Category: Data

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Data

The Challenges Facing Location Data & Location Intelligence In 2020

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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Data

Location Data And Location Intelligence In 2021 – What To Expect

What is location data and location intelligence

In 2019 the number of connected devices will produce more data than ever before. As this increases the data will become fundamental to many industries and businesses.

Data will fuel everything from city planning to advertising and marketing. Location-based data will be more accurate than ever before, and it will be used more in areas where big data has already had an initial impact.

Across many industries, location data and location intelligence is proving to be a powerful tool for companies looking to maintain a competitive edge. It is being used to deliver insights that have previously been inaccessible. In 2019 accurate and precise location data will be leveraged to generate new insights and power better understandings of behaviour and movement.

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

These interactive data sets are used alongside a business’ current solutions to create a powerful competitive edge and optimise business functions.

With strong roots in advertising location data and location intelligence are increasingly being utilised in new verticals from finance to planning and construction. In 2019 location data will be more commonplace, and location intelligence solutions will be fundamental to the success of many different businesses.

 

The future of location intelligence in 2019

With the rise of location data and location intelligence businesses will see new use cases and more powerful datasets.

Changes that we expect to see in the space will include the following:

 

Combining datasets

The next step for location data sets is combining with extra information to enhance the value for data users.

In 2019 data providers will provide more detail around datasets as standard. Demographics and other metadata will add value out of the box. As well as this there will be an increased number of businesses that will combine their datasets with identifiers in the location data to improve functionality and create new ways of understanding existing datasets.

This also means that it should be clear and transparent which data sets are used. Providers should have a standardised way that business can filter and understand which data points should be ingested and used alongside the correct datasets.

In 2019 location data will be more transparent and more accessible to use alongside existing customer datasets to maximise business functions. By linking location data businesses will instantly have a more detailed view of their customers or relevant segments.

 

More uses

Location intelligence is beginning to gain prevalence outside of the marketing industry.

A considerable majority of marketers (82%) are now planning on upscaling their use of location data over the next two years.

As location data use in marketing reaches a critical point, we will begin to see it adopted more readily in other industries and feature in new use cases.

As more organisations document and formalise their use of location intelligence the value of these datasets will become more apparent and are adopted outside of the traditional verticals, such as marketing and advertising.

While marketing and advertising are still the most common use case for location data and location intelligence; there is a dramatic increase in both the number of industries that say they will invest more in the technology and those that already have.

Expect to see location data involved as a fundamental part of any effective BI strategy. Understanding device movement with precision will fuel predictive capabilities. Location intelligence will be widespread in everything from City planning through to logistics, automation and investment.

New use cases will emerge. Location data will be used to understand global trends for journalistic purposes to understanding environmental changes and populations.

 

Data accuracy and quality

New industries will require better accuracy and a better way of consuming the insights that location data can provide.

In 2019 we will move away from talking about postcodes and large scale geofencing. Instead expect to see granularity, three-dimensional location and precise location intelligent solutions.

Businesses must take advantage of a focus on accuracy in the industry and start visualising and analysing datasets at a deeper geographic level.

Many businesses are currently using geographic boundaries such as postcodes or large geofences around more extensive areas.

The technology is now much more granular than this and businesses should be aware of the new and custom functionalities that the leading location data solutions can provide.

Expect to see more detailed datasets that include variables to filter out inaccuracies and other data points that are not useful for the end data user. These processes will become automatic in 2019, and the best providers will be able to boast systems that can automatically detect these outliers in the data.

 

Analysing the data

As big data becomes fundamental to many organisations, more datasets will be available.

More data types mean better unification is needed for customers because of this 2019 will see the emergence of LaaS (Location as a service).

Ready to use location platforms will empower businesses to leverage the unique insights that location data offers. It will allow them to visualise and digest insights easily. It will support manipulation of data and provide functionality to integrate these into current business functions and solutions.

These platforms will be closer to real-time than before and provide more granular insights that will allow businesses to act immediately on these insights.

