Sharing Customer and Competitor Knowledge

Customer knowledge has mainly been related to larger accounts in B2B markets, but is becoming more related to consumer-level data. However, the customer and competitor knowledge that you gather is only useful if it is shared among the people who need to know, or to is directed to sales or service systems. For customer-facing staff this means access to relevant information that can help build the case for a sale. However, in B2B situations passive databases that simply record and display information may not be sufficient. The database also needs to be designed so that it can push key information to relevant parties so they keep up on the news about the customers and competitors they are serving.


Customer and competitor databases and analysis can be the preserve of an individual or a small team in the head office who collect and store the information they have on an individual computer. More sophisticated systems will use CRM and large data systems to provide front-line staff with information about each individual customer, but often the periodic reports and presentations from the central team, typically at the macro level can feel quite removed from the day to day experiences of the customer facing sales and service teams.

If customer knowledge is to be really useful, it has to be seen to add value to people's day-to-day work. If it only captures information to a central point, then use will quickly tail-off as the database disappears from view among the hundred and one other things on peoples' desks (the black hole problem). For instance if the customer service team reports minor dissatisfaction with a new product, if the data is not used to correct the problem, the service desk will be tempted to stop reporting the problem.

So in asking staff to collect or share information about customers, it is extremely important that something is done with the data and seen to be done, so that people can see that it makes a difference for the business.

A key aspect of the customer database design is in creating a database that will also package up and send out information to interested parties either in a news flash, for information marked as urgent, or in an electronic newsletter format where data is considered interesting but not urgent.

Typically each user will have a different range of customers and subjects that they are interested in, and different levels of security access to different pieces of information. The database therefore needs to match appropriate information to each user and send it out at the most appropriate time. A news flash or a newsletter will simply provide top-line information plus a hyperlink. To access the full article or document will require use of the hyperlink to access the information. In this way, the database is continually being used to keep people informed and to keep people up-to-date. By making the data and knowledge circulate, the use of the database will increase.

In a web-sales or Big Data world, the volume of work is likely to be too large to be dealt with other than automatically, but the use of algorithmic marketing where algorithms use and build on customer data can be used to refine marketing messages and approaches. The use of algorithmic marketing will depend on the types of data available. An obvious approach is a simple 'also see' algorithm where customers can be directed to new products, services or materials based on how their history matches against other people's web-journeys. This can be extended to unstructured data by, for instance, looking for keywords in communications and targeting those keywords with offers or following up on negative sentiment with specific remedial actions

The most important part though is that the customer data you collect is shared and acted upon. Any customer or competitor knowledge programme needs to include an outline of what will happen with data, what actions can be taken and to monitor to show that the data is delivering outcomes.


For help and advice on building customer, competitor or marketing knowledge systems contact info@dobney.com