Customer Opportunity Advisor

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Many vendors offer software to identify marketing opportunities by examining customer transactions. These systems all work roughly the same way: Users define patterns of customer transactions that indicate marketing opportunities; the system scans transactions for those patterns; it sends the resulting opportunities to sales departments as leads. But the products differ in important details, including:


· Automated or manual methods to identify patterns. Automated systems are easier to run and may find unexpected patterns. Manual systems are easier for developers to build and for users to understand.


· Analysis of summarized historical data or individual past transactions. Individual transactions allow greater precision and flexibility. Summarized data take less processing.


· Complexity of patterns the system can track. Complex patterns may involve time series analysis, identifying expected events that did not occur and relative value calculations that identify what is normal for a given customer. They are more precise than simpler patterns, but harder to define and more reliant on detailed information.


· Use of standard relational database or specialized file formats. Standard databases are more familiar, and their contents are more accessible. Specialized formats can be more efficient for specialized processing.


· Hosted or in-house operation. Hosted operation is easier to deploy and often requires less initial investment. In-house operation keeps customer data inside the company and may cost less in the long run.


· End-user ability to change inputs, patterns and outputs. End-user control allows quick changes but sometimes limits what can be done.


· Opportunity ranking based on static priority codes or customer-specific value estimates. Static codes are simple to define. Customer-specific values are theoretically more precise but hard to calculate accurately.


· Linking of leads to specific marketing approaches such as telephone scripts. Explicit instructions help agents know what to do with a lead, but may deflect them from exploring a customer's actual situation.


· Provision of a lead management tool for sales agents. Many firms lack such a tool. Others already have one or would rather buy a more sophisticated product separately.


· Option to simulate the effect of rule changes using past transactions. Such simulation is helpful but adds complexity to the product.


No single combination of features has yet emerged as standard. Perhaps one never will. Users with different needs will buy different configurations. The variety of options makes it critical for buyers to examine each product to ensure it matches their needs.


Customer Opportunity Advisor (ASA Corp., 412/220-9300, www.asacorp.com) provides an opportunity extraction product configured for simplicity. It is built on ASA's DecisionBuilder rules engine that lets users define patterns in terms of hierarchical rule trees. These are built with a graphical interface that is accessible to non-technical users.


DecisionBuilder can generate complex rules with calculations, table look-ups, calls to external programs such as scoring routines and references to other rules. Though it does not easily support certain types of complex pattern detection, ASA reports that most opportunity identification users do not think these are important. Data mapping and transformation tools can connect with nearly any data source and rule sets can be called as services through a broad range of technologies.


In setting up Customer Opportunity Advisor, users define DecisionBuilder rules to identify marketing opportunities. Each opportunity is classified by type, such as retention or cross sell, and can be linked to text that describes the opportunity or gives instructions to sales agents. The system also can assign a priority rating, using either a fixed value or customer-specific calculations. Rules can limit the number of opportunities per customer over a specified time: for example, no more than one opportunity every two weeks.


Customer Opportunity Advisor can distribute leads to sales agents and help agents manage those leads. Setup is done by non-technical system administrators who choose from configuration options, define bank branches and create accounts for individual agents. Administrators can specify the number of leads sent daily to each branch and to individual agents, with different limits for each opportunity type. Leads can be distributed to agents automatically, by the branch manager or based on assignments of specific customers to specific agents. The system can import leads from external sources such as campaign management systems and referrals made by other agents in the system. Agents also can enter their own leads directly.


The agents interface is straightforward, listing leads and letting users drill down to details. These include the opportunity description, other opportunities for the same customer, contact information, a form to enter call results and sales and logs of previous interactions. Security limits agents to their own leads and lets branch managers access all leads in their branch. Standard reports show processing volumes and basic sales management information including leads sent, lead status, outcomes and sales. They can be viewed by date range at agent and summary levels.


DecisionBuilder runs on Windows, Linux or Solaris servers. Administrators and sales agents access the Customer Opportunity Advisor interface through any Web browser. Clients operate the system in-house, though ASA also offers a hosted option.


Pricing of Customer Opportunity Advisor is based on the number of branches using the system. The cost ranges from $2,000 to $500 per branch per year, depending on the total number of branches. Implementation fees are additional, but are fairly small since setup is limited largely to configuration of existing software options. ASA helps clients establish initial rules, starting with a dozen standard opportunity definitions. These are simple, such as "customers with a new mortgage and no other accounts," and are supplemented by policy rules such as constraints on contact frequency. Clients typically refine the rules and add new ones by themselves soon after deployment. The product is sold mostly to institutions with 15 to 20 branches.


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