The experts in precise location

Get in touch to get ahead with location intelligence or to see how you can use location data to benefit your business.

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Business Data

5 Amazing Ways Big Data is Transforming the Education Sector 

Big data and Education are closely interconnected as it helps school, colleges, universities, institutions and many more educational organizations to make the overall decision about in the organization’s overall outpace, scholastic outreach, and much more. 

Big data analytics in education will not only help in academic performance but also increases the efficiency and effectiveness of the faculty as well as technology. 

The educational Sector these days prefer big data in education as it makes sure to reduce business expenditure which will eventually be beneficial for the organization. 

Not only the present time, but data for education will enable you to predict different trends that will be adopted in the future in the respective industries. It leads the employees to have better planning which will help in the overall development of the education sector. 

Image Source: IntechOpen 

As rightfully said by Chris Lynch, an American Writer of Books “Big data is at the foundation of all the megatrends that are happening.” So, your educational institution and students will for sure benefit from big data. 

Importance of Learning About Big Data

Big Data helps all learners, students, professors, teachers and individuals involved in the educational sector to understand the overall strategies as well as the individualized learning process.  

Image Source: Springer Open 

Let’s get familiar with the importance of studying/researching big data in the education sector: 

  • Big data helps to map student learning by measuring the teaching-learning process of the classroom. 
  • According to Salt Lake Tribune data for education not only helps teachers and students but is also equally significant for financial and administrative management. 
  • In general, the cost-saving process will be quick, simple, efficient and easy to adapt with not much confusion. 
  • You can do individual manual searches or studies based on the initial search as per your own preferences and requirements. 
  • Along with big data and affordable writing services, you can increase accessibility and save costs. 

The list simply goes on and on so we have concluded the importance of learning about education data analysis in the best five points. 

Ways Big Data is Transforming the Education Sector

Even today many people think and assume that big data is significant when it comes to only business. But this is not a precise piece of information. 

Not only in business but big data is important for the financial market, detection of fraud, newly adapted smart traffic system, the healthcare industry, the government sector, media and much more. Along with all these sectors the Education sector is one of the most important sectors. 

As we already know about the importance of big data, let’s get familiar with all the ways big data is transforming the education sector. 

Find Out Strengths of Students 

Learning about big data doesn’t only solve short-term problems rather it focuses more on long-term things. It will help students to analyze, influence, discover and ascertain long-term goals. This will eventually help them out in the future. 

Big data can be helpful for students and teachers as it will help them gain better information about all the possibilities that are likely to appear in the upcoming days. This way they will get better to sort of thing and tackle all of the hassles that come through their path. 

Not only about the overall prospects but big data will also help them have a better understanding of themselves. 

Improve the Grading 

When an educational institution decides to let big data foreplay in their institution, they will be able to gain information about all the tracks and records of the students. 

This way the teachers will be able to gather all the fields that interest students through which creativity and collaboration will increase in the learning process. Students can gain what they want and teachers can get the proper feedback through which they can help students improve. 

Not only this but it has a long positive impact as this way they can gain all the necessary skills which will eventually help them in their career path. Hence, this way big data will help to transform the overall education sector. 

Targeted International Recruiting 

The application process is considered one of the most important factors in the education sector. More the number, the better as when more students enroll for better education more amazing students will gain quality education. 

This education will eventually help them to gain better jobs which will eventually improve their lifestyle and increase the overall economy of a nation. 

The application process can be made better using big data analysis in education by analyzing and guessing all the possible and essential factors. When analyzed better things can also be planned in a better way. 

Minimizes the Dropout Rate 

As everyone will get what they need, especially the students will be satisfied. This will eventually decrease the dropout rate of students from schools, colleges and universities. 

Sometimes even bad results discourage students, but that’s not the case once the education sector starts using big data. It is said that the analysis made with the help of big data will help both teachers and students understand problems and find out solutions without any hassle. 

There is less rate of error found after using the big data, not only that it will eventually help students to improve their overall academic performance. Hence it will improve their rank and performance which will eventually result in a deduction of the dropout rate. 

