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The Challenges Facing Location Data & Location Intelligence In 2020

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The Challenges Facing Location Data & Location Intelligence In 2020

January 30, 2019

What is location data and location intelligence

In 2019 the number of connected devices will continue to grow to its highest ever. With more devices and increased sensors, the amount of data generated will explode.

It will be more accessible than ever before to use data to inform everything from business intelligence to advertising. Location-based data will be more accurate than ever before. These factors will mean it be used more commonly in areas where big data can have a profound effect.

Across a wide range of industries location data and location intelligence is helping to maintain a competitive edge. It is being used to deliver insights that have previously been inaccessible.

Location intelligence is the practice of using location data to achieve business outcomes. The process uses mobile devices and sensors to visualise and enrich understanding of how devices move in the real world.

The growing amount of precise data available will provide some challenges for those in the industry.

Privacy concerns will remain front and centre as they have done for most of 2018. Data quality is still an issue that many providers need to address. Businesses will need to find an effective and seamless method of consuming and getting the most value from location data.

Here’s what we think will be the biggest challenges facing the location data and location intelligence industry.

 

Challenges in location data

With this in mind, what are the biggest challenges that location faces in 2019?

 

Consent and privacy concerns

2018 saw the introduction of GDPR in Europe.  In the US the upcoming CCPA act data privacy will still be front and centre in the data community. We are quickly moving towards a world where each individual will have control over their data.

Businesses using location data will need to take a similar approach. It’s pivotal to allow the individual to take control of their data. Companies must inform users of how their data is used. They must provide clear opt-in and opt-out solutions so that transparency can be placed at the centre of the big data revolution.

Businesses that utilise location data will need to be clear on how they collect and use consumer data. Location data providers need to have a clear opt-in process that allows consumers to understand how their data is used.

Data providers should provide solutions at the point of collection which allow them to manage consent preferences all the way through to the point of data use.

 

Data quality and standardisation

Many businesses look at a lack of accuracy in the location data that fuels location intelligence as a big challenge for the industry.

With the growth of geodata, many new providers have offered sub-par datasets with limited accuracy. These providers often have little transparency in how their data is collected and how accurate it is. For the proper application of location data, businesses need to be able to verify the data collection methodology.

The most accurate providers will be able to verify their first-party data sets. They can provide a detailed explanation around data collection. Accuracy in location data can be useless when it is just a metre out.

To avoid these poor data sets, location intelligence solutions should actively verify and remove inaccuracies in the data. The space requires a clear and transparent process for data users to see the entirety of the process, from collection to use.

For example, Tamoco is providing an extra data set which provides a clear and transparent rating for every data point collected. Our visits dataset demonstrated the accuracy of each datapoint. It can be used by business to filter out inaccuracies. It also provides transparency, allowing the end data user to understand data collection and data methodology.

 

Being ready to consume the data

More industries are looking to benefit from location intelligence. It will be more critical than ever for these businesses to be ready to consume the dataset.

For some, the use of location data to understand movement patterns will be a new data source. Providing a dataset that is ready for instant consumption will be a crucial challenge for many location intelligence providers.

Another challenge will be creating a solution that allows business to combine and manipulate location data alongside current datasets. This will maximise the effect that location intelligence can have on business functions.

There will be a move towards integrated solutions that will work as a service for location intelligence. With standardisation, it will become easier for companies to ingest large amounts of location data.

 

Effectively cleaning and normalising the data.

Many businesses that are interested in location data have concerns when processing data. Location data can be a challenge to clean and normalise for a business’ analytics or other functions.

These challenges usually involve transforming the data into a workable format. Verifying the data is up to date, and accurate is another issue for companies using location data.

A related but slightly different challenge is being able to understand when the data is appropriate for specific analytics.

At Tamoco we are working closely with our partners to create a data source that is thoroughly verified and cleaned. Our sensor driven approach makes us industry leading concerning accuracy and provides a more precise base to clean our data for customer use.

In 2019 location data providers will need to work closely with their customers to understand the data cleansing process. They must provide standardised documentation and solutions that help partners to get the most from the data.

The potential for location data remains enormous. In 2019 challenges in data collection and processing will need to be addressed. Fine-tuning a robust process that addresses security concerns will be the highest priority. Developing and managing the standardisation of location data will be another.



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