The deluge of customer data shows no signs of abating. The perpetually-connected customer leaves data footprints in every interaction with a brand. This presents tremendous opportunities for customer insights professionals and analytics practitioners tasked with analyzing this data, to not only get smarter about customers but ensure that the insights get appropriately used at the point of customer interaction.
When we asked customer analytics users about the challenges and drivers of customer analytics adoption, we found that data integration and data quality continue to inhibit better adoption of customer analytics while users still want to use analytics to improve the data-driven focus of the organization and drive satisfaction and customer retention.
Forrester’s Customer Analytics Playbook guides customer insights professionals, marketing scientists and customer analytics practitioners into this new reality of customer data and helps discover analytics opportunities, plan for greater sophistication, take steps towards building a customer analytics capability and continually monitor progress of analytics initiatives. It will include 12 chapters (and an executive overview) that cover different aspects of customer analytics.
Customer Intelligence (CI) professionals invest in data-mining, predictive analytics and modeling tools and technologies to make sense of the deluge of data. In the past, they've had to adapt horizontally-focused analytics and modeling solutions to a customer intelligence and marketing context. Today, however, they can consider a gamut of customer analytics and marketing-focused analytics providers that have not only analytics production expertise but also domain and role-focused expertise.
We just published our first evaluation focusing on the customer analytics category here: The Forrester Wave™: Customer Analytics Solutions Q4 2012 . After screening more than 20 providers for analytics products specifically catering to customer analytics applications, we identified and scored products from six of the most significant providers: Angoss Software, FICO, IBM, KXEN, Pitney Bowes, and SAS. Our evaluation approach consisted of a 70-criteria evaluation; reference calls and online surveys of 60 companies; executive briefings; and product demonstrations. The core criteria included key dimensions such as core functionality (data management, modeling, usability); analytics production; analytics consumption; analytics activation and customer analytics applications. The evaluation also included the strength of the current product and corporate strategies in the customer analytics market as well as the future vision for this category.
We found that four competencies define the current customer analytics market:
I’m excited to announce that our new research on how firms use customer analytics was just published today. The new research reveals some interesting findings:
Customer analytics serves the customer lifecycle , but measurement is restricted to marketing activities. While customer analytics continues to drive acquisition and retention goals, firms continue to measure success of customer analytics using easy-to-track marketing metrics as opposed to deeper profitability or engagement measures.
Finding the right analytics talent remains challenging . It’s not the just the data. It’s not the just technology that hinders analytics success. It’s the analytical skills required to use the data in creative ways, ask the right questions of the data, and use technology as a key enabler to advance sophistication in analytics. We’ve talked about how customer intelligence (CI) professionals need a new breed of marketing scientist to elevate the consumption of customer analytics.
CI professionals are keen to use predictive analytics in customer-focused applications, Forty percent of respondents to our Global Customer Analytics Adoption Survey tell us that they have been using predictive analytics for less than three years, while more than 70% of respondents have been using descriptive analytics and BI-type reporting for more than 10 years. CI professionals have not yet fully leveraged the strengths of predictive analytics customer applications.