We need to bring attribute data, behavioral data and deep engagement data together all in one place. Attribute data A lot of basic attribute data about prospects and customers tends to be scattered across your organization, doing you absolutely no good. Behavioral data Of course, the characteristics of a person don’t give you the whole picture of who that person is and what she is interested in. Whenever people interact with you, they’re telling you something by using the language of clicks. Retail companies need to know which products a person clicks on, which products she adds to her cart, and which emails have captured his interest enough to make him click through. Engagement data On top of basic behavioral data, engagement data goes further to allow you to uncover a deeper understanding of an individual. Just like a store clerk watching a visitor interact with products in a store, you’ll be able to use deep engagement data to make a meaningful recommendation to that person. Once you realize a person’s a person at the heart of your business, and once you bring together all of the attribute, behavioral and engagement data you have on each person into a unified profile, you’ll be ready to start personalizing -- all the way down to the individual level. For example, attribute data tells you that one of your B2B prospects is the head of IT in the financial services industry. Engagement data tells you that he spent the most time interacting with blog posts about the benefits of FinTech for attracting global customers.
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Recently, while I was watching one of my kids perform in a musical rendition of Horton Hears a Who, I recognized that Dr. Seuss’s life lessons about personhood are applicable in business, too. A person is a person, not an audience or a segment. A person is at the heart of your business.
To succeed in business, we need to understand our customers as people. And we need to do that holistically, creating a portrait of each person’s interests, wants and needs.
Personalization starts with a deep understanding of the person. The problem is, when we look at data about a person, our understanding is often too broad and not nearly as in-depth as should be. We need to bring attribute data, behavioral data and deep engagement data together all in one place.
1. Attribute data
A lot of basic attribute data about prospects and customers tends to be scattered across your organization, doing you absolutely no good.
Attributes describe any characteristic of a person. An individual’s geolocation, industry or company, the source that brought him to the site right now, whether or not he’s from a customer account or a target prospect account, whether he’s a member of the loyalty program or not — all of these are considered attributes.
Each of the attributes I’ve listed are typically captured and stored in different locations. It may exist in a CRM system, an order fulfillment system, a data warehouse, a marketing automation system, a personalization platform, or even jotted on a notepad on the desk of a salesperson.
Keeping attributes stored in different places typically means they can’t be leveraged for personalization. Instead of letting this attribute data languish in silos, bring it all together into a meaningful, actionable, unified customer profile.
2. Behavioral data
Of course, the characteristics of a person don’t give you the whole picture of who that person is and what she is interested in. You need to include that person’s behaviors as well.
Whenever people interact with you, they’re telling you something by using the language of clicks. Everything that happens in digital channels counts as behavioral data — what they’re clicking on and what they’re not…