Do you want batteries with that?
How to improve customer interactions with real-time decision making
When your customers are making decisions on the spot, the timeliness and relevance of your interactions with them become even more critical. But how often does on-the-spot decision making actually occur? According to the Peppers & Rogers Group article “Stop Random Acts of CRM,” as much as 50 percent of the customer decision-making process occurs in real time.
Now more than ever, it’s vital that your customer contacts know how to make high-quality, real-time decisions during each customer interaction. Immediate decisions must be relevant to customers’ needs and values, reflect the strategy of the business, and help maximize the organization’s profitability. Being able to make those top-notch decisions repeatedly can separate highly successful businesses from those that struggle or fail.
Using real-time decision-making technologies can provide a framework for:
- Meeting the ever-changing needs of the customer.
- Automating and controlling the decision-making process.
- Adapting to changing business strategies.
New technology makes previous approaches obsolete
Making decisions in real time is nothing new. What is new is the latest breed of decision-making technology that enables an organization to manage real-time decision making effectively. These technologies are designed with easy-to-use interfaces for call-center and customer-care employees, but they are managed and controlled behind the scenes by business analysts.
Because decision criteria can be modified within the system, analysts can make changes to streamline the development and implementation of new business strategies. Prior to the availability of this type of technology, decision logic was hard-coded in a call-center or Web-based system.
Today’s technologies take advantage of a service-oriented environment, so organizations can react to changes in the marketplace at the speed of business – not the speed of IT development cycles. Prior to the availability of real-time decision making, organizations would often precalculate many important factors in an attempt to predict a customer’s future behavior. However, this approach had three main problems:
- The factors often became obsolete as situations changed and new information was gathered.
- The sheer volume of alternatives, and the frequency with which they were calculated, placed a huge burden on the IT infrastructure.
- Most organizations used only the most simplistic rules or business logic.
Now, organizations can be more successful and increase the long-term value of customers with business-oriented technology that:
- Employs an open and scalable architecture.
- Delivers advanced decision-making capabilities.
- Provides the information needed to make smarter marketing decisions.
Making real-time decisions in the call center and online
Today’s customers expect a personalized experience whether it’s through the Web, call center or other customer touch points. Customers want to be sure that companies address their needs and treat them as individuals.
Let’s illustrate how a real-time environment might work in a call center. A customer calls in to check her account balance and inquire what the minimum balance is to avoid penalty. Based on these inputs, plus the customer’s past behaviors and transactional history, the real-time decision-making system determines that her profitability is above average and she shows great potential for future returns. However, the system also shows that this customer has a high probability of leaving for a competitive service.
To discourage the customer from leaving, the decision engine now looks for the most appropriate offer to increase the probability of this customer’s loyalty. The results are given to the call center representative, who can quickly act on the information and propose a win-win situation for the customer and the organization.
Web sites can benefit from real-time decisions, too. Take, for example, the process of assessing the risk of a potential applicant. Using a credit score provided by a bureau can become stale and not fully reflect the creditworthiness of a customer. By using real-time decision making, a Web site can augment the standard information about an individual’s credit with payment history and other transactional information to calculate a real-time credit score that can potentially outperform those provided by the bureaus alone.
With in-house predictive models and a model-management process, you can make the most of your customer data by consistently using the most up-to-date predictive information. This best-practices approach leads to a competitive advantage for your organization.
In a retail e-commerce environment, customers often feel overwhelmed by the broad range of products and services that are available. Real-time decision making can recommend banner ads or other small advertisements for products or services to help focus the customer on the most relevant products. These choices are often determined through analyzing the past purchasing behaviors of your entire customer base or through making standard offers surfaced for all customers – in other words, messages are not tailored to a specific customer.
Real-time decision making can increase the precision of offers by looking at not only the products that an individual customer has recently purchased and other key customer information, but also by looking at products that the customer is currently exploring on the Web site or that the customer has placed in a shopping basket. Performing market basket analysis and other forms of predictive analytics in real time lets the retailer make more appropriate and relevant marketing decisions.
Integrating inbound and outbound marketing in real time
Outbound campaigns will continue to be a popular mechanism for communicating with customers. However, inbound marketing has been underused and presents a tremendous opportunity to increase profitability and enhance the customer experience. Moreover, coordinating inbound and outbound marketing in real time can provide a way for organizations to communicate with customers with a single, cohesive voice.
Let’s take a look at a cellular phone user to illustrate the real-time coordination of inbound and outbound marketing. While using his phone one day, the phone user experiences three dropped calls in a row. He becomes extremely frustrated and calls the service provider to complain. The call-center representative who responds is alerted through real-time decision making that this customer has experienced difficulty. The call-center representative can pre-empt the discussion about the dropped calls by acknowledging the problem and making a special offer.
The real-time decision-making system is integrated with an e-mail marketing system and sends a coupon to the customer immediately. It then places the customer’s name in a queue within a campaign management system to receive a courtesy mailing the following week.
The SAS® solution
SAS Real-Time Decision Manager automates the decision-making process to provide recommendations for customer-facing systems. The solution lets business users construct decision-making processes in an interactive, visual environment. These customized decision flows can operate on data from any source and apply advanced analytic techniques and business logic to determine decisions and recommendations.
SAS Real-Time Decision Manager integrates with many types of customer-facing operational systems, including call centers, Web sites and ATMs. When SAS Real-Time Decision Manager receives a decision request from an operational system, it processes a decision flow that can determine a customer’s eligibility, score a customer’s propensity to buy a certain item and calculate the customer’s creditworthiness based on the latest transactional information. The result of the decision flow is a recommendation that is passed back to the operational system, where it is presented to the customer.
Recommendations might include:
- A simple product offer, such as, “Do you want batteries with that?”
- A simple yes/no decision, such as whether to authorize a transaction.
- A prioritized list of offers that a call-center representative can present, such as 10 percent off; buy one, get one free; or free shipping.
- Specific conditions that should be applied to an offer, including terms, transaction fees or annual percentage rates.
These processes can be repeated as many times as needed during a customer interaction. Plus, the solution ensures that the same criteria can be used for consistent communication and treatment of customers across channels, products and business units. All of this adds up to a dynamic, highly relevant and profitable relationship with customers.
Larry Mosiman is Product Marketing Manager for SAS Customer Intelligence.