How to Use Data for Better B2B Sales Prospecting: A Practical Guide

The new B2B sales prospecting paradigm

In old school sales outreach, companies would buy lists of leads and cold call down the list (“dialing for dollars”). Growth came from hiring more sales staff, and the secret weapon was a high paid, well-connected sales rep. 

In the new way, we use data and AI to identify the most highly qualified targets, to understand what will resonate with those audiences, and then to engage in a relevant, multi-channel way. In this approach, the secret weapon is better data and better intelligence. 

Fortunately, the industry is recognizing the need for change. With email clients becoming more adept at filtering spam, there’s a growing emphasis on quality in prospecting efforts. Starting February 1st, Google will be imposing stringent requirements to curb bulk sales prospecting, especially from sellers using sales engagement platforms to send more than 5,000 emails a day. Specifically, senders will need to keep their spam output below 0.3 percent, and follow other rules around unsubscribing and authentication. The goal is for people to receive fewer prospecting emails, and for each one to be more relevant, more engaging, and thus, more valuable.

This evolution sets the stage for a new era in B2B sales prospecting — one that underscores the imperative for quality over quantity, one where data becomes more critical than ever, serving as the foundation of a smarter, more effective prospecting strategy.

As we navigate through this landscape, let’s explore how data helps us reach out with relevance and precision to unlock more B2B sales pipeline by:

1. Precisely targeting the right accounts, buying groups, and individual people
2. Crafting more personalized and more relevant messages

Use data and predictive analytics to precisely target the right accounts, buying groups, and people

Precision in B2B prospecting strategies is crucial to the new approach, and precision comes from meticulous data, enhanced by artificial intelligence, that enables us to target our outreach campaigns with unmatched accuracy. When done right, this approach ensures that our messages not only reach the right organizations but also resonate with the individuals who have the power to make decisions.

The key is to recognize that, according to the Ehrenberg-Bass Institute, only 5% of B2B buyers are in-market to buy at any given time. This means 95% of the companies you want to prospect to are not looking to make a purchase. The old model would attempt to “challenge” them to get them to move into a buying cycle, but today’s buyers increasingly want to do their research on their own time using self-service channels — not a conversation with a sales rep. 

So the sensible strategy is to focus your sales outbound efforts on high-intent accounts that are most likely to turn into opportunities. And this is where data plus AI shines, letting you look at past opportunities and activity patterns and identify the accounts that are showing similar behavioral patterns. 

Going deeper, you want to not only identify in-market accounts, but also the specific B2B buying groups inside the enterprise — and what products or solutions they are looking for. This involves understanding the roles, responsibilities, and decision-making authority of each individual member of the buying committee. In the past, this was a time consuming, manual effort. In today’s world, cutting-edge, generative AI can sift through millions of data points, leveraging vast databases of B2B contacts, enriched with intent, advertising, and engagement data, to generate dynamic B2B buying groups with members identified, roles and personas assigned, and new contacts recommended.

By using account intelligence, you can focus your B2B prospecting efforts on the key decision makers at ICP accounts that are actually in-market and looking for potential solutions. By narrowing down the list, you can then afford to be more personalized and relevant in each interaction (see the next section) — and the combination drives dramatic improves in prospecting efficiency.

Crafting more personalized, relevant messages using data

Buyers today are overwhelmed. Even if they are in-market for your solutions, they’ll still reject anything uninteresting, hit “SPAM” on emails that smell like sales, and ignore your cold calls.

None of that is a good experience. But a meaningful, relevant interaction driven by rich account intelligence is. 

The Salesforce State of the Connected Customer report states that 84% of business buyers are more likely to buy from a company that demonstrates an understanding of their business goals. And ITSMA studies show that 75% of executives will read unsolicited materials if relevant to their business, but the key here is that it must be relevant — which means it reflects:

• Knowledge and understanding of the industry 
• Understanding of the account’s unique business issues 
• Fresh ideas to advance the business

To deliver fresh ideas based on knowledge and understanding of an account’s industry and unique business issues, your team needs good data and account intelligence — and then they need to use it to craft more personalized outreach. In fact, data from McKinsey & Company shows that personalization reduces acquisition costs by as much as 50% and increases revenues by as much as 15%. At Demandbase, our sales team achieves considerably higher results from personalized outreach than generic; we find the extra effort increases open rates from 29% to 53% and replies from 4.5% to 10%

The goal is to make sure the prospect feels the email really is written to him or her, as an individual who works at a specific company. That’s not a trick, it’s the truth (if not, you’re doing it wrong). If you can swap out basic variables, such as name and company, and then send the email to someone else, then you probably have “robo-spam.”

