need? Well, you’ll have to ask. That means when prospects come inbound through your lead capture forms, or you’re on the phone with them, you’ll have to specifically ask them if they have these characteristics. And if you can’t proactively identify prospects that have these hidden characteristics, how can you scalably attract them? That’s where things like content and inbound marketing come into play. More on that later—for now, for identifying a hundred potential targets, direct prospecting, coupled with discovery questions when key characteristics aren’t readily observable, will be your approach.
When you think about your ideal customer profile, you need to be thinking about not just the minimum requirements for product/prospect fit but also the magnitude of demand that prospect may have. This helps for a couple of reasons. First, knowing the size of an account’s demand can help with understanding how much of your solution you can potentially sell them, so you can focus on accounts that might buy lots of your solution. It also can help you understand the magnitude of their business pain and, as such, how motivated they will be to pay for your solution. It can also help you prioritize various opportunities, so you can spend your time on those with higher pain. (We’ll talk about small versus medium versus large accounts in a bit—but more pain usually means more money.) You’ll eventually be able to converge on a customer attractiveness algorithm that will help you (and later, your sales staff) judge the relative attractiveness of a prospect.
exampleWith TalentBin, the score would be based on any combination of the following: number of recruiters, volume of engineering hiring, passive-candidate recruiting acumen, and ability to pay. So an account that has a single recruiter in-house, but ten open iOS and Android engineering requisitions, and that just recently raised ~$5M might be as attractive as an account with four recruiters, all sharing a LinkedIn Recruiter seat, and only a couple of engineering reqs. And both would pale in comparison to an account with three recruiters—and three LinkedIn Recruiter accounts—15 open engineering reqs, and a history of doing manual sourcing on GitHub and Twitter. Note that all of these accounts have the minimum viable criteria that we set at TalentBin: at least one recruiter and at least three open engineering roles. Think about what this looks like for your ideal customer. What factors will you consider—perhaps it’s number of field sales reps or how bad the company’s Glassdoor reviews are or its volume of e-commerce sales—and how will you weigh them in combination?
Now that we’ve discussed the various places where you could go and look for accounts, let’s get very specific about doing this in practice, shooting for that goal of 50–100 targets.
Later we’ll get into CRM and where to house your list of accounts and contacts to attack, but my recommendation at this stage is to just use a Google Sheet as your initial repository of prospects. This doesn’t mean that you’ll use this spreadsheet as your CRM (though you probably could for this limited scale of engagement), but you do want a place to house the structured prospect data. You can use a spreadsheet template, with both role-specific prospecting and hiring-specific prospecting.