There's a never-ending supply of information about almost every company in the world available on the web today. That said, big data on companies is of little to no use to you as a salesperson when in its unprocessed state. With the help of technology, you can make sense of haphazard company data and get a better understanding of your target accounts' basic characteristics as well as their more hidden traits, their interests, pain-points and current situation. This information is what we in this article refer to as company data.

Contents of this blog

What is Company Data?

Firmographic data

Technographic data

Buying Signals

Predictive and prescriptive company data

What is company data?

Company data is, just as the name indicates, data about a company that provides information on a company’s characteristics, interests, and tendencies. Company data helps salespeople make well-informed decisions about both which companies to work on and when, where and with what message they should reach out to a specific company. In other words, this type of data allows salespeople to be more pointed and timely in their sales efforts.

In this article, we’ll dig deeper into each type of company data. We'll also look at why company data is valuable for sales professionals and go into the details of how you can access comprehensive, real-time company data most effectively.

The majority of raw data, particularly big data, doesn't offer a lot of value in its unprocessed state. But by applying the right set of tools, we can pull powerful insights from this stockpile of bits.

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What’s Firmographic Data?

Firmographic data is basic company information such as industry, location and company size. Companies can be analyzed by using firmographics the same way as people can be analyzed with demographics.

For example, Vainu’s firmographic data could look like this:

Industry: Software, SaaS, Cloud
Location: Helsinki, Finland
Company size: 180 employees, 10 million US dollars in revenue 2017

Firmographics have significant value to salespeople who target companies in a specific industry or a chosen size-range, as it allows them to quickly filter promising prospects from a longer list of potential customers.

Firmographic data includes very basic data, and its biggest flaw is that it's often just too … basic. For you as a salesperson to be able to make a well-informed decision about whether a company is a solid prospect or not, you’re likely to need more information about the company than what firmographics can offer.

Not all companies in the same industry or of the same size have the same needs.

Let’s take a company’s size as an example here: A company with $10 million in revenue that’s in hyper-growth mode will be investing vast amounts into something important to them, while another company of the same size might be in cost-cutting mode and have entirely different priorities.

Sometimes, firmographics also refer to other variables such as performance (growth, credit rating), status and hierarchy (legal status, a relation of one organization to another), age, ownership, and position (market share, industry position).

What’s Technographic Data?

Technographic data is data gathered from a company’s technology stack, website, social media profiles and general web presence.

Technographic data includes a number of categories such as marketing automation, e-commerce platforms, customer feedback management, application tracking systems, live chats, event management and many more.

Let's showcase what technographic data is with an example: The California-based information technology company Synopsys released a new e-book a few months back. The e-book’s campaign page provides a lot of useful insights from technographic data. Researching the page, we can determine Synopsys does systematic large-scale content marketing (they use Eloqua), they try to systematically improve conversion rates (they use Crazy Egg for A/B testing) and that they are also willing to advertise their content (they use Facebook Pixel). They also believe in account-based marketing and web personalization because they use vendors from those categories (Demandbase and Adobe Target). All this information comes from the source code from the campaign page.

If you’re selling an enterprise marketing automation software, firmographics can help you weed out companies with a turnover too low to find your offer relevant. Technographics can then help you find companies mindful of new technology that is currently using a marketing automation software. By looking at a company’s both firmographic and technographic information, you’ll get a more detailed understanding of its organization and needs.

What are Buying Signals?

Buying signals, also frequently named prospecting signals, sales triggers or, sales signals, refer to events that indicate an opportunity for you as a salesperson to reach out to a prospect. Buying signals help you determine when a company is likely to need your product or service so that you can focus on the accounts most likely to turn into paying customers now.

Many changes in a company (recruiting, funding round, expansion, new product release, merger or acquisition) open up a window of opportunity to you as a salesperson. You can quickly improve your hit rate on every step of the sales funnel by processing companies that match your Ideal Customer Profile AND recently sent out a buying signal that indicates they have an increased need for your product or service now.

