Drive customer satisfaction with cloud-based analytics in the contact center

Understanding your customers and knowing what satisfies them and creates loyalty is one of the key differentiators for businesses in the world today – especially if you are in highly competitive markets like finance, insurance, gaming, retail, telecommunications and many more. 

By understanding your customers and analyzing what they want and need, and perhaps what they don’t want and need, can turn out to be a very important competitive differentiator in your industry. It can create that extra feeling of personalization in the customer experience, that results in a satisfied customer, and eventually turn them into loyal customers, who will continue to come back to your brand. 

Optimize contact center performance by leveraging conversational analytics 

Years ago, companies started to selectively record customer calls, and store them for compliance purposes. Then came the recording of all calls. Front running companies then started realizing that they were sitting on a gold mine of customer data and started analyzing the stored recordings. What they quickly realized was, that all these customer calls were extremely valuable in understanding who the customers really were by analyzing what they said during the calls and how they said it. 

Later came the tools that could do this for the companies in real-time, providing insights on the customer while on the call and also on a big data scale, only by the click of a button. 

Key operational improvements from analyzing customer interactions 

1. Ensuring compliance

The “old” reason for recording and storing the customer conversations is still as valid for most industries as it was "back in the day". Companies still need to comply with regulations and rules. 

2. Reduce average handle time (AHT)

The AHT is an important KPI for almost any contact center, and to improve – by reducing – the AHT, contact center managers can show that they are running a top-performing contact center, and also focus on other aspects of the business – perhaps the human-touch leader and developing the agents? Studies show that the longer calls are due to lack of training among the agents. 

3. Improve first-contact resolution

Repeat callers can often be avoided with proper analytics and training of the agents. Find the root of the problem from the very beginning to resolve it the first time.

4. Customer self-service enhancement

By leveraging the conversational data from the interactions with your customers, you can identify opportunities to improve the customer self-service solution you might already have in place or create a business case for implementing such a solution.

5. Upsell and cross sell

Turn your contact center into one of your best-selling departments, by developing the skillset and opportunity for your agents to start selling (more). By understanding what your customers really want, you can create that sweet selling spot, where the customers actually desire a product without perhaps even knowing it themselves, and then your agents come to the rescue with a “special offer” to fix a certain problem. 

Base your sales/marketing strategy on real data from customer insights 

You no longer have to guess what your customers think of your products, what questions or issues they have, and what they love about it. Get that insight from the interaction analytics you have implemented. 

When your marketing and sales departments are creating their strategies to eventually sell your product and solution, they can base the messages on real data from real customers. Bye-bye guessing! 

This has been attempted for a long time, but only the brands and contact centers with the right resources and skillsets in place was successful to some extent. This was very time consuming and had major limitations such as it didn’t take into consideration that people change, sarcasm, and it only relied on people guessing about the customer’s feeling during the call. 

Today you can have pre-configured analytics tools powered by neural phonetics, Machine Learning (ML), and Artificial Intelligence (AI). These features make it possible to understand sentiment, tone, emotions, topics, entities and relationships with almost zero-to-none human effort. And the best thing is, that is does it with perfection in all the Nordic languages among 40+ other languages, dialects and accents. 

An analytics tool will not remove the human factor – and it shouldn’t! 

Well, it shouldn’t be removed completely. It is important to remember that an analytics tool is only as powerful as the humans who use it. And a seamless and perfect customer experience comes from the interplay between an agent, his/her skills to deliver an outstanding customer service and the tools at his disposal. Are all these aligned and in top-class, then you have the right cocktail for a perfect customer experience. 

How and where to start with interaction analytics 

Step 1: Define the main business drivers

Always define your main business drivers. The analytic tool should in all cases reflect your business agenda and goals.

An example: Is "increasing revenue" on the top of your agenda and therefore your main goal, then the analytics should be pointed at upsell / cross sell and analyze what your top-selling agents are saying to customers that make them thrive and use that knowledge to pinpoint education for all agents.  

Step 2: Be concise

Define key factors for a successful data analysis, and be concise about it. "Increase upsell by 10%", is a good key factor that is measurable and will help you to define a good project outcome; a guiding star. 

Step 3: Identify your top-selling agents

You should be able to define top-salling agent and run the analysis on them, and extract the data you need to define a good sales strategy that needs to be implemented on all sales agents. 

Step 4: Dedicated analitycal agents

Assign dedicated analytical agents to work with the data and learn the organization from a new perspective that they couldn’t before. In the data you will find all kind of material you knew were there, but were never easy enough to extract and understand.

Step 5: Information and transparency

Inform and be transparent toward your organization, about what you are doing with this analysis. Bring them in to the scope and show results on a regular basis. This will create ambassadors for the “new” data you will find and also get ideas on how to use the tool.

This scenario can be applied to all processes you find using the interaction analytics tool. Many benefits come from an interaction analytics tool. All from agent coaching to full end to end automation discoveries! 

Learn more about this topic and the specific solution we offer by clicking here.