In my research area, a lot is said and written these days about optimizing the customer experience. Some say it is done by improving key performance metrics such as customer satisfaction (CSAT), net promoter score (NPS) and customer effort score (CES). Others say customer experience management (CEM) is the “new CRM”; some think it is part of a multichannel service strategy, and for others it is as simple as managing social media. In my view it takes all of these, and other efforts, to optimize the customer experience, and thus it is difficult for companies to achieve. Customer experience management is the practice of managing the effectiveness of customer interactions so the outcome meets the customer’s and the company’s expectations. In any case, the key question is how companies achieve this goal.
We consider CEM as a form of performance management, which Ventana Research defines as the strategy, methodologies and process of managing the performance of the organization and its business network by leveraging assets to achieve a common set of goals and objectives. In practice performance management requires measuring what happened in the past and what is currently happening, understanding why things happened and then taking action to improve the efforts of people, processes, information and technology. In the context of customer experience management this means measuring the outcome of all types of interactions (ads, marketing campaigns, calls to the contact center, IVR menus, visits to the website, emails, letters, text messages, video calls, watching videos, instant message sessions and even one-on-one meetings), identifying the reason for the interaction (such as a product complaint, a request for missing information or an inquiry as the result of a marketing email), analyzing why the outcome was what it was, and then making the necessary changes so that subsequent customer experiences match up to the customer’s and the company’s expectations.
Measuring the outcome of customer interactions is in many instances straightforward, among them the time a call took to complete, the sales value of the interaction, sales conversion rates on the website or whether the customer’s issue was closed. In cases such as NPS and CES it is a case of following the required process – usually a simple poll question – and companies can derive concrete answers. But rather often what appears to be simple is actually complex. Take first-call (or contact) resolution (FCR) for instance. Determining whether the customer’s issue was resolved during the first interaction can be complex because companies need to link past interactions across different communication channels to be sure that customers don’t have to get back in touch because the issue wasn’t resolved on the first channel or the underlying issue wasn’t really resolved. Another increasingly popular measure is the lifetime value of customers; in general, the higher the value, the higher the likelihood that the customer is satisfied because he or she continues to spend. The complexity here derives from the number of systems that have to be accessed to arrive at the full cost of doing business with a customer (including marketing, sales and support across multiple channels) and to a lesser extent the number of systems required to determine the revenue per customer.
One of the most important outcomes is satisfied customers; indeed, my research into CEM shows this is the most important metric for most companies. This research also shows that companies use numerous methods of measuring CSAT, from simply getting agents to click on a smiley face, to outbound calls, to IVR surveys and several others; some of these produce more objective and consistent results than others. The most reliable way is to solicit feedback by asking customers to complete a survey after each interaction. This should be done by choosing the survey method of the customer’s choice to increase the numbers of completion. The most efficient way to analyze completed surveys is to use a text analytics tool that can be programmed to analyze all text-based inputs to spot hot issues, trends and customer sentiments. The most mature feedback management tools, based on the Ventana Research Customer Experience Management Value Index, can also produce CSAT scores based on rules applied across all interactions. The leading vendors according to this index include Verint, Confirmit, ResponseTek and MarketTools.
Understanding the outcome of interactions is important. But it is equally important to understand why customers contact the company, as this is likely to have had the initial impact on the customer’s satisfaction and mood. Was it, for example, because their bill was wrong or they couldn’t understand it? To gain this understanding the most mature companies use root-cause analysis that can track trends and events across business units, processes and communication channels. It can, for example, explain an increase in complaints resulting from a mobile phone cell failing, or a particular email campaign having resulted in more than the expected numbers of calls, or an increase in the number of complaints increases because queue lengths increases as a result of agents going sick. With this type of understanding, companies can address the underlying causes, leading to fewer calls to the contact center and less adverse social media comment.
The final step is to take action for improvement. This step can be automated by deploying software that raises alerts based on rules (for example, if a key metric falls outside a set range it sends a message to a designated person), includes workflow tools that create tasks and monitor their flow through a predefined process, and produces a dashboard that shows not only metrics but also trends in how they change over time.
This is not to say that improving the customer experience is just about technology; technology’s role is to support people, processes and information. Outcome analysis, for example, should be linked to people’s performance: If a particular customer was satisfied because this agent acted this way, gave this information and said these things, that might constitute a best practice for interaction-handling. Armed with this analysis, a company could create focused training and coaching that address each individual’s needs and bring everyone as close as possible to using a best practice.
The same is true of processes: Analysis enables you to discover that the best outcomes were achieved by people who followed this path and took these actions when handling interactions of a certain type. Process or desktop analytics products can map how different people handle different interaction types and generate the best practice processes. Companies can then use a combination of training, coaching and technology (for example, a smart agent desktop from top-performing vendors such as Upstream Works, OpenSpan, Cicero, and Cincom) to increase the number of people following best practices. Finally, companies shouldn’t ignore the impact of metrics and the way they reward people for achieving certain metrics; for example, I have seen how agents who are rewarded for holding down average handling times (AHT) find ways of staying within target, often to the detriment of customer satisfaction. Companies need to have a balanced set of efficiency and effectiveness (outcome) metrics that relate to their targeted business goals and to reward people for achieving them.
It is has never been more important to ensure that customers feel satisfied after every interaction, not the least because companies can quickly find themselves exposed on social media. And it has never been more difficult to achieve this goal because customers are now more demanding and want to communicate over many more channels. Technology can help, but successful CEM requires companies to be more customer-focused and willing to change.
Is your company engaged in customer experience management? If so, I’d love to know how you do it, so please come and collaborate with me.
Richard Snow – VP & Research Director