Structured Data

Content management 2.0

Structured data is data that is stored in in its simplest form without repetition making it easy to create, update, translate, find, purchase and deliver. 

Populate has been built to allow data records to be created, have attributes attached, to be grouped together, and then the records to accessed from multiple directions, linked and output in any way you want. The typical use of this is for product management and ecomerce but it can be applied to anything that needs to be catalogued. Populate has been built to that we can create custom elements on demand and attach attributes, images. location and additional fields to them without having to re-engineer the code or extend the database structure each time, while benifiting from future improvements with mimimum labour required and therefore cost

All of the data is fully integrated and can be pulled and manipulated as required. If you've ever tried to integrate a WordPress site with data from multiple plugins you'll know what we're talking about here.

Attributes

The following is a list of attribute types that can be linked to a data record. All of these attributes can be used as an access point or a property:

• Text and html in multiple languages.
• Pricing in multiple currencies.
• Purchasable SKUs - this can be anything from sizes and colours of a t-shirt to a specific seat in a cinema or auditorium.
• Multi point Geo location data.
• Images.
• Files.
• Input fields.
• Dates.
• Booking calendars.
• Colours.
• Stock.
• Options.
• Pricing.
• Numeric values.
• Boolean values.

Grouping data

We have many ways of grouping this data. Using an ecommerce store as an example, you have a normal products in sections scenario, you can tag products and then group by the tag. We have methods of creating linked types, for example you have a printer in section called office equipment, it can be tagged in special offers and new products and any other tags you want to set up, you can then create linked types e.g. alternative products, these can be rendered on the product page, you can set up another called 'supporting products' these can be shown as the user adds to basket to try and increase the order with paper and toner. You can have a news blog that then has linked products where you can select your printer so that if a user hits your site reading about the 'latest printers from HP' you can link them directly to your printer page and hopefully drive a sale. All these link are fully managed, if you stop selling the printer, change its URL, price or it stock level, these changes are reflected wherever the data is rendered.

Output

The output of this data can then be approached in a similarly flexible manner, think of this data as a ball floating in space which can be approached from any direction, whatever data you or your customer needs can be retrieved based on any criteria and any fields within the dataset delivered however you want.

A few examples:

• A visitor to your ecommerce store searches for products that are red, below £10 and in stock.
• You have an event website and a user needs to search for sporting events in a 100 mile radius, that are football related, in June this year and still has availability.
• A user of a booking app needs to find accommodation in a certain town that allows pets and is available on June 27th.
• You have an app that needs to pull live stock feeds from the same data source as your website.
• You have multiple stores that all carry stock and the customer needs to know which is the nearest store that has a certain product.
• You have a catalogue site for your product range where you can attach whitepapers, software downloads and safety data to your products and make them searchable.
• You want your products to be customisable upon purchase, where a user can input various criteria before purchasing.

Our approach to data is truly modular. If we don't do it already we're pretty sure we accommodate your requirements, get in touch, we're more than happy to discuss your requirements.