What to measure to drive strategic change.
To date, contact center technology has predominantly focused on cost and operational efficiency through investments in interactive voice response (IVR) systems, automatic call distribution (ACD) systems, order entry, web chat and more. As a rule, organizations have done this well, using technology to drive cost efficiency. Many businesses have successfully reduced the number of calls going to agents, enhancing those agents’ productivity while controlling costs.
An area where contact centers still struggle is in leveraging the data available to them to drive operational improvements and enhance customer satisfaction. Despite the growing volume of data available to business decision makers, they still find it difficult to get a full picture of the customer experience. Today, a single customer call to a contact center often involves several different systems, such as the IVR, ACD, order entry and customer relationship management (CRM) system—systems that aren’t made to share data with each other. The company usually knows what the callers did in the IVR (e.g., that the callers traversed a certain menu or were possibly transferred to an agent), but it usually does not know why callers left the IVR, or how what happened in the IVR relates to the eventual disposition of the call by an agent. An inability to connect the dots leads to an incomplete picture of what the customer was trying to accomplish or how that process went.
Too often organizations focus on lower-level data elements. But what if this is the wrong approach to growing the business? What if focusing on efficiencies means that the organization is squandering its best asset—its existing customers—or failing to convert many of its best prospects? And how would you even know if this is the case? You can’t, without the right data. And to get that data, you need to measure the right things. To drive strategic change, you need to focus on the higher level customer journey, essentially the sum total of your relationship with your customer.
When examining the activities of a contact center, one finds that there are four levels of data: (1) Events, (2) Transactions, (3) Interactions, and (4) Engagements. Events are the lowest level and when aggregated together yield transactions. Similarly, transactions when aggregated together yield interactions and eventually engagements.
Each level encapsulates the previous one(s), leading to the Customer Journey Level, the sum total of your relationship with the customer.
Event Level: Discrete Facts, Limited Value
The Event Level is the lowest level of the pyramid. An event is a discrete, individual contact between the organization and the customer. There are many customer events, most of which are short. For example, every single key a customer presses in an IVR system menu is an event. A web-chat entry session is an event, as is each email response or call routing decision by an ACD. A caller might trigger events within each of the company’s systems, including the IVR, ACD, an order-entry system and the CRM. Companies can learn discrete facts (e.g., the most popular menu items or auto responders) from analyzing this data. With that information, they can fine-tune the choices, reordering the menus to put the most popular items first and making them easier to select.
However, this does not help you learn anything significant about your customers. For that, you need to look at higher levels. A customer journey consists of multiple engagements. Each engagement is an issue the customer is trying to solve, and consists of one or more customer interactions. A customer interaction is, from the customer’s point of view, a block of time the customer spent working on the issue. Each customer interaction typically consists of multiple transactions—that is, it touches multiple systems within the contact center.
Customer “Transaction” Level: Internally Focused Information
Any customer contact (be it a call, email, web form or social media entry) will typically touch multiple systems. Each system, within a single session, counts as a customer transaction. For example, going through the IVR system and then talking with an agent on the phone counts as two individual transactions, even though the contacts resulted from a single call.
Put another way, a transaction consists of all the events that a customer triggered within a single system in one session. So all the keys a customer punched in the IVR system during that 3:05 p.m. call represent a single transaction. Plenty of data is collected at this level, and many vendors (especially providers of point solutions) focus their reporting and analytics at this level because that is all the data they have. However, because the information maps to the internal systems, it does not give us insight into the overall customer experience, and can’t help us make strategic business decisions.
For example, an analysis that only looks at transactions in an IVR system may encourage contact centers to focus on automating more calls, and as a result, they might decide to incorporate a self-service cancellation path in their IVR. But if they looked at data across both the IVR systems and a CRM application, they might find that good agents “salvaged” 30% of cancellation requests, and instead of automating cancellations, they were better off sending these calls to agents who performed best in saving customers.
Customer Interaction Level: More Than the Sum of Its Parts
More information is available at the Customer Interaction Level. A customer interaction is a time block the customer dedicates to solving his her issue (a “session”). The interaction includes all the “transactions” the customer had with each internal system during that time period. When a customer calls into a contact center, he she views that as one call or one interaction, regardless of how many internal systems the call touched.
