A couple of years ago, the focus within CRM was directed at major strategic investments, which required substantial remodeling of operational infrastructures. Currently, businesses adopt a more pragmatic approach, looking for ways of achieving cost savings or increasing revenues quickly within their existing environment. They increasingly choose to implement predictive analytics software that allows them to better understand and predict individual customer behavior and directly act upon this knowledge in their marketing or call center environments. The analysis of customer data can result in short-term cost reductions and increased customer profitability.

The basis: analyzing customer data

Predictive analytics enables marketers to accurately analyze and predict an individual customer's future behavior, product needs, attrition and fraud risk, but also his preferences with regard to in what way, at what time, and through which channel he is approached. The results of these analyses are known as customer profiles. For example, analytics software automatically identifies profiles in customers' calling behavior, which indicate the likelihood they will churn in the future.

Customer interaction strategies

These customer profiles form the basis for each interaction. For every customer contact, whether via direct mail, internet, the branch network or the call center, the best possible action to take will be defined. This could be for example cross-sell offers for a specific product, or discount offers to customers whose profile indicates an increased churn risk.

Deciding upon the most effective offer

The moment a customer contacts the company, all possible actions are reviewed. When doing so, both the individual needs of the customer on the one hand, and the value that is generated for the company on the other hand, will be considered. The offer that is finally selected is the one that best matches the customer's individual needs and generates the greatest potential value. As a result, a recommendation is displayed on the call center agent’s screen, a banner is shown on the customer's web page, or a personalized direct mail piece is sent to that particular customer. Several organizations have achieved substantial cost savings by better targeting their marketing campaigns, and have improved call center sales performance by doing targeted commercial offers based on predicted customer needs.

Companies generally use a phased approach when integrating analytic software into their sales, marketing and services activities - they mostly start deploying analytic software at one channel and then roll it out to the other channels. A typical phased introduction encompasses the following steps:

Step 1: move from bulk outbound campaigns to small, event-driven campaigns

This first step can be divided into two phases. Using predictive analytics helps to predict which customers are likely to respond to a mailing. As a result, only customers who are potentially interested in a product are approached, allowing for a substantial reduction in mail volumes. This leads to immediate savings: direct mail costs can be reduced by approximately 25 to 40 per cent.

By keeping track of changes in customer data, analytics software can also be used to identify when a customer needs to be approached. Events such as the purchase of a house or a deposit to a bank account, can be used to determine the ‘window of opportunity’, i.e. when somebody will be interested in a particular product. This enables event-driven marketing campaigns, where exactly the right offer is brought to the customer's attention at exactly the right moment.

Analytics software automatically investigates each customer in the database to determine whether recent behavior indicates a need to contact the customer, via direct mail, email or by telephone. The software also identifies which messages are available for this specific customer and which of them generates the most value for the company and the customer. If a customer qualifies for more than one campaign, the offer that generates the highest contribution margin (i.e. the likelihood that it will be accepted in combination with the value it generates) will be selected – this is called ‘cross-campaign optimization’. As a result, the software generates outbound calling lists or personalized files for direct mail and email. Predictive models can again be used at this point to forecast which channel the individual customer would prefer.

Step 2: optimizing inbound contacts

At inbound customer contacts, the best commercial offer is identified for that customer at that particular moment. The software analyzes all available customer data and the interaction options that apply to the customer, and then defines which option best matches the customer profile. The value of this offer to the customer and the company is also analyzed. The recommendation is transferred back to the relevant channel, which might result in a news flash on the customer's personal web page, or a sales recommendation to the call center agent during the telephone conversation.

Step 3: multi channel customer contacts

A number of companies have progressed on to the following stage: they realize that revenues can be increased even more by making the offers on the various channels consistent, so that each message reinforces the others. These companies are in the process of implementing a true, centralized multi channel approach.

The main challenge in managing multi channel customer contacts is that if commercial offers are presented via multiple channels, they have to complement each other. Inbound and outbound customer contacts must be exactly matched to each other. When preparing an interaction, the software will look at the most recent customer data and any interactions via other channels, ensuring that consecutive messages sent to each individual customer are consistent and match the customer's profile. This way it will provide an up-to-date picture of all ongoing promotional actions for individual customers, the effectiveness of the messages, and the influence they have on the objectives for each segment. This central monitoring function allows rapid adjustment and improvement of customer strategies.

The advantages of centrally orchestrated customer contacts

An environment in which all customer interactions can be centrally defined, executed and monitored, and which is linked to all available channels, offers companies several advantages, such as:

• Optimized customer contact approach

Customers are approached on the basis of their behavior and needs as individual customers. As the most suitable and profitable message is determined for each of the channels (inbound and outbound), all potential opportunities are exploited to the full. All interactions on the various channels are made consistent with each other for each individual customer. This way, maximum profit can be generated from the existing customer data.

• The ability to control and manage

Controlling and monitoring the customer strategies across all channels in a single and central environment makes it easier to administer and oversee interactions. This results in lower administration and maintenance costs, and allows for rapid adjustment where necessary.

• Rapid implementation, immediate results

The implementation of a centralized multi channel approach is relatively easy. As it is achieved using standard software that integrates with any existing call center, internet and direct marketing environment, it can be implemented in a short time frame. The implementation and use of the software only places limited demands on available resources. The application has proven its value with many leading companies and starts to deliver results almost immediately.