For app based businesses, there’s a world of data that can be obtained from user behaviour and actions taken on the app. And the good news is that this first party data now extends to TV viewership insights as well -- a previously data dark area in the media landscape. This means, TV spends can be utilised to reach audiences based on consumers’ actual TV viewership data, rather than depending on demographic estimates. Therefore, first party app user data on TV viewership consumption can now power TV media plans in ways that’s never been done before!
Let’s take a look at how Zapr’s solution called “Convex” has enabled this new model of consumer based TV media Planning for app based businesses:
1. TV viewership data (shows and channels app users watch) can be used to create effective TV media plans:
Most app based brands tend to overlook the fact that their TV campaigns are not effectively reaching the most important TG - app users who are most receptive to the brand’s marketing message. The segmentation they use currently includes only demographic, NCCS (New Consumer Classification System) and location filters. However these are not synonymous with the TG definition followed by brands which may include filters like digital awareness and savviness, potential to install and use apps, openness to digital transactions etc. For example, if there are seasonal offers being advertised on TV, the ads need to reach users who will take action on the app. To create such customized media plans for their own app users, brands need to know the exact shows and channels frequently watched by the relevant set of users.
By conducting overlap analysis, Zapr finds out the actual users of the app and understands their behaviour which can be used to target more such, similar sets of audience. Zapr conducts in-depth study on the TV viewership preferences of the brand’s app users and narrows down the shows and channels that they watch. To make life simpler, we even create the complete media plan for brands by providing a combination of shows and channels that are guaranteed to reach users.
The most interesting part of this analysis is that we’re able to further customize TV viewership analysis for specific segments of app users. For example, if a brand wants to launch a TV campaign for those who are heavily influenced by its competitors, Zapr can handpick the right shows and channels to reach them.
Here are some of the sample segments which can be useful for brands and for whom we can provide insights to create custom TV plans:
Light, moderate and heavy app users: We can analyze the TV viewership of frequent shoppers, lapsers who are not active on the app, or occasional buyers. Using this data, brands can create TV media plans that will influence them towards a desired behaviour.
Users exposed to competitor TV ads: It’s no secret that the brand which gets the most eyeball inevitably grabs higher share-of-mind among audiences. Therefore to neutralize the impact of its competition, it’s important for brands to identify those users who have been highly exposed to competitor ads, especially in the world of e-commerce apps where products are moving rapidly and consumer decisions are made quickly. Zapr finds those users who have been exposed to competitor’s ads and creates a highly customized TV media plan to win back their attention and hopefully, their loyalty.
Affluent users who can afford premium products: Let’s say a brand wants to launch a TV campaign for a range of premium products, they need to know where their affluent users spend time on TV. One way to do this is to identify users who use high-end devices and advertise on the channels they watch. Zapr divides an app’s user-base by the kind of mobile devices they use and gives TV viewership data for each segment: high-end devices which cost above 15k, mid-end phones around the range of 7 - 15 k and low-end devices which are below 7k. This way, depending on the price range of products they want to push for, a brand can bid for specific channels and shows to reach users having high, medium or low purchasing power.
2. Impact of TV ad exposure can be measured through user behaviour on the app. This attribution data can then be used to plan for a more effective TV campaign.
App based brands previously could not attribute TV ads to app usage because they didn’t know the TV ad exposure of app users. This made it impossible to connect huge TV advertising spends (which can go upto 685 crores for a single quarter) with actual user behaviour on the app. So while you can tell that a TV campaign has boosted sales to some extent, you can’t be certain of how it impacts individual actions on the app such as increased browsing or buying, while similar estimates and measurements are available for digital advertising.
After a brand’s TV media plan has been executed, Convex provides an in-depth analysis of how the TV ads performed among app users.
First, the brand provides cohorts which they want us to analyze, such as people who downloaded the app while the TV campaign aired live, or existing users who became active and made transactions during or after the campaign period. We basically find the unique reach (how many people watched it) and frequency (how many times they did) by granularities of channels, genres and time-slots such as primetime or non-primetime and even device classes. This way, the brand is able to analyze every factor that contributes to the campaign’s success metrics, and can use it to optimize its future campaigns.
Now the brand can map every action an individual user takes on the app to their TV ad exposure, for example Do they buy something after watching the TV ads? Have they become more active? Do new users join the app?
This way app based brands can accurately measure ROI for their TV campaigns, and use these attribution insights to plan campaigns even more effectively.
Get in touch with us if you’d like to explore this offering for your brand as well!