A New Mindset: Making Bottom-Up, Dynamic Media Planning Work

Published on August 23, 2019
blog, insights

Originally published on AdExchanger

The constant growth in the numbers of devices and media outlets has rapidly changed the ways in which consumers can access content. That has in turn created new challenges for brands to understand how to maximize their digital media investment to yield stronger business results.

Surprisingly, though, many brands still haven’t properly modified their media-planning process to mirror the dynamic behaviors of the consumers they want to reach. Many brands apply a top-down approach by allocating budgets to specific channels, proclaiming that they know where their target users will be.

But today’s consumers flow seamlessly among devices and channels as they go through their media-laden days. Media planning and buying must adjust in real time to match.

The way to capture and engage consumers is with dynamic media planning, which flips the typical media-buying strategy on its head. Dynamic media planning is a bottom-up approach that helps marketers meet consumers where they are.

Dynamic media planning lets media buyers shift budgets among channels and screens and assemble the right creative elements in real time to reach and persuade consumers. It lessens the risk of both oversaturation and missing valuable prospects to instead provide the right levels of reach and frequency.

There are five important capabilities media planners and buyers need to make dynamic media planning work.

1. Fast data 

To make media planning truly dynamic, media planners must access statistically significant levels of data quickly – within hours or at most a few days after consumer exposure to messaging. Ideally, there’s a feedback loop in which data leads to action, which begets more data, and the campaign is continually honed based on increased insights.

It wouldn’t be surprising if eventually planning were led by teams of data scientists. The need to leverage proprietary tools that can merge and organize a brand’s first-party data with rich third-party data will give planning teams an edge in identifying unique value and efficiencies throughout the media landscape. This is already happening to a certain extent.

2. Custom measurement

Today, brands are moving away from single-metric optimizations, such as click-through rates, and toward more custom multimetric optimizations that tie media activity to business outcomes.

For example, let’s say a brand’s business goal is sales. There are several online and offline touch points leading up to a sale that determine a consumer’s propensity to purchase a brand’s product. By understanding the unique weighting of those touch points and developing a custom score, strategists can understand the tactics and budget allocations needed to drive the most effective outcome. This requires a high level of collaboration among the brand, its agency and partners to tie touch points to metrics that meet the brand’s business goals.

In many cases, a single media metric is still used as a proxy for success, and there’s a lot of opportunity left on the table.

3. Tailored AI applications

As custom metrics become more prevalent, the need for algorithmic optimization strategies to generate decisions from large data sets becomes an underpinning for success and scale. Skillful use of artificial intelligence is key. There are many forms of AI, but to leverage AI for optimization, most technologies suffer from the aforementioned insufficiency of focusing on a single metric.

To maximize the value a brand can garner from digital, custom metrics with multivariate components are ideal. For instance, a custom model that applies weighted scores to valuable trends in data can more accurately identify new consumers who are likely to perform a desired action.

Read the rest of the article on AdExchanger

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