Create a Whole Customer View by Combining Digital and Non-Digital Data
by Bret Gundersen
posted on 05-31-2016
Recently, I spoke with a financial-services company that was building a data lake from which all customer information would be available for mining. When I asked what actions the company would take once their data was pooled, the response was familiar: “We don’t know yet.”
In the 1990s, data about online-marketing activities (websites) was owned by the information technology (IT) team. Anyone who wanted access to that data had to get in line. Decision makers today have much more access to data-driven insights with tools like Tableaux, Power BI, and Domo that can pull information out of data warehouses and put it into the hands of business users.
The problem, though, is that only specific types of questions can be answered using these tools. Fully understanding who your customers are is MUCH harder: “Who drove this spike in traffic?” “What did these people do before they took this action?” are the kinds of questions smart tools can answer that others just cannot. AND, these are the questions that drive meaningful improvements in the customer experience.
Smart Tools Are Essential to Stronger Data-Driven Marketing
Cross-channel analytics tools that marketers can understand — and with which they can engage — are a crucial part of any data-driven marketing campaign. But, not just any tools will do. Smart tools will enable a conversation between the marketer and his customer data. In my view, your tools need to accomplish three things:
1. Tools Should Make Flexible Querying a Reality.
Tools should empower marketing teams with the ability to flexibly query data — not just spit out reports. Executives are saying, “Hey, we’re going to bring all the data together so we can query it and understand it.” That is absolutely the right thing for any company to be doing. They should be investing in bringing their data together in internal warehouses.
But, they must have a mechanism to enable a conversation, to interact using an easy-to-learn data-query interface. For example, Adobe Analytics allows attributes from customer-relationship management (CRM) systems to be combined with Web data for a wider view of online customers. This data can then be queried by thousands of people in an organization. Adobe’s Data Workbench provides a full, cross-channel view of customer behavior — and you don’t have to know SQL to use it!
2. Tools Should Help You Get to Know Your Customers on Deeper Levels.
Tools should also empower marketing teams to look at much more than visits and visitors, and instead, focus on actions that affect ROI. They should change the conversation entirely to a conversation focused solely on your customer. Business intelligence is much more valuable when you start to understand your customers as people and uncover how and why they buy.
3. Tools Should Focus on People-Centric Analytics.
By “people-centric analytics,” I mean the type of analysis that changes the mindsets of people within the organization so they look at what does and does not resonate with your customer at a personal level. Unfortunately, most companies see analytics as a means to gain insights on content only. How effective is my campaign? How effective is this page? How many clicks is the call to action (CTA) getting?
However, the more you rely on people-centric analysis, the more you change the mindsets of people in your organization. What are your customers doing when they engage with your brand? How are they purchasing your solutions? Your entire organization is then focused on the right target — using tools that surface behaviors not results. For instance, at Adobe Summit 2016, we revealed an Adobe Marketing Cloud feature, called Segment IQ, through which you can surface insights from certain populations. Who responded to my messaging? Who went all the way through to purchase? You can understand specific behaviors across an entire market segment.
Adobe Has Been Doing This for Years!
At Adobe, we have been unlocking data by using the initial capabilities of cross-channel analytics within a Web interface for a few years. Here is just a sample of the different ways to ask “who” questions in Adobe Analytics (and we have more coming):
- Transaction ID Data Sources will connect offline data to online data via a transaction ID that ties to the customer.
- Customer Attributes (released last year) is intended explicitly to take data from your CRM system and upload it into the Web-based interface.
- Contribution Analysis (also released last year) will identify an anomaly in any trend — and uncover the metrics, dimensions, and customer attributes that relate to the anomaly — uncovering who contributed to the spike or drop.
- Segment Comparison (coming in June) will also query every behavior and dimension of visitors in a segment to identify what is statistically different between those users and everyone else.
Smart Tools = Smart Businesses
With smart tools, you have the ability to enable meaningful conversations with customer data. For instance, looking at a gold-member customer segment that has an amount of revenue associated with it, you could ask “Which products did they buy?” or “What is common among people who respond to my back-to-school campaign?” The good news is that your questions can easily be answered in a Web-based interface that doesn’t require extensive training for marketers to use.
Smart tools help smart businesses turn content analytics into customer intelligence. And customer intelligence is revolutionizing how brands interact with and optimize customer experiences. Welcome to the future of marketing, folks. Isn’t it amazing?