Rethinking Demand Generation to Scale a B2B Business

Artificial IntelligenceB2B Demand Generation

According to IDG, 61% of B2B marketers say increasing demand is the top challenge they face today. Intuitively this makes sense, considering that B2B companies achieve growth when salespeople have access to larger and higher quality pipelines.

In theory, scaling a business requires just boosting demand. In actuality, however, demand generation is becoming an increasingly difficult challenge for B2B marketers to meet.

On the one hand, buyers are becoming much savvier. According to Forrester, 74% of business buyers conduct half their research independently online before making a purchasing decision. That means buyers are becoming more sophisticated, and are less willing to speak with salespeople. 

Instead, buyers want to educate themselves about their options using free resources provided by B2B companies. Only when they’re close to making a purchasing decision are buyers willing to speak with a salesperson.

On the other hand, sales teams are becoming much more sophisticated and are asking more of demand-generation teams. Sale team wants highly qualified leads that will efficiently convert to closed-won revenue. They are hesitant to invest time in less-qualified leads.

Demand-generation teams, then, must generate demand from more discerning buyers while satisfying greater internal expectations from sales and leadership. For demand-generation teams to be successful, they will need to consider new solutions that identify and deliver top prospects at scale.

Today’s Demand-Generation Strategies Are Outmoded

Today, most demand-gen teams employ a mix of inbound and outbound marketing strategies to generate demand. Inbound marketing can be effective, but it can also be time-consuming, costly, and slow to show a real return on investment. Plus, inbound marketing provides sales teams less control over the kinds of leads that request more information.

Teams interested in a faster or a more targeted strategy often opt for outbound demand generation. This approach often involves cold calling a list of contacts. These lists are expensive and frequently filled incorrect contact information.

Moreover, scaling an outbound demand-gen team requires significant hiring increases and thus higher operating costs. So generating a good return on investment from this move becomes much more difficult.

Salespeople Need Better Leads, Not More Leads to Scale

It’s a common refrain among experienced heads of demand generation: “The sales team needs more leads, or we won’t hit our revenue goal.”

In theory, this might be correct. If the demand-generation team provided more leads, assuming the conversion rate from prospect to customer stays the same, then the sales team will hit the company revenue goal, assuming it gets enough new leads.

But there is a better way to do demand generation and sales: Generate better, more qualified leads instead of just producing more leads. A demand-gen team able to generate fewer leads of higher quality is doing the entire company a favor. Cutting out low-quality leads reduces inefficiency and the time and unnecessary expenses of sifting through unqualified leads to find gold.

Jason Lemkin, the co-founder of EchoSign and founder of SaaStr, says that the difference between the top 1 percent of salespeople and the top 10 percent is in how they spend their time. The top performers consistently spend their time working the best leads, while second-tier performers divide their time more evenly over less-qualified leads.

By increasing the quality of the leads provided to sales, the demand-generation team can elevate the performance of the entire sales team, meet higher revenue targets, and boost return on investment. It’s a win-win for everyone involved.

Artificial Intelligence Is Revolutionizing B2B Demand Generation

The best demand generation strategies work backward from an ideal customer profile. Typically, companies build these profiles painstakingly by speaking with past customers or highly qualified prospects. Even when companies create an ICP, however, the results are less than scientific, so you need to review them constantly to ensure that the findings are in line with reality.

Thanks to artificial intelligence (AI) tools like the demand-generation platform developed by LeadCrunch, it’s now far easier to identify ideal prospects. These tools streamline and speed the identification prospect cost-effectively.

In most cases, demand-generation managers have access to basic prospect information. Sometimes this information can be appended using a third-party platform, but even so, the data is limited and can be inaccurate.

Also, thanks to machine learning, demand-generation platforms based on AI have the ability to analyze offline indicators associated with a company’s best-performing prospects. These indicators include firmographic and demographic data, like company size, industry, and location, the tech stack the company is currently using, and the social signals a prospect is unknowingly transmitting online.

Today, the best demand-generation teams are focusing AI tools on internal data to create a living ideal customer profile based on internal and external indicators. Then LeadCrunch’s tools scour the web to find prospects who fit this advanced profile.

Consider the following example. Traditionally, an enterprise-level B2B company relying on inbound marketing will have a few pieces of data about a prospect and will append this data with tools like Datanyze or

This new way of working uses outbound demand generation principles that target specific high-value prospects. They’ve sent buying signals and already use software that indicates need and budget. Plus, they work in industries that companies have already penetrated.

The modern way of generating demand based on artificial intelligence is more efficient and more cost effective than either traditional inbound or outbound demand generation.

The Last Word: Scaling Requires Disrupting

For readers searching for a solution to boost demand-generation to the next level, the answer lies in disrupting existing processes instead of simply doing more of the same and expecting a better result.  A demand-generation strategy that identifies verifiable buying patterns and then provides leads featuring similar characteristics is the future of demand generation best practices.

Building a demand-generation process that relies on AI technology will help to scale demand generation while providing sales teams with higher quality leads. This process reduces the time spent sorting through unqualified leads, makes it easier for B2B businesses to hit ambitious revenue goals, and boosts return on investment.