CHAPTER

2

Developing an Ideal Account Profile

The SWOT analysis we completed in the previous chapter provides sales professionals with the ability to clearly communicate the differentiated value proposition of their company and its products. In the Predictable Prospecting method, you’ll learn how to identify those you can successfully approach with that message. This will be done in two steps: deciding on the ideal accounts to target, which is covered in this chapter, and identifying the ideal people to target within those accounts, which is covered in the following chapter.

The maxim “You can’t be all things to all people” perfectly expresses the philosophy behind developing an Ideal Account Profile. In reality, even if a company were able to sell its products to every other company on the planet, neither the company nor any individual salesperson could do so without infinite time and infinite energy. The process revealed in this chapter, known as market segmentation, is all about maximizing the return on effort by focusing on those companies with both a high lifetime value and a high likelihood of buying.

Market Segmentation

Lifetime value takes into account both sides of the long-term profit equation as well as intangibles. The revenue side of the equation includes factors such as the transaction size, renewal rate, and expansion opportunity. The cost side of the equation includes standard product costs, customer acquisition costs, and service-support costs. In addition to these measurable quantities, signing a particular customer may have enormous intangible benefits, the strongest of which would be the value of the customer as a reference.

While we share a universal framework for building market segments, there is no universal set of segments since every company’s situation is unique, even among seemingly direct competitors. Our approach considers segmentation factors in three categories: firmographic fit, operational fit, and situational fit (Figure 2-1). The “fit factors” within these three categories are proxies, to a greater or lesser extent, for customer needs and budget. As such, they function as a coarse mechanism for prioritizing those companies with which to attempt to do business and identifying those to avoid.

  FIGURE 2-1 Segmentation Factors for an Ideal Account Profile (IAP)

An Ideal Account Profile is simply a set of market segments that meet the criteria of high lifetime value and high likelihood of purchasing. We use the word “high” rather than “highest” or “maximum” with intent. A segment with maximum lifetime value and purchasing likelihood could easily be a segment of one. For a set of factors to be usable, those factors need to satisfy certain basic requirements.

First, when applied, the segmentation factors should identify the right number of target companies. Too few companies and the salesperson will not be fully occupied; too many companies and the salesperson will not have enough time to devote the level of activity required to meet his or her goals.

Second, the factors should be measureable with reasonable effort. Again, the whole point of developing an Ideal Account Profile is to maximize the return on effort. Focus on factors that are high impact and low cost to obtain and ignore factors that are low impact and high cost. Factors requiring a judgment call are those that are either high impact and high cost or low impact and low cost.

Third, the factors should identify distinct target segments, each possessing a specific set of needs. In addition, distinct segments should be accessible through homogenous communication channels to ensure efficient outreach.

Fourth and final is stability. Market segmentation is a strategic process, and as such changes should be made only over longer time horizons (a year or more) or when the company’s overall strategy is in rapid flux (as is often the case in new businesses).

The Fit Factors

These factors include firmographic, operational, and situational characteristics.

Firmographic Fit

Similar to business-to-consumer segmentation based on demographic factors, business-to-business segmentation classically begins with firmographic factors that include industry, company size, and geography. These factors are relatively inexpensive to obtain since the market for business data is quite competitive with long-established providers such as Hoover’s and S&P Capital IQ and newer entrants such as ZoomInfo and DiscoverOrg, in addition to scores and scores of other providers.

Industry: If the starting point of market segmentation is firmographic fit, then the starting point of firmographic fit is industry. Currently, there are two standard classification systems: SIC, first established in the United States in 1937 and used internationally, and NAICS, first released in 1997. We’ll start with the newer NAICS (last revised in 2012), which was intended to replace SIC. Note that NAICS has 24 active two-digit codes, 312 active four-digit codes, and 1,065 six-digit codes. Familiar two-digit industries include manufacturing, information, and retail trade.

The most useful industry classification is manageable in size (typically 10 or fewer) and includes nonoverlapping combinations of NAICS codes. The set will vary based on your target industries, but a good starting point of 10 items plus an “other” category is as follows (codes in parentheses): education (61); energy and utilities (22); finance and insurance (52); government (92); healthcare (62); information technology (334x, 5112, 518x, 5415); manufacturing (31 to 33 excluding 3254 and 334x); media and entertainment (71); pharmaceutical (3254); and other (11, 21, 23, 42, 44 and 45, 48 and 49, 51 excluding 5112 and 518x, 53, 54 excluding 5415, 55, 56, 72, 81).

Most companies manage a semicustom industry target list aligned with business opportunity. Like our reference example, a given list may go deeper or broader in various segments. We strongly recommend creating an “other” category to hold industries that are a poor fit. As a reminder, each segmentation factor provides a rough way to screen in desirable companies and screen out undesirable ones. Undesirable industries may have little expected demand for a company’s products, too much (or too little) regulatory intensity, or poor industry health.