If you can identify an actionable lead through one, or a series of signals, using this data should be the foundation of your prospecting. Once you find a correlation between a happy new customer and a buying signal, you can find a large number of warm, actionable leads in little time.

  • Offering recruitment services?

    Look for companies that expand and are about to open up an office in a new location, they will need to increase their employee base. (For more inspiration, read our case studies with Academic Work and aTalent!)
  • Working in the logistic and transportation industry?

    Look for companies initiating a new construction project or ones that are opening up a new production facility. In this article we share more in-depth prospecting tips for transportation and logistic companies.

What’s Predictive and Prescriptive Company Data?

Firmographics, technographics, and buying signals can all be seen as a result of basic descriptive analytics. These types of data summarize hard facts about a company. With this data in hand, you can then begin to do more advanced analytics. It’s here that predictive and prescriptive analytics come into play. Once you have enough company data, you can use technology to find patterns.

With a model for how certain data points correlate with one another, you can predict future events and likely outcomes from specific actions.

Predictive data

Predictive data is the result of predictive analytics, advanced analytics which is used to make predictions about unknown future events. Predictive analytics use many techniques from data mining, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about future data. The goal of predictive analytics isn’t to tell you what will happen in the future; it can not do that. The goal of this type of analytics is to forecast the future as accurately as possible. Predictive analytics is probabilistic in nature.

With predictive analytics, you take data that you have to predict data that you don’t have.

Prescriptive data

The emerging field of prescriptive analytics goes beyond descriptive and predictive models. It does this by recommending one or more courses of action for a given situation and showing the likely outcome of each decision.

Prescriptive analytics is, in a way, a type of predictive analytics. The prescriptive model predicts the possible consequences based on a different choice of action. This type of analysis can thereby recommend the best course of action for any pre-specified outcome. Prescriptive analytics can be scaled when machine learning models are automatically collecting feedback and adjusting these suggestions accordingly. Prescriptive data can, for example, suggest with what method and message you as a salesperson should reach out to a prospect.

Prescriptive analytics can recommend the best course of action for any pre-specified outcome.

Most companies are still figuring out how to get their predictive lead scoring models in place, but the frontrunners are already moving from predictive to prescriptive models. At the end of the day, salespeople are not that interested in all those positive and negative attributes in the predictive models. They just want to know what to do next to move their cases along the funnel toward a sale.

Why is Company Data so Valuable for Sales Professionals?

Now that we've covered the basics and gone through what company data, let's look into why detailed, real-time company data is so valuable for salespeople.

Today's sales landscape is highly competitive, and modern buyers are more well-read than ever before. A generic or poorly tailored sales pitch is a recipe for little to no success for salespeople. By looking at a wide range of data points from different datasets, you’ll get an in-depth understanding of a company’s organization and situation. This will help you:

  • Define a more detailed ideal customer profile and find companies matching it. In other words, target the accounts you’re likely to have the the best chance of turning into a paying customer now.
  • Tailor your sales pitch for each prospect’s unique organization and needs.
  • Predict when and how you should reach out to a specific company.
21 % of sales rep’s time is consumed on doing research

Get Easy Access to Company Data with Sales Intelligence

According to a study conducted by Salesforce, 21 percent of sales rep’s time is consumed with doing research. Other studies show that sales prospecting can take up to half of the average salesperson’s workday. By decreasing the time you spend on looking for potential customers and company information, you'll free more time for actually selling or taking care of existing customers.

You can cut down on the time spent on sales prospecting and lead qualification by automating as much of these processes as possible. Invest in a sales intelligence tool that gives you easy access to real-time data about all companies in your market.

With a sales intelligence tool, you don’t have to make it your life mission to read every piece of printed media out there, scan all social media feeds and subscribe to every company’s newsletter. Sales intelligence can collect enormous amounts of data from millions of open and public data sources on a daily basis. Powered by artificial intelligence and machine learning, the technology can also read, understand and structure the data into information you can easily understand.

Why Real-Time Data is King

A common problem in marketing and sales is outdated data. The data in purchased prospect lists is often based on data from companies annual reports and other sources that only gets updated one or a few times a year. Add to that, that it might often take a while between that your list provider extracts the list you’re working with and that you use its information in a sales call or marketing outreach and it becomes evident that using data from static lists often mean working with outdated data.

