The TV industry has been clamoring for a solution on attribution for obvious reasons — cord-cutting and digital have eaten into TV ad budgets.
Unlike digital media, TV can be notoriously challenging to measure, but it’s also one of the most powerful channels in the marketing toolbox. TV advertising can help reach a massive amount of people — quickly — but proper measurement has been a tough nut to crack. There is no longer a straight line from long-form direct-response TV to 1-800 numbers or from vanity URLs to purchase. This is where TV attribution comes into play.
Effective TV attribution requires an approach driven by data science rather than assumptions, intuition and other questionable correlations that could be used to describe the “good enough” measurement techniques of the past. It approaches measuring TV’s performance differently by applying analytics to data and uncovering what’s truly working and why, definitively proving ROI.
Successfully implementing these metrics depends on organizational readiness in three primary areas: Data, technology and cultural framework. Whether you’re handling the analytics in-house or partnering with a solution provider, here are three steps to get started.
Define Your Business Goals
TV attribution starts with a clear understanding of what you’re trying to measure and how you want to use that information. A robust measurement practice answers specific and targeted business questions such as:
■ What is my baseline without TV?
■ What is my TV ROI?
■ Where should I spend my next dollar to maximize TV return?
■ What stations, programs and/or creative are most effective?
■ What tactics will get me more scale?
■ How can I get conclusive results for testing with these programs or spots?
■ How does TV influence other channels in my media mix?
Answering these questions will help map the appropriate KPIs needed to ensure everyone is on the same page with what’s being measured and why.
Collect and Prepare Your Data
A necessary component to get up and running with TV attribution is getting access to the right data sets.
Data ownership and governance continues to be a huge issue for marketers. Historical data may be paramount for analysis, but it’s found within multiple silos such as your technology partners and agencies and spread across multiple systems of record. Make sure there is a centralized source of marketing data that partners can feed into, with identified owners. This way, you can ensure the data is supporting the organization’s growth as transitions are made while also facilitating future analysis.
To enable accurate modeling, put two years of historical data in place to ensure the capture of seasonality and of dynamic patterns of consumer behavior. A year or more of historical data enables advanced machine learning algorithms to uncover impactful trends and insights.
Analyze for Trends and Insights
With your data collected and prepared, you can go beyond basic statistical analysis to find real answers. Depending on your business objectives, you may focus on long-term baselines or short-term impacts. A well-planned approach will help with both.
Once the trends and impacts are identified, the benefits of TV attribution are undeniable. They include insights on the best ad lengths, categories or programming changes to cut back on waste and find new customers and evaluate which time of the day works best.
TV attribution gives marketing organizations a powerful way to make effective decisions and get the best return possible for TV media spend and a solution can be implemented in a couple of weeks! TV marketers shouldn’t have to settle for “good enough,” and with these steps and paths crossed, you’ll be able to gain fast, accurate, actionable insights designed to drive business impact.
Brian Baumgart is co-founder and CEO of Conversion Logic (conversionlogic.com), a cloud-based marketing analytics platform. For a longer version of this piece, go to multichannel.com/Feb19.
Weekly digest of streaming and OTT industry news
Thank you for signing up to Multichannel News. You will receive a verification email shortly.
There was a problem. Please refresh the page and try again.