B2B sales intelligence is one of the most critical aspects of the sales process. Sales reps need relevant information about prospective customers to target them appropriately. Also, since personalized messaging is now in greater demand than ever, data becomes an integral part of the sales process.
Public web data has many use cases, but today, I will cover how it can provide you with better business intelligence. To simplify this process, let's first break down sales intelligence data into three main categories: company data, intent data, and contact data.
In this article, I will deep-dive into two categories—company data and intent data—and explain how both can help boost your B2B sales intelligence and increase revenue.
I'll also briefly mention contact data and why it's not as essential to the sales process as company and intent data.
What is sales intelligence?
Sales intelligence, also known as sales data, is information that salespeople use to make data-driven decisions about the target market and its prospects, with the goal of increasing conversions.
One of the best sales intelligence use cases is enriching existing customer records with company size, new hires, employee reviews, and other data fields. This allows you to offer a more personalized deal, and sales intelligence enables you to switch to account-based sales with a much higher success rate.
Moreover, sales intelligence gives you B2B intent data for targeting ready-to-buy leads. This effectively eradicates cold-calling from your sales playbook.
Sales intelligence might also include contact data. Although it's less important in B2B, it can still help you contact decision-makers instead of filling out a contact form on the prospect's website.
What is company data?
In short, company data refers to a business or organization's characteristics, such as size, industry, location, and ownership structure. You can use this data to create a company profile and better understand its customers, competitors, and market position.
Company data will help you better target your marketing and sales efforts, identify qualified leads, and evaluate the overall competitive landscape.
How does company data help with B2B sales intelligence?
I selected 4 main use cases to present how company data can enhance your B2B sales intelligence. Let's delve into it:
- Target the right prospects. By analyzing company data, sales teams can identify the companies most likely to become clients. For example, if your company sells software for small businesses, you can use firmographics to target companies with fewer than 100 employees.
- Personalize sales pitches. Company data can also help B2B sales teams tailor their sales pitches to individual prospects. For example, suppose you notice that the target company is growing rapidly. In that case, they may benefit from HR software (that your company provides) to alleviate some of the HR department's responsibilities. Since you know this information, you could reach out to them and offer your services at the right time, resulting in higher chances of success.
- Prioritize leads. Firmographic data can help sales teams prioritize their leads based on their potential value. For example, if you sell accounting software, you may want to prioritize leads from large companies with high revenue.
- Identify cross-selling opportunities. By analyzing firmographic data, B2B sales teams can identify cross-selling opportunities with existing customers. For example, if your company sells IT services to a client, you may also offer cybersecurity services based on the client's characteristics, such as industry and size.
What is intent data?
Intent data is a form of business intelligence data that reveals a user's purchase intentions through their online behavior analysis, utilizing first-party and third-party data sources.
First-party data tracks user interactions on your site—such as page views, downloads, and conversions—using cookies and IP addresses. In contrast, third-party data provides insights by monitoring users across various external sites, including social media platforms and search engines.
This data is particularly valuable in B2B marketing, where understanding the buyer's journey and their intent strength is crucial for personalizing experiences to meet increasing buyer expectations.
Marketers and sales teams can leverage intent data to pinpoint when prospects are considering a purchase. This enables companies to optimize their marketing strategies, enhance user engagement, and significantly improve the chances of conversion.
Examples of intent data usage
Regarding B2B markets, you could utilize job posting data to identify buyer intent. For example, in the job descriptions, you can see what software a company is using and offer better alternatives.
You can also check what departments the company is looking to grow. If the target company is searching for additional members for the sales team, they might be interested in upgrading or replacing existing business intelligence software.
Moreover, you can use employee data to see if there is a new CMO in town. The new C-level employee will likely revise the company's tools, allowing you to offer your cutting-edge technology as a better alternative.
How does intent data help with B2B sales intelligence?
We talked about company data before. Now let's see how intent data can bring value to your business:
- Identify potential customers. Job postings often indicate when a company is looking to hire for a specific role, which can signal that the company is growing or expanding in that area. By tracking job postings in specific industries or regions, your sales team can identify potential new customers to target.
- Understand industry trends. By analyzing job postings across different industries, sales teams can gain insights into which sectors are growing, which roles are in high demand, and which skills are most valuable. This information can help them tailor their messaging to specific industries and customer needs.
- Determine pain points. Job postings often include information about the specific skills and qualifications required for a role, which can show you the challenges and pain points that companies are facing. By analyzing job postings for common requirements, sales teams can better understand the specific pain points that potential customers are experiencing and tailor solutions accordingly.
- Monitor customer activity. By tracking job postings from existing customers, sales teams can gain insights into their customers' growth plans and hiring needs and identify potential upsell or cross-sell opportunities.
Coresignal's data expert and head of the sales team, Martynas Simanauskas, also considers job posting data the most effective dataset for detecting B2B buying intent.
Job posting data is especially valuable for identifying buying intent. Using it, you can pinpoint what technology is being used within the organization, what technology the organization plans to start using, etc. Employee data can also be used for similar purposes.
Martynas Simanauskas, Coresignal’s data expert
Is personal contact data crucial to the B2B sales intelligence process?
Contrary to the common belief, contact data isn’t necessarily as important in B2B sales as it may seem. The most important thing is to identify the company with potential client qualities. After all, even if you unexpectedly contact someone on their home number or email, it’s highly unlikely that they will be interested. Furthermore, it’s not very ethical.
Contact data is not crucial to the whole B2B sales process as it depends on the platform and way of connecting with your potential customer. The first and most important part is identifying precisely which company could be the next potential buyer.
Martynas Simanauskas, Coresignal’s data expert
Conclusion
In conclusion, using B2B sales intelligence data can help you increase sales and better understand your customers' needs and preferences. By gathering and analyzing relevant business data, you can determine potential clients' pain points, understand industry trends, and target the right prospects with a personalized approach.
