Company data is essential in both Account and Lead Scoring practices.
In this article, you’ll learn
- what is account and lead scoring
- why it’s beneficial to use company data in lead scoring
- how to plug Vainu data in your lead scoring models
What is Account and Lead Scoring?
Lead scoring ranks contacts based on their likelihood of becoming a customer. It’s about prioritizing your most qualified leads based on various characteristics, e.g., their role, the industry or company’s size, or the behavior they’ve exhibited on your website.
Account scoring is the process of sorting all the potential customers in an order from the most to the least valuable, i.e., prioritizing your saleson the companies most likely to convert. Account Scoring takes into account company-level data points and the various roles involved in making a purchase decision.
In both account and lead scoring, you must decide which factors increase the likelihood of a prospect to turn into your customer, and then these attributes should be weighted more heavily. Variables used in account scoring often affect lead scoring, and, concurrently, variables used in lead scoring affect account scoring.
Why use company data in lead scoring?
Especially in B2B, using company information to qualify leads is a pretty smart move as many factors affect the decision to buy: the financial situation of the company, the company’s strategy, stakeholders’ opinions, technologies already in use, and future events, for example. When you prioritize your leads only based on contact level information, you may end up focusing too heavily on highly engaged contacts in poor-fit companies and miss out on those with lightly engaged contacts but with a current need.
Adding account-level information to your lead scoring models will help sales and marketing spend resources more efficiently. You can focus your sales and marketing efforts on the accounts that have the highest probability of converting, buying more, or churning right now. You can do this by combining internal data with Vainu’s company information.
Here’s an example of two sales directors from separate organizations:
(1) The first sales director is very enthusiastic about your product, goes through all your content, attends several webinars, downloads eBooks, and requests a demo. Based on lead scoring, it’s a perfect match! However, his organization is currently going through layoffs, pulling out from international markets, and has no budget to spare. Despite the excited sales director, there’s little chance of a deal anytime soon.
(2) The second sales director is aware of your product but has only subscribed to your newsletter. However, his company is actively investing in web technologies, hiring new employees, and has emitted buying signals announcing new markets, product launches, and new head of sales. The second sales director isn’t THAT excited, but investing in the product makes much sense for their organization.
How to plug Vainu data in your lead scoring models?
A simple way is to build an Excel and manually weigh the different criteria. A more advanced method is to use artificial intelligence and a combination of internal, behavioral, and company data.
Start by creating an Ideal Customer Profile
At Vainu, we rely on a framework called Ideal Customer Profile (ICP) to draw a picture of a customer that is a perfect fit for us. The estimated value of an account is equal to the proximity to your ICP, i.e., a customer that receives the most value out of your offering. Creating either one or several ICPs is a prerequisite for applying company data to your lead scoring scheme.
A great starting point for creating a top-notch ICP is to look at your current client base and see what they have in common. You can use, e.g., Vainu Analyzer for this purpose.
Once you have analyzed your customer base, you must decide, which factors will increase the likelihood of a company to turn into your customer, and then these attributes should be weighted more heavily.
The process in practice
In Vainu, there’s a vast amount of data points you can utilize varying from basic company information, e.g., industries, location, age, or size, to more sophisticated factors, e.g., online technologies or buying signals.
For us at Vainu, the factors increasing the score are, e.g., certain technologies the companies are using, such as Pipedrive, HubSpot, Dynamics, or Salesforce, since Vainu integrates with all these CRMs. We ask, for instance, “which CRM your company is using?” on our landing page forms. Furthermore, companies matching our ICP actively invest in web technologies or hire new salespeople. There’s a new head of sales or other relevant buying signals, such as announcing new market entries, product launches, or received funding.
However, the most critical data point for your company may be geographic location, e.g., a particular city, state, country, or specific industry. Here's how the system can work in practice:
- A new person converts into your marketing automation tool. You can use Vainu data to shorten your lead capture forms and subsequently increase conversions!
- Integrate Vainu with your marketing automation tool, and Vainu will match the lead's email domain (e.g., @spotify.com) to a company in its database. This way your leads can be automatically enriched with business-relevant data points: company name, industry, size, key technologies used, you name it.
- A new lead can be scored based on contextual, behavioral, and company data enabling you to improve personalization across different channels, such as emails, phone calls, websites, and ads.
- Variables used in account scoring can affect lead scoring and, concurrently, variables used in lead scoring can affect account scoring. For instance, the number of individual contacts of a company, or the last visit from a contact associated with a company, can be variables in account scoring even though they are actions of an individual. Simultaneously, the number of employees, the CRM system in use, revenue, and location can be attributed to lead scoring even though they are related to an organization.
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💬 If you want more information regarding Lead or Account Scoring, write us in the chat or email us at email@example.com.