Home CTV Predictive Analysis And Performance Go Hand In Hand

Predictive Analysis And Performance Go Hand In Hand

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Kicking off the POSSIBLE conference in Miami on Monday, Nielsen announced a new outcomes-based measurement capability called Predictive Sales Lift. The feature is designed to help media buyers predict sales lift and incremental revenue for video ad campaigns they run via the company’s comprehensive measurement platform, Nielsen One Ads.

Nielsen wants to help brands run video ad campaigns with performance as the goal. The next age of connected TV advertising is about proving business outcomes, said Nichole Henderson, Nielsen’s SVP of global measurement and outcomes product. That trend is expected to continue as marketers face more pressure to justify every dollar of media spend to their CFOs. 

And yet, brands are not measuring lower-funnel metrics for 90% of campaigns run through Nielsen One Ads, Henderson said. This disconnect is not due to disinterest, she said. Instead, advertisers – especially smaller advertisers – need a better way to predict performance before making the investment. Predictive Sales Lift is designed to help marketers do just that, according to Nielsen.

The product will be generally available in the US by next month, covering connected TV, mobile and desktop, with linear TV to follow soon. Predictive Sales Lift isn’t directly tied to Nielsen’s upfront offerings, such as its currency options. But Nielsen is having active conversations with clients throughout the upfront season about how they might work the feature into their general measurement strategies, Henderson said.

Predicting the future 

Nielsen already has outcomes-based measurement tools, including within Nielsen One Ads.

But measurement is different from predictive analysis, Henderson said. Whereas measurement tells marketers what already happened, predictive analysis gives marketers a sense of what outcomes are likely to occur – and a chance to make adjustments to active campaigns for better odds of achieving those outcomes.

Nielsen’s Predictive Sales Lift tool is built with sales lift data from hundreds of prior Nielsen One Ads campaigns. “Clients can use data in-flight to flag underperforming campaigns early enough to reallocate spend,” Henderson said. 

Nielsen’s latest product also aims to serve smaller and medium-size brands that may not meet the minimum investment required to get meaningful information from a typical measurement report. “Our sales lift study typically costs anywhere from $25,000 to $50,000 for an individual campaign,” Henderson said. “This predictive approach will be a fraction of that cost.” 

Smaller-scale campaigns are also better suited for predictive analysis over sales lift studies, she said. If a smaller brand was running a campaign intended to achieve roughly 10 million impressions, for example, that wouldn’t be enough data for Nielsen to match up with its sales data compared to a campaign with 100 million impressions. But a predictive sales lift can still help a smaller brand make a connection between campaign distribution and sales impact.

This strategy can also be useful for brands that have larger media investments and want to predict how a campaign might perform before putting spend behind it, especially if that brand is trying to target a more niche audience segment, Henderson said. 

Pragmatic predictions 

So, what does Predictive Sales Lift look like in practice? 

While the platform doesn’t play a direct role in media allocation, “it really does play a role in driving accountability,” Henderson said.

For example, “one of the biggest use cases for this solution is channel optimization,” she said. Brands will want to see which platforms are having bigger impacts on predicted sales lift. Based on that analysis, they can reallocate spend to platforms where their ads are more likely to perform. 

So far, Nielsen says some interesting trends have already emerged while testing the platform. For example, groceries and supermarkets appear to drive higher sales lift on average compared to other verticals, such as fast-food restaurants. One possible reason involves a degree of customer loyalty, Henderson said. Consumers may be less likely to have an exclusive preference for supermarkets because they generally carry products across a wide breadth of brands, but many of those same consumers may have very strong opinions about whether they prefer McDonald’s or Taco Bell.  

Another interesting insight: “Campaigns that have higher frequency don’t necessarily result in higher lifts,” Henderson said, and overfrequency can diminish the effectiveness of impressions. (Say it louder for those in the back!)

Ultimately, Henderson said, Nielsen’s objective is to help brands run higher-performing campaigns with more cost-effectiveness and less ad wastage.

Here’s hoping some of these insights eventually lead to less ad repetition, too.

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