Definition of Interaction Analytics:
Interaction analytics begins with raw data – multichannel interactions, such as chat transcripts, social media posts, recorded contact center calls, SMS, emails, and other – and transforms it into structured data that can be sorted, filtered, searched and analyzed to better understand your customer interactions and customer satisfaction.
Notably, interaction analytics do not stand on their own; rather, they’re most often leveraged to boost contact center performance and improve the overall customer experience.
How to Improve Interaction Analytics
The simplest way to improve your interaction analytics is through specialized interaction analytics software, which not only records data, but also analyzes it on your behalf.
The process is simple: Interaction analytics software will evaluate your interactions across all customer communications channels, including contact center calls, chats, and emails, as well as SMS text messages, social media posts, and more. The result is comprehensive analytics that represent a complete picture of your company’s customer interactions.
What’s more, the best software will not only capture your interactions, but it will convert them into an easily analyzed format (e.g. text) and make analysis easy through:
- Performance scoring
- Free-form search and playback
- Contact evaluation for various metrics, including sentiment/acoustics, categorization, and performance scoring
- Evaluation and comparison of key metrics, via data visualization
- Auto topic analysis to determine root cause and identifying outliers
- Measurement of key performance indicators across channels
- Easy extraction of analytics data
Examples of Interaction Analytics
Interaction analytics case studies easily demonstrate the immense value of proper analytics – and their implementation in improved customer service and experience, as well as in internal processes.
For example, vacation club management company Bluegreen Vacations was able to leverage interaction analytics to improve CSAT by 26%, improve agent quality scores by 19%, increase sales performance by 48%, and achieve ROI in under a year. Conclusion: Bluegreen Vacations turned their contact center operations from cost center into profit center.
In another example, English language-instruction company Open English was able to use interaction analytics to reduce silence and call avoidance, improve their call efficiency, increase marketing effectiveness, and boost sales performance.
Benefits of Interaction Analytics
Leveraged well, interaction analytics not only improve customer satisfaction, but also help your company become more efficient and profitable. By capturing and analyzing multi-channel interactions, you can:
- Improve Customer Experience: Take the guesswork out of improving the customer experience, by identifying areas of improvement, ensuring agent compliance, and share successful behaviors to please customers.
- Identify Agent Training Needs: Use analytics to pinpoint agent coaching and training opportunities.
- Improve Operational Performance: Identify areas of improvement, to not only increase customer satisfaction, but also to improve efficiency and reduce costs.
- Qualify Leads: Follow up quickly on “hot leads,” to close new business and generate revenue.
- Set Better Appointments: Ensure all necessary information is captured for appointments. If data is missing, effect timely customer follow-ups and prevent unnecessary truck rolls.
- Reduce Liability Exposure: Take immediate action on any legal threats, to de-escalate situations and reduce liability exposure for your company.
- Auto-Generate Reports: Compare and contrast analytics, and then create reports to highlight or identify desired information.
Challenges of Interaction Analytics
There are two major challenges to interaction analytics – the how and the what? Specifically, how to gather, compile, and analyze customer interactions; and what to do with the data, once you have it?
Thanks to technology, the how is relatively simple today: robust interaction analytics software can compile the raw data, including audio, email, chats, surveys, social media, and texts. What’s more, good software will auto-analyze your interactions to provide multichannel analysis, giving you immediate insight into your data.
These insights then help define the what – what your analytics say, where your company excels, and where you need to improve. Flexible, ad-hoc analysis of your customer interactions can determine root causes through topic analysis and automatic outlier identification, and can also sift through all your interactions to find certain buzz words/phrases (e.g. “I’d like to speak to a manager.”).
Best Practices for Interaction Analytics
When it comes to interaction analytics, best practices have less to do with the analytics, and more to do with how you use them. The key is to know your customer and know your company: What do your analytics tell you about areas to improve, and what can your company do to improve those areas?
Develop a 360º view of your customer. Use analytics to aggregate customer interactions, transactions, feedback, and agent data, to then build a beginning-to-end picture of the customer journey. Identify how to improve those customer interactions along the way. And, when customers are satisfied, work on how to deliver superb customer service while reducing your costs and increasing profitability.
How is your company leveraging interaction analytics to optimize contact center performance?