In this blog, we will discover:
- What is Interaction Analytics
- How does Interaction Analytics work
- What is Interaction Analytics about
- Predictive Modeling in Interaction Analytics
- What are the stages of interaction analytics maturity in organizations?
- What is a Good Interaction Analytics Governance Program for Call?
- How Interaction Analytics Automates Call Center Process Analysis
- FAQs about Interaction Analytics
What is Interaction Analytics
Interaction analytics is about looking at all the touch points that you have with your clients. In today’s market customers are interacting with companies in a multitude of different ways. They are not just calling. On average a company has about six channels such as social media, chats, online forms, phone calls, and emails. These are all different points of contact.
The biggest issue with all these interactions is that they are usually siloed, smashed up, unconnected, and unstructured. Organizations rarely have a good place to look at all of them in one place.
Interaction analytics focuses on bringing all these touch points together and analyzing them in a unified way. It allows organizations to take unstructured interaction data and transform it into insights that can drive real business improvements.
Explore more: Traditional vs AI Call Center Metrics: The Complete Guide to Modern Contact Center KPIs
How does Interaction Analytics work
Companies already have a large amount of interaction data. They have CRM data and data warehouses containing information about customer interactions. However, this data is often fragmented.
Interaction analytics takes these unstructured interaction methods and structures them into large-scale behavioral data. It helps organizations understand what agents are truly doing in conversations, chats, and emails. It also helps identify what customers are talking about and what kind of retention offers agents are giving when customers threaten to leave.
Interaction analytics works with different business teams to solve important problems:
- It works with sales and marketing teams to improve sales effectiveness.
- It works with churn and retention teams to create predictive models that identify which customers are more likely to leave and why.
- It helps operations reduce average handle time and increase first contact resolution.
- It works with security teams to ensure compliance in stored data and recorded conversations.
- It works with customer experience teams to ensure agents and the company are represented correctly during conversations.
Every touch point with a customer is a treasure. If organizations are not examining or using these interactions, they are missing valuable insights.
What is Interaction Analytics about
Interaction analytics begins by taking interaction data from many sources. In some cases this could be audio data, but it can also come from hundreds of different sources.
All these different sources are structured so they become searchable and valuable. Interactions are organized into large-scale taxonomies to understand what customers are talking about. Organizations can identify why customers are calling, why they are chatting, and why they are visiting websites.
Once interaction data is structured in an organized information, the system looks for events that occur during conversations and examines how those events influence the direction of the conversation.
The next step is quantification. Executives want hard numbers. They want to know how often certain events occur. Interaction analytics helps quantify how frequently specific events happen.
Once events are quantified, organizations can identify two important outcomes:
- Opportunities for automation
- Opportunities for agent training and behavioral improvements
Analytics only becomes valuable when the insights are applied to business processes. Organizations must use the insights to automate processes or improve agent behavior.
Predictive Modeling in Interaction Analytics
Predictive modeling becomes important because customer behavior evolves over time. Customers do not leave a company suddenly. There are usually many events in the past that influence churn.
Predictive models combine structured data and unstructured interaction data. For example, telecommunications companies already have structured data such as:
- Customer plan
- Contract status
- Contract expiration
- Billing spikes
Interaction analytics adds unstructured signals such as customer sentiment and conversation topics. It identifies whether customers are unhappy, whether they are discussing service outages, and how satisfied they have been in recent interactions.
All of this data can be fed into predictive model generators to forecast customer churn and other behaviors.
What are the stages of interaction analytics maturity in organizations?
Organizations adopt interaction analytics in stages of maturity.
Some companies are in the early phase and are only running proof-of-concepts. They may analyze a single channel or run analytics in batches such as quarterly analysis.
Other organizations operate at a more mature level where analytics is repeatable and measurable daily. These organizations often analyze single channels or a limited set of interactions.
The most mature organizations operate strategically. They use real-time analytics with a measurable omni-channel approach. They analyze interactions across all channels and integrate analytics directly into business decisions.
The market is evolving as companies move from ad-hoc analysis to operational and strategic interaction analytics.
How Organizations Start the Interaction Analytics Journey
For companies that haven’t really started interaction analytics, it always comes down to what is the easiest smallest portion they can manage and what they are looking for in that particular case.
A company may know it has a lot of processes in its call centers and even in its back office. The challenge is figuring out which processes are truly inefficient, which processes are causing agents the greatest heartache, and which processes are causing customers the greatest heartache.
If a customer is waiting 20 minutes to figure out why a late fee was charged because the agent has to log in to 50 different systems, that is a great process that can be automated. You have to have the right problems to solve.
Educating the market
The way the market is educated is by highlighting the issues that customers are facing. One of the most important things for essentially any organization is going to be what the customer is feeling.
The goal is to ensure that the highest number of frustrations from the customers are really brought to the client’s attention. Oftentimes companies don’t know that their customers are facing issues in the context of waiting 45 minutes for an account to open. They also do not know how to figure out how happy a customer is in a conversation. No one can really answer these questions. The focus is on educating customers on what is driving all of it.
A lot of people are still in the process of not knowing what they are looking for or what their business is really lacking. It is not a bad place to be in if they are still examining the market. The goal is to help strategize around what the business lacks, what issues it is having, and how the products and consulting out there can help fix those issues.
What is a Good Interaction Analytics Governance Program for Call Centers?
A successful interaction analytics program requires strong governance.
When organizations and call centers implement interaction analytics they often discover thousands of possible projects. Some projects may be small, such as analyzing how many times customers say certain words.