The Efficiency of Technology in Education 

In the 21st era, technology plays an important role as it provides opportunities for people to change their overall life. One without technology information can actually be a brick on the wall. Due to the use of big data in education, all the individuals involved in this sector will gain basic knowledge about it. 

Not only the teachers and students but other sectors of an educational institution like finance and administration can utilize them properly. 

This will eventually lead to bringing effectiveness, completeness and overall productivity in the overall education sector. Moreover, along with great learning, they will also get creative by predicting all the future aspects. 

Hence there are hundreds of way big data can transform the education sector, but we along with our research team has read and selected the 5 best ways. We made sure to include the most important ones so it turns out to be helpful for our readers. 

Wrapping Up: 

This is the end of our article ‘5 Amazing Ways Big Data is Transforming the Education Sector‘ We hope this article helped you learn about the importance and the way big data can bring positive impact in the education sector if used properly. 

Moreover, if you have any more points that are valuable, feel free to share it with us in the comments section below. 

Big data can actually be a precious gift in the education sector in the upcoming days if used properly. So, make sure to use the big data properly and shine out!

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Data

Big Data And Big Brands – Why Data Is The New Brand

Big data brands

The modern brand faces many challenges. In today’s world consumers exist in multiple locations, across many devices and they have different expectations of what a brand should be.

The modern consumer has set the bar pretty high. Brands need to keep up with consumer’s fast-changing needs and desires.

From personalization to the user interface, the consumer has demanded that brands can adapt and communicate with each consumer on an individual level.

Information should be the heart and soul of a brand. Big data is helping to achieve these goals and create a new kind of brand.

In this way, data is becoming the new brand.

Why is big data important?

Most brands realise that data is important to the success of their business. But the brands that are really at the forefront of the digital revolution are the ones that have learned how to make the most of this data.

Placing data at the centre of business strategy is more important than ever. As the competition gets smarter, those that can find a way to utilize the data that is generated from the modern world will be the ones that succeed.

 

Why is data the new brand – big data applications

Big data and personalization

Data is the new personalization. The best brands know exactly what their customers want. They know when they want it. They know how they want it.

The thing is this isn’t guesswork. These brands are delivering personalization with information. Big data and personalized messaging form part of any successful brand strategy.

These brands have a method of generating data from their customers. They are effective in managing this data. And finally, they are efficient in using this data to understand customer success.

 

How does data inform personalization?

Big data personalization is being utilized by more and more brands. It involves using consumer-generated data to understand behaviour. The brands that are doing this best utilise multiple data sets in order to deliver engaging and personal experiences to customers.

 

Big data and product development

Developing products is hard. Data helps to generate product ideas by helping to illustrate how the customer actually use a brand’s product.

Brands that get product development right are using information to inform their process. They are using data in product rollouts and how new features are used to inform future product development.

These metrics can be more than just simple usage data. The explosion of different data types has provided much better insights into how customer use a product.

Powerful data mapping techniques are being used to map new datasets over existing data sources to provide even more insight to product designers. It’s not just about when and how much the customer interacts with the brand.

It’s now about looking at where and why customers use a product or interact with your brand. The top brands are using this data to inform their decision making. Extra datasets, such as location can give far more insights into how your product is being used.

 

Big data and business intelligence

Implementing a data strategy has had a wide-ranging positive impact outside of the marketing and product departments.

Data is helping brands to become predictive instead of reactive to consumer trends. The leading brands don’t just understand what their customers want, they can identify these earlier than ever before. All thanks to data.

In verticals such as retail, analytics data can be crucial. Becoming a digital-first brand involves using actionable data to gain a competitive advantage.

New data sets are helping brands to fill in the gaps. Especially in industries that have traditionally been slow to gather consumer data.

Business intelligence is now fuelled by data sets such as purchase data, location data and IoT data, amongst others.

The financial sector is using data sets such as location to predict the earnings and ultimately the financial success of brands. So why can’t brands use the same data to inform their strategy?