For example, Customer “X” calls into a contact center and starts through the IVR menu tree. When the customer is not able to get the response they need through the IVR self-service application, their call is sent to an ACD system which queues the call and selects an agent for routing. The agent receives the call, solves a problem or makes the sale by retrieving and entering the information into a CRM application. In this simple case, the customer’s call traversed three systems: IVR, ACD and CRM. The customer, however, doesn’t know or care about these multiple systems and instead thinks of this sequence as a single interaction.
To analyze at the Interaction Level, you need to “follow” the customer as he/she moves from system to system, and link those transactions together. Today, this type of analysis is rare or is limited to just a few transactions within an interaction. Many interactions are not even tracked or, if they are, that information is not readily available to the contact center staff.
By linking together transactions across systems and making them available to contact center staff to analyze, supervisory personnel can now see interactions in the way they were experienced by the customer as they traversed these systems. This allows contact center managers to connect the dots and determine how best to deliver optimal business outcomes on a predictable and repeatable basis. For example, they can correlate paths taken in the IVR to dispositions in the CRM application to determine how best to tailor the IVR to improve self-service rates, or how to adjust agent-level routing strategies to ensure that callers are handled by the most appropriate agent.
Customer Engagement Level: Utilizing Your Data
The Customer Engagement Level typically consists of multiple customer interactions, which a customer undertakes to handle a particular issue. Often, there are multiple interactions with the same intent per engagement, especially if customers are unable to accomplish their tasks easily. The engagements might be separated by time, and might include several methods of getting in touch with the company.
For example, a customer might do “progressive research,” first reading information on the web, then contacting the company via a web form or email, and then calling an agent (perhaps several times) about a single issue. Or a customer might call in, go through the IVR and ACD to an agent, only to get disconnected, and start over again. Determining the relative value of the various touch points can help maximize effectiveness of your sales, service and support operations.
Analyzing the Custom Engagement Level could yield valuable insights, which are not available at lower levels. For example, this could reveal how many actions it takes for a customer to receive what they need or the behavioral patterns that people typically take to resolve issues.
Customer Journey Level: The Sum Total of the Relationship
Which brings us to the final stage, the Customer Journey Level. This is the collection of all the customer engagements a customer and the company have over the course of their relationship. A customer journey can take place over many years. Analyzing at this level, allows contact centers to determine valuable information, such as the estimated lifetime value of each customer, how to provide better support, and how to improve net promoter scores and customer satisfaction survey results.
Tracking Customer Engagements and Journey
By linking data among different contact center systems, contact centers can generate meaningful insights into how to best serve customers to optimize business outcomes. The first step in this process is turning data into information by collecting and organizing the various events, transactions and interactions that make up a customer journey. Bringing this data together has historically been a challenge since the various contact center systems don’t talk to each other, multiple interactions can be separated by time, and that call centers are often geographically dispersed and outsourced.
Until recently, such mapping has been restricted to big organizations with the time and resources needed to build and maintain complex data warehouses, and keep them up to date as technology advances and business changes. Fortunately, things are different now, as there are many technologies available to fundamentally change the contact center by making analysis at the Customer Engagement Level possible, no matter what the size of the business.
These technologies include:
- The Big Data technologies derived from the work of Google, Facebook, Yahoo!, LinkedIn and others;
- Data-analysis and visualization techniques coming out of universities and open source communities;
- NoSQL databases;
- Predictive analytics; and
- Last, but not least, cloud-based infrastructures.
The result is that, today, organizations of any size and budget can gain dramatic insights into customer behavior at a realistic price point for the contact center budget. They can analyze the historical view to improve customer interactions and relationships to truly trace the customer journey and learn what works, what doesn’t and what they can improve.
Through focusing on the Customer Engagement Level, you can change the focus of your contact center from promoting efficiencies and cutting costs to making your customers happier, becoming easier to do business with, and driving better business outcomes. By approaching your analysis at this level, you can get a full picture of the customer experience, information that can help you improve your business, increase sales, and enhance the overall customer journey.