It’s no stretch to say the marketing data landscape has changed quite a bit over the past two years. For one, the ways companies collect user data have been under the microscope, and policies from Apple and Google are forcing marketing data analytics changes across the board.
Also, customers are more thoughtful than ever about what information they’re willing to share and how it’s being used. Finally, scalability and personalisation have become buzzwords, but you can’t accomplish either without strong analytics – and getting that has been an uphill climb for many businesses.
How are companies succeeding in this new era of marketing? We spoke with marketers from Cox Automotive and Sobeys about charting their own paths forward and how they’re finding ways to connect with customers in this complex landscape.
Here’s how those companies adapted their marketing data analytics to become more efficient and improve outcomes across the customer journey.
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Rethink your marketing data analytics strategies
The movement toward consumer privacy protections is accelerating, and that’s a good thing. However, the downstream effects of increased data collection restrictions mean various metrics — like open rates and measurement methods used to benchmark success — are no longer reliable. Because of this, you’ll need to shift your strategies.
As the previous metrics of success are deprecated and customers are increasingly experience-oriented, marketers are realising how important it is to gain a more complete view of how campaigns are performing. Instead of evaluating marketing channels individually or in silos, they are assessing performance across all investments together as part of a unified strategy. Last year, 83% of marketers described their cross-channel coordination as dynamic as opposed to siloed or duplicated – up from just 68% in 2021.
Marketers are also more focused on first-party data — information gained directly from the customer. Instead of relying on old systems like open-data exchanges to buy audience data, they are modernising the way they build first-party data assets through the lens of user consent.
Cox Automotive has spent the past two years building a more complete picture of prospects and clients, including combining role, engagement, and product purchase data from across its brands into a centralised location. Now, their teams can target specific audiences with custom product or service messages.
By unifying their data, Cox Automotive can better segment their audience and deliver more personalised messaging to their customers. They have defined value by segment and role so they have a clear idea of the problems they are solving and the messages they need to convey for each product.
Use automation to free up time for smarter insights
Having a clear vision for your marketing data analytics is critical for a successful marketing strategy. And building a trusted data foundation is the first step in executing on that vision. Automation can handle menial tasks like gathering and segmenting data, giving you a clear view of the information you need to make decisions.
Marketers are using a growing number of different platforms in their tech stack to advertise, engage customers, deliver better experiences, and ultimately get people to convert. This complexity often leads to teams spending too much time on connecting and harmonising data to create reliable insights instead of optimising their efforts.
Instead of relying on a jumble of platforms, you can invest in automated data governance to relieve your teams of manual data aggregation. This includes managing campaign naming and taxonomy, tracking requirements, data delivery, and quality assurance.
A proper marketing intelligence platform facilitates data connections, with all clicks and no coding. With a platform that uses technology like automation and AI, you’ll spend less time on data prep and more time on connecting with customers.
But it’s not only about connecting the data. Marketing intelligence helps harmonise it to create a consistent framework that enriches raw data: helping you find actionable insights, rather than get lost in a sea of data points. You can take this even further with automated taxonomy management, flexible harmonisation logic, and holistic data governance tools.
With an accurate data foundation that evolves with the changing data ecosystem, you’ll move more efficiently and gain time back to do more testing and learning. The end result? Less wasted time trying to decipher inaccurate marketing data analytics, a better return on your investment, and happier customers.
Turn insights into outcomes with marketing data analytics
With access to cross-channel and first-party data, you can measure customer-based outcomes across an entire marketing journey. Then, you can use those insights to achieve your marketing initiatives. For example, instead of focusing on upper-funnel metrics like clicks and opens, marketers can optimise for downstream outcomes such as signups and purchases.
Grocery chain Sobeys is using qualitative and quantitative data to improve how it measures success across the customer lifecycle.
“What gets measured, gets done,” said Erika De Haas, vice president of marketing communications at Sobeys. “As we continue to build our connected full-funnel experiences, establishing clear baseline benchmarks based on all of the first-party data we have will be critical to not only connecting our experiences but driving their impact and growing our loyal customer base.”
Sobeys’ strategy is to approach the sales funnel as one connected experience, with every interaction helping build customer loyalty.
“At the top of the funnel we focus on which emotional benefits drive Canadian families to choose Sobeys. We research brand preference, and what matters most is brand ownership and equity,” said De Haas. “As that same customer moves through our funnel, we develop communications and experiences that provide more functional benefits, and success is more measured on transactions.”
De Haas said Sobeys’ success will always be measured by the same metric: Is it providing families with what they need so they continue choosing Sobeys as their place to shop? Now, the team has new tools to achieve that metric across the customer journey.
“Knowing if our customers engage with our brand at the top of the funnel but drop off in the middle will require a different strategy than if they’re engaged at the middle but drop at the store,” she says. “Monitoring our data in a holistic way will be the difference-maker that ensures we are connecting our customers with our brand throughout the entirety of their journey with us.”
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Connect with customers across your channels
Once you have your strategy, automation, and insights all in order, the next step is putting them all together to start generating engagement across all your channels. That engagement generates more high-quality first-party data, which in turn leads to more data analysis, better insights, and even better engagements on the next go round, as your data analysis operation grows into self-perpetuating and self-improving marketing powerhouse.
The first step to getting there is building connected customer journeys that guide every customer through relevant interactions across their favourite channels. That will mean different things for different businesses – maybe for you it’s about increasing engagement in your customers’ inboxes, or reaching them at the right time via SMS.
But no matter what the individual steps along the way might be, you can build the perfect journey from good strategy and clean data, with AI helping your customers along the way as sort of an invisible tour guide.
You can find more success on that journey by being smart about automating elsewhere. Using first-party data instead of cookies gets you lower cost conversions. Automating more basic customer communications saves time and frees up your marketers to do more big-picture work.
That all may sound like a lot to manage, but with the right intelligent reporting and a connected dashboard, you can easily keep track of all of it in one place. You can get the most from your marketing data analytics when you let AI and automation eliminate the guesswork, letting you focus on your customers.