These data sets can be instrumental in helping brand management plan intelligently. Big data can help predict where to open new stores. They can help understand what consumers want and help find where these customers will be in the future. As well as this big data can be used across a brands marketing arsenal, from targeting to SEO tactics. You could even get yourself a UK SEO consultant to implement these. Even when using the big tools (such as BuzzSumo) there are many great free BuzzSumo alternatives to help with these tactics. 

Using data as a competitive advantage should be a fundamental part of any brand’s strategy.

 

Brands and big data examples

Many brands come to mind when you think of big data. What do all of these brands have in common? They understand the value of different datasets. They use the data effectively

 

Netflix

Netflix has understood the benefits of data from the very beginning. A user’s viewing history is used to suggest new content in real time. It’s used to recommend new shows and it’s used to do this at the right moment.

Netflix uses data and analytics to understand what it’s users want to watch. This data is also used to predict trends and it’s used to commission new original content. This is an example of using data sets to become a predictive brand.

 

Hedge funds

The investment space is quick to realise the impact that data can have. This is an industry that lives and dies by its ability to predict the trends of huge amounts of people and the businesses that they interact with.

The sheer quantity of data is not all of the story. Getting the right data is more important. Hedge funds have seen some success by utilising data sets that aren’t commonly used. These are useful as they can provide insights that have previously been unattainable.

A great example of this is location data. Accurately mapping footfall and visits with location data can give a new insight into the offline world – a place where large-scale macro trends have been difficult to pin down.

Using these insights to predict financial trends can give financial companies the edge.

 

Conclusion – data is the new brand

As a brand you need to ask yourself – Is there a better kind of data that can help to inform your needs. You need to be sure that you can use data quickly and effectively.

Data is instrumental in the process of personalization, building great products and gaining business intelligence.

If you want to be a smart brand that can understand and predicts what the consumer wants you need data. If you want to deliver this in a personal and engaging way you need data. If this is what you aspire to then you will eventually arrive at big data. That’s why data is the new brand.

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Data

Location Data Accuracy – What Makes Good Location Data

Location is a powerful tool to understand how audiences move in the offline world. It is being used across a number of industries, fuelling everything from innovative mobile apps to providing detailed intelligence and analytics around device movement.

For these applications to prosper the data that underpins them needs to be accurate. This is not always the case. We’d like to talk about some of the attributes which make location data reliable and actionable.

 

Accuracy and precision

These two things sound similar. But in the world of location, there is a subtle distinction. Accuracy refers to how close the measured location is to the actual location of the device. Precision refers to how close together a number of separate measurements are.

The precision provides the granular insights that overlay the accurate data sets. At Tamoco we add this precision through sensors and our proprietary SDK.

 

How we determine device location

Tamoco uses sensors that exist on our network to help with issues in accuracy.

The Tamoco SDK identifies these sensors which are in ‘known locations’. This allows the SDK to determine where the device is in relation to wither Bluetooth or wifi signal booster strength.

In some locations, GPS location can be inaccurate and imprecise. For example, inside a shopping centre where the GPS signal is not as strong. This is where Tamoco’s sensor-driven approach provides extra precision.

What are the sensors and what are the benefits?

Beacons

Beacons provide very accurate and precise data. These sensors can be used to place devices with an accuracy of 1m. Beacons are the most precise location sensor that is widely deployed.

WiFi

Very useful in identifying precise location in densely populated areas. These sensors help identify device location in areas such as shopping malls and large buildings.

GPS

Under the right conditions, GPS can be extremely accurate. The signal quality deteriorates quickly when the device is indoors and in areas where the device does not have an unobstructed view of GPS satellites.

The Tamoco SDK uses multiple sensors simultaneously to identify the location of the device. Often the device location is constantly updated as more sensors are identified. The SDK uses this information to determine context and then discount outliers in the data.

This process of identifying location can be visualized as a linear process. In this process, the Tamoco SDK uses a number of sensors to validate and adjust an initial location signal to a finalized and verified location, in the form of latitude and longitude.

