When you are trying to understand the customer experience or CX maturity of an organization, Maslow’s hierarchy of needs is a useful analogy. To simplify it to death, before thinking of self-actualization needs (e.g., living a fulfilling and meaningful life), a person must meet their basic needs for physical survival (e.g., to fill their belly).
Similar to an individual, a CX organization must meet its more basic needs before advancing to higher ones. This pyramid with four levels provides an easy way to plot CX maturity for a given organization.
The 4 Levels of CX Maturity
The levels are:
- “Just do it”: any support is better than no support, even if it is the CEO/founder answering customer emails from her bedroom.
- “Competency”: run a tight ship. You as Head of CX (yes, at this point this role is filled) are running a high quality support operation efficiently. You know what drives contact and how to respond to customers. You have processes in place to manage the resources required to perform your job and achieve the right outcomes, but running these processes takes a lot of manual work. Reaction time is slow. Achieving full visibility and high specificity of analysis and action is hard.
- “Expertise”: improve visibility, precision, and speed of reaction. Specific and timely insights are available to you and they enable precise actions with rapid reaction time.
- “Mastery”: move from reactive support to turning CX into an engine for proactive action and business growth.
Let’s take the major areas of concern a CX department must deal with and see how they evolve as an organization moves up the pyramid. The areas are:
- Customer contact reasons
- Outcome measurement
- Workforce management
- Agent evaluation
- Agent enablement
- Self-service
- Automation (chatbots and email auto-responders)
- Trends/insights
Customer contact reasons
In the “Just do it” phase, you are lucky if you know the most popular reasons for contact from your intuition and memory. It is completely qualitative (and potentially misleading), but you get by with you have.
In Competency, you have manually created a list of tags for contact reasons. You are asking agents to tag conversations. You have built some reporting dashboards for tracking the volume of various contact reasons. You review the taxonomy every few months. An emerging issue might take a couple of weeks to notice. Data coverage and accuracy are questionable.
In Expertise, Natural Language AI based products help you discover reasons for contact and organize them in a taxonomy. Issues are specific and actionable. AI tags conversations automatically in real time. You are alerted to emerging issues the same day.
In Mastery, you anticipate customers’ issues instead of reacting to them. You are aware of the broad context of the business (upcoming product and feature launches, marketing campaigns, etc.) and partner cross-functionally on the best ways to predict and monitor contacts. Your knowledge of your customers allows you to proactively help them in their customer journey in a personalized way.
Outcome measurement
In the “Just do it” phase, the only KPI is “did we respond?”
In Competency, you start asking yourself “Did we respond well?”. You run CSAT or/and NPS surveys after conversation completion. They do provide answers, but suffer from all the known limitations of these surveys: 10-20% response rate and a bias toward the more extreme opinions.
In Expertise, you have a way of knowing the resolution status and customer satisfaction for the majority of conversations close to real time. Detailed analysis can be performed by contact reason and other groupings. You can dive deeper and know how particular macros and techniques your agents are employing contribute to your success metrics.
In Mastery, the way you are measuring yourself goes beyond satisfaction. Now you are fully aligned with the goals of the business – LTV, customer activation and retention, purchase behavior, etc.
Workforce management
In the “Just do it” phase, you don’t have enough workforce to manage. And even if you did, it’s all hands on deck so there’s no free time to manage anyone.
In Competency, you use basic spreadsheets to manage a shift or two. Agents know when they work and which channels they work on. You know how many people you need for each channel to be staffed at the bare minimum. You don’t play with this model too frequently and don’t optimize every hour.
In Expertise, you move to a more granular management of hours and shifts. Workforce Management products help you with some automation. You input the resources you have and they recommend and staffing levels, including predicting spikes. You are able to optimize not just days, but also hours.
In Mastery, your agents both handle the more complicated inbound tickets that are not resolved through self-service and automation, and proactively help customers in. Workforce management must accommodate both these objectives.
Agent evaluation
In the “Just do it” phase, you might stop by an agent’s desk or occasionally check out a random conversation.
