Customer knowledge systems
Customer knowledge can be collected in a wide variety of ways. The key to a successful customer knowledge system is making it easy to gather and update the data and making it useful to those people looking at the data. Customer knowledge systems have mainly been developed for use in B2B markets, but with the internet and Big Data, it has become possible to build systems for capturing consumer interactions as well, though the principles are different
The traditional method for building B2B customer knowledge systems has been to write up and store reports on account meetings and sales contacts.
The difficulty with such an approach is the volume of paper based information that is generated, often for little effect as few people actually read the information, valuable though it is.
The second generation approach was to use computers to gather the same information. However, this also suffered from a weakness that the data was not really completed as effectively as it was on paper and most of those completing the data tended to be away from the office in the field.
The third generation approach has seen use of the Internet and intranets to collect information that can be shared amongst colleagues - for example Salesforce.com or other CRM vendors. Theses online or cloud-based solutions allow data to be shared about individual customers on a multi-national scale, and allow smaller businesses to maintain track and manage small scale business relationships.
This can be taken a stage further with the development of self-maintained databases where customers keep their own information up-to-date in return for a discount or financial incentive or just because you're the best to deal with. As the boundary between customers and suppliers blurs, these are likely to become a more common approach to doing business and sharing information.
In the consumer world, customer knowledge used to be restricted purely to transaction databases and being transactional in nature, they often couldn't be searched or used in real time. The arrival fo CRM systems made it much more possible to keep track of communications and contact with individuals, but the dramatic change since 2010 has been the availability of social media, plus web-tracking on top of web-based transactional systems. The result is the idea of a Single Customer View (SCV) where all elements of an individual customer are brought together in real-time, for instance to allow customer services or telesales to see more about the behaviour and interests of the person they are talking to on the end of the phone
This single view is also leading to the development of algorithmic marketing. That is targeting of individuals based on what you know or can model about that individual. For instance Amazon shows related products based not just on what you are looking at, but also based on what you have looked at in the past and your purchase history. Similarly Google is using personally tailored advertising to direct adverts to individuals based on who they are, rather than just on what they are searching for.
In algorithmic marketing, the knowledge system uses a range of modelling, similarity and experimentation techniques to tailor content and offers based on the information known about the visitor or customer. These are early days, but this type of marketing is likely to become much more dominant in coming years.