Evolution of B2B Data and Why Marketers Need Personalized Data

B2B data
Bespoke Data
Data Collection
Database Alternatives
Data for Prioritization
Scraping data
June 11, 2024

Knock, knock. Who’s there? If we go back to the early 1900s, it was likely a door-to-door salesman who drove around town looking for the ideal customer. Back then, that usually meant stumbling upon an expensive neighborhood where he could recalibrate pricing and packaging in real-time. Fast forward to today, and you’ll see companies leveraging digital data to identify their ideal customers while customizing pricing or packaging based on their past purchase history or willingness to pay. History really does repeat itself. But, how’d we actually get here? How’d we go from door knocking to using marketing automation and B2B data? Where is B2B data headed next? First, we have to look at the history of B2B data, from door knocking to web scraping and how easy access to standardized data is causing the push towards hard-to-find personalized and custom data.

The Phone Books: Moving from Door Knocking to Cold Calling

Phonebook was a major revolution to modern-day sales? With its official launch in 1878, the phonebook was the precursor to the B2B data industry, enabling consumers to make appointments or find friends’ numbers. Beyond consumer use, now salesmen could sit at desks and call up potential customers rather than slugging their supplies around town. By 1910, America’s telephone books were keeping track of 7,000,000 phone numbers. It was the very first set of standardized data – first name, last name, phone number. The phonebook kept getting bigger and bigger…but organizations weren’t getting smarter. While phone sales allowed more volume with access to millions of records, it didn’t allow for prioritization. Companies needed more than just this single source of data. They wanted their own databases that were customized to their business needs and where opportunities could be ranked and prioritized based on a certain set of characteristics.

The Call Centers: Collecting “Custom Data” Through Call Centers

With the increasing adoption of dialing for dollars, the B2B data space underwent a transition from data scarcity to data abundance. Sales organizations couldn’t possibly call every phone number and needed a way to easily prioritize and qualify opportunities without wasting their team’s time.This paved the way for outsourced B2B call centers, which were tasked with calling into businesses and gather custom data and ask a series of personalized qualification questions. Outsourcing this work to call centers meant that the organization would now have access to lists of companies that matched their qualification criteria. Individual reps could then call into these businesses themselves and have more informed, personalized conversations. The use of call centers to produce data led to capturing new data points such as intent to buy, information around past purchases, sub-industries and much more. Some of this data began to get modeled for comprehensive coverage. It was easy to provide your custom data requirements to a call center and have them call into businesses and acquire it…over time. Some of the largest data companies of this period used call centers. However, call centers had one major deficiency. They circled around a manual one-to-one process that was too labor-intensive, time-consuming, expensive, and ultimately inefficient. It was only a matter of time before they gave way to a more efficient and scalable process of data collection.

The Internet: Scraping the Web for B2B Information

Then, the late 1980’s and early 1990’s computer boom happened and every company and individual started to come online. Now decision-makers could be reached over email and phone. The rise of the personal computer and internet also brought about the rise of the CRM – which allowed organizations to easily store, update, and manage data of their customers and prospects. Now all companies, big and small, needed data to fill up their CRMs. The B2B data industry needed to switch gears and adapt to these changing times. The initial wave of these high-tech B2B data companies scraped the web for standard data to re-create the phone directory, but using a much more scalable method. They churned through billions of web pages looking for people and company-related information. The next wave of B2B data companies scraping the web looked beyond the basics by exploring job posting and user behavior to re-create some of the custom data around past purchases and intent to buy. Such data was already available using call centers, but the use of web scraping caused a dramatic increase in volume. This caused a wide abundance of data and data related companies resulting in a lower unit price per record and increased efficiency for sales & marketing organization. This abundance of data ensures that even smaller companies take advantage of the efficiency that came from using B2B data. Five years ago, access to accurate company and contact data was coveted. It seriously changed the game — and it came with a hefty price tag. Organizations realized knowing things like the number of employees, estimated revenue, direct dial number of the decision-maker, etc… gave them a competitive advantage. It was worth investing in access to millions of records they could have only dreamed about a few years before. Today, access to standard B2B company and contact data that once provided a competitive advantage is now simply table stakes. If you don’t have it, you’re nearly guaranteed to lose. If you do have it…well, in today’s world, you’re not necessarily guaranteed to win. Why? When everyone has access to something, it no longer provides a competitive advantage. It becomes the new baseline. Everyone has access to millions of records at the click of a button. Today, organizations are drowning in data when, just ten years ago, there used to be a drought. As a marketer, how do you gain back that competitive advantage? It’s about finding the signal through the noise. It is, and always has been, about prioritizing the right prospects and finding those niche pockets of an audience that are interested in your offering. Don’t chase the mainstream, chase the future.

Personalized & Custom Data: From Standardized Data to Custom Curation

The internet is like a vast phone book but with tens of thousands of data points about customers and prospects. Websites talk about their product line, team members, and press announcements. Job postings offer insights into the technology they are using and their strategic intent. Media outlets provide insights into revenue and customer counts. And this is just the start of the data available. Custom data is what cannot be found in a traditional phone directory, company website or a Linkedin record. Access to custom data is the new competitive advantage that enables organizations to think strategically about planning, prioritizing, prospecting, and permeating organizations.

The realm of B2B sales and marketing is increasingly recognizing the limitations of one-size-fits-all solutions offered by large contact and company data providers. While these sources are invaluable for obtaining basic contact information and company demographics, they fall short when it comes to delivering the nuanced, personalized data that can significantly enhance targeting and outreach strategies. Custom data, tailored to the specific needs and contexts of your business, emerges as a critical asset in this landscape, offering a level of depth and relevance that generic datasets simply cannot match.

