3 Important Roles of Omnichannel Analytics in Contact Center

Omnichannel is meant to offer a uniform customer experience across multiple channels, products/services and the buying stages. Therefore, analysing how a customer’s journey progresses, the touch points they come across and the time they spend on each channel i.e. omnichannel analytics is crucial to delivering the right customer experience. It defines the criticality of each channel in customer experience delivery and helps derive an effective channel strategy respectively.

In this article, we will learn about the challenge businesses face with distributed data coming in from different channels and the importance of unified analytics in the functioning of a contact centre.

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A contact centre has data coming in from different directions and in different formats. For example, with telephony, for a simple but crucial act of identification, a call center gathers data related to the caller’s identity, which may include their name, contact number, email id, address, at times even birthdays and marriage anniversaries. The call center also records and stores the previous interactions of the customer. Now imagine this information being collected for thousands of calls a contact centre receives and makes every day.

And we have just spoken about a small portion of telephony till now, there are multiple other channels that customers and businesses use to interact with each other today, like SMS, Emails, Social Media, Chat, Bot interactions, etc. Every channel gathers data, the collection, management, and action which is crucial for a brand’s customer experience and ultimately their brand perception.

 

Here is the summary of a survey conducted by ICMI, on the challenges a contact center faces in collecting and managing data. You will see that the top most challenge faced by a contact centre is – ‘Too much data collected from too many disparate sources and no good way to consolidate it.’ The second challenge is – ‘Too much data and no time to manually parse it and report on it.’

This has been a consistent challenge with contact centers offering multi-channel support and handling extensive level of calls daily.

Omnichannel analytics becomes one feasible solution for such contact centers. It brings together all the interactions with a customer across channels in a chronological order and thus helps in unifying data coming from disparate sources and consolidating it. It also parses data automatically by identifying key phrases and reports on different aspects of a customer’s behavior like sentiment analysis.

The most important value-adds of omnichannel analytics is in understanding the customer, properly engaging them, predicting propensity toward specific behaviours (such as likelihood of purchasing certain things), and formulating and monitoring delivery, whether it’s a product, service or support.

Unified Analytics in Contact Centers are highly important for effective omnichannel initiatives - just like how important they are for most of the customer experience programs - at both: tactical and strategic levels.

Omnichannel analytics can be put to multiple uses if collected and analyzed correctly, like:

• Laser focus your marketing
• Optimize merchandising
• Adjust your supply chain
• Enhance store operations
• And most importantly improve customer experience

Omnichannel analytics accelerates the productivity of different moving wheels of a contact center.

As per Omnisend Omnichannel Statistics, marketers using three or more channels in any one campaign earned a 287% higher purchase rate than those using a single-channel campaign

The first on our list to explore is the relationship between Omnichannel analytics and agent productivity. On any average day an agent has to navigate around multiple screens and interfaces to gather necessary data and information. They must:

• Work through multiple screens
• Ask for basic contact information the company already has
• Manually and repeatedly key in the customer contact information 

Omnichannel analytics smartly captures the desktop activity of an agent like how many times an agent had to move between screens to conclude one interaction, which channel consumes most of the agent’s time, etc. With the report of these analyses, an administrator or supervisor can easily plan the workforce for each channel.

For a successful experience delivery, it is not just important for an agent to be prompt but it is equally important to be accurate. In a normal scenario a contact centre that is integrated with different agent support tools like a knowledge base or chatbot to fetch the information needed by an agent, and has agent assistance features like whisper coaching, call transfer, barge in etc can help promote accuracy of the service delivered. In the omnichannel world, all this gets backed up by an understanding of context. An omnichannel analytics tool can analyse all the interaction of a customer across platform and match that with the historic instances to predict or suggest to an agent the course of action that is most accurate in a scenario. It can also effectively warn an agent if it detects a negative sentiment in the customer.

Consumers in today’s marketplace are much more tech-aware, sometimes using multiple devices at the same time. By employing omnichannel analytics, business can build a detailed picture of the customer journey, bringing them closer to their customers than ever before. But none of it is possible without a good customer relationship management (CRM) system. A CRM helpdesk tool can effectively grab and record all the information collected by a customer like - Average satisfaction of a contact, Customer mood after an agent interaction, Customer likes and dislikes, Customer channel preferences, Geographic location information of customer etc. The analysis of this data collected from different channels can help a contact centre administrator to

• Use customer preference data to proactively move the interaction through the best channel and to the most adapt agent
• Taking customer feedback to improve escalation procedures
• Leveraging speech analytics to assist customers who have previously struggled with comprehension issues
• All this with one intent – to provide a unique experience customised to a customer’s choice every time.

It is clear form above that whether the application of Omnichannel analytics is to improve agent productivity and efficiency, or to quickly diagnose customer challenges and move to a higher satisfaction level, businesses should continuously evaluate their investments into data collection, mining, and analysis. They should aim to spend less time gathering and storing the data that does not create value instead focus on the data that affects strategic goals like improved operational efficiency and increased customer loyalty. By using Omnichannel Contact Center analytics as an input to a solution, rather than just an output, a business can be equipped to truly make improvements across all aspects of the customer journey.