product data

NFC technology in packaging: does it have a future?

Rarely a day goes by when the Econsultancy editorial team doesn’t receive an email or 10 updating us on an ‘innovative’ development from one brand or another. 

Usually I only glance over emails like this. But on a recent Friday afternoon I got one related to booze, and suddenly the sender had my attention. 

The importance of data personalisation and localisation

Last year Econsultancy published an article claiming that some businesses doubt the value of personalisation.

Although 94% of companies agree that personalisation ‘is critical to current and future success’ less than half of companies are personalising their website experience.

This isn’t because they think personalisation is unimportant, but because they don’t actually know how to make the most of it.

However, even the smallest of companies can target their consumers directly using personalised content.

The importance of high quality product data

If advertisers want to be truly multichannel then they need to have access to, and control of, their product data.

By extracting product data from several different sources, you can fulfil any required channel marketing application. 

Data can be extracted directly from your ecommerce site, existing data feeds or an API, and can then be distributed into hundreds of different online channels, increasing the visibility of your products in front of online consumers.

However, it all hinges on having high-quality product data that is comprehensive, accurate and consumable. 

Keeping product data clean: five steps for quality and consistency

Clearing data rubbishWhether you’re in B2C or B2B,
product data influences buyer behaviour. The quality and clarity of your data
will influence the decision making success of website visitors.

Good decisions require high quality data. The more complex the purchase
decision, the higher the demand for detailed product information.

There is a direct cost to
poor product data; someone has to retroactively go back and make changes, which
can be incredibly time consuming.

In previous roles, I have spent long evenings
correcting data mistakes because it wasn’t done properly in the first place.
Not a good use of anyone’s time.