Company size: This is the next most common firmographic fit factor. Since most companies sell to both public and private entities, bands consisting of the number of employees are usually the easiest to deal with. Unfortunately, company size classifications are far less standardized in comparison to industry classifications. Nonetheless, a useful set of categories are as follows (revenue ranges are based on a reasonable, albeit rough, estimate of $500,000 per employee; the number of U.S. headquarters from Hoover’s based on revenue):

Microbusiness and/or small office or home office: 10 employees or fewer; up to $5 million; 228,657 companies

Small business: 11 to 100 employees; $5 million to $50 million; 114,187 companies

Medium business: 101 to 1,000 employees; $50 million to $500 million; 23,653 companies

Large enterprise: 1,001 to 10,000 employees; $500 million to $5 billion; 5,119 companies

Extra-large enterprise: More than 10,000 employees; over $5 billion; 983 companies

While the above employee and revenue bands will serve most businesses, the optimal breakpoints can be different for each business. Additionally, employees and revenues may not always be the best measures of size. For example, a business providing secure office-to-office communications services might be more interested in the number of locations, or a company providing facilities services might be more interested in a prospect’s total square footage.

There is an old adage in sales that it takes as much effort to win a deal with a large company as it does a small one. If that assumption is correct, then why not just focus on selling to the Fortune 500 or Fortune 1000? As of 2015, all Fortune 500 companies fit in the extra-large enterprise category by revenue ranging from number 1 Walmart at $485 billion to number 500 McGraw-Hill Financial at $5.2 billion. The Fortune 1000 cuts off at E*TRADE Financial with revenue of $2.0 billion. The problem is that it is actually easier to sell to smaller companies. Jumbo companies are highly risk averse, and they have many hoops to jump through; it takes only one no to scuttle the deal. Moreover, competition is more intense when trying to sell to a Fortune 1000 company.

Geography: The main considerations surrounding geographic targeting include language, the ability to provide high-quality service, and tax complexity.

With firmographic theory in hand, turn back to the analysis of Salesforce.com. Rob Acker, the executive tasked with lead generation and account management, had pored over the data he had been collecting and noticed that Salesforce.com was experiencing success with small companies having fewer than 30 employees. The value of segmentation is in the results. CEO Mark Benioff confirmed this by saying, “It turned out to be a very good decision to focus more attention on smaller businesses. The close rates were high, and the sales time and cost of sale were low. We experienced phenomenal growth in this area and expanded from 4 sales reps to 20 reps in just six months.”

Despite being a cloud-based company and possessing unlimited reach, Salesforce.com also benefited from industry and geographic segmentation. Specifically, the company found early success right in their backyard among high-technology companies in Silicon Valley. Their first customer was Blue Martini Software, a vendor of e-commerce applications for retailers based in San Mateo, California (and a company in which Benioff had previously invested). The second was iSyndicate, a San Francisco–based content syndication provider. The third, the web-hosting provider colo.com, was also based in San Francisco. As Salesforce.com matured, it was able to expand to larger prospects in new industries and wider geographies. Its initial success hinged on starting in a niche, and it has grown over time such that today it is a successful sales organization that, like every successful sales organization, is a harmonious aggregation of countless industry, size, and geographic niches, what sales professionals refer to as “territories.”

If segmentation completeness were measureable, firmographic fit would get companies 80 percent of the way to the finish line. Using the 80-20 rule, firmographic fit only takes 20 percent of the effort required to get to 80 percent of the way to an Ideal Account Profile.

Operational Fit

If firmographic fit is too coarse, operational fit is the next set of segmentation factors to consider. This includes everything about a prospect’s medium- to long-term business operations, including processes and installed equipment. While some of these operational variables may be available for purchase via a third-party database, most are not and require some degree of discovery. We will explore three common operational fit factors, but each company should investigate only those factors worth the effort for their business.

Current equipment: The first operational fit factor takes into consideration the prospect’s current equipment and technology. For instance, consider SalesLoft, whose excellent sales workflow management tool works best when integrated with Salesforce.com. To maximize its return on effort, SalesLoft should segment on companies known to be Salesforce.com users. Similarly, a company that provides spare parts for agricultural equipment would segment farms based on their use of Caterpillar, Case IH, John Deere, New Holland, and so on.

Purchasing policy: This is the second operational fit factor. Imagine selling parts to Boeing for its 787 Dreamliner. From project launch to first delivery, the airplane took over seven years and $32 billion to develop, according to the Seattle Times.¹ The plane sells for anywhere between $125 million and $225 million. Boeing’s suppliers must deal with long cycle times, extreme quality standards, complex inventory management, and unimaginable insurance indemnification. At Boeing and elsewhere, purchasing policies may contribute to a better or worse fit. This type of purchasing policy also includes, but is not limited to, companies with a preference for leasing rather than ownership, buying from minority-owned businesses, purchasing based on sustainability requirements, or selecting from a Government Services Administration (GSA) price list.

Buying decisions: This third operational fit factor focuses on not just how the prospect company makes buying decisions but whether the company centralizes purchasing within a procurement team or decentralizes to individual business units or branch offices. No single purchasing approach is inherently better or worse from the perspective of a supplier. Centralized purchasing, for example, is a great fit for large, complex orders.

