For the third year in a row, Adobe Analytics was named a leader in Gartner’s 2017 “Magic Quadrant for Digital Marketing Analytics” research report1. Of the 12 vendors evaluated, Adobe was positioned as the highest in “completeness of vision” and the second highest in “ability to execute” in the Leaders quadrant of the classic industry report.
So why does Adobe Analytics continue to fare well in this and other analyst evaluations? We believe the role Adobe Analytics plays in the larger Adobe strategy has everything to do with it.
Think about the experiences your customers have with your brand in digital, mobile apps, email, social as well as connected cars and even voice assistants. Are they experiences that your customers and prospects enjoy? Do they make your customers love you more, or wish they didn’t have to deal with you? Do your digital experiences accomplish the goals you’ve established for them?
We’re now in the era of experiences. Experiences are considered the difference between what makes a brand a leader and a laggard in any industry. In fact, using customer experience data to evaluate both transactional and subscription businesses, Harvard Business Review found that customer experience is a major driver of future revenue growth.2 As consumers, this finding shouldn’t surprise any of us. As digital marketers, we’re all trying to figure out — how do I create digital experiences that my customers will love?
In my experience working with customers of all industries and sizes, one thing stands out — customers who are truly insight driven are outperforming their competition. They create compelling digital experiences based on customer insights. They use the best-in-class analytics tools to measure their customers’ journey across devices and channels and then translate that data into behavioral insights. The customer experience leaders are moving beyond standard reporting to customer analytics including advanced segmentation and prediction. Of all the vendors in this report, Adobe facilitates this the best because we have the most in-depth behavioral pathing, the most powerful segmentation, and we deliver it within a user-friendly experience, Analysis Workspace, that is second-to-none.
With different objectives, purchase cycles and marketing strategies, most marketers and analytics teams are still struggling to move beyond standard reporting. In fact, according to Econsultancy, most cite “improving data analysis” as a top factor to how they expect to improve the customer experience.3
To help you develop better insight about your customers, here are four best practices that use the powerful capabilities within Adobe Analytics:
1. Flow Exploration & Fallout Analysis: the first step to delivering great customer experiences is having an understanding of how people are navigating your digital channels and where they are hitting stumbling blocks — some people call this “behavioral pathing.” One of our behavioral pathing tools in Analysis Workspace is called Flow Exploration. It lets brands visualize customer movement through digital experiences, showing the steps taken from entry point through to conversion or churn. Users can easily overlay key metrics to further break down and explore user behavior, allowing them to drive improvements on content and flow which increases the likelihood of conversion and retention. When you discover a common usage pattern, you can now create a dynamic audience segment of that cohort of users.
2. Analyzing Cohorts: Suppose that you want to analyze how customers who sign up for your newsletter or install your app engage with your brand over time. Does signing up for your newsletter increase a customer’s likelihood to purchase over time? Are customers who install your mobile app more likely to remain loyal in 6 months? A Cohort Report within Analysis Workspace allows you to isolate a specific event and then see how often the same users completing that event go on to complete a future event. It’s a powerful analysis tool that helps you better understand how your digital experiences are impacting your customers lifetime value.
3. Comparing Customer Segments: Segmentation is a core strategy crucial to any marketer’s success. Segment Comparison within Analysis Workspace intelligently discovers the differences — and similarities between your sets of target audience segments through automated analysis of all underlying metrics and dimensions. In speaking with customers, we see analysts spending an incredible amount of time comparing various segments in order to understand the actionable differences between them. Segments often overlap with each other or have non-obvious differences lurking deep within the data, and uncovering these insights is like picking a needle out of a haystack. With Segment Comparison, marketers and analysts use the simple construct of a Venn diagram to gain new visibility into which segments are most important to their businesses and why, so they can acquire and convert customers much more efficiently—saving time and budget.
4. Enrich Customer Profiles with Offline Attributes: One of the most helpful ways to improve your ability to understand your customers is to enrich your first party behavioral data with offline customer attributes such as CRM data. This helps analysts and marketers develop better customer segmentation enabling more effective measurement of your marketing campaigns, messaging and digital experiences. Some common examples of enriching your customer profiles through what we call Customer Attributes include: applying loyalty, demographic or lifetime value to your visitor data. This revolutionizes the way you see your customers, leading to better insights. Better insights inevitably lead to better targeting, messaging and optimization of digital experiences.
These best practices are just a sampling of what our leading customers are using to extract insight about their customers and put that insight into action. It’s no longer enough to simply be data-driven. Organizations need the systems and tools to be able to turn data into insight and insight into action as quickly as possible to optimize digital experiences. The cost of companies satisfied with status quo insight tools is the difference between being a leader and getting left behind. Standard web analytics will no longer suffice. In the era where experience is the differentiator, organizations need the best-in-class customer intelligence tools and best practices.