Poor quality data is costing organisations upwards of $15 million per year, on average*. Worse yet, nearly 60 per cent of organisations don’t even measure the financial cost of poor-quality data**.
When you make decisions using the wrong data, you can end up steering your organisation in the wrong direction and it can be hard to get back on track.
Find out how your organisation could operate much more effectively, generate more revenue, and waste less time and money with our free data health check. Get a free data health check or download a free, sample data below.
Pitney Bowes is a global technology company with 100 years experience' helping businesses analyse, visualise and integrate accurate location-based data
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Access accurate, global data from more than 250 countries including addresses, streets, businesses, landmarks, demographics, consumer spending, risk data, and more.
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Solutions for Insurance
Five per cent of homeowner insurance policies and up to 10 per cent of vehicle insurance policies are incorrectly priced because of imprecise location data, which can mean you’re not bringing in the premiums you should be***.
Read this report to learn:
- How precise location data can help you minimise risk and reduce policy under-pricing by as much as $2,000 per policy.
- How you can assess risk more accurately and even predict disasters in near-real time.
- How hyper-accurate data can help you improve your book and increase your profits.
Solutions for government
Between 1967 and 2013, the average direct annual cost of flooding was approximately $943 million (excluding deaths and injuries). More effective disaster management planning could potentially reduce this cost****.
In addition, as Australia’s population grows by around half a million people every year (Australian Bureau of Statistics), government agencies need accurate data to provide the right services to the community, in the right locations.
Watch the webinar to learn how accurate location data can help government agencies to:
- Plan and implement flood management strategies that reduce costs and save lives.
- Determine where community services are required based on population and demographics.
- Plan for and manage natural disasters and emergencies more effectively.
- Identify areas suitable for urban development.
Solutions for Retail
Two-thirds of retailers agree the accuracy of address details is critical to their business so they can target the right customers with the right message based on who they are, where they live, and where the opportunities are.*****
Read this short whitepaper to learn:
- How accurate data can vastly improve the customer experience.
- How to lower costs and increase profitability through better decision making based on accurate data.
- How to leverage your own data to drive revenue and remain competitive.
“Accurate territories mean Domino's doesn't waste time and energy marketing to dead addresses or missing out on new opportunities. It also minimises any territory disputes.”
- CIO at Domino’s Pizza Australia
Location Intelligence Data products
- Visualise routes, calculate drive times, and pinpoint addresses for better logistics planning and cost savings.
- Covers roads, streets, highways, and navigational data.
World Points of Interest
- Decide where to locate new businesses or set territories and catchments.
- Includes retail stores, schools, hospitals, restaurants, emergency services, banks, hotels, and more.
- Provides a comprehensive view of businesses, landmarks, and features around the world.
- Determine areas at risk of natural hazards, and define retail catchments and sales territories.
- Includes suburbs, postcodes, and census boundaries as well as industry data such as telecommunications, risk, and building and property data.
- Target and segment your customers more effectively, identify potential new markets, and better understand their needs.
- Estimate the business potential of an area based on daytime population and consumer spending habits.
- Covers demographic and socioeconomic data, population estimates and projections, and consumer spending data.