Let’s apply each of these three operational fit factors to Salesforce.com, as it relates to two cases: one is a newly formed business, and the other is a large, established enterprise. In the case of the newly formed business, Salesforce.com’s fit is excellent since there is no installed base of technology, and new businesses often prefer to use cloud-based solutions where possible to avoid infrastructure purchase and maintenance costs. In the case of the large, established enterprise, Salesforce.com will most likely run into a competitive on-premises CRM solution. Since the switching costs of moving data and retraining sales teams are very high, the prospect must be deeply frustrated either with the functionality or total cost of ownership of their existing solution. Salesforce.com may find more success knocking out certain competitors rather than others; and if that is the case, knowledge of the competitive CRM solution in use will help it prioritize prospect segments to target.

With respect to the second operational fit factor, purchasing policies, Salesforce.com should experience far less friction with either business than a Boeing supplier would, so the company does not need to segment here. Similarly, with buying decisions, it is not worth Salesforce.com’s effort for either the new or the established business in this case.

Situational Fit

When firmographic fit and operational fit do not provide sufficiently meaningful target segments, then companies must turn to situational fit. In contrast to operational fit factors, which are medium- to long-term prospect company characteristics, situational fit factors are more opportunistic. As such, they require more effort to ascertain and are more evanescent.

Strategic initiatives: This is often the most fruitful area to find situational fit factors. Since our overarching goal here is efficient segmentation, we are after information that can be gleaned before engaging decision makers in conversation. Some of the best sources for this type of information include annual reports and analyst reports. For example, the “Message from our Chairman” section in Boeing’s latest annual report² highlights the following initiatives to create likely opportunities for a wide range of vendors:

Under the moniker of “Partnering for Success,” Boeing is working to increase quality and reduce costs by asking suppliers for more transparency into their manufacturing processes and financial statements.

To control development costs, Boeing is standardizing its product development process. In addition, the company is working to adopt common parts across its products.

Boeing is investing in safety standards, tools, and equipment to reduce serious injuries.

To reduce the company’s environmental footprint, Boeing is investing in a range of options, including renewable energy, sustainable aviation biofuel, and airplane noise reduction technology.

Internal capabilities or the propensity to insource or outsource: This second situational fit factor complements the analysis of a prospect’s strategic initiatives. For instance, Boeing may consider its product development process to be a source of competitive advantage and may not, therefore, look to outside consulting or training organizations for assistance. On the other hand, Boeing will likely always need partners to help improve worker safety. Sadly, in late 2012, a Boeing painter died from injuries sustained after falling from a scaffold. The company turned to Zebra Technologies, a maker of physical asset tracking solutions, to develop the Painter Fall Protection Solution. Zebra’s ultrawideband (UWB) radio frequency identification (RFID) sensors are embedded inside the safety harnesses of workers who stand on (and lean over) work platforms called stackers that move right, left, up, and down to reach every spot on an airplane’s fuselage. Not only does the Painter Fall Protection Solution track the location of workers but it also shuts down the stacker if the worker is not harnessed in properly.

Financial health: This third, and comparatively easy to obtain, situational fit factor concerns finding profitable, free-cash-flow positive prospects who are likely to have open pocketbooks. While most people would be able to name only Boeing and Airbus as airplane manufacturers, there are a decent number of smaller though still sizable competitors to evaluate such as Bombardier, Cessna, Dassault Falcon, and Embraer.

Short term: The fourth situational fit factor arises during executive transitions, especially those of corporate officers or business unit leaders. Case in point: Boeing announced the retirement of CEO W. James McNerney, Jr., on June 22, 2015.³ His replacement, Dennis A. Muilenburg, as with most executives, will most certainly develop a slew of initiatives to put his own stamp on the company. Similarly, we would be wise to closely monitor changes in senior sales leadership at Salesforce.com. We have found that DiscoverOrg, GainSight, and Relationship Science complement LinkedIn and are excellent sources for detecting changes in leadership. Of course, companies that have great relationships with their clients and prospects know well in advance when such changes are coming.

Value, mission, and culture alignment: The fifth and final set of situational fit factors relate to the “softer side” of target accounts and are the most challenging to ascertain at scale. Here we are talking about whether the prospect is an early or late adopter or has a preference for form versus function. Going back to Boeing, which prides itself on innovation, safety, and diversity, it would be more likely to do business with suppliers sharing the same ethos.

In Figure 2-2, we illustrate a hypothetical example of Salesforce.com’s early Ideal Account Profile.

  FIGURE 2-2   Hypothetical Example of Salesforce.com’s Original IAP

This chapter has covered a litany of firmographic, operational, and situational fit factors. We recommend expending effort only on those factors necessary to allow sales teams to focus on companies with high lifetime value and high likelihood of buying. While institutional knowledge and a modicum of gut feel can often be reliable inputs for selecting factors, a more dependable practice is to examine the shared characteristics of a company’s most profitable customers. Compare attributes of your best customers to your worst. If you do not yet have a large customer base, simply interrogate web traffic with an IP lookup service provider like DemandBase or ReachForce to identify which prospects are already interested in your products.

Remember, the Ideal Account Profile (IAP) process identifies the most desirable prospect companies to call upon. The next chapter will delve into the Ideal Prospect Persona (IPP) development process so you can accurately target which individual decision makers to engage inside those companies.