Contact center managers need analytical tools beyond the typical contact center reports. But there are so many choices!
- Performance Optimization/Workforce Optimization suite vendors (e.g., Verint, Nice, Aspect, Envision, and others) that offer speech analytics, usually some level of data analytics (including scorecards and dashboards), and (perhaps) desktop analytics
- Speech analytics vendors (e.g., Utopy, Callminer, Nexidia) offer applications for gaining value from audio recordings
- Data analytics vendors (e.g., Merced) offer applications to consolidate the plethora of data produced by a variety of contact center applications
- Desktop analytics vendors (see It’s Time to Put the Spotlight on Desktop Optimization)
- Enterprise analytics or BI tools from suppliers such as Cognos (IBM), Hyperion (Oracle), and Business Objects (SAP)
- Multi- or cross-channel analytics (e.g., ClickFox) that integrate the data from various channels to drive understanding of the total customer experience
- Home grown solutions
- Other sources (e.g., CRM, web analytics, business process management, or channel specific tools)
With so many choices, which one(s) is (are) right for you? The answer should be an outgrowth of a strategic planning process in which the business, the contact center, and IT collaborate. Here’s a step-by-step process:
- Define the vision consistent with your business, service and technology strategies for what you want your analytics application to deliver.
- Inventory your existing contact center and enterprise applications for reporting and analytics – whether in use or not.
- Analyze the gap between what you have and what you need. Compare your specific requirements to the existing capabilities you uncovered. Prioritize the requirements that you cannot fill with current tools and define the technology needs and people and process implications that accompany them.
- Develop a plan for meeting your requirements that includes the overall timeline and milestones for each phase of the project.
- Perform a thorough evaluation to ensure you optimize your choice.
- Plan the implementation effort recognizing the complexity and realities integration entails. [If analytics was easy, everyone would be doing it!]
A successful implementation will require a solid integration plan and well defined pilot with time for refinement before roll out. Once rolled out, you will need to continuously refine and optimize your processes.
What to learn more? Want to learn more? Read an article that I co-wrote with Lori Bocklund entitled Turning Data into Insights with Transformational Reporting and Analytics Tools.