At its core, people-based measurement is about allowing brands to use the process of identity resolution to better understand their customers and build truly customer-centric organizations.
That can feel like a challenge to companies who have so far used identity resolution for campaign activation only. If you’ve already made an investment in identity resolution for targeting, it’s not a stretch to apply this same workflow toward measurement and understand what’s truly driving results for your brand.
Think about people-based measurement as climbing a mountain—perhaps daunting at first, but it’s about taking that first step, then the next, then the next, all the while keeping your eye on the summit. As you acclimate with simple use cases, you climb higher and get a better view of your customers.
Use case: campaign measurement
At the foot of the mountain, start with increasing the accuracy and efficiency in measuring baseline digital KPIs, like reach and frequency, to count individuals, not devices or cookies.
Even though the baseline reach and frequency metrics are simple to understand, measuring and managing these KPIs requires a lot of technology—not just an ad server, but a DSP, DMP, and identity translation technology that enables connectivity among different identity spaces. Luckily, most of these should already be included in your Mar Tech stack.
The first step toward building an omnichannel view of the consumer begins with activating audience data via a data connectivity platform, which enables you to attach it to unique, pseudonymized identifiers and link to impression data from the ad server, cookies, and device IDs.
By using a media analytics tool capable of ingesting those unique identifiers and stitching the data sets together, you’ll be able to understand how many people saw an ad, how often they saw it, and, to the extent possible, who they are (e.g. demographics, behaviorgraphics, audience segments).
Stop seeing double
With people-based campaign measurement, you can more accurately measure true unduplicated reach for your audience across devices, putting you in a prime position to reach for more sophisticated use cases like frequency management and sequential targeting. This helps you use your marketing dollars more efficiently.
Let’s say you want to understand how many messages a loyal customer needs before conversion and compare them to new or infrequent customers.
You can uncover this by using ad server analysis to measure the impact of frequency on branding and sales among those different customer segments. Looking at the different touch point thresholds each audience requires to move through the purchase funnel allows you to adjust frequency and timing of exposure appropriately.
Along with your newfound frequency management and sequential targeting skills, use people-based campaign measurement to understand the impact of improved sequencing of marketing messages across devices, better communicate with consumers across channel and device, and unlock customer journey decision points between mobile and desktop.
Eager to achieve greater measurement feats? Download our e-book, The Journey to People-Based Measurement.