 

Other factors that help to identify location

We use other device information to identify the accuracy of each location signal. We use vertical and horizontal accuracy to show the reliability of the lat-long derived from the device.

These fields are intended to provide transparency around location signals. Tamoco wants to include these so that partners, developers and clients can understand the level of accuracy in every data point that they process.

Standardizing this into an industry-wide and agreed measurement is the next step. Only location data providers with inaccurate data sets will have a reason not to adopt these standards.

 

Benefits

Why is this relevant for publishers?

These levels of accuracy mean that app partners can maximize their CPMs from the monetization of location signals. Many monetization partners pay higher amounts for accurate data sets. They are, unsurprisingly, unwilling to pay for data that is either inaccurate or imprecise.

If you use location in your app experience adding extra accuracy and precision will boost the experience for users. Delivering location-based communication and contextual app experiences are more likely to be a success with greater location accuracy.

Why is this important for data buyers?

Of course, the most important thing for a data buyer is the accuracy of the data. This is true regardless of the desired use.

Accuracy in location data means that insights are more reliable. Targeting is more effective. Using location data for complex tasks like visit attribution is nigh on impossible if the data is unreliable.

All data buyers should be sure that the location data they use is verified. Location data providers should be able to explain their methodology in detail to demonstrate that data sets are precise.

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Data

How Big Data & Location Intelligence Is Changing The World

There’s no doubt that the explosive rise in the number of smartphones has changed the world as we know it. The increased number of sensors and connected devices has produced mountains of data. This is being used to transform the way that we live our lives.

IoT, location data, location intelligence, big data. Whatever your name for it, it’s hard to dispute the potential across a variety of industries

It’s now apparent that granular location data can provide unprecedented insight into the offline world. More businesses are realising the value of mobile location data and the impact it is having across the globe.

As we move away from unreliable data sets, sensor-driven accurate data sets are taking centre stage. This kind of accurate data has many applications. But I’d like to look at some that are having the greatest disruptive impact.

Business intelligence

The ability to notice trends by using data isn’t new. The ability to do this based on people’s activity in the offline world, in a close to real-time manner is.

Location intelligence reveals relationships between big data sets that often would be missed. It turns these insights into actionable business intelligence. Helping inform decisions, from the boardroom to the storefront.

From the small bar that is competing with huge chains of venues through to the small retailer competing with online mega corporations. These businesses are gaining valuable insights from using this kind of big data to inform their business strategy.

The truth is that mobile location data has now matured enough to solve many problems that both small business and enterprise face. Let’s look at a few:

Financial services – understanding footfall through big data sets is valuable for the financial sector. Mobile device data can help to forecast earnings and other KPIs before they are formally reported. This helps inform investment decisions.

Retail – big data can help both small and large retailers. Understanding store visits, as well as customer behaviour through mobile device data, is having many positive effects on the retail sector. These insights can help inform business decisions such as store layout, opening times, staffing and more.

 

Infrastructure and planning

We’ve all heard of the term smart city. We like to think that there’s more to it than just adding a few data points and putting the word smart in front of it. It is, in fact, more than that. We’re moving towards urban centres with huge populations and aspiring towards self-driving vehicles. Big data is the key to unlocking this truly smart future.

The rise in mobile device data has provided better opportunities to understand how cities work.  It’s helping to create systems and infrastructure that reflects this.

Combined with the increasing number of connected devices in cities, central planning authorities now have a set of tools that can inform decision making in many different areas.

Mobile location data is contributing to a better understanding of where demand for public infrastructure is greatest. For example, examining mobile device location data to understand the most cycled roads within a city. This information is precise and invaluable when planning where to implement new routes.

The same is true of traffic and congestion. In increasingly crowded and polluted megacities, it’s important to understand how traffic issues can be alleviated. Understanding traffic flow and where to build new road structures, or introduce new low emission zones is crucial to building the kind of smart city that can sustain current levels of population growth.

Big data is having a huge positive effect on this kind of planning. Thanks to the accuracy and uniqueness of mobile device data and location intelligence, it is changing how decisions are made in cities and towns around the world.

