Marketing intelligence databases
With the need to be able to track and monitor customer relationships and competitor activity, it soon becomes essential to have a good system for capturing this market intelligence so that it can be shared within the organisation and used for analysis purposes.
dobney.com can design and implement bespoke marketing intelligence databases for both competitor intelligence and customer knowledge. See our Notanant product for a live example of a generalist marketing intelligence database.
What we mean by a knowledge database
Market intelligence databases are systems that allow for the capture of information about customers and competitors and help disseminate that information to appropriate staff. For example Notanant. This differs from existing CRM (customer relationship management) systems in that typically CRM systems are used for providing automated scripts, taking and recording orders and providing event driven prompts to users.
Instead we are looking at a database that enables the capture of relatively unstructured information about customers, that allows for this information to be searched and that enables this information to be forwarded directly to interested parties. We can link these knowledge databases to existing CRM or transactional databases, however this usually entails a level of processing overhead to sift and summarise the transaction data and adds to the overall complexity of the system
How it works
Typically a knowledge database will enable anyone to contribute a snippet or titbit of information about a customer or a competitor. Data entry is carried out via a web-browser and files can also be uploaded or published to the database (for instance copies of documents sent to clients). Data can also be gathered and added through the use of spidering agents that monitor key web-sites such as your competitors.
To help maintain the usefulness of the data, editors can be appointed, or a system of peer-review incorporated. These are simple systems whereby one person or more must pass the information before it is incorporated onto the database. This enables the data to be checked and classified appropriately.
Once data is accepted onto the database, the system can be triggered to push the information out to interested parties. For important information this can be done immediately, for less important but useful data this might be in the form of a weekly "newsletter" tailored to each user.
Interested parties are also be able to search the database by customer, theme and by content to extract useful information or to look for historical trends. By using certain standard fields and data, key summary data can also be extracted easily.
These knowledge databases can also be supplemented with information that monitors the customer's views, such as Relationship Assessments, or other surveys where the customer provides information directly. This approach can be extended directly into self-maintaining databases (see below) or take a look at Notanant to see how this is done.
Most databases suffer from the problems that data entry is a laborious manual task and that the data that the database contains deteriorates over time (for instance addresses and contacts change).
One solution to this is to build a knowledge database that allows customers to view and update (some of) their own information and provide their own comments and description of what they do and what they are looking for.
Using an approach similar to that of knowledge databases, it is possible to extend the data entry and viewing so that your customers can look at and modify their own data as appropriate. By using a system of reminders, and possibly incentives, customers can be encouraged to maintain their own data.
For help and advice on building marketing intelligence databases please contact email@example.com