Tomas Rodriguez, Product Marketing Manager, Signal

By now, you’ve read the many “Marketers already have all the customer data they will ever need” thought-pieces. You have listened to speaker after speaker at technology conferences discuss how customers are evolving faster than brands, and the brands that catch up will be ones that make it.

You are determined. You are focused. You will conquer your data.

And now, you’re ready for your Rocky montage.

You know, the one where you get up early in the morning, drink raw eggs for breakfast, slow-motion run on the beach to an 80’s drum-machine beat, and punch raw meat in a walk-in freezer? And three and half minutes later, you’re in peak condition to knock out all of those barriers between you and your first-party data!

I’m here to tell you: Hit the snooze button on your alarm. Slow down, Champ. Before Rocky jumped in the ring, he had Mickey show him the ropes. And that’s what we’re going to do: learn the fundamentals.

You are collecting enormous amounts of customer data every day from your websites, point-of-sale systems, mobile applications, and advertising campaigns. Each of those media channels collects different data in various formats, but rest assured, there are some consistencies. All customer data can be classified within three different categories: Identity, Behavior, and Attribute.

Identity Data

What it is:

A hot topic these days, identity data is any data point that can be used to distinguish one consumer from another. Virtually every one of your media channels uses identity data at some level. Browsers identify unique users with cookie IDs. Mobile devices have unique device IDs. And recently, you’ve probably been asked to provide your email when checking out at a department store or casual restaurant–another example of capturing identity data.

Identity data is incredibly powerful. By distinguishing one person from another, it enables messaging to be customized for the individual, rather than broad messaging communicated to a wide audience.

How it’s used:

Identity data is used all throughout digital analytics and advertising. Publishers use it to measure site visitation by looking at monthly unique visitor metrics. Brands leverage identity throughout their marketing and transactional practices. It’s used to maintain rewards programs and to conduct email campaigns. Nearly any digital marketing strategy used today employs the use of identity data.

Best practices:

Not all identity data is the same. Some identity data, such as cookie IDs, expire after a certain number of days and really only identify a web browser, not the customer himself. That means that browsers being used by more than one person result in inaccurate cookie IDs. Other identity data points, such as email addresses or rewards program numbers can be used across media channels, do not expire, and are specific to the customer rather than the browser. Successful advertisers will prioritize the generation, security, and storage of these more durable identity data points.

Behavior Data

What it is:

Behavior data is all about action. A customer action could be the downloading of a brand’s mobile app, or completing a transaction in-store. It could even be as simple as visiting the homepage of a brand’s site. The behavior data that records these actions can be further categorized into two separate buckets:

• Events – These data point define the event taking place. For example an ecommerce website event could be “visited product details page” or “completed checkout”.
• Associated Data – These are data points that help add context to the event. A timestamp of when the event occurred is almost always collected along with the event data. For an event like “visited product details page” some of the associated data collected might include: product ID, advertised price, image URL (the product image), or referring URL (the page that the customer was on before the product details page).

How it’s used:

Marketing strategies that use behavior data include customer experience analytics, display advertising retargeting, and email campaign segmentation. For analytics, behavior data provides the managers of each channel with information relaying how customers are interacting with their channel. It can reveal opportunities for more efficiency and effectiveness. Advertisers leverage behavior data to target customers based on their previous actions. Email campaigns may only target customers who have downloaded brochures, where display retargeting could remarket to customers who abandoned items in their shopping cart.

Best practices:

Strike while the iron is hot. Behavior data can take your campaign performance to new levels, but only if your marketing can act on it quickly. The effect of recency on response times in the form of ad click-through rates was studied by Simpli.fi from more than 200 display campaigns in the personal finance industry, where Simpli.fi found:

“First, recency drives up CTR. We’ve learned that CTR and conversion rates are highest within one hour of the campaign-triggering search. Once the search ages beyond 24 hours, the numbers fall off dramatically. In fact, CTR begins its decline as soon as 30 minutes after the triggering event.”

With display advertising retargeting, a user’s actions are seen as interest indicators. A timely response to a customer’s interest with an email message or display ad unit can make the difference between a good ad campaign and great marketing.

Attribute Data

What it is:

Attribute data details characteristics of a customer. Demographic information such as gender, geography, and age can be classified as attribute data. Additionally, brands can elect to create attributes unique to their organization such as classifying customers under different tiers of loyalty levels (silver, gold, platinum). This is where the line that separates behavioral data and attribute data can blur, since attributes are often based on a customer’s behaviors. For example, a life-time value score, calculated using a customer’s purchase behavior, may be associated as an attribute for a specific customer.

Marketers can determine whether a data point is an attribute or behavior by asking, “Does this data point drive a marketing campaign or drive an advertising tactic?” Attributes should be broad enough to build entire marketing campaigns around, while behaviors are best used to optimize advertising within a campaign.

How it’s used:

Attribute data can be used to drive the planning, buying, and targeting of marketing campaigns. Targeted initiatives such as incentivizing a Silver member to upgrade to Gold sit at the strategy level of marketing campaigns.

Best practices:

The creation of custom attributes is one of the best tools in a marketer’s tool chest, but it requires some forethought. To take full advantage of this data, brands need to look months and sometimes year ahead, by asking the question, “What type of customers do I want to message in my future campaigns?” Posing this question should help marketers determine what type of attributes they would like to capture.

You did it!

Atta kid, Rock! You survived your first round in the ring. Can you feel your data muscles swelling? Your confidence growing? At the very least you should be sweating. A couple more rounds like this and you’ll be more than ready to lace up the gloves for a bout with your data.

If you’re looking to continue to build on your data fundamentals, come back and visit the blog where we’ll be continuing our dive into understanding first-party data. For those of you ready to start tackling your data with an expert trainer in your corner, reach out to us via our contact page so that our consultants can get you in peak condition to finally conquer your data.

Yo, Adrienne! We did it!

See the original post here: http://www.signal.co/blog/attribute-behavioral-data-management/