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Aphrodite Brinsmead
Aphrodite is a principal analyst in the Customer Engagement team at Ovum. She analyzes trends on customer service technologies, having...
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Aphrodite Brinsmead | February 22, 2016 |

 
   

3 Analytics Trends to Watch for Your Contact Center

3 Analytics Trends to Watch for Your Contact Center As contact centers strive to better understand customers and make faster decisions, they might find help from a new wave of analytics tools.

As contact centers strive to better understand customers and make faster decisions, they might find help from a new wave of analytics tools.

Today's digital customers generate data as they traverse channels, read reviews and articles online, and click on marketing posts and ads. And contact centers need new ways to harness this data and react quickly when those customers reach out. They need to ensure that customers have easy access to timely information and the ability to reach the representative who is best empowered to assist them.

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Traditional contact center analytics tools, such as agent performance management and customer surveys, provide limited customer insights based on historical data. But a wave of analytics tools aimed at helping contact centers better understand customers and make faster decisions is emerging. Using customer interaction analytics alongside agent performance data, contact center managers can develop more tailored agent recruitment plans, and train and schedule agents in the most relevant channels.

Contact centers should be aware of three big trends in analytics that will help them achieve these goals in 2016:

  • Real-time data – Whether for predicting customer satisfaction and churn or delivering automated responses to Web chats and emails, emerging analytics solutions are placing increased emphasis on real-time insights. Contact centers will benefit from the ability to provide better guidance for agents, alert managers when customers are dissatisfied, and ensure customers receive tailored messages. Real-time data enables intelligent predictions around customer behavior and intentions so that businesses can act quickly to improve customer satisfaction during an interaction. This also applies to automated responses within chat sessions or emails that provide customers with links to relevant articles or Web pages.

  • Customer journey analytics – Understanding customer journeys takes more than an analytics platform; it involves workshops, collaboration across departments, and data cleaning and integration. However, analytics will play an important role in the ways that businesses track customer behaviors across channels. Providers are adding new journey analytics options to contact center applications such as agent desktop tools and workforce optimization suites. Greater visibility into the different stages of a journey and channels that customers use will help contact centers better align their internal resources, resolve issues before they escalate, and send personalized, proactive support messages.

  • Simplification of tools – The biggest challenges with deploying analytics in the contact center have been expense, complexity, and aligning ownership of Web data across marketing and customer service. But increasingly vendors are introducing simpler analytics packages that align with business goals. They are also delivering data insights that are embedded within applications. Examples include: customer satisfaction prediction within a CRM platform, cross-channel journey mapping within the agent desktop, and intelligent prediction that helps determine when to offer Web chat sessions. With more data insights embedded within existing products, contact centers will have less concern over how to implement analytics and be able to focus on how to use data to improve specific metrics or tasks, such as resolutions in self-service or customer satisfaction.

As customer behavior becomes more complex, contact centers need to predict customer requirements, simplify user interfaces, and automate personalized messages. Analytics is essential for them to understand which trends are most relevant to their businesses so they can improve decision making about how to evolve and engage with customers. They should be thinking of ways to use data and analytics to personalize interactions across channels and pre-empt customer needs in order to present resolutions and offers before customers are at risk of churn. They need to learn from the data continually and evolve with customers, making changes more often.

If you're attending Enterprise Connect, taking place March 7 to 10 in Orlando, Fla., join me for an in-depth discussion on contact center analytics during my Thursday 8:00 a.m. session, "How Analytics Is Changing Customer Service in 2016." I'll be convening a panel of experts and providing a look at available solutions, sharing examples of deployments, and making recommendations for contact centers looking to evolve their analytics strategies. I hope you can join the conversation!

View the Contact Center track sessions; register now using the code NJPOST to receive $200 off the current conference price.





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