“Give me a place to stand, and a lever long enough, and I will move the world” (Archimedes)

Since the recent, 2022 slowdown of the tech economy, the pressure on every B2B marketing team to build a scalable marketing spend engine has been growing intensely, where most are being asked to generate a lot more pipeline with a lot less budget. Add to those pressures changes in B2B buying behaviors and every B2B tech marketing team has to clearly demonstrate how to maximize the number of qualified leads for every dollar spent in sales and marketing and to reduce their customer acquisition cost (CAC) (sales and marketing spend / total number of customers). Given these pressures, marketing teams need to build leverage into your marketing spend … but how?  

What is leverage?

Simply put, leverage is the way to generate more and better-qualified leads out of every marketing dollar spent. Think about all the activities and spending that go into generating your qualified leads. We just mentioned several that probably take up most of your marketing budget like: Paid advertising, sponsored web content, new marketing staff, PR spend, or marketing automation software. Driving the selection of those lead sources and associated activities should be your target market and, more importantly, your Ideal Customer Profile (ICP) – those lead sources should intercept your most likely buyers where they congregate. For example, CISOs learn about new products in very different places than developers or Clinical Research Directors – your go-to-market design should reflect those differences. 

Now, most marketing teams know they have a target market to go after and need an ICP to support all the marketing activities from messaging to SEO to content build to webinar topics. The difference is how deep you go about truly understanding and defining your ICP.  More importantly, identifying attributes and data you can use in your marketing automation tools to clearly identify and evaluate your ICP and the campaigns that find and attract them into highly qualified leads.  And whether they can be gathered and used throughout your marketing journeys and funnels. It is not enough to just have a clear MBA PowerPoint presentation, but these targeting criteria need to be translated into specific attributes and filters that are externally targetable.

To paint a picture of what we mean by leverage and how to build it, imagine a seesaw.  A seesaw in its simplest form is a lever that kids (and some adults 🙂 play on. Envision the seesaw as perfectly balanced so neither side is up or down. In our example one side of the seesaw represents marketing spend and the other side represents the qualified pipeline that is to be generated. Now if you put a feather on the marketing spend side, the other side of qualified leads wouldn’t move much, would it? In other words, you wouldn’t get much leverage. Now instead of a feather, let’s drop a heavy object, an anvil for example, on the spend side. What happens? The other side shoots up representing your qualified pipeline shooting up. Great. Well, how do we get our marketing spend to act more like that heavy anvil? Let’s talk about how using a deeply detailed ICP definition turns your marketing spend from a feather into an anvil. 

Let’s look at examples of both to show the differences between a weak and less informed ICP; a feather and a well-researched, data-driven ICP that gives more granular detail for your customer persona; an anvil.

Feather vs. Anvil

Let’s build an ICP for a financial technology company selling an enterprise accounting application with the goal of generating qualified leads from our marketing content used by marketing automation tools. We can use this ICP for SEO within website content, to create blog content, to nurture with recorded webinars, and to share purchased research. 

A well-definedICP contains firmo-, demo-, techno- and psychographic data that together define highly qualified leads. Firmographic information is data on the companies you target, including company size by revenue and employees and industry category, while demographic data captures elements such function, title, seniority, education, etc. Technographic data dives a little deeper by identifying what technology your targets use that tells you something about them. For example, a company may use HubSpot for its marketing automation tool, NetSuite for its ERP, or Salesforce for its CRM. No matter what they use, knowing this information and mapping it to your closed-won deals helps build that ICP. And psychographic data gets at dimensions such as how people make decisions, are they early adopters or laggards, or how mature is their understanding of the to-be-purchased technology.

On top of these areas, you can start to add “behavioral” data. How does the company make decisions? What roles are involved in the sales cycle and what role do they play in the ultimate decision to buy or not? What activities do their marketing teams undertake if you are pitching marketing automation? What activities do their finance teams handle daily, monthly, or annually if you are pitching ERP or a finance automation platform?

Type of data	Examples
Firmographic	Company size (revenue, employees), industry category
Demographic	Title, function, hierarchy, seniority
Technographic	What is their complementary or competitive tech stack? Leverage filters that capture companies’ existing tech
Psychographic	Besides human observations, use boolean filters in LinkedIn Navigator, or apps like CrystalKnows
Behavioral	Decision-making process, roles involved in decision-making, how users perform your product’s job-to-be-done today

The problem is most marketing teams stop at the surface without diving deep into all this rich data. The critical success factor to driving scale in your marketing spend will be to collect and gather this data to paint the clearest picture possible and then combine it with your marketing automation platform.

