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Sharing customer and competitor knowledge

Customer knowledge started as being related to larger accounts in B2B markets, but is becoming more related to consumer-level data.

In B2B situations, customer knowledge databases are not just for data collection, but also need to be designed so that they can also send out key information to relevant parties, both automated and curated by analysts. So for instance, an account manager sees news about his or her customers.

In consumer markets, sharing customer knowledge is less about news going out, and more about providing customer-facing staff with key summary points and a history for the customers they contact.  In both B2B, and consumer markets, controlling access to private information also has to be built in.

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 data store without giving back useful insights, 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 collecting and asking staff to 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.

Consequently, a customer knowledge system has to include tools that 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, or via quick to read dashboards of key information.

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 to the right people.

Where contacts are made, through which ever channel, that information needs to be available and visible to front-line staff. The customer will remember the conversations they had, and the chats they were involved with. The staff need to have this information at their fingertips, so the business feels personal and able to react to customer needs.

The need to reach to needs, and event-driven data can be taken a stage further to make communications with customers more systematic. Algorithmic marketing, where algorithms use and build on customer data, can be used to refine marketing messages and approaches and used to create a system that responds to customers at a more personalised level. This can include self-help chatbots, recommendations and suggestions, or reminders and suggestions dealt with and handled on an event-basis.

The most important part though, is that the customer data you collect is shared and acted upon.

In designing a customer knowledge system, 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. Customer knowledge is not just a passive store of data.


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


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