So leveraging data to craft personalized and compelling content is crucial in B2B prospecting. 

Essential data for B2B sales prospecting

Now that we see WHY data is critical, let’s look at WHAT data types are most useful for B2B sales prospecting.

Firmographic Data: Segmenting and targeting

Firmographic data is crucial in segmenting the market and targeting specific groups. It includes critical details like company size, revenue, industry, and location. By analyzing these aspects, you can find accounts that match your ideal customer profile and create segments that are not just broad categories but meaningful clusters of prospects with similar characteristics. This granular segmentation allows you to craft messages that resonate with the specific challenges and aspirations of each group, making your outreach efforts more relevant and effective.

Account Hierarchies: Navigating corporate structures

The largest accounts often have multiple divisions, each with sub-accounts. For example, The Walt Disney Company has divisions that include Studio Entertainment, Parks & Resorts, Media Networks, and Consumer Products & Interactive Media. Prospecting to global enterprises requires understanding these account hierarchies, allowing sales teams to strategically navigate complex business relationships to land, and expand, customer relationships.

Contact Data: Personalizing outreach

Contact data is the bedrock of B2B prospecting. It includes essential information such as names, job titles, email addresses, and phone numbers. This data is pivotal in tailoring your communication to the individual, going beyond generic messages to create a dialogue that speaks directly to the prospect’s role, interests, and potential needs. By understanding who you are reaching out to, you can adjust your tone, language, and content to align with their professional profile, enhancing the chances of engagement and response.

Technographic Data: Tailoring messaging to technology needs

Technographic data sheds light on a prospect’s technological environment, including their current software and tools, the complexity of their tech stack, and their patterns of technology adoption. Our AI models at Demandbase show that for many technology companies, this information is the top predictor of accounts in a company’s ideal customer profile. Technographics are also invaluable for creating messages that are not just relevant but also contextual. For instance, understanding a prospect’s current tech stack can help position your product as a complementary solution or an upgrade, making your value proposition more relatable and compelling.

Intent Data: Identifying active researchers

Intent data is an indicator of an account’s current level of interest in your company or category. It uses artificial intelligence to track online activity and uncover the topics that companies are actively consuming across the web. Baseline levels of interest can show an account is a good target for you; and upward trends in interest levels can indicate an account is actively seeking solutions, allowing you to reach out to them with timely and relevant information. 

Engagement Data: Refining follow-up strategies

Engagement data involves tracking how prospects interact with your content and communication channels. By analyzing metrics like email open rates, click-through rates, and website engagement, you can gauge a prospect’s interest level. This data helps you refine your follow-up strategies, focusing your efforts on those who are most engaged and thus more likely to convert. It ensures that your resources are invested in nurturing the most promising leads.

Journey Stage: Aligning your message to their experience

​​A company’s stage in their account journey is the single most important piece of information for a relevant account experience. Knowing where the account is in its journey gives you clues about when and how you should engage. Early-stage accounts aren’t interested in hearing about your products or being sold to. Late-stage accounts want help comparing vendors, validating their thinking, and building consensus. Knowing when an account is an in-market marketing qualified account is critical to knowing the right time to engage. 

Social Connections: Getting warm referrals

In B2B prospecting, leveraging social connections and referral networks is about creating trust and credibility. Analyzing social connections can reveal mutual contacts and shared interests, offering a pathway to warm introductions. These connections often lead to more fruitful engagements, as prospects are more receptive to communications coming through a known or trusted source. The strategic use of social data enhances your ability to connect with prospects in a more personalized and effective manner, complementing the analytical approach of data-driven prospecting.

Wrapping it up

The transformation in B2B sales prospecting is clear: a shift from the traditional, volume-based approach to a more refined, data-driven strategy. This evolution focuses on quality engagements over quantity interactions. It emphasizes the critical role of data in understanding and targeting potential clients, enabling you to engage at the right time and craft personalized, relevant, and impactful communications. By using data and AI to identify and engage with the most promising prospects in a way that is both efficient and effective, this approach promises not only better results but also a more rewarding and meaningful experience for both sellers and buyers in the B2B space.