ABM Vendor Guide: Features to Customize Messages

Moving along with our series on sub-functions described in the Raab Guide to ABM Vendors, let’s take a look at Customized Messages.

ABM Process	System Function	Sub-Function	Number of Vendors
Identify Target Accounts	Assemble Data	External Data	28
	Select Targets	Target Scoring	15
Plan Interactions	Assemble Messages	Customized Messages	6
	Select Messages	State-Based Flows	10
Execute Interactions	Deliver Messages	Execution	19
Analyze Results	Reporting	Result Analysis	16

According to the Guide:

Vendors in this category build messages that are tailored to the recipient. This tailoring may include insertion of data directly into a message, such as “Dear {first name}.” Or it may use data-driven rules to select contents within the message, such as “show a ‘see demonstration’ button to new prospects and a ‘customer service’ button to current customers”. Systems may also use predictive models rather than rules to select the right message. Customized messages can appear in any channel where the audience is known to some degree – as an identified individual, employee of a particular company, or member of a group sharing particular interests or behaviors.

The Guide lists just a half-dozen vendors in this category. That’s not because there are so few systems that do this: to the contrary, nearly any email, marketing automation, or Web personalization tool would fit the definition. What is rare is ABM specialists who provide this function. That’s because, ultimately, message customization for ABM is pretty much the same as message customization for any other purpose. So the customization vendors in the Guide either provide customization to support a different ABM function such as display advertising (Demandbase, Kwanzoo, Vendemore) or have a broadly-usable customization tool they have targeted at ABM applications (Evergage, SnapApp, Triblio).

Some differentiators to consider when assessing a customization system include:

• types of data made available to use in customization rules (behind the scenes) and in presentation (actually displayed).
• ability to work with individual and account level data for rules and presentation
• complexity of rules that can be used to create customized content
• use of machine learning or predictive models to create customized content (either to select content directly or to use scores within rules that select content)
• channels supported  (emails, Web site messages, display ads, etc.)
• effort and skills needed to set up customized content
• ability to use the same content definition in multiple locations or promotions (some systems tie the content definition directly to a single Web page location or email template; others store the content definitions separately and let any message call them).
• generation of messages in real time during interactions, using data gathered during the interaction
• customization level (are messages unique to each contact, same for all contacts in an account, same for all contacts in a segment such as account industry and/or contact role)
• complexity of created content (single page, multiple pages, interactive content, etc.)
• ability to coordinate messages received by different individuals within an account
• ability to recognize individuals, accounts, locations, etc.

Only a few of these differentiators apply specifically to ABM. Many marketers will be able to use an existing customization system to generate their ABM messages. But for marketers whose current messaging systems lack adequate customization features, a specialized ABM customization system may make sense.