Ideally, salespeople want to classify and segment companies after closing a deal to find similar companies and continue on a successful path. They will look for similarities based on a particular situation. Are two ten-million euro marketing agencies located in Stockholm similar or not? Are two restaurants, which are looking for similar customers the same if one is in London and the other one in Liverpool? Is every B2C leisure activity company similar? The answer always depends on the context. Most of the time, a salesperson wants to define their own criteria for the similarity, so they can, for example, search in their CRM and find new potential customers.
In contrast to marketing activities, for a salesperson it isn't important to find all the companies in one category—a few good ones will do. Marketers want the opposite because volume is key to their success. If their activities reach hundreds or thousands of companies, segmentation must be done systematically.
Firmographic attributes such as size, location, and industry are a good starting point because each company has its own characteristic. Using these attributes and some filtering marketers are able to send the right messaging to all of the right companies. Data-driven marketers don’t stop there because nowadays there are so many more data points that allow them to create complex classification schemes. Let’s see next how to tap into data.
Our core business is plugging real-time company information into our customers’ CRM platforms to fuel their sales activities and marketing campaigns. Therefore, it’s easy to justify the significant investments that we’ve made into compiling data to help build different classifications.
First, we compile data from a public source, or we buy it from another data provider. That’s only a fraction of the company information in our database.
Then, we proceed to label and classify each company. We automate this process as much as possible, but occasionally humans need to step in and validate the data. This process not only improves the quality of our taxonomy and datasets, but it also enhances our algorithms for a more accurate classification in the future, for example, looking into a company’s website or press releases.
Such categorization happens in the background. For the end-user, it doesn’t matter. What matters is having access to all the data and attributes right in the system they use to manage their sales activities and marketing campaigns. Typically, those systems are the CRM (Salesforce, Dynamics365, Pipedrive, or SuperOffice) or marketing automation tools like HubSpot, Marketo, Pardot, or Mailchimp.
These sales tools have the possibility of adding categories and values into the account level, and, in many cases, they have advanced workflow capabilities for building different campaigns and automations.
At the end of the day, in B2B sales, you only want to sell and market to those companies that match your ideal customer profile (by the way, here’s a template in case you need to create or refine your ICP). This guarantees to be creative, smart, and relevant in sales, knowing that you’re reaching at the right time and without wasting any resources in the process. Classifying your accounts will help you reach those companies that match your ICP.
Beyond company classification, there are also the people behind the business ID. Data can also help you categorize the different stakeholders. That’s something for another post, though.
Topics: Sales Intelligence