Generating Inquiries for New Brands and New Businesses in BtoB — An Integrated Design of Lead Generation and Nurturing Starting from Research

The starting point of design is not the selection of initiatives, but understanding customer purchasing behavior through research. The research referred to here is not limited to organizing target attributes such as industry and company size. The objective is to understand the behavioral structure of "how customers purchase."

Even for BtoB service offerings, for example, the purchasing flow differs completely between "customers and deals that plan budgets in advance and compare multiple vendors" and "customers and deals that immediately look for a vendor in response to an urgent issue." The former gather sufficient information through web searches and industry publications, obtain comparative quotations, and proceed to internal approval. The latter omit most of the consideration process and decide based on response speed and technical fit. The information they value, the touchpoints they use, and the perceived distance to making an inquiry are all different.

To grasp such differences, research should cover four perspectives.

First is the overall picture of the purchasing process—who initiates, who compares candidates, and who makes the final decision. Visualizing this flow clarifies when and to whom information should be delivered.

Second is information needs at each stage—at the initial stage, customers often seek to understand "what options exist in the first place," while at the comparison stage they seek concrete information such as "track records and post-implementation effects."

Third is identifying information touchpoints—clarifying where customers gather information, including web searches, industry media, exhibitions, consultations with acquaintances, and information discovery via generative artificial intelligence.

Fourth is the decision-making structure—the content and granularity of information required differ between frontline staff who assess technical fit and executives who question return on investment.

Each of these four perspectives becomes a concrete starting point for initiative design. When the purchasing process is visible, the timing for initiatives is determined; when information needs are understood, content direction is defined. When information touchpoints are clarified, the rationale for media selection is obtained, and when the decision-making structure is understood, it becomes possible to differentiate information for initiators and decision-makers. While the purpose of research is to "understand customers," more specifically, the true aim is to "obtain starting points for initiative design."

Furthermore, research results directly inform content design and media selection. For example, customers who gather information using both web searches and industry media require different touchpoints and content granularity than those who first consult acquaintances or business partners. In addition, because the "concrete picture of issue resolution" sought by initiators and the "basis for investment decisions" sought by decision-makers differ in nature, it is necessary to differentiate information even along the same journey. Such design also becomes a prerequisite for collaboration with the sales department. The higher the resolution of purchasing behavior obtained through research, the greater the accuracy of handoff from marketing to sales, and the quality of decisions such as "at what stage to pass leads to sales" also changes.

Research only gains meaning when it is converted into concrete design requirements such as content design, media selection, and criteria for sales connection, rather than ending with "understanding" customers. Lead generation methods and models are built through this conversion process, and this is not an area where simply applying general methodologies will produce results.

For example, in designing BtoB marketing for robots and industrial machinery used in factory automation, it was found that customer purchasing behavior differs significantly depending on whether the customer has a specialized department considering automation (Figure 1). Companies with specialized knowledge narrow down candidates on the web before making inquiries, whereas companies without such departments do not know what criteria to use and begin with consultation. For the former, web-based information development—such as detailed product specifications, technical comparison content, and case studies—was key, while for the latter, interactive approaches such as seminars and individual consultations were effective. Even for the same offering, effective lead generation methods change fundamentally depending on organizational structure and knowledge level. Such differences cannot be seen without research.

Once the To-Be customer journey has been drawn, the next phase is to select and place specific initiatives. What should be kept in mind here is not to frame inbound initiatives and outbound initiatives as a binary opposition (Figure 3). Inbound initiatives that guide customers to the company in line with their thinking and exploration behavior and outbound initiatives that proactively reach customers whose issues or objectives have already become explicit differ in effectiveness depending on customer state. Therefore, it is important to combine the information the company wants to convey with purchasing characteristics and processes, while considering customer state and status. In addition, when digital advertising as an outbound initiative is not used due to budget constraints, issues arise such as the inability to secure sufficient touchpoints and distribution volume, making it difficult to verify initiative effectiveness.

To avoid such situations and make maximum use of customer data, ABeam Consulting supports advanced marketing through artificial intelligence personas. This will be introduced on another occasion.

When customers are actively searching for information, inbound approaches—such as search engine optimization, content marketing, white papers, and public relations—tend to be effective. On the other hand, when targets are clearly defined and customers have not yet strongly recognized issues, creating touchpoints through outbound approaches such as direct mail, seminars, and exhibitions may be more appropriate. Decisions on which initiatives to place at which stage are examined based on the information touchpoints identified through research.