In Competency, you have set up a process of manually QA-ing a small percentage of conversations, with a delay of at least several days. Your scorecard is solid, but it is not easy for you to prove that every agent behavior you are checking for is optimal. Visibility is limited, coaching is delayed, but you know how your agents are doing.
In Expertise, AI automatically scores the majority of scorecard’s line items across almost all conversations. It also helps QA analysts choose the most impactful conversations to review the rest. QA’a output feeds into effective agent coaching that is done close to the time of the interaction. You can link the agent behaviors that you are checking with outcomes.
In Mastery, agents handle only higher value and more complicated tickets and they are expected to drive business goals. Agent evaluation focuses on the contribution to these goals (LTV, retention, etc.), not just on agents performing the behaviors that are expected from them.
Agent enablement
In the “Just do it” phase, you created a document with common macros. You and your agents (if you have any) use it to save time replying to emails and chats.
In Competency, you have built a curriculum and use it to conduct new agent training and periodical refreshment. Agents have access to a doc that documents current policies and issues. It is possible that you have moved beyond one doc and adopted a knowledge base tool created an internal and try to keep it up to date. Manually created macros.
In Expertise, Agent Assist solutions make knowledge distilled from all the KBs, documentation, and previous interactions available to agents in real time. The most effective and appropriate macros, snippets, and solutions are suggested based on the context of the conversation (contact reason, customer’s segment, history and sentiment) and help agents maximize resolutions and customer satisfaction faster.
In Mastery, agents handle only higher value and more complicated tickets and they are expected to drive business goals. You enable them to do faster research, see the full picture of the customer they are helping (client health, churn risk level, and total LTV to date, etc.), and interact cross-department.
Self-service
In the “Just do it” phase, you most likely have created an FAQ page, based on your immediate experience of which questions belong there.
In Competency, you made a help center available for customers. You manage its content manually. You have instituted a process of periodic review and update. Analysts can run an ad-hoc analysis of articles effectiveness for deflecting contacts.
In Expertise, opportunities/topics for self-service are continuously surfaced automatically based on conversations. Technology monitors the interaction of customers with the content and suggests improvements. The table of content is automatically managed for relevancy and personalization.
In Mastery, you move from reactive to proactive self-service. You automatically reach out to your customers in critical moments (e.g., their credit card is about to expire, a shipment is out for delivery, etc.)
Automation (chatbots and email auto-responders)
In the “Just do it” phase, it is unlikely you have any automation.
In Competency, you have deployed a chatbot and/or email auto-responder. The setup required significant manual work to create flows and answers. The automation deflects some contacts and saves agent time by collecting basic information from customers. It is difficult to know its effect on customer satisfaction and to improve it.
In Expertise, the setup of automation, monitoring its effect on conversation outcomes and surfacing of improvement opportunities are heavily assisted by AI. The automations become more self-managed and generate answers based on all the knowledge it has access to, such as internal knowledge bases, ticket history, company websites, etc.
In Mastery, automation looks a lot like self-service – proactive, personalized and focused on business outcomes, not just on status quo.
Trends/insights
In the “Just do it” phase, you rely on occasional anecdotes. You have no real visibility into what is going on. You are in the ocean of darkness and know that you found a rock only because you stumbled on it.
In Competency, you have enough data for an analyst to start telling interesting data stories. Your QA may double as analysts, because they are the one reading the transcripts. Prioritization is a challenge because of limited visibility and manual process of this analysis.
In Expertise, automated continuous mining of conversations surfaces emerging issues, trends and anomalies that help drive product roadmap, development, policies and marketing. Automation creates broad visibility, specificity and prioritization.
In Mastery, you are running a powerful Voice of the Customer (VOC) program that correlates trends with business outcomes and enables the entire organization to make decisions and optimize the overall business.
Taking the next step in your CX maturity
The Hierarchy of Needs makes it easy to tell the story of any organization’s CX maturity. But it also gives you a clear roadmap for ways to get to the next level, along with a clear way to tell if you’ve arrived. The next step is putting it to work to make it easier to give your customers the best experience.
