In this article, we’ll dig deeper into types of company data and analytics. 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.
What is company data?
Company data is information on a company's characteristics, interests, and tendencies. Subcategories of company data are internal data from tools such as customer relationship management (CRM) and external data including firmographics, technographics and buying signals.
Contents of this blog
Company data consists of internal (e.g. CRM data) and external data. Types of external company data are firmographic information (including industry, location and company size) and technographic information (including company’s technology stack and web presence). There're also buying signals, which are news or other company released information that reveal a possibility to sell.
Descriptive analysis describes the current situation of the company and it’s based on firmographic data, technographic data and buying signals. Predictive analysis predicts the future based on the data. Prescriptive analysis goes a step further and recommends actions based on the data to maximize sales.
Company data, analyzed, 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.
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.
Vainu’s firmographic data:
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. It allows them to quickly filter promising prospects from a longer list of potential customers. 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.
Let’s take an example: Company A with $10 million in revenue in hyper-growth mode will be investing vast amounts into something important to them. Simultaneously, company B with the same revenue class might be in cost-cutting mode and have entirely different priorities.
Depending on the service you’re selling, you likely only want to contact either A or B.
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 categories such as marketing automation, e-commerce platforms, customer feedback management, application tracking systems, live chats, event management and more.
The California-based information technology company Synopsys released a new e-book and the e-book’s campaign page provided a lot of useful technographic data. Researching the page, we were able to determine the following:
- 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.
- They are also willing to advertise their content = they use Facebook Pixel.
- They believe in account-based marketing and web personalization = They use vendors from those categories including Demandbase and Adobe Target.
All this information is gathered from the source code of the campaign page.
When you’re selling an enterprise marketing automation software, firmographics help you weed out companies with a turnover too low to find your offer relevant. Technographics help you find companies mindful of new technology and, currently using a marketing automation software. Looking at both firmographic and technographic information, you’ll get a more detailed understanding of its organization and needs.
What are Buying Signals?
Buying signals are events that indicate an opportunity for you, as a salesperson, to reach out to a prospect. Events, such as recruiting, funding round, expansion, new product release, merger or acquisition open up a window of opportunity to start a conversation and eventually make a deal. You can quickly improve your hit rate on every step of the sales funnel by favoring companies that have recently sent out a buying signal.
As soon as you can identify an actionable lead through a buying signal, using buying signals 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 actionable leads in no time. Here’re a few examples:
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!)
- in-depth prospecting tips for transportation and logistic companies.
What’s Predictive and Prescriptive analysis?
Firmographics, technographics, and buying signals constitute a descriptive analytics. It summarizes undisputed facts about a company. With this data in hand, you are able to do more advanced analytics. It’s here that predictive and prescriptive analytics come into play.
Predictive data is the result of predictive analytics, which is used to make predictions about unknown future events. Predictive analytics use techniques from data mining, modeling, machine learning, and artificial intelligence to analyze current data to make predictions about the future. The goal of predictive analytics is to forecast the future as accurately as possible and provide a set of data otherwise unavailable.
The goal of predictive analytics is to forecast the future as accurately as possible and provide a set of data otherwise unavailable.
The emerging field of prescriptive analytics goes beyond descriptive and predictive models. It recommends courses of action for a given situation and showing the likely outcome of each decision.
Prescriptive analytics is 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 data can, for example, suggest with what method and message you as a salesperson should reach out to a prospect.
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 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.
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 collects enormous amounts of data from millions of open and public data sources on continually. Powered by artificial intelligence and machine learning, the technology can also read, understand and structure the data into information you can easily understand.
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.
- 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.
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. It's evident that using data from static lists means 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 difficulties. If you 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.
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: You’re working as a salesperson in the real-estate industry and the hyper-growth company mentioned above adds 20 new openings to its career page. Predictive analytics suggests 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 probably the first from your industry to offer the service.
Don’t Underestimate the Importance of Any Company Data
Only looking at company's firmographic data or technographic data will tell you only so much about its organization and needs. By monitoring buying signals and 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 looks like this:
Industry: Software development
Location: New York
Size: 70-150 employees
Revenue: $70 - $110 million USD / year
An advanced Ideal Customer Profile based on both firmographic and technographic data looks like this:
Characteristics: High digitalization
Buying signal: 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?
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 a sales professional needs to know of: firmographic data, technographic data, buying 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.
To sum it up: 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.