Since then the LDS has released a number of basemap services and this blog will outline how to access and use these basemaps in the latest versions of MapInfo Pro and Spectrum Spatial Analyst.
Spatial analysis is about releasing insights from data and visualising it in a way that can be easily communicated. Before you get to the maps, it’s all about the data.
There are two principle forms which the data used in a Geographic Information System (GIS) can take, vector based and raster based.
There’s no getting around it. The user interface and ribbon introduced as part of the MapInfo Pro 64-bit release can take some getting used to.
If you’re a seasoned user of MapInfo, you would have built habits around working efficiently with the 32-bit toolbar and menu interface of the classic MapInfo and you can’t change those habits overnight.
However, we want to share with you some tips for getting the ribbon working for you, because when combined with the other user interface improvements in the 64-bit MapInfo it does provide a much improved user experience.
So here are our top tips for getting the ribbon working for you.
Pitney Bowes has started 2015 off with a hiss and a roar. Not only have they unveiled a global launch of their brand and identity they have been busy rolling out a strong update to MapInfo Stratus – the easiest way to publish and share and visualise data from MapInfo Pro. This update to MapInfo Stratus contains some significant new functionality and updates to existing functionality that will be of significant benefit to all users.
So, here’s what new and shiny in the latest release of MapInfo Stratus
The decision to open or close a retail site represents a significant investment for any retailer. Bunnings Warehouse for example, announced a 3 year investment of $1.5bn in 78 new stores across New Zealand and Australia in 2012. Choosing where to expand or pull back requires a solid understanding of the economic potential within each pursued market. Combining location data with location intelligence helps to understand the sales potential for each alternative site in terms of total revenue, specific customer segments, product mix and service range.
Having the ability to visualise “what if” scenarios can help analyse the impact of new competitors, store consolidation, expansion and cannibalisation. For retailers who have numerous locations, customised store site modelling systems can help to identify specific pockets of opportunity by quantifying the relationships between store performance and various market and buyer parameters.
At Critchlow, we eat, sleep and breathe spatial data and we typically use FME to get the job done. In our minds, there’s simply no better spatial data transformation engine available that can connect, transform and automate spatial data the way that we can using FME. That said, we still get a lot of questions from folks about why we love FME as much as we do, so I wanted to list out a few of the more major reasons in a blog post. To help me I asked some of our consultants who recently had some FME training about what they love about FME – you’ll see their comments below.
Note that this is NOT meant to be an all-inclusive list by any means or a rundown of all of FME’s features – in fact, I’m purposely leaving out quite a bit as that would be a waste of time. Hopefully, however, this post will provide you with a better idea for what the rave around FME has been. Enjoy!
Why is good data so important?
To identify profitable retail locations, acquiring customer and target market data is essential. It is estimated that over 80% of collected data has a location component. However, this data has to be accurate and up-to-date in order to get the best results from Location Intelligence software.
You need to be careful when using data with a location component as common data quality issues can occur. For example, when a customer moves location this can trigger a duplicate customer record, instead of a modifying an existing customer record. Knowing that more than 49% of the New Zealand population had lived in a different dwelling as that at the time of the 2013 Census during prior five years, this is no trivial scenario.
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.