Harness the Power of Machine Learning to Drive Performance-based Marketing
Find out how brands leverage CDMPs to navigate the post-cookie era marketing world and grow their revenue.
Brands across the globe are harnessing the power of Customer Data Marketing Platforms (CDMPs) to drive performance-based marketing. Marc Mathies, SVP of NXTDRIVE Vericast, explains how advanced machine learning technologies propel conversions, acquisition, and customer loyalty.
With the loss of third-party cookies, marketers are actively exploring new solutions and strategies to help retailers achieve their goals. Customer data marketing platforms (CDMPs) use advanced technologies and big data to gain insights into consumer behaviors, preferences, and trends.
Marketers across industries have been experiencing a lot of pivotal shifts in recent years regarding strategies, methods, and tools for reaching the consumers they want to connect with. From the phase-out of third-party cookies in Google Chrome to the growing need for more accessibility in analyzing and managing complex data sets, marketers are looking to technology to support them in engaging customers in more meaningful and personalized ways.
Many marketers and marketing teams use a Customer Data Platform (CDP) to help them understand how to reach target audiences. If you’re a marketer, you’re likely already familiar with a CDP and may use one yourself. CDPs bring value in providing brands with a view of how consumers previously engaged with them across platforms. Based on this historical data, brands can develop new touchpoints for engaging consumers on their buyer journey.
However, CDP implementations tend to have a high cost and a wide scope where marketers often compete for organizational prioritization. Marketers start to lose a lot of value with a CDP in the customer activation layer, i.e. when they want to predict the next phase or step of a consumer’s journey with their brand.
Data from a recent study Vericast conducted in partnership with Prosper Insights & Analytics uncovered that 73% of marketers agree most first-party data solutions available are not delivering effective media across channels – from print to digital. This is where a marketing-focused solution can help.
New technology and machine learning solutions are increasingly coming into play to advance predictive capabilities and show marketers what consumers will likely do next, outside of what their past interactions may dictate. We’ve coined this new marketing technology as a Customer Data Marketing Platform (CDMP).
A CDMP takes the guesswork out of managing and acting on a brand’s first-party data. It drives performance-based marketing to propel conversions, acquisition, and customer loyalty while remaining compliant with privacy regulations and adapting to emerging industry challenges in real-time.
A CDMP can empower marketers across industries to drive targeted engagement, enhance consumer experiences, and optimize ROI by leveraging advanced machine learning technologies. These insights can create highly personalized and relevant marketing campaigns that resonate with target audiences.
See More: How Conversational AI Is Enabling Brands To Move beyond Third-party Cookies
Drive Targeted Engagement in the Post-Cookie Era
To effectively interact with consumers authentically and personally, brands must unite their customer data to derive actionable insights that will inform the experiences marketers create for these customers. Sounds easy enough, but while the concept is simple, the execution comes with a distinctive set of challenges.
In today’s post-cookie world, marketers face a unique data dilemma – the overwhelming surplus of customer data makes it harder to glean the right insights for improving brand-consumer engagement. A CDMP can uncover exactly what a brand needs to know about a specific customer to make strategic decisions about how to market to that person.
Using this data to support how a brand engages customers isn’t new. However, a CDMP differentiates because it’s trained to find the right signals through the data noise and can be used for full-funnel tactics beyond the next customer touchpoint.
Know The Customer: Really Know Them
CDMPs offer features like data visualization, data enrichment, predictive modeling, and media recommendations. The platform collects all this information from disparate sources and systems, simplifies, enriches, and applies insights to present an enhanced view of customers.
With all this super-sized customer information in a single place, marketers can figure out what people like and don’t like, using that insight to build tailored experiences that will retain existing customers and acquire new ones. In June 2022, Ryan Stuart of Hubspot wrote about the importance of experience for the ROI: companies that prioritized the experience of consumers saw revenue growth rates 1.7 times higher than those that didn’t, while customer lifetime value increased an average of 2.3 times.
CDMPs also help to organize data data. Marketing teams can query customers into different groups based on age, what they buy, or where they live. Targeted ads that are just right for each group can be deployed to enhance individual experiences and make consumers feel more of an emotional tie to a brand. Giving each customer a personalized experience enables marketers to strengthen those relationships and likely have a positive return on sales.
Boost The Bottom Line
With a CMDP, marketers are supported in expanding their target audiences through personalized and authentic approaches built from the DNA of their customer profile. For example, American Furniture Warehouse (AFW), a lifestyle furniture retailer, was looking to expand its customer base beyond traditional areas the company had already saturated. Their struggle was harnessing their vast customer data to target new regions and boost their revenue. Looking to gauge immediate and future revenue potential, AFW looked to our CDMP to help them diversify media outreach in specific regions.
By unifying and enriching AFWs data, an overlooked opportunity was uncovered. We advised AFW to extend their standard 20-mile trade radius to pinpoint and engage with premium look-a-like audiences within an expanded 40-mile radius.
Reaching out to this broader geography brought AFW a significant 50% customer lift across all segments, bringing in more customers to achieve a 54.7% boost in sales and a more than $350K increase in revenue within the expanded test geography.
AFW can now iterate future media executions in other markets and has concrete evidence that supports continued investment in media channels such as Connected TV (CTV). This campaign leveraging a CDMP helped inform future strategy discussions and resulted in shifts in budget allocations for the brand to favor high-performing media types and drive additional ROI.
CDMP: The Backbone of a Strong MarTech Stack
The business landscape is more saturated and competitive than ever, so investing in a CDMP is pivotal for brands focused on growth. It’s not enough to simply have data. That data needs to be leveraged strategically, and a CDMP provides a comprehensive set of tools so brands can capture, synthesize, and leverage customer data for powerful and personalized marketing campaigns.
Transformative technologies allow marketers to build deeper relationships and achieve greater results in the digital landscape. With the right data tools and a strategic approach to defined goals, brands today can make informed decisions that propel them forward in the competitive market.
Has your business embraced the power of CDMPs and machine learning? What strategies have you implemented to grow your revenue? Let us know on Facebook, X, and LinkedIn. We’d love to hear from you!
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