Tier 1: Sales Cycle, Average Contract Value (ACV), Win Rate

The goal of Tier 1 is to understand the sales velocity (i.e., the number of opportunities multiplied by the ACV, multiplied by the win rate, divided by the sales cycle) of your customer base.

• These data points will form the basic foundation and expose any outliers in the customer data.
• Invest time to validate the integrity of your data.

Tier 2: Industry (and Vertical), Employee Size, Growth Score, Location, and Technology Stack

The goal of Tier 2 is to add an additional layer of firmographic data that will form the basis for your size and scope analysis.

• There are a number of large data sources to validate industry, vertical, employee size, growth score, and location, including Mattermark, FactSet, and Hoover's. When you are evaluating your potential database partner, use the following criteria to help guide your choice:
  • Matching percentage (i.e., number of your customers that are present in the list)
  • Number of additional data (commonalities) points
  • Data integrity—check third-party sources to validate
• Industry and vertical are interdependent (and often confused). An example of the relationship is that Box is in the cloud storage vertical within the technology industry.
• If your customers have adopted a set of technologies, surfacing this data at scale will provide an additional proxy. For the technology stack, there are several sources to capture this data: Datanyze, Ghostery Enterprise, BuiltWith, and SimilarWeb. Using these providers will help you determine if your customers are using website analytics, marketing automation, Pay Per Click advertising, A/B testing, and so forth.

Tier 3: Company Specific Data

• By using freelancers (from Upwork, CrowdFlower, etc.), you can add valuable data from your competitors' websites, the AppExchange, or any website. If you have a hypothesis that you'd like to test (e.g., your buyer is a vice president of marketing), you can have the freelancers do a pass against your customer list via LinkedIn.
• The scope of this collection is broad, so identify a few hypotheses, and then you can validate them from your Tier 1 data points.

Step 1: Map Your Customer Data

1. Using Excel, create a data sheet for each Tier.
2. Form a consistent list of your customers across each data sheet.
3. Cluster (and sort) the companies with high concentration across each variable, specifically those that perform well across the Tier 1 data points.

Step 2: Identify the Early Adopters and Mainstream (see Geoffrey Moore's Crossing the Chasm)

Place your customers into two buckets:

1. Those that have a high number of variables and high-performing characteristics from Tier 1. Companies that are early adopters and have a faster than average sales velocity will surface on this list.
2. Those that are outside your (assumed) ideal customer profile (ICP) but possess high-performing characteristics from Tier 1. This list will provide companies that have a faster than average sales velocity but may not be in your present ICP.

Step 3: Validate the Size and Scope

1. Based on your two customer data sets, use the confirmed variables to export companies from the largest database available for your given industry and set of verticals.
2. Separate the two distinct buckets (from Step 2) to ensure that you can test the performance of each data set.

Step 1: Confirm the Variables

When you check the weather, are you interested in the barometric pressure? Probably not, so apply the same logic to the data fields that you have collected. The goal in Step 1 is to understand the optimal information that can be effectively positioned to personalize the team's outreach.

1. Take a holistic approach to how the team can use this data:
   • Industry/vertical will align future customers (see Geoffrey Moore: “Bowling Pin Strategy”).
   • Geographical concentration adds degrees of separation and can be valuable for marketing events.
   • Technology providers will allow easy dynamic fields within e-mails.
   • Competitive takeaways will provide great talking points.
2. Limit the variables to four to five (to avoid paralysis by analysis).
3. Choose your filters (for the Dashboard) so that you have overarching segmentation.

Step 2: Create Custom Fields within the CRM System

Add a collection of custom fields, and be particular about how you present the data (i.e., on the account record and/or the contact record). This will involve using a feedback loop with the sales team around what they would find valuable—that is, specific to the sales process.

Step 3: Mapping the Fields to Reports in Salesforce

In Step 3, you want to think about the optimal method for presenting the data so that (1) the sales team can quickly interpret the chart and (2) you are telling a story with each data point.

My advice is to use a combination of different charts and leverage feedback from the sales team on how they interpret each report. The longer it takes for individuals to understand the context of the report, the less valuable the report is.

CrunchBase and AngelList

CrunchBase and AngelList are your free and simple sources for gathering the information you need on technology companies from pre-seed to post-IPO (initial public offering) to exit. Both CrunchBase and AngelList have application program interfaces (APIs) that you can use, which are good but still somewhat limited, as they don't want you to rip off their entire database. If you're somewhat technical in basic Ruby on Rails or Python, or you think you can learn quickly, check out the blog posts of Chief Operating Officer (COO) of Scripted, Ryan Buckley, on Scraping CrunchBase.

If you're not too technical, you can use the nontechnical Web-scraping tools that were previously mentioned (Import.io and Kimono Labs) to scrape the information you require. Supplement this with virtual assistants, and you'll have everything you need to start building massive lists in one shot.

Glassdoor is also a good place to get company data.

Owler

Owler is like a souped-up version of CrunchBase, with a better ability to sort companies, get alerts, and surface information more clearly.

In Owler, you can sort by funding, acquisitions, or leadership changes, or you can visit a company page and see all of its competitors.

Owler provides data and profiles on over 10,000 private and public companies, but the key features are its alerts and snapshots. Get weekly competitive intelligence reports on data comparisons that include information on the following:

• Chief executive officers (CEOs)
• Revenue
• Press releases
• Blog posts
• Social media statistics
• Competitive set
• And more

Mattermark

Mattermark offers a way of sourcing, analyzing, and tracking private companies around the world. By using the wealth of data that Mattermark has gathered on companies, using proprietary information such as a “Growth Score” or “Mindshare Score” allows business-to-business (B2B) sales professionals to identify more readily potential private companies they would like to do business with.

Mattermark provides a feed into any user's instance of Salesforce, giving the user the ability to leverage the data in his or her CRM system. You can connect your LinkedIn account to see how your first-level connections are connected to the people in the private companies you have identified on Mattermark. This is a great way of getting warm introductions to these private firms.

For even more records that are both private and public, check out PitchBook VC and S&P Capital IQ.

Socedo

Socedo allows you to pick conversations, keywords, hashtags, and handles to track prospects. Just set up search criteria for each prospect, and Socedo selects accounts across Twitter that might be relevant to you. Then you approve the prospects it has selected.

Once you have your list of prospects, Socedo favorites a recent tweet of the propect's. An hour later, Socedo follows the prospect. When the prospect follows you back, Socedo sends you a direct message using the prospect's first name, a reference to the prospect's tweet, and a Call to Action (CTA). This CTA is trackable, and the entire flow, including the direct message, is customizable.

CEO of Socedo, Aseem Badshah, adds:

It's important to spend time coming up with some really good keywords that will help you find your target customers. Think about what they are tweeting about instead of what you or your competitors are tweeting about. What events do they attend? Who do they retweet? What do they read? The prospect search criteria takes some time, but it is crucial to your success no matter how you prospect.

You've done a great job on gathering lists of companies. The next step is figuring out the right way in the door.