With deep roots in household targeting, Nielsen is no stranger to helping marketers manage reach and frequency at this level. But increasingly, marketers relying on Nielsen Marketing Cloud want to do this at an individual level as well. eMarketer’s Lauren Fisher spoke with Greg Bayer, Nielsen Marketing Cloud’s senior vice president of product, about how marketers can strategically coordinate their use of household- and individual-level targeting to have more control over reach and frequency—and how to avoid overspending on ads and annoying their customers. Bayer was interviewed as part of eMarketer’s July report, “Ad Targeting 2018: Households, Individuals or Both? Why a Blended Approach is Often the Answer.”
How are marketers approaching ad targeting at both the household and individual levels?
Users are fragmented across so many different devices. At a high level, marketers are looking to manage their ad delivery. They have to be very pinpointed in their messaging strategy; otherwise, they risk overexposing a message and giving a user a bad user experience—and ultimately, spending too much.
The objective is trying to control how and when they reach a user, and being mindful of the context and device a user sees the ad on.
How could this work in practice?
One case is marketers targeting at the product level. A CPG [consumer packaged goods] company might want to target products such as household items like toilet paper or paper towels at a household level separate from products like adult care items that they want to target on an individual level. They use the different levels and the different models to message those products to different groups, segments or audiences.
Another tactic is targeting more generally on a household level across different products for brand building. Marketers look at that similar to how they look at TV or radio. It’s reaching households, and it’s brand building. That’s an important part of some of our CPG clients’ marketing mix. Then they can move to lower-funnel messaging as it relates to conversion tactics or coupons, so they can try to customize those messages at the individual level.
So even if marketers tailor messages at the individual level and use digital to do so, they could still be targeting those individuals from a household-level lens on digital, correct?
It’s very fluid, especially in digital. Some of our clients leverage the DMP’s [data management platform’s] device graph to help them model out the households on a digital level. For example, they might bring their anonymized customer data, or a subset of it, and use some of the features and capabilities in the DMP to model out how that looks at the household level so they can build different clusters that they can message differently.
That approach has been very helpful for brands that come from TV and radio and still plan and think around households. That’s still a big part of their spend, so the strategies and messaging they’re bringing to the DMP to build those audiences around households are coming from the work they’ve already done. It’s a nice way to connect everything together, but still use the digital space for execution.
Do you see marketers treat individuals within the household uniformly?
We see some clients narrowing as they go down the funnel to gender, income, geography and other interests and purchase intent. That just follows the natural sequence of how they want to think about moving down the path of their campaign. They may want to start with a broader message to the full household, but they might have an additional six or seven creatives for the campaign that they want to drive to the mother of the household, the father of the household, or another adult.
You mentioned that a benefit of tying together individual- and household-level targeting is the ability to manage reach and frequency. What do marketers need to be mindful of here?
Marketers need to be hypersensitive to any platform’s capabilities for reach and frequency. They can be very granular or very broad.
When you build audience segments, you can get very complex and granular with a customized audience. Some of our clients like to have frequency caps on granular subsegments. They might say, “In this campaign, I want to make sure I reach target X only five times, but Y three times.” They may also want to set a global frequency cap so they’re in control of how often an individual is exposed to an ad across all buying platforms, not just one.
For example, we have an ecommerce client running multiple categories of products, such as electronics and apparel. At any moment in time, they may be running 50 digital campaigns across their vertical, across promotions and their customer database. There’s a risk that one person could get 50 ads in a given week from the same brand across different verticals. That’s a huge risk, not just in terms of how much they’re spending on those ads, but in turning off that customer.
On a global level, you have to put some rules and parameters in place so the individual brand marketing teams can do what they need to do.
Taking that ecommerce example a step further, do you see brands starting to coordinate their reach and frequency efforts across multiple online retailers?
For example, if I’m P&G and selling Bounty paper towels, can I control the reach and frequency of my own efforts coupled with what’s being done across Target and Walmart?
That’s a big opportunity for marketers. We’re working on some ways for brands and retailers to be able to share data—not customer data, but segment-level data to make sure these sort of things can be controlled.
But still, a retailer can control their frequency. But if the brand is also targeting, there’s a risk of double targeting. It’s very early for some brands to start to be able to manage this.
We do have one client that partnered with a retailer on different addressable segments and coordinated the messaging for a specific product promotion at that specific physical retailer. That’s been successful, because both groups are really involved. But it has to get planned out ahead of time.
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