The introduction of “Web 2.0” initiated a massive increase in data volumes in 2005; then 2007’s emergence of the big data craze sent organizations scrambling to organize, clean, acquire, and store massive amounts of data. After data warehouses were filled and the foundation was created, a new challenge emerged: how does a large enterprise company leverage all that data to create relevant experiences for its customers?
Forrester research states that while 73% of companies can agree they need to be data-driven, only 29% confirm they are successful at connecting analytics to action. While most organizations now have an infrastructure in place to capture data, many are unclear on how to best use it to inform decisions and marketing investments. So where do you start? It’s important to establish a process and a framework. To help you get started, below is a field tested three-phase framework to data execution.
Phase 1: Data Gathering
The first phase involves activating the technology and tools that set your data foundation. This ranges from basic customer relationship management (CRM) tools and transactional data to more advanced behavioral data, online tracking, and offline data capture.
If executed properly, you can enable an initial 360-degree view of the customer. Full-spectrum data gathering capabilities touch each checkpoint of a customer journey, including the time before the customer lands on a business's webpage, behaviors once they’ve interacted with the page (such as clicks, views, and time on page), and eventually conversions (for example, a purchase in a B2C environment or a form completion in B2B).
At this primary level, a brand's technology, tools, and strategy can accurately follow and collect a customer's information to form a foundation that helps a brand understand the customer and his or her journey to convert.
As mentioned, one of the biggest hurdles for brands is advancing past this initial collection phase. To do this, it’s essential to develop a strategy to move from data to insights. Here are a few key variables to consider as you’re gathering information:
- What questions are you hoping to answer with the data you’ve gathered?
- Which stakeholders (e.g. product owners, developers, content creators, media channel owners, and general business leaders) need to be informed?
- Are there any major changes or updates coming soon to your web experience that require consideration when preparing for analysis?
Developing a clear vision and combining this vision with the right resources (e.g. technology and data experts) will allow for a seamless transition to the next phase.
Phase 2: Insight Creation
Now that you have your data and a strategy, the next step is to select a data set, manipulate and mine it for patterns, and then apply business logic to create insights you can leverage. These insights can enable better decision making, illuminate new segments or groups to target, and even help identify key pain points or opportunities that may require immediate adjustment within the customer's experience. Generally, a structured, organized data set can reveal a variety of low hanging fruit and provide initial descriptive insight into device usage, demographics, geographic information, and basic conversion metrics.
Though basic insights—such as the correlation between behaviors and conversion—are valuable, it often takes more advanced analytical techniques to uncover the largest opportunities within the data.
One example of an advanced technique marketers can use is developing data-driven personas with statistical software and clustering algorithms. By leveraging behavioral segmentation to group similar customers into clusters based on website and CRM data, brands can better understand these individuals. This allows enough insight to strategically target specific groups or people and optimize one’s brand experience.
As we move into the next step, note that to successfully activate and deploy data-driven solutions, a brand must develop a culture of testing and ensure it is adopted across all involved departments. Though initial data can be convincing, a data-driven approach would recommend any and all changes be tested through a testing software or random segmentation approach, which can provide a number of indicators on how to evolve a customer's experience. Conversely, acting hastily, without undergoing appropriate testing, can create new problems or leave you worse off than before. Aligning teams such as marketing, analytics, development, and strategy around how insights will be used to influence the decision-making process is key and enables you to effectively activate on the data, which leads us to the third and final phase.
Phase 3: Activation
Regardless of how impactful your initial analysis and insights may be, if you are unable to execute business change or enable stronger decision making, the investment in the data process is lost. Activating your insights to optimize, execute, and measure changes allows you to drive measurable ROI and increase customer satisfaction. Each of your data-driven programs should align to a key business goal, even before the data gathering tools are implemented. Holding the analytics and business teams accountable in achieving this goal will enable the company to work cohesively and ensure these key data investments are producing results.
Avoiding confirmation bias is one of the most difficult challenges analysts and businesses face when it comes to data analysis, so it is key to separate the signal from the noise. By agreeing on a decision-making process before the data is available, as well as having project management teams in place, you’ll have a much easier transition from insights to action. It can’t be stressed enough that this must be done from the top down, starting with your key business executives.
What does data activation look like? It can come in many forms such as updating a landing page, executing a new marketing campaign, changing design and user experience on your site, and even potentially doing nothing at all. Data will often recommend the current state is preferred to any alternatives--and this should not be considered a loss. At Rise, we’ve helped clients make hundreds of data-driven decisions, from redesigned websites to revamped media campaigns; and each has opened the door to opportunity for further insight.
Whether you’re gathering data, leveraging analytical tools to foster insights, or activating data-driven marketing solutions, there is always room for continuous innovation.This involves optimizing efficiency and accuracy, recognizing that the customer is always evolving. For more on how to leverage “next level” data opportunities or for recommendations at each phase of execution, reach out to Rise.