Marketing and advertising

Big data and marketing have always complimented each other. Marketers have always looked to use data sets to improve the efficiency and effect of ads. Using big data to create tailored and relevant audiences is not a new practice.

But mobile location data allows marketers and advertisers to connect digital advertising to how consumers behave when they are offline. Understanding how consumers move in the offline world is helping marketers to become more effective. It’s assisting marketers in providing more personal advertising to consumers.

Location intelligence is disrupting many stages of the consumer lifecycle. It’s bringing the analytical capabilities that have been available for the web to the real world.

 

Segmentation

Mobile device data is helping to build up complex pictures of how people move and behave. This helps advertisers to build complex customer profiles. Brands are finally understanding the places that their customers go and how they interact with the physical world around them.

This is far more effective than other methods of audience segmentation. This is because a person’s location is often a much greater sign of intent than when they are searching for something on a computer, or browsing on their phone whilst sat on the couch.

This allows marketers to identify exactly where consumers are on the buyer journey. Moreover, it allows them to do this with a greater level of detail.

 

Personalisation

One big breakthrough that big data has had on marketing and advertising is by increasing the ability personalise at scale.

Location data is allowing brands to be helpful and human by understanding the situation of the customer. The concept isn’t new, but the accuracy and increasing size of data sets in the space have allowed commutation to really get personal.

Location help provide promotions at the moment when the customer can actually redeem it. It allows the ‘customers also bought’ experience to reach the real world retail store. In this way, big data is providing digital solutions to offline problems. Location intelligence is tailoring brand communications to a person’s unique experience of the real world.

 

Customer experience

Big data has changed customer experience for the better. Location intelligence can help to automate way-finding, ordering, assistance and queue management. Understanding the physical location of a person has helped improve the guest experience across many sectors.

Stadiums, resorts, airports, transport hubs all stand to improve the experience of the people who spend time and money in these places. It might be location based ticketing – you buy your ticket by walking onto a train. Or it may be ordering food and drink to your location.

There’s still huge scope for big data and location intelligence to be applied to improve the customer experience.

 

Attribution

Mobile device data as we have seen has connected many digital walks of life to offline consumer behaviour. Another way that this technology is revolutionising the marketing and advertising space is through attribution.

Traditionally many advertisers have been blind when it came to measuring the impact of offline ads on offline KPIs.

But the mobile device location data is filling in the blanks. Location intelligence can understand when a person is in front of, for example, OOH advertising. It can then measure how many of these people are then seen inside a store or in front of a specific physical product.

Connecting the two provides an accurate way for marketers to measure the impact and ROI of offline advertising inventory. it also allows them to measure the effect of digital advertising on an offline goal. These things have just not been possible with certainty before. But big data has changed the way that advertising can be measured.

 

AR

If AR is really going to live up to its promises, it will have to rely on complex data sets and accurate location intelligence.

As AR gains prominence it’s application will move beyond fun to play games to useful productivity applications (you can even combine it with some powerful notion templates to really level up). As AR develops, it’s used as a way of reaching audiences with content and advertising will grow. Like previous marketing activity, it will be improved by the use of big data and location intelligence.

AR will require huge amounts of accurate and real-time location data to function properly as a user moves around the real world.

Optimising the supply chain

Big data and location intelligence is impacting organisations that want to optimise the supply chain.

The obvious application of location intelligence in the retail supply chain lies in the ability to understand and track deliveries and supplies. It already being used to generate data sets which can optimise and improve these services.

But location intelligence isn’t just helping business to optimise the process. It’s helping to understand the demand for products. There’s a lot of history of people building something in the hope that people want it to then find out that actually, they don’t.

Another way that big data is helping manufacturing industry to optimise is by helping it to adjust the type of transportation, pickup location or place of sale.

With the rise of location data, these insights are now fuelled by information from the offline world. Insights that have previously been unattainable or have lagged are now available in real-time. This lies at the heart of what is disrupting how the supply chain operates.

