Today’s consumers are quick to speak up when they are dissatisfied with a company’s customer service.  Further, they appear increasingly inclined to switch brands if they don’t believe they’re getting a good experience. According to Accenture’s 2013 "Global Consumer Pulse Survey," 51 percent of U.S. consumers switched a service provider in the past year due to poor customer service experiences, up 5 percent from 2012.
The Connected World Breeds Big Data

Our networked digital economy generates swarms of bits and bytes, and today’s advanced analytics give organizations the power to turn this data into meaningful real-time information about consumer desires and preferences.  As a result, companies can take advantage of more customer insights to meet customer expectations.
But, as reality and the rising consumer tendency to switch brands shows, many companies are either not making proper use of analytics or they’re not translating big data insights into actions that will make improvements for customers. Organizations are failing to put their customer knowledge to work to deliver a personalized level of service that anticipates, meets and  ideally  surpasses their customers’ expectations.  
What’s the Next Best Action?

For companies seeking to make the leap from insight to execution, an analytics-driven marketing approach proves fruitful. The “next best action” approach gives companies a pathway to execute against big data insights, using the optimal blend of channels, platforms and offers for any given customer in any given context. 
In short, next best action extracts predictive insights from big data to direct what offer you should make next time you talk with a customer, whether that’s a new product, a discount, an apology or nothing at all. Leveraging advanced analytics, this personalized marketing approach uses information about the customer’s interests and needs and marries it with the marketing organization’s business objectives, policies and regulations.  In sharp contrast to traditional marketing, with the next best action approach companies create an offer for a product or service first, and then work to find interested and eligible prospects.
Driving the next best action approach is “time decisioning” technology that leverages call center data, transaction data, customer information and a set of business rules to determine the one or many offers for which the customer is eligible at the moment of interaction. The offers are then prioritized and optimized to determine the most compelling offer. This prioritization is driven by an algorithm that combines advanced analytics, which compute the customer’s propensity to accept the offer, and complex business rules that determine how the customer offer is structured.  
Delighting Adam

It’s beneficial to understand some of the specifics of how a next best action approach uses analytics to drive an overall improvement in the customer journey across multiple touchpoints.
Consider the example of Adam, who has a problem with his most recent cell phone bill. Adam contacts the contact center of  his telecoms provider.  The call center agent quickly deals with Adam’s billing request, and is then prompted by the CRM system to tell Adam about some offers on his call plan. 
The offers are specially generated for Adam by the next best action system, based on his profile and call reason. The top offer from the agent is an additional 2GB of free data use, since Adam’s usage rate has increased in the last period, but Adam declines it. The agent records Adam’s response in the system, which then immediately calculates a new proposition. The next offer takes account of Adam’s lack of interest in data, and instead proposes a free text messaging add-on, which he accepts.
Later, Adam accesses his account through the telecom provider’s Web portal to activate his text message add-on, and the offer from the agent is displayed. A couple of clicks, and he is ready to go.
But Adam is still concerned he is spending too much on calls and wants to review his package options. He decides to stop in at one of his provider’s stores. The shop agent enters “Complaint – high spending” as the reason for Adam’s store visit and the provider’s next best action system proposes a specific telephony bundle designed for his needs. Additionally, the agent tells him that he can get a new smartphone with this bundle, while noting that his overall spending will be lower than his current package. Adam is pleasantly surprised by this offer and signs up.
Real-Time Analytics for Real Improvement

As this example illustrates, the key to the next best action approach is the ability to learn from, and react to, customer information in real time. At every stage of Adam’s journey, for example, the system gives the telecom provider relevant offers at the right time to make a positive experience for the customer. Brought to life by advanced analytics and big data solutions, it’s this ability to respond intelligently and on time, with offers that are personalized and relevant to both the customer and the context, that lets the telecom provider turn a dissatisfied customer into a delighted one. 
Today’s connected customers are more demanding and inclined to switch providers than ever before. For companies that can harness the power of analytics to provide better experiences to dissatisfied switchers, $1.3 trillion in revenue  is up for grabs, according to Accenture research. The next best action approach vastly increases the chance that the next step in the customer journey is the right one – and also a successful next step for the company toward analytics ROI.

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