Benefits of Data-Driven B2B Prospecting
The first step to data-driven b2b prospecting is understanding the way your prospects are linked to one another. This could be based on ownership, personal relationships, or even payments from one company to another. Rich datasets allow you to identify new opportunities based on specific information about your prospect or the ecosystem within it. These are only a few of the benefits of data-driven b2b prospecting.
Predictive Purchase Data
For B2B prospecting, predictive purchase data can help guide sales strategies and improve team efficiency. The data can also lower operating expenses and increase return on investment. Moreover, validated results can help marketers gain buy-in from team members. It is essential to understand what exactly B2B prospects are looking for before creating a marketing campaign. Here are some key factors to keep in mind while using predictive purchase data.
Traditionally, retention marketing was focused on pursuing customers who had already converted. However, new paths to purchase are changing the dynamics of this strategy. To gain the trust and loyalty of your customers, you must meet them at a stage in their journey. For example, you can target your audience on social media – Instagram users are likely to have already checked out your content and saved posts. These users are your prospective customers. In order to build a strong relationship with these people, you can focus on audience development rather than counting traffic. However, the value of predictive prospecting lies in people.
Personalization of Sales Messaging
The use of company data to personalize sales messages can improve a company’s sales strategy. While data about target companies can help a company determine whether it should engage with a given prospect, a sales message should always be personalized based on the needs and desires of the prospect. Data can help companies create meaningful customer profiles and improve their overall hit rate. A recent guide published by HubSpot explains how data can be used to personalize messaging.
Using data about a lead’s behavior and interests can help a company personalize offers to each person. For example, it can gather information about a lead from open sources like their website analytics, and previous deals with the same lead in a CRM. The best way to personalize offers is to create a B2B buyer persona and determine what each customer needs.
Using company Data to Identify Prospects
Using company data to identify prospects in a broader B2B prospecting effort can yield significant benefits. By using firmographic data from company websites, social media profiles, and other available information can help you refine your offerings and spot trends. Data such as revenue, size, and industry can help you classify prospect companies into specific segments based on shared pain points and characteristics. By using such data, you can create personalized prospect profiles and tailor your messages accordingly.
Using company data to identify prospects is a great way to anticipate customer needs and formulate a value proposition before contact. Prospects will be more likely to convert into customers if they feel the company has solved their pain points and can drive profitability. To stand out in the competitive B2B landscape, personalization is key. Using company data to identify prospects can give your sales team the information they need to make a tailored pitch.
Adoption by Sales Teams
Without a clear roadmap, it is impossible to determine which aspects of your business convert prospects to paying customers. Another common barrier to adoption is data management. To effectively prospect and follow-up with prospective customers, you’ll need a wealth of contact and company data. By leveraging data-driven sales strategies, your team will be better able to support each stage of the sales funnel.
For example, if a sales team wants to target a decision-maker, it may be more effective to contact an entry-level employee of the buyer first, rather than a mid-level one.
