Key Takeaways

Most marketers want to answer one key question: Did my ads actually cause new-customer behavior, or would the people who saw my ads have converted anyway? 

As marketers brave the new world of increasingly complex targeting, cookieless attribution, and analysis strategies, the need for an all-encompassing measurement method is increasingly apparent. 

Omnichannel marketing is the integration and cooperation of the various channels organizations use to interact with consumers, with the goal of creating a consistent brand experience. This includes physical (e.g. stores) and digital channels (e.g. websites). The goal of an omnichannel marketing strategy is to create a convenient, seamless user experience for consumers that offers many opportunities for fulfillment.  An omnichannel strategy may give consumers the chance to find and purchase online, in-store, or a combination thereof – such as “buy online and pick up in-store”. Today, organizations across industries are leveraging omnichannel strategies, including healthcare, retail, finance, technology, and more.

The Role of Speed to Insight in Marketing

A Single Customer View (SCV): Everything You Need to Know

For ages, achieving optimal model accuracy has been revered as the ultimate goal, with marketers relying on model fit as the benchmark for discovering the ideal equation that harmonizes with their data. However, what if there’s a deeper layer to model accuracy beyond mere numerical alignment? What if we challenge conventional wisdom and explore alternative dimensions of accuracy that transcend traditional models?

explored the origins and convergence of Data warehouses and Customer Data Platforms (CDPs) and how their integration has become the cornerstone of modern enterprises’ growth strategies. As we continue the series, we’ll focus on building a cross-functional team to maximize the potential of data warehouses and CDPs working in tandem. We’ll identify critical stakeholders from engineering, data, and marketing and discuss strategies for uniting them to address use cases and drive innovation in customer engagement and retention.

You’ve heard the buzz about customer data platforms. You’ve heard the letters CDP bandied about. Maybe your boss asked you if your company needs a CDP. Maybe you’re a boss wondering the same thing.

If you dream of achieving better business results with less effort, allow us to introduce you to marketing automation.

Every marketer understands the importance of collecting and utilizing customer data to streamline your customer relationship management, your marketing efforts, and to increase conversions. But before you can put all of your customer data to work, you need to choose the right tools for the job. 

Want to make more sales? You’ll need to gather lots and lots of customer data. 

The marketing industry constantly changes, and new techniques and technologies are being developed daily. One promising development is the growth of generative AI in marketing. Traditionally, marketing relies on machine analysis and human prediction. However, generative AI allows for greater creativity and effectiveness by leveraging the speed of a machine with how about saying ‘super-human’ instead of ‘human-like’ predictive abilities. This rapidly growing technology can automate content generation, design, and strategy with algorithms and machine learning, providing a window into the evolving future of marketing.