Sunday, May 8, 2016
When You Need to Look Beyond Look-Alike Modeling to Select ABM Target Accounts
Technically, this approach is known as look-alike modeling, and it's an effective way for companies to select ABM target accounts in most circumstances. In some business situations, however, look-alike modeling isn't a good option, and it's important to understand when you need to use a modified approach to select accounts for your ABM program.
For look-alike modeling to be effective, your company needs to have enough existing customers to build a customer model that's reliably predictive. In a webinar earlier this year by Lattice, the presenter stated that you need at least 500 "successes" to build a sound customer data model. Ideally, these "successes" will be existing customers, but you can include late-stage sales opportunities if that's absolutely necessary.
While 500 may not be an absolute minimum, you do need a substantial number of existing customers to build a reliable customer model, and there are two circumstances when this may pose a problem. First, a start-up or young business may not have acquired enough customers to create an accurate profile of the ideal customer.
A similar problem can arise when a mature business wants to use ABM for a new or recently launched product or service. If the new product or service appeals to a different type of customer than the company's other products or services, a customer model based on existing customers may not be useful for the new product or service.
In these cases, the best way to select target accounts for your ABM program is to identify and use the basic attributes that make a business an attractive prospect for your company. I discussed these attributes in some detail in my last post, but at the highest level, attractiveness is a function of the value that a prospect will potentially produce for your business and the likelihood that a prospect will purchase your products or services (buying potential).
Choosing target accounts for an ABM program also becomes a little more complex if your company needs to sell to new types of customers in order to reach growth objectives. For example, suppose that your company has been selling primarily to businesses in a particular industry. To reach your revenue growth objective, you need to begin marketing and selling to businesses that operate in a different industry, and you want to use ABM to focus your marketing and sales efforts on the right prospects.
To use look-alike modeling effectively in this situation, you need to look beyond basic firmographic attributes - things like industry vertical and company size - and identify the key operating characteristics that your best existing customers share.
To use a simplistic example, suppose that your company has been selling distributed marketing automation software to technology companies that sell through independent systems integrators. You want to begin selling your software to manufacturing companies that sell through independent dealers. When you analyze your best existing customers, you find that they usually have more than 500 system integrator partners, and that they rely on their channel partners for a significant percentage of their total revenues. Given these shared operating characteristics, you would probably want to target manufacturers that sell through a large network of independent dealers and rely on dealer sales for most of their revenues.
As I noted earlier, look-alike modeling is an effective way for companies to choose ABM target accounts in most circumstances. But like any business tool or methodology, look-alike modeling has some limitations, and it's important for marketers to understand when a different or modified approach is needed.
Illustration courtesy of Kate McCarthy via Flickr CC.
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