Role/Title:

Feather example: CFO, COO, VP of Finance 

Main Issue: It’s certainly important to have the finance leadership role when marketing a financial platform. The problem here is the role is limited to leadership and it’s not clear if the C level would be the driver of a process or the decider of the budget or both. If the application solves a problem the credit manager recognizes but the CFO never sees then you may never get the lead. We need to understand what role each title plays and each role in the sales cycle.

Anvil example:

• Decision maker role is clear = e.g. CFO, SVP/VP of Finance
• Influencer roles understood = e.g. Controller, Finance Director
• User/Administrative roles know = e.g. Credit Manager

Solution: Get more clarity on each role and title and what impacts they have in the sales cycle. With his data, you can better nurture at the proper stage in the sales cycle from lead generation to a successful close. You can do this through both qualitative customer interviews and validating through quantitative surveying of Closed-Won deals.

Company Size and Industry: 

Feather example: 

Size: Small to Mid-Market companies doing $50M – $1Billion. 

Industry: Business Services, Software, Financial Services, Manufacturing, Distribution

Main Issue. Notice how broad the revenue band and industry categories are. A finance team for a $50M company most certainly will have completely different jobs to do, pain points, and problems to solve than a finance team for a $1 Billion dollar company. A finance team operating in the distribution industry certainly has different jobs to do than a Financial Services company. That’s not to say they might not have similar problems but there is most likely a better product-market fit with one or the other.

Anvil example: 

Size: Mid-Market companies doing $50M – $1Billion

Industries: Food and Beverage Manufacturing, Distribution

Solution: Get more narrow in your firmographic data. You can use data sources like Apollo to overlay against closed wins and find out the MOST likely target size and industry that has the strongest product-market fit with your offering.

Some behavioral data to include that adds more leverage:

Selling activity

1. What does ICP sell? Sells both products and services
2. Who does ICP sell to? Large enterprises
3. Does ICP Extend Credit/Send Invoices? Yes
4. How does ICP accept payments? Checks, ACH, and Credit Cards

Add more leverage by collecting technographic data from:

1. Surveys
2. Website scraping
3. Third party purchasing

With all these categories of data there are plenty of ways to gather data and build an understanding of your ICP.

• For Firmographic and technographic data you can purchase data overlays
• For sizing the biggest categories you can use quantitative surveys of wins and map to their LTV
• For deeper insights and more authentic understanding to help drive things like SEO and content you can do customer interviews

The main takeaway is to get the data and build deeper insights and understanding of your ICP so that you can leverage across all of your marketing spend. ICP is at the fulcrum of leveraging every dollar.

Before you get started

Now that you have more clarity and detail on your ICP you can LEVERAGE the value of your marketing automation more effectively. First, you need to get clear on what your marketing goals are. No amount of detail you have on your ICP will matter if you’re not clear on what you want to do with it.

Here are a few examples of marketing level goals:

• Marketing sourced bookings or revenue
• Customer acquisition cost targets
• Lifetime Value Improvements
• Increase Suspect to Prospect to Opportunity to Win Ratios

All of these targets should help your marketing team understand whether they are leveraging marketing dollars because they should show improvements relative to what the spend was before you developed a more informed ICP. Integrate the ICP data into marketing automation tools to start executing campaigns behind this knowledge. Now you can get more granular down to the campaign level. You need to establish campaign-level goals to again make sure you are getting improvements with the ICP data you are using in your marketing automation. Have campaign-level goals to target and then evaluate. 

Here are a few examples of campaign-level goals:

• Campaign ROI with cohorted analysis
• Marketing Qualified leads
• Sales Qualified Opportunities
• Closed wins

You should design testing approaches across multiple marketing journeys from the top of the marketing funnel (leads) to the bottom (wins) to ongoing client marketing (LTV) to pressure test your ICP effectiveness and its impact on scaling your marketing spend.

Summary

Leveraging and optimizing your demand generation investments requires insightful, data-driven, and tested ICPs and target market segmentation. By marrying powerful ICP understanding and data into your marketing automation tools you can drive more pipeline with less marketing budget across multiple marketing journeys from MQL to Wins to expanding Customer Lifetime Value.