Modern sales intelligence tools can provide you with data that's always up to date, so called real-time data. Real-time company data is dynamic company information that updates automatically as companies’ characteristics and conditions change.

A common problem in marketing and sales is outdated data.

A company in the hyper-growth phase that had 100 employees by the turn of the year might have more than doubled its headcount and tripled its revenue by the start of H2. Real-time data about this company will help you tailor your sales pitch according to the company’s current situation and pain points. If you as a salesperson instead only base your outreach on data from a static list that includes information from the company’s half-year-old annual report, there’s a high risk that your offer isn’t at all relevant for the company today. Another advantage of real-time data is that it can include buying signals.

Studies show that between 30 and 50 percent of sales go to the vendor that reached out first when a company started to detect a new need.

Example: Say you’re working as a salesperson in the real-estate industry and the hypothetical hyper-growth company we mentioned above just added 20 new openings to its career page. Simple predictive analytics can then suggest to you that there’s a good chance this company will need a new office suitable for its increased head-count within a not too distant future. By acting on this predictive data, you’re likely to be the first from your industry to offer your service.

Don’t Underestimate the Importance of Any Company Data

Only looking at, for example, a company's firmographic data or technographic data will tell you only so much about its organization and needs. By looking at insights from both descriptive data sets and predictive and prescriptive analytics, you’ll get a better holistic understanding of your ultimate prospects. You’ll also gain a better understanding of how you should process each company to improve your chance of winning the sale.

A traditional Ideal Customer Profile only based on firmographic data can look something like this:

Industry: Software development
Location: New York
Size: 70-150 employees
Revenue: $70 - $110 million USD / year

A modern, more advanced Ideal Customer Profile based on both firmographic and technographic data can look something like this:

Characteristics: High digitalization
Sales trigger: invest heavily in new technology, has recently hired a new CTO or implemented a new technical tool
Characteristics: run online demos
Industry: Software development
Location: New York

What Company Data is Most Relevant for You?

While it’s true that you have a lot to win by looking at all types of company data, you shouldn’t focus on every data point possible when prospecting or researching an existing lead.

Some information about your potential customers you will do just as well without. No need to find out what breed the office dog is or what color the walls are.

Finding out which data points help you set apart a prospect of high quality from one of poor quality for you is what’s referred to as defining your ideal customer profile.

Your Ideal Customer Profile is a description of a fictitious account which gets significant value from your product or service and provides substantial value to your company in return.

Start looking at your current customers, especially the most satisfied ones. Find their common characteristics and find a pattern of events at these companies that happened right before they signed a deal with you. The data points setting your most happy customers apart from the average company are those you should mainly focus on in your sales prospecting. In this article, we describe in detail how you can create a detailed description of your dream customer.


The majority of open and public data doesn’t offer a lot of value in its unprocessed state. However, when you take help from smart sales technologies to both collect and read company data, you can start to see patterns and learn which companies to focus on and how to process these companies with the best possible hit rate.

There are mainly four types of company data that you as a sales professional in forefront should know of: firmographic data, technographic data, sales signals and predictive and prescriptive company data. By only looking at one or two types of company data, you’re missing out on many valuable insights about your prospects and existing customers. By investing in technology that provides you and your sales team with all types of company data, you’re better equipped to make well-read decisions throughout the sales process, ultimately leading to an increase in revenue.

Insights from smart company data make you and your sales team better equipped to make well-read decisions in every step of the sales process.

Modern sales intelligence technologies give salespeople access to real-time company data. While old-school static prospect lists often include outdated data from e.g. year old annual reports, dynamic databases like Vainu update their data on a constant basis.

If you want to know more about how Vainu collects, reads and structures company data and also creates new data thanks to predictive analytics, our product specialists are happy to assist you. Sign up for a 30-minute free demo of our platform here and find out how you and your team can benefit from using insights from company data in your daily sales business.

Topics: Company Data

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