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What We Can Achieve Together
Customer Analytics Deliver Improved Customer Retention
A research study by Aberdeen, titled Customer Service Analytics: Exploit Data to Improve the Customer Experience, found that call center business intelligence drove a 72% improvement to customer retention.
Predictive Analytics Forecast Agent and Customer Results
Predictive analytics show how performance metrics can be aligned, manipulated and improved to increase the agent experience, customer experience and contact center performance results.
Agent Dashboards Drive Productivity Improvements
An agent dashboard prioritizes what needs to be done, highlights variances for swift resolution, displays performance measures alongside industry benchmarks, and shows the financial impact of both action and inaction.
A Better Way
The goal of call center business intelligence (BI) is to get the right information to the right people at the right time, so they deliver improved customer experiences and make more informed decisions.
Selecting the best intelligence tools is less about technology and more about identifying the information use cases that drive the biggest performance improvements. Here are some examples.
Contact center intelligence can identify the combinations of channels, knowledgebase artifacts, agents and more to meet customer expectations at the lowest cost. They also identify when these resources and assets fail to meet customer expectations and need improvements.
BI surfaces the agent and case factors that can deliver repeatable successes and identifies when those factors increase labor costs or fail to achieve predicted outcomes.
Customer churn insights identify customers at risk of churn, why customers defect and the financial impact of those losses.
Customer analytics can attribute the cost of support to each customer and identify customer profitability. They can show which 5-10 percent of customers are unprofitable, and which 20 percent of customers contribute about 70 percent of margins and profits.
They can identify the high volume of low complexity calls well suited for customer self-service channels. They can aid proactive customer support by resolving issues before they happen.
Predictive customer analytics go further to connect data, insights, action and outcomes and thereby shift information reporting from hindsight to foresight. The below model shows how performance measures cascade to impact the most important business outcomes and financial goals.
There are several tools in the customer support BI continuum.
A mix of technologies is generally needed to display timely and detailed variance notifications that permit course corrections before performance problems exacerbate. Many of these tools also reveal the causes and linkage among performance problems so you can fix them at the root source.
Helping Clients Use Analytics is Our Business
We help clients make better use of their data. We apply tools such as agent dashboards, contact center business intelligence and call center predictive analytics in ways that immediately improve the agent experience and customer experience while simultaneously lowering cost to serve.
Our prescriptive methods and repeatable best practices bring proven techniques to achieve predictable outcomes. Our purpose-built reporting brings visibility to progress and predictability to forecasted results. And our digital analytics consultants tie it all together.
To de-risk our programs, we round out our services with architecture engineering, program management and governance oversight.
Converting Data into Your Most Valuable Asset Starts Here
If you are looking to make your data actionable, we have some options.
Visit the Customer Service Insights Hub for expert recommendations, best practices, research findings and BI technologies.
Or for professional help, schedule an introductory call with a digital analytics consultant using the form below.