When it comes to customer analytics, companies are at various stages in their gymnastic careers, with trials for the Olympics fast approaching. It's time to raise the bar. In order to reach the next level, firms, like gymnasts, must have a strong understanding and demonstration of their analytics capabilities across multiple dimensions to qualify for the competition:
- strategy, which projects a company's level of commitment to analytics;
- organization, which speaks to keeping all data in-house or partnering with others to fill the gaps of their internal capabilities;
- data, which is the lifeblood of customer analytics, and how companies parse the data and manage different streams;
- technologies, to determine how data is used to create predictive models, which can ultimately lead to decisions that can enhance customer intelligence; and
- process, which involves how insights are derived, shared, and prioritized within the organization.
We find that firms typically fall within four maturity categories, depending on their capabilities in each of the five dimensions outlined above.
Rookies. These firms do not formally invest in customer analytics; they treat it as an uncoordinated and ad hoc activity tied to overall business intelligence and business analytics activities. Rookies' analytics teams consist of marketing generalists working with limited behavioral data available in transactional systems.
Dabblers. Firms in this category have some type of customer analytics capability aligned to meet business needs, for example, by brand or region. They support primary business objectives of acquisition, retention, and loyalty with a foundational segmentation approach to marketing. Dabblers augment behavioral data with customer interaction data from the Web site and email channels and typically react to business needs with customer analytics solutions.
Pros. Those in this category treat customer analytics as a strategic priority, use advanced predictive analytics for customer analysis, and are proactive about infusing insights into the business that drive customer decision-making. Customer analytics is tied to digital analytics, attribution analysis, marketing, and business analytics. Pros extensively use customer lifetime value as the guiding metric to plan their customer portfolios.
Gurus. Firms in this category use customer analytics to influence every customer interaction and improve customer experience across touch points. A multidisciplinary team of business-savvy marketing scientists and marketing technologists work with a customer analytics platform and services partner network. Customer analytics has significant executive buy-in and is used to guide decisions that drive business metrics across the customer life cycle. Formal ROI methodologies build the business case for customer analytics investments.
With a firm grasp of the analytics persona that your firm closely represents, you need an understanding of the tasks required to advance from one maturity level to another. For example, for dabblers to become pros, they must measure ROI at the campaign level and link it to customer segmentation, while pros aspiring to become gurus must use cross-channel attribution methods to establish the incremental impact of marketing campaigns. To plan a detailed road map, firms must do the following:
- Define the urgency. How late in the game is your firm? Are you playing catch-up to peers or leading the way?
- Outline the time frame. The urgency will help determine the time frame of efforts. For your organization, understand whether a three-month time frame is considered short term and what the appetite for change is within a given time frame. Some efforts and initiatives will take longer than others.
- Plot the tasks. Use a prioritization framework to sequence the tasks in the road map and focus first on the must-have and should-have tasks. Visualize the effort involved in building an effective customer analytics capability and communicate the vision to the rest of the organization.
In the end, for some firms moving toward customer analytics maturity, the analytics planning road map may mean going from the high beam to the uneven bars, and to others it may mean just getting the chalk on their hands.
Sri Sridharan is a senior analyst at Forrester Research, serving customer insights professionals. Her research agenda focuses on customer analytics best practices and technologies, services, and analytical applications that convert customer data into meaningful insights.