Customer analytics have never been more important, but effectively creating and managing them is not easy. The data that’s required to achieve visibility into all customer activity involves many applications and systems and it’s a challenge to ensure the data used is accurate and consistent. Even once data is assembled, organizations often struggle to apply analytics to create the metrics that best represent an understanding of the past and, more importantly, the path to the future.
Our latest Ventana Research benchmark research on the State of Customer Analytics provides insight into best practices on using data effectively for business. The research was designed to examine in depth the needs for and use of analytics and metrics by all lines of business involved in customer-related activities. In designing this research, one major goal was to provide organizations with a better understanding of their challenges and requirements and thus improve their ability to formulate a successful path to improvement.
The first challenge organizations must address in customer analytics is to ensure data quality — in other words, that data is accurate and available to inform analytics. Unfortunately, confidence in the quality of the information being generated by customer analytics is not uniformly high. Most participants in the research indicated they are either very confident (27%) or confident (47%) in the quality of the information their systems are generating, but more than one-quarter (26%) said they are only somewhat confident or not at all confident.
Similarly, most organizations told us their customer analytics data is very accurate (15%) or accurate (48%), but one-third reported it is only somewhat accurate (26%) or not accurate (7%). We attribute this partly to the persistence of spreadsheet use as an analytic tool in half of participating organizations; spreadsheets are difficult to work with in an enterprise setting, inflexible and prone to errors. Improving confidence in customer analytics requires tools that enable reliable processing of a wide variety of customer-related data types that span every type of interaction.
Once an organization has confidence in the quality of customer information and the underlying data, it then must apply analytics and generate the portfolio of metrics and key indicators needed to assess performance and guide improvement. But what analytics can best meet the need for insights into customers?
For more than two-thirds (68%) of organizations, the most important analytics are those that are focused on customers (for example, CSAT, NPS, CES and CLV), followed by financial (60%), agent performance (53%) and contact center operations (45%) analytics. Organizations report that they use a wide array of important metrics. Topping the list are those associated with customer satisfaction and profitability, cited as important by 59 percent and 52 percent, respectively. Other important metrics include financial ones such as revenue attainment and adherence to budget, and process metrics such as call outcomes, sales conversion rate and agent quality scores. Other customer-related metrics include customer lifetime value, cost to serve and, lower on the list of priorities the research yields, the net promoter score.
Deeper insights into customer analytics are possible with the right techniques and technology. More than half (55%) of organizations indicated they view advanced analytics as very important and an additional 29 percent said they are important. And they reported that using such advanced analysis yields information
The timeliness of customer analytics is critical for their effective use in processes and performance assessment. The largest percentage of organizations (42%) have important metrics available for use in two to five business days after the period close; 17 percent deliver the metrics immediately on close and an additional 12 percent deliver them within one day. Organizations most often review their important metrics and indicators on a monthly (25%) basis, but almost as many do it daily (20%), weekly (21%) or quarterly (20%).
Organizations should consider how to assess and improve the quality of their customer data to ensure sufficient confidence in the metrics they create. Only then can these metrics effectively guide the operations of the business to maximize the value of customer relationships. Examine the efficiency with which your organization can process customer analytics and improve the customer experience across every interaction.
Ventana Research has for nearly two decades conducted market research on customer experience and the contact center as well as many other business technologies, including contact centers in the cloud and customer engagement through any channel or department such as marketing, sales, support and services. Click here to learn more about our research and services for vendors and technology buyers.
Regards
Mark Smith