Cross-channel marketing campaigns allow organizations to create a seamless experience for customers, engaging them at various touch points throughout their journey on any and all of the channels that they might use.
However, ensuring that your campaigns are reaching the right audience, with the right content, on the right channel, at the right time—throughout their entire journey—can be extremely challenging. Plus, marketers are constantly being asked to do more with less. So they need to ensure that their efforts (and budget) are being spent in the right places, with the highest return on investment is paramount.
One of the most foundational and crucial components of making all of this work is data analytics. By leveraging the wealth of customer data generated across different channels, marketers can gain invaluable insights, optimize campaign performance in real-time, and accurately measure their return on investment.
The Cost of Driving Blind
While some modern marketing organizations realize the crucial nature of leveraging data analytics to drive each stage of their cross-channel marketing strategy, many don’t. But the cost of running your cross-channel marketing campaigns without leveraging data analytics to drive the optimization can be pretty significant. In fact, according to Forrester Research, organizations waste an estimated 37% of their marketing spend due to poor data quality and management.
That’s a staggering amount, but it only scratches the surface of the true cost. Without data analytics, marketing efforts become a guessing game. You’re investing budget and personnel resources without valuable insights about your target audience, content or campaign performance, or what truly resonates with your customers. This translates to missed opportunities for engagement, conversion, and ultimately, revenue growth.
How Data Analytics Can Make a Difference
Whether your organization hasn’t been prioritizing data analytics or there’s room for improvement, it’s important to understand the role of data analytics and precisely how data can be used.
To start off, let’s take a look at where data analytics might be used throughout the campaign process and at which stages it might be used.
Real-Time Analytics
In the early days of digital marketing automation, the usual practice was to deploy a campaign, wait for it to be complete and then analyze the results to find opportunities for improvement. However, with the current, fast pace of modern marketing and the technologies that are available to marketers, waiting until a campaign is complete can be a costly mistake.
For example, your campaign may have an error in the way the audience is segmented, or within the journey flow, or there might be a problem with the content itself. Through the use of real-time analytics, you can monitor campaigns after they’ve started and catch errors before the campaign gets too far, you can make adjustments on the fly to save the day. Keeping your finger on the pulse of active campaigns through real time analytics allows you to know about any functional or content related issues, allowing you to correct them before they become true problems.
A/B Testing
Real-time analytics isn’t only used for problem mitigation, it’s also a great tool to leverage for A/B testing. Whether you’re running manual A/B tests, where you actively monitor current message performance and then adjust flow to winning variants, or your campaign automation software does this for you automatically, being able to monitor what’s happening with the variants in real time can provide valuable insights and help you make optimal, automated changes when needed.
Post-Campaign Analytics
Once the messages on all of the various channels have been deployed and enough time has passed to allow subscribers to interact with the content, it’s time to do some post campaign analysis. At this point, you’ll look at standard metrics such as opens, clicks, unsubscribes, message delivery (push & SMS), dismiss/close (push, in-app) to find areas of opportunity where you might iterate on content items, message timing, channel efficacy and campaign flow.
Aggregate Campaign Analytics
While basic message interaction metrics are essential, they only represent part of the picture and analyzed within a silo, they can sometimes lead to inaccurate conclusions. To see the whole picture, marketers need to understand the contributing events that transpired prior to message deployment as well as the actions that took place after subscribers clicked on those messages. Combining this data to pieces together a detailed picture of overall performance— which is where aggregate campaign analytics comes in.
A common best practice for aggregate campaign analytics is to export all message interaction data up to a data warehouse, storing it alongside historical customer information and transactional details. By merging these datasets, marketers can see the complete customer journey. Upstream data from social media and advertising platforms becomes even more insightful when analyzed alongside downstream metrics like registrations, sign-ups, and sales from CRM or e-commerce platforms. This unified view empowers marketers to understand campaign effectiveness, customer behavior throughout the entire funnel, and ultimately optimize their campaigns for better results.
Traditionally, getting the wealth of customer data from your cross-channel marketing platform into a data warehouse might have involved working with data engineers to build custom data pipelines. This could be a time-consuming and resource-intensive process. Thankfully, some modern marketing automation platforms now offer built-in solutions to simplify data integration.
Necessary Components of Data Analytics
Now that we have an idea of the types of data analytics we’d leverage to optimize cross-channel campaigns, let’s dive into what would be required to accomplish it all.
1. Data Capture
The first and by far most crucial component of a successful data analytics strategy is capture. To report and analyze customer behavior across channels, organizations must first build the infrastructure to capture customer interaction data. This is where many organizations tend to fall short. They’ll often build out their tech stack without data capture considerations and, as we all know, trying to build new functionality into established systems after they’re implemented is challenging.
The good news is that message interaction data capture is built-in with most modern marketing automation tools.
2. Data Integration and Management
The cornerstone of leveraging data analytics for cross-channel marketing campaigns is a robust data integration and management process. This involves creating a central repository, like a data warehouse , to house historical data from your marketing channels.
Think of your data warehouse as a central library for your customer journey data. By storing information from various sources in a unified format, you can analyze how customers interact across different touchpoints and understand how each channel contributes to the overall marketing funnel. This storage and management mechanism empowers you to identify trends, compare performance across channels, and gain deep customer insights. Having a place to store, access and manage this data is crucial but the magic happens when you bridge the data gap between your various marketing tools.
For instance, with features like Iterable’s Smart Ingest, co-developed with Hightouch, marketers can seamlessly connect Iterable directly to their data warehouse, eliminating the need for complex engineering tasks. This empowers marketers to take control of their data strategy and focus on extracting valuable insights, rather than wrestling with data extraction processes.
3. Data Analysis and Reporting Tools
The journey from raw data to actionable insights requires the right tools. Business Intelligence (BI) tools, people, and processes play a crucial role in this process.. BI can help you clean, explore, and analyze your marketing data from various channels.
Once you’ve extracted these initial insights, it’s time to transform them into a compelling story. This is where data visualization comes into play. Marketers can leverage data visualization tools to identify trends and compare performance across channels.
4. A Culture of Data-Driven Decision Making
Building a successful data-driven marketing strategy goes beyond just the technical aspects. It requires fostering a culture where data informs decision-making across the organization. Organizations that value customer data are more likely to invest in the necessary tools, resources and processes while encouraging a data-driven approach within their teams.
Conversely, organizations that struggle to leverage customer data in this way tend to have a culture that does not prioritize these investments. According to a study conducted by Harvard Business Review, 79.8% of executives surveyed identified cultural impediments, not technology, as the greatest barriers to becoming data-driven companies.
Open to Collaboration
Collaboration is another key element. Marketing teams should work closely with data engineering, data analysts, and IT teams to ensure a smooth flow of data collection, analysis, and communication of insights. Regular communication and collaboration help bridge the gap between data and action. This is where that executive sponsorship can help by driving the data-first strategy to break down silos and encourage cross functional collaboration.
It’s important to encourage data literacy among marketing teams. This involves providing training and resources to help marketers understand and leverage data effectively. When everyone has a basic understanding of data and its potential, organizations can unlock the true power of data-driven marketing.
From Insights to Results
By leveraging the power of data analytics, you can gain a deeper understanding of your audience, optimize your cross-channel marketing campaigns, and ultimately achieve your marketing goals. Remember, data is a powerful tool, but it’s up to you to transform it into actionable insights that drive real results. So, get out there, embrace data analytics, and take your marketing campaigns to the next level.
To learn more about Iterable’s data activation capabilities, explore our Ingest Toolkit or schedule a demo today.
