The Australian Business Awards 2017 were held recently, with Pitney Bowes taking home a win in the ABA100 Software Innovation category for MapInfo Pro Advanced.
The latest six monthly release of NationalMap™ is being rolled out as we speak and, while it boasts a number of reviews and updates to contextual and POI data; motorway junctions; and retail and shopping areas, the biggest and most notable additions are evident in the roads.
Here at Critchlow, we’re always hard at work. One thing that we’ve been working particularly hard on lately in the geospatial data and solutions side of our business is route optimisation. More specifically, we’re reviewing and improving the alignment of New Zealand roads. Every single one.
Every year, the New Zealand Spatial Excellence Awards pay homage to the best of the best in the spatial industry. It's about recognising the incredible Kiwis who contribute to the sector and provide a benchmark for generations to come.
With a whole lot of free map data apps and programmes available at the push of a button or the tap of a finger, it’s easy to turn your nose up at the offer of what seems to be the same thing but at a price. We get it. Map data that costs precious dollars is the big, contentious, lumbering elephant in a small room brimming with the latest, greatest, hippest developers throwing shiny, colourful free stuff at you.
How do you define urban, rural and remote?
Here’s a predicament you may know well: you deliver services right across New Zealand and charge for the privilege. The service delivery, that’s fine. But when it comes to the pricing of said delivery, that’s where things start getting a little murky.
Location intelligence is now widely used to improve a variety of marketing and advertising activities. The tools and data now available enable decision makers to make evidence based decisions to improve their campaigns based on knowing who their target market is, where they live and work and how they spend their money. While location intelligence has an impact in improving the effectiveness in traditional marketing and advertising it can also have a significant impact in improving the measurement of the 3% of spend on outdoor advertising (billboards, buses/transit, bus shelters etc).
Location Intelligence can be used to consider how different characteristics of proposed locations align with the organisation’s business needs. Organisations may classify retail site desirability, based on its centrality and accessibility within a region whose residents share common demographic and behavioural attributes.
Depending on the target market, different infrastructure issues have to be considered. If students are the target market for a retailer, then being close to public transport is essential. If targeting older demographic then good parking options, easy store access and close public transport access would be important. Or perhaps you might be targeting convenience purchasers on their way home from work. The store therefore, should be located on a main thoroughfare.
In such a competitive industry like retail, businesses need to put their customer and transaction data to work – to enhance decision support to gain competitive advantage. It is imperative a business understands the relationships between trade area demographics, customer profiles and competition for prime site selection and business growth. This information in-turn formulates the value of an area for a business’s products and services. With it retailers can generate more accurate site-specific sales forecasts and create a compelling customer acquisition strategy.
Trade area analysis has its focus on locating and describing the target market. Analysing the trade area is important to determine the reach of existing and new store locations and if sufficient target customers reside within the trade area. To analyse trade areas, the use of Location Intelligence is essential to effectively model physical trade areas. The accuracy of these models will depend on the number of variables being considered, like customer location, competitors and consumer spend or attitudinal data.