October 29, 2012
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:
• Analytical prowess. The variety and depth of customer analytics algorithms, predictive analytics methods, and data-mining discipline are key characteristics that customer analytics vendors bring to the table. These are essentials for customer analytics professionals looking for a breadth of analytical and statistical tools to mine customer data.
• Execution. The customer analytics journey is a futile intellectual exercise unless the output is activated through marketing communication, interaction management, decision management, or campaign management. Customer analytics users are also keen to understand how analytics providers connect the last mile when it comes to analytics activation, consumption and execution.
• Automation. For customer analytics professionals looking to spend more time generating insights than generating models, vendors offer solutions to automate repeatable modeling and analytical tasks. Automation also extends to data preparation, model performance management, variable transformations and other analytical tasks.
• Usability. Although the traditional analytics user was a statistician or a quantitatively trained user, vendors now cater to multiple user types and roles to make customer analytics more accessible to a broader audience.
Forrester clients can access the full report to learn more and also customize the Wave model with personalized criteria weightings using our interactive Forrester Wave scorecard tool.
I want to thank the vendors and their clients who participated in the evaluation for their time and effort during this process. Special thanks to my colleagues Dave Frankland, Suresh Vittal, Allison Smith and all my CI team members for their inputs, guidance and support during this Wave process.