 

Privacy and transparency

As usual with new disrupting activity, the focus in on the responsibility of these new technologies. And rightly so. Indeed those in the big data space will need to be more transparent in how data sets are sourced.

It won’t be enough to simply check a box and start collecting and aggregating personal data. More needs to be done in order to clean up the data supply chain. More control needs to be handed to the user.

In this way, it’s our responsibility to communicate the value of big data and location intelligence to the user. It’s having a huge positive impact across the globe, and that’s just more reason to get the privacy part right.

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Data

Location Data And Location Intelligence In 2018

The big data analytics space is growing at an alarming rate. We’re all increasingly connected through our mobile devices. This growth has provided huge amounts of data around audiences and how they behave. What kind of competitive advantage can we expect to see from this location data going forward?

Location data is rising in importance. But there are challenges that companies face as location data becomes commonplace. Businesses will need to understand the best application for this data. We’ll look at this as well as how location intelligence will be put to use across many verticals.

How will location data change the way that businesses approach marketing?

Attribution

Location data will become invaluable to marketers as they look to close the online to offline attribution loop. Traditionally this has been a problem for marketers. It’s difficult to attribute real-world visits and purchases to online marketing. 

Location intelligence will help to illuminate what happens in the offline worldwith unprecedented accuracy. Big data will provide insights well beyond the capabilities of loyalty scenes.

As programming becomes more prevalent, location intelligence will be used to ensure that budgets are optimised. With the improvements in attribution, marketers will be able to accurately understand where ad fraud occurs.

Personalization

Big data breeds personalization. Many a case has been made for the importance of big data in personalization. Location intelligence will help marketers to automate personalization. This, in turn, will deliver accurate, personalized content to the right user in the right place.

Big data insights from location data

Location data will provide a competitive advantage, and not just in marketing and advertising. More industries are realising the benefits of real-time mobile location data.

Location data is being collected and stored by over 90% of companies with over 500 employees. The applications of this data are wide-reaching. Understanding consumer behaviour accurately, and in real-time will signal the adoption of location intelligence outside of the marketing and advertising industries. Location data will allow cities to become smarter. It will allow transportation to become more efficient. 

 

Accuracy and reliability of big data

The accuracy problem

The problem has previously been the accuracy of the data. For companies to use big data to inform business decisions, the data has to be reliable beyond doubt. Location intelligence and precise sensor-driven data now provide this certainty. 

Accuracy and precision will become of paramount importance as technology gets better.  It’s important that businesses that benefit from location data and location intelligence can safely say that they are working from accurate sources. 

First-party location data

Challenges in sourcing accurate first-party data were found with scalability. With a lack of first-party data, unreliable third-party data was used. Often out of date and imprecise, the insights were not reliable. Especially for businesses serious about using location intelligence for commercial success.

Today Tamoco adopts a network approach to location intelligence. This means that through our mobile SDK we can understand mobile device location directly. Thanks to our network approach, we can understand these signals across multiple sensors types. 

This improves accuracy and will allow businesses to act based on a more precise understanding of audience behaviour. 

Real-time data

Location intelligent decisions must be informed by real-time data. Location data must be instantaneous. Data that is out of date is simply not useful for businesses. This means that data must be communicated in real-time to optimise and achieve the desired goals. 

This is another reason why first-party data is important. It allows for location intelligence to occur quickly.

The location of things

The IoT will soon be in everything. For example, by 2020 IoT technology will be in 95% of new product designs for electronics. Now that’s great but it’s only the beginning.

This huge growth will produce large amounts of data. However, it’s may be difficult to interpret data sets without location. Location adds context and a better understanding of what is happening in a specific location. This allows us to better understand the offline world. 

The location of things – the IoT is actually only useful if you know where the thing is. Tamoco’s sensory agnostic approach allows us to gain location intelligence across a wide range of sensors. These range from beacons, Wi-Fi and Geofences to connected IoT devices. This approach allows us to understand location across many different sensors. This creates a deeper understanding of the offline world. Businesses using location data will have to take a similar approach to understand the connected world we live in.

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Discover location data

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