Without governance, organizations and call centers struggle to extract value from analytics.
The best approach is to focus on the right business objectives and prioritize projects accordingly.
For example, if reducing average handle time could save a company 1.6 million dollars, that becomes a clear objective.
Once objectives are defined, the next step is to connect the issue with data. Interaction analytics structures data so organizations can produce quantifiable results.
Organizations must also ensure the analysis plan is not fragmented. Decisions should be based on quantifiable data rather than anecdotes or isolated examples.
Quantification and Business Impact
Once a business objective is defined, organizations quantify its value. The objective could relate to:
- FTE reduction
- Financial savings
- Customer satisfaction improvements
For example, a company may discover that agents are transferring calls within the first few seconds of the conversation. This behavior creates poor customer experience and increases hold times.
Interaction analytics helps quantify these issues and measure their impact.
Operationalizing Interaction Analytics
After quantification, organizations must identify events and behaviors occurring in interactions.
They must determine:
- Whether processes should be automated
- Whether agent behaviors should be improved
The most important step is operationalizing the insights. Analytics alone does not create value unless it leads to changes in business processes.
Companies must implement changes and then measure whether those changes produce the expected results.
Governance Challenges: Major Blockers or Resistance
One of the major blockers is teams that are afraid of change.
It is important to approach the entire process the right way. The goal is to help organizations be more efficient and be better. It is never about taking over someone’s job. The goal is to make the company more efficient so that people can do the things that they like, and do them more efficiently.
Governance Lessons Learned
Every single time a customer fails using interaction analytics, and again any product that is available, it is because they do not have the right governance around solving the problem.
There are going to be too many people asking questions. It is not that the goal is not to answer questions, but it is necessary to make sure that the right questions are being answered, the questions that have the right drivers behind them.
Without the right drivers and without the right ROI, the question is not really being answered, a requirement is just being fulfilled. It is important to make sure that a need in the business is fulfilled via the analytics that is done. That is what a governance program helps aim towards.
Governance and Privacy Laws and Regulations
There has to be internal governance with the right committee to approve projects, but it is also important to help companies comply with rules and regulations.
A good example comes from a collections company in the U.S. Collections companies have different requirements and different laws that regulate them based upon how a conversation is going.
If in a conversation a customer says they filed bankruptcy or that they have involved a lawyer, the conversation actually has to change and be different. The system helps customers comply with these rules to make sure that they are not fined, to make sure that they are tracking what the government is tracking, and that the whole process is being audited.
How Interaction Analytics Automates Call Center Process Analysis
Automation in interaction analytics often begins with conversation segmentation.
Organizations categorize conversations from different channels such as emails and chats. Interactions are grouped and routed to the appropriate teams.
This allows quality teams to focus on the most relevant interactions instead of randomly sampling calls. Instead of reviewing a small number of calls per agent, they can analyze a large number of targeted interactions that provide real insight.
Automation can also involve integrating interaction data into unified platforms. For example, interaction analytics can capture events from agent desktops and overlay them on conversations.
Organizations can track when agents start processes such as account opening and when they finish them. This helps identify inefficient processes that could be automated.
Interaction analytics also shows how agents spend their time during processes. For example, it can identify whether agents are working in Salesforce, browsing the internet, or using email during customer interactions.
Bringing all these pieces of information together in a unified platform helps organizations identify inefficiencies and opportunities for automation.
Where automation creates the most benefits
Process automation creates the most benefit where companies have the greatest amount of overhead.
If you think about telecommunications companies, they’ve got 20 different processes. If they want to open an account, they may have one system where they have to provision a phone number, another system if they want to transfer a phone number, then they have to go to the banking and finance department to create an account for billing, and then they have to check the customer’s credit to make sure they can open an account.
All of those can be automated very easily if interaction analytics is used to really figure out what is the biggest change that can be made and what is the biggest driver for inefficiency.
How automation is identified
When thinking about what is going to come into the conversations, the focus is on marking down what is happening within agents’ desktops and figuring out what the processes are that the agents are going through via automation.
Desktop tags come into the interaction analytics product, and reporting shows which processes are really taking the longest. Then it becomes possible to drill in and quantify what changing a process would mean to the business.
If shrinking a process by 10 seconds would mean a million dollars, then that project can be selected. Once the project is selected, the interaction analytics applications help guide the process and help create the events, figure out what agents are doing or doing wrong, and how to drive that change all the way down.
FAQs about Interaction Analytics
1. What is Interaction Analytics
Interaction analytics is about looking at all the touch points that you have with your clients.It focuses on bringing all these touch points together and analyzing them in a unified way. It allows organizations to take unstructured interaction data and transform it into insights that can drive real business improvements
2. What are the drivers for automation?
Companies adopt interaction analytics and automation for several reasons:
- Cost reduction
- Process efficiency improvements
- Competitive pressure
- Improving customer experience
Across many regions the main driver is improving process efficiency. Organizations want to discover what makes their call center processes inefficient and use analytics to fix those inefficiencies.
3. How is the interaction analytics market evolving across different regions?
The United States has a mature interaction analytics market where many large companies already have analytics platforms. Asia is an emerging market where organizations are just beginning to discover the value of interaction analytics. Australia is slightly more mature than Japan. China and India are rapidly growing markets with many vendors and increasing customer experience requirements.
4. How do organizations quantify business impact using interaction analytics?
Once a business objective is defined, organizations quantify its value. The objective could relate to FTE reduction, financial savings, and customer satisfaction improvements. Interaction analytics helps quantify these issues and measure their impact.
