2. Opt-outs: Site visitors should be able to use the privacy reports to opt out of any data collection or targeting. By providing these opt-outs, the use of data is always at the discretion of the website visitor. If visitors are deliberately avoiding tracking (via disabling scripting etc) then you shouldn’t make any attempt to continue collecting their data. Respect the user’s privacy.
3. Education: It’s important to tell visitors how their data is being used. This will help you build trust with them and recapture a “village store” relationship. When a regular customer visits looking for a particular product, you can make a specific offer using your knowledge of their previous preferences. You might also point out that something they were looking for previously is now back in stock, or send an offer. As the visitor gains trust in the brand or site, and volunteers more information, your customer profiles will become richer and more personalised, allowing you to present the visitor with new, more relevant, targeted content and messages that will further improve their experience of the brand.
4. Never share the data: Customers generally don’t expect you to share their personal data with others – and they’ll react badly if they discover you do this. It’s a trust thing; they provide you with information about their personal needs and, in return, you provide offers and information personal to them.
5. Use of voice: You should know exactly what products a customer has looked at, and whether they bought them or not. Using this information in a cross-channel telesales programme, however, could scare them off. Go easy. Politely remind them of offers in their areas of interest.
6. Be sure you know who you are talking to: While the PC is often (as its name implies) “personal” many machines are used by more than one person.
7. Don’t blow it: The world is full of examples of companies misusing data in their communications, offering life insurance to two-year-olds, for example. This can really undermine brand perception and credibility. Make sure that your data quality is good – and make sure you use it carefully.
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