This guest post was authored by Connexity VP of Business Development, Christopher P. Curtis.
As the menu of data targeting options continues to accelerate in our industry, a few basic questions can help buyers hone in on the right choice of providers.
When considering any new data provider, the two first questions you should ask are:
It’s important to evaluate not only the volume (or size) of audience you’re buying, but the quality and uniqueness of the data. Your data provider should be comfortable giving details about where their data comes from; the more you know about the data source, the more confidence you can have that this data will help you meet your marketing objectives.
High quality data is often unique data, and will be largely unduplicated. While there will inevitably be some overlap between providers and within similar categories, too much overlap means that the target audience will already be receiving a wealth of competitor advertising. By conducting an overlap analysis, you can evaluate whether the segment contains a high percentage of new targets; this allows you to not only expand your reach to additional prospects, but your message will hit a fresher audience that hasn’t been overwhelmed by similar advertisements in your space.
When purchasing data, it’s important to evaluate whether you’d like to target people who are at the tipping point of a purchase, or consumers higher up the funnel who may be likely to have future intent.
An observed audience consists of people who have literally engaged with a product page, made a specific purchase or taken another designated action. Meanwhile, a modeled audience takes a seed set of people who have purchased, and models a new audience of (ideally) high-propensity buyers from that original set.
A modeled audience can be an excellent option for those who have a limited amount of data and need to broaden their reach by emulating known buyers of their product. It’s key is to know the difference when you are purchasing a segment; how much of your audience was modeled, and how much was observed? How important is it for you to hit bottom-of-funnel shoppers, versus finding a new set of potential buyers who look similar to your customers?
Understanding data recency (or, how often the data sources are updated) is important for a variety of reasons.
While everybody likes the idea of fresher data, newer isn’t always necessarily “better.” In some cases offline data, such as CRM or past purchase data, is brought back online and leveraged to target customers again. This can be very useful for specific campaign goals, but it’s not the same as “real-time” data.
In cases where you are trying to target audiences who are in a prime pre-purchase phase, real-time data is much more critical. While data uploaded on a weekly or monthly basis is valuable, daily (or even real-time) streaming data can be the cornerstone to hitting leads at the exact right place and time.
At the end of the day, all data is not created equal when it comes to source, intent or recency. As a marketer or data buyer, it is key to know the specifics about what is powering your data-driven marketing in order to set yourself and your clients up for success.
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