But what does custom data entail, and how can organizations identify the specific types of data that will most effectively drive their sales process and business growth? Custom data is essentially information that has been meticulously curated or generated to align with the unique aspects of a company’s target market, sales strategy, and overall business objectives. This kind of data offers precise insights that are directly applicable to the company’s products or services, facilitating a more targeted approach to prospecting and customer engagement.

Here are a few illustrative examples of how custom data can be leveraged across different industries to prioritize and tailor outreach efforts:

  • Point of Sale (PoS) Companies Targeting Restaurants: For a PoS company aiming to expand its footprint in the restaurant industry, custom data might include metrics such as average order size, operating hours, service types (e.g., dine-in, takeaway, delivery), and cuisine types. Such detailed insights enable the company to tailor its value proposition to the specific operational needs and customer profiles of each restaurant.
  • E-commerce Software Vendors: An e-commerce platform provider might prioritize prospects based on the number of Stock Keeping Units (SKUs) they manage, average product price points, and the presence (or absence) of an integrated shopping cart system on their websites. This custom data helps the vendor identify e-commerce businesses that are most likely to benefit from its software solutions, based on their scale and complexity.
  • Cloud Storage Solutions for Hospitals: In the healthcare sector, a cloud storage company looking to serve hospitals could benefit from custom data such as the number of hospital beds, the size of the technical and IT staff, IT budget allocations, and the contact details of tech purchase decision-makers. This information allows for prioritization based on the potential volume of data storage needs and the likelihood of a hospital’s readiness to invest in cloud storage solutions.

Unlike generic B2B data providers, crafting and utilizing custom data requires a partnership approach, where the data provider works closely with the organization to identify, collect, and analyze the specific data points that will most effectively inform and support their go-to-market (GTM) strategies. This collaborative process not only ensures the relevance and applicability of the data but also empowers organizations to innovate in their marketing and sales efforts. Creative marketers can leverage these personalized data fields to conduct GTM experiments, test new market hypotheses, and refine their targeting approaches based on real-world feedback and outcomes.

In essence, the transition towards custom data represents a strategic move away from broad, undifferentiated marketing and sales tactics towards a more focused, data-driven methodology. By pinpointing exactly what data is needed and understanding how to apply it effectively within the sales process, organizations can achieve a competitive edge, making more informed decisions and engaging their target markets with unprecedented precision and insight.

LeadGenius: Data vendor for the creative marketer

LeadGenius realized that companies need this custom data to get ahead and stay ahead. It’s why we build personalized information extraction tools and teams to collect data individually for every project, a stark difference from the one size fit all datasets. Understanding what custom data an organization needs typically starts with strategic meetings where last-mile knowledge or the information reps use to prioritize and close deals, is extracted. From there, we look at how we can deploy technology and teams to uncover or model this data. From uncovering total available markets to creating ABM lists based on special characteristics, our team and technology have helped leading organizations succeed. Gathering personalized data has always been critical to success — LeadGenius has just figured out how to do it more efficiently. But… what comes next?

The History of B2B Data: From Customization to Always On Signal Tracking

an always-on, dynamic future. Initially, organizations relied on bespoke datasets tailored to their specific needs, identifying key buying indicators to pinpoint the most promising opportunities. This approach, while revolutionary at its inception, posed questions about depth and responsiveness. How can businesses transition from merely reacting to market signals to actively anticipating needs? When is the precise moment for engagement to ensure maximum impact? And how can companies maintain a pulse on their target accounts throughout the sales cycle to enrich conversations with continually updated insights?

Historically, B2B data has been characterized by its static nature. Updates to CRM systems were infrequent, and the refresh of records occurred sporadically, at best quarterly. This rhythm is increasingly misaligned with the rapid pace of today's business environment, where timing and context are not just advantageous but critical for success. The static nature of traditional data management fails to accommodate the dynamic shifts within target organizations—shifts that could significantly affect sales strategies and outcomes.

Recognizing this gap, LeadGenius is at the forefront of pioneering a transformative approach: the Dynamic Signal Tracking (DST) system. DST represents a leap towards an always-on model of data management, where updates are not just periodic but instantaneous. This system ensures that custom data—once a static, occasionally updated snapshot—becomes a living, breathing entity, continually refreshed to reflect the latest developments within key accounts.

Dynamic Signal Tracking encompasses a wide array of signals, from the employment changes of decision-makers and engaged prospects to hiring trends for pivotal roles and shifts in resource allocation or spending. These signals offer a real-time glimpse into the operational and strategic evolutions within target companies, providing sales teams with a powerful tool to not only stay informed but to anticipate and react to opportunities with unprecedented speed and relevance.

The shift towards DST negates the need for periodic, large-scale data projects by providing organizations with an always-on stream of customized data. This stream is perpetually updated, ensuring that sales and marketing teams have access to the most current and actionable insights. The result is a sales process that is not only more efficient and effective but one that is capable of engaging prospects with a level of timeliness and contextuality previously unattainable.

This evolution from customization to always-on signal tracking marks a pivotal moment in the history of B2B data management. It heralds a future where data's static past is replaced by a dynamic, continuously updated present, enabling businesses to engage with their target markets and individual prospects in ways that are more meaningful, timely, and impactful. As LeadGenius moves forward with building this future, the promise of transforming the landscape of B2B sales and marketing becomes increasingly tangible, setting a new standard for how businesses approach and leverage data in their growth strategies.

Similar Articles