By organizing the roles of initiatives along customer interest stages, the overall picture becomes clearer. In the initial awareness-building stage, stimulating interest through public relations and advertising is central. In the information exploration stage, search engine optimization and content marketing play a major role in exposing customers to the company’s information. In the comparison stage, white papers and case studies function as decision materials, and just before inquiry, direct dialogue at seminars or individual proposals can provide the final push. In this way, the allocation of inbound and outbound roles changes by stage. There is no single correct answer, as which stage to emphasize differs by offering and market environment. What is required is the perspective of identifying at which stage the company’s customers tend to stagnate and concentrating initiatives there.

In addition, the flow of initiatives does not necessarily proceed in a single direction. There are cases where the first touchpoint is created through outbound initiatives and, once interest emerges, customers are guided to inbound content. There are also back-and-forth movements, such as customers entering through web-based information gathering, participating in a seminar, and then returning to the web to research details. Customer behavior is not linear, and may move back and forth depending on rising interest or changes in internal circumstances. Flexible journey design that can respond to such movements is required.

It is also important to organize the concept of placing appropriate information at each information touchpoint used by customers. Respond to customers who search with search engine optimization and content, reach those who read industry media through public relations and article advertising, and engage those who value face-to-face information gathering through seminars and exhibitions. Initiatives should be designed not in terms of "what to do," but "where to place what information."

Once initiatives are designed, it is also necessary to organize indicators to evaluate their effectiveness. For web initiatives, metrics such as traffic volume and content-specific page views can be considered; for white papers, download counts and subsequent site revisit rates; for seminars, inquiry rates after participation. However, tracking only individual initiative key performance indicators makes it difficult to improve the overall journey. Understanding transition rates between stages—that is, "the proportion that moved from one stage to the next"—and identifying bottlenecks becomes the starting point for journey improvement. For example, if content view counts are sufficient but do not lead to material requests, there may be issues with information depth or presentation. Such analysis functions as feedback to improve journey design accuracy.

Defining Marketing Qualified Leads is also essential. A Marketing Qualified Lead does not simply refer to a lead for which contact information has been obtained, but to a state that has reached a level of prospect readiness that sales should engage. By setting handoff criteria based on overlapping behaviors such as multiple content views and seminar participation, the goal of nurturing becomes clear and the overall journey gains direction.

The criteria for Marketing Qualified Leads should not be decided by the marketing department alone. It is important to align with the sales department on "which state of leads to hand off." Organize cross-functionally which behaviors—such as material requests, seminar participation, revisits to comparison pages, and viewing specific content—are considered increases in prospect readiness. Without this alignment, marketing feels that "the leads we hand off are left unattended," while sales feels that "leads that do not become opportunities are coming in"—and this gap in perception easily undermines the effectiveness of the entire journey. Marketing Qualified Lead definitions are not fixed; by adjusting them through operations while receiving feedback from sales, handoff accuracy gradually improves.

Ultimately, the goal is to build a lead generation model tailored to the characteristics of the company’s offerings and customer behavior patterns. Typologies such as search-driven, event-driven, named-account-driven, and content-nurturing-driven can serve as conceptual references, but which is optimal differs by customer. Even within the same industry, effective models can vary depending on the novelty of the offering, the competitive environment, and customers’ information literacy. Only through research-backed design does a truly effective model emerge.

It should also be noted that a lead generation model is not complete once drawn. For example, even if a search-driven model is assumed, in practice event-based channels may lead to higher-quality Marketing Qualified Leads. A stance of continuously reviewing the model based on execution results—examining where drop-offs occur and which information provided the push to the next stage—is indispensable. By continuing to run the cycle of "design, execution, verification, and improvement," model accuracy increases. There is no problem in initial hypotheses being incorrect. Rather, what separates medium- to long-term results is whether the organization has a system that can revise hypotheses based on execution data. It is important to build mechanisms from the early stages that feed post-launch data back into design.

In recent years, customer touchpoints have changed, with some search behaviors being replaced by generative artificial intelligence. In lead acquisition that starts from search, in addition to traditional search engine optimization–centered design, responses to AI search optimization and large language model optimization are increasingly required.

At present, traffic via search engine optimization maintains a certain share, while traffic via Google AI Overview is expanding, and traffic via generative artificial intelligence remains limited. However, it is expected that the expansion of information exploration starting from generative artificial intelligence will change the traffic structure itself.

Therefore, based on changes in customer information exploration behavior, it is important not to view journeys such as search engine optimization, AI search optimization, and large language model optimization individually, but to design them in combination (Figure 4). In other words, a shift in perspective is required—from "which channel to create touchpoints in" to "within what kind of exploration behavior the company is recognized and selected."

ABeam Consulting consistently supports the advancement of marketing while taking into account the impact of generative artificial intelligence. Specific measures will be explained separately.