The biggest platforms in the digital advertising landscape — Google, Amazon, Apple and Facebook — are making huge changes to accommodate current and upcoming consumer data regulations. And while many marketers bemoan this loss of data, thinking it will make it much more difficult to manage client campaigns, Sam Tomlinson, executive VP of strategy and analytics at marketing agency Warschawski, says this data, by itself, was never as valuable as once believed.
“Decision-making was never that simple, and some of the data that may have been taken away wasn’t that good,” said Tomlinson in his presentation at SMX Next. “The same thing goes for conversion tracking; we have had that for a long time and it’s been hit-or-miss.”
“Just because some data has been taken away and some control levers have been taken away doesn’t mean that we’re in a world of hurt,” Tomlinson said. “It just means we have to adapt.”
There are still plenty of actionable insights to be gleaned from the data that is available. Here are three ways Tomlinson says marketers can succeed with PPC despite having access to less data.
Improve data measurement with marketing mix models
“The world is bigger than PPC,” Tomlinson said. “For over a decade, PPC’s have been focused on conversions and using last-click attribution models. And that let us obsess about this little world that is ‘PPC’ and forget about the big world that is ‘marketing.’”
Tomlinson recommends marketers grow their data pool using marketing mix models (MMMs), which are statistical analysis methods that determine the effectiveness of campaigns by measuring the impact of marketing strategies alongside sales and customer retention efforts.
“Historically, they [MMMs] have been staggeringly expensive and incredibly complicated and have taken weeks, months or years to put together,” he said. “But now, we can open-source them. If you have an intern who knows Python, they could make one in a couple of days.”
Marketers can gather even more customer insights by adopting automated MMMs. Tomlinson cited Facebook’s open-sourced Robyn as an example, which aims to reduce human bias in data measurement.
“An automated MMM ingests data using cloud computing and cloud storage, taking what had historically been a barge of a tool and turning it into a speedboat with rocket engines on it,” said Tomlinson. “We can now experiment and calibrate our models.”
Obtain more accurate client data
Having access to less data isn’t the only issue affecting PPC campaigns today; many marketers fail to let clean, accurate client business data inform their strategies.
“Most agencies or freelancers just don’t know their clients’ businesses that well,” said Tomlinson. “They don’t know how their clients make money. They don’t know the cost of revenue, their cost of capital, their target rate of return, or the time horizon for that return.”
Tomlinson also noted that most agencies don’t have realistic forecasts or models for clients. Without an accurate view, marketers are “going to be lost in this dataless world.”
To address this issue, he recommends marketing teams combine both client business metrics and campaign metrics into one spreadsheet, letting these sets inform each other so mistakes are avoided.
As an example, Tomlinson shared an integrated data sheet (shown above) to show how this information can be cross-referenced: “I’ve combined some of those basic metrics that campaigns export with some of our clients’ business metrics. That includes their cost of goods sold, their cost of capital and their time horizons for return. And those have allowed me to calculate our net present value per click.”
“This data is available to you and can be put into your platforms. We just don’t do it enough,” he added.
Use lower intent goals in your campaigns
Despite the digital advertising landscape becoming more and more dataless, the machines that make campaigns run continue to demand it. And while they need less data than in years past, they still require a lot to be effective.
Unfortunately, the upcoming deprecation of third-party cookies and other identifiers leaves many gaps in this data, making it more difficult for marketers to procure seamless, actionable customer information.
“There are more and more gaps in that data,” said Tomlinson. “Apple restricts tracking, Google deprecates cookies, Firefox deprecates cookies and other providers don’t allow data collection on third-party websites. That poses an interesting challenge because now we aren’t able to connect as many dots as we used to be.”
Tomlinson says marketers should address this issue with lower intent goals, which can help them forecast consumer behavior despite lacking the insights from higher-value actions: “So, instead of conversions, we may push the goal up a little bit and go for a white paper download. Something that allows us to capture first-party data earlier in the journey and also feed that data into the machines to help us measure incrementality more accurately.”
Capturing customer data earlier on in the process can set marketers up for success in the long run. This will help prevent unforeseen events from derailing campaigns — something that happens far too often when marketers focus solely on bottom-of-funnel goals.
“Lower intent goals serve as useful forecasting barometers to make sure that we’re on track,” said Tomlinson. “Since our end conversions get fuzzier and that path gets muddier, we want to start tracking earlier before all the mess destroys the integrity of our data.”
“The one way we do that is with lower intent goals and emphasizing our data capture earlier,” he added.
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