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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.

Categories
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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Categories
News

Apple Special Event – Support For NFC Without Third Party Apps Is Huge

 

Hidden away in the countless announcements during the latest Apple special event was some news in relation to NFC.

Apple has already declared support for third-party application to read NFC technology. But these latest announcements offers support that is more closely aligned with iOS.

Users were previously required to launch a third party app to read NFC tags. The latest Apple NFC update means that new models will be able to read tags in the background. This allows users to simply walk up to an NFC tag, wake the screen and the device will read the tag.

This will materialise in the form of a notification on the home screen, or in the feed if the phone is unlocked. Tapping this notification will automatically take the user to the correct app for the NFC function. This provides a simpler way for those who struggled to understand how to use NFC to get the most from the technology.

 

What does Apple’s latest NFC update mean?

At Tamoco we’ve always taken a sensor agnostic approach when deciding which proximity sensors to support on our network. Tamoco’s long-term support for multiple proximity sensors is further validated by the announcement.

The ways that consumers interact with the physical world is always changing. By supporting multiple sensor types Tamoco provides support for clients to bridge the gap between the digital and physical worlds.

The latest update in the NFC provides fantastic benefits when working with Tamoco, including:

 

More interactivity with NFC

The most obvious benefit for those interested in consumer engagement via NFC is the potential to interact seamlessly with NFC in the real world.

In the past iOS users have been required to download a third party app to use NFC. This provides a huge barrier to interaction.

With this update, Apple has removed this obstacle and this provides brands with the opportunity to reach more people, more often with NFC campaigns.

Whilst this will only be available for Apple’s newest range of devices, this still presents a great opportunity to create a more interactive experience for consumers.

 

Direct access into the notification feed

Support allows the NFC tag to be read and display a notification to the user. These notification dialogues use part of the native iOS notification system. This is a great way to reach users in a trusting and powerful way.

A user gets the opportunity to tap the notification and the device will head to the right app, depending on the content type.

This means that brands can offer consumers multiple types of media and be sure that the experience is seamless on an iOS device.

This provides a powerful, direct and interactive channel in which to reach consumers with relevant content.

 

Better opportunity for users to connect with the physical word

The announcement shows how far the link between physical and digital has come. Apple has realised that consumers want their digital devices to connect to the real world around them.

They want this connection to be simple and quick. NFC has always provided this opportunity, but the developments mean that this connection is now available at scale.

NFC carries huge potential as it has already been adopted in the payment and travel spaces. It seems like this new announcement will have a large impact and will be pivotal in the way that users can use their devices to connect with what is around them.

 

About Tamoco and NFC

Tamoco is the leading sensor driven location company. We help businesses to reach consumers based on context and provide extensive support across a wide range of technology. Our aim is to provide the content to consumers in the right moment and providing the vital link between the digital and physical worlds.

To find out more about what you can do with NFC and Tamoco’s powerful network, please get in touch with one of our campaign managers.

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News

The Digital Marketing Trends To Look Out For At DMEXCO 2019

Europe’s largest digital marketing conference begins this week. Around 40,000 brand innovators, ad tech masters, digital marketers and everything in-between will convene in Cologne for DMEXCO 2019.

To get ready we will be looking at the key digital marketing trends that will define the conference. 

 

GDPR is still on the agenda

Whilst the 25th of May seems a long way back, It’s still difficult to avoid this topic at the moment. There’s still a large amount of the digital marketing space that is uncertain about GDPR and what it means for their business.

The industry is beginning to accept the responsibility that comes with the digitalization of the marketing space. Many companies are talking more about transparency and privacy. They have shifted to make these ideals fundamental to their company operations. 

Getting the balance right between privacy and relevant, personal marketing is the challenge. The digital marketing industry needs to win the argument on privacy. To do this it needs to explain the true value that using personal data can provide for the consumer. It must do this whilst developing a trusted relationship with customers regarding data. 

At DMEXCO 2019 expect GDPR to still be front and centre. It will still be the elephant in the room for many talks and sessions. We hope that more discussions on the topic will focus on what the industry has learned.  As well as this we want to see best practices for companies to make the most out of the legislation. 

Personalisation is still what consumers want

More and more consumers are aware that brands are using their data. After the introduction of GDPR and an increased number of data breaches they expect this data to be used to provide high value, improved and highly personal experiences. 

Consumers want a personalised experience. Brands are moving towards this but there’s still a way to go. Many consumers are still finding a majority of their brand experiences are falling short of the mark. 

At DMEXCO 2019 expect to see personalisation take centre stage. We hope to hear valuable lessons on how leaders are getting it right.

There will still be conversation around the nature of generating data for this purpose. But expect more focus to be on how to use the data more effectively. Look out for discussion on how new data types can be used to create memorable, personalised consumer experiences. 

 

AI and automation is now everywhere

Consumers are demanding instant responses from the brands that they interact with. The best brands are starting to engage with their customers automatically. These brands have drastically reduced the time between a customer touch point and the desired result. 

The companies that are succeeding in this space are the ones that are experimenting with AI. They are using technology to automate their response to consumers at every point of the consumer journey. 

Treating customers on a one to one basis and providing an omnichannel experience is top of many brands wish list. Some are even getting this right already with the increasing presence of AI, chatbots and other automation tools. 

Technology in this area is advancing extremely quickly. The top brands are learning how to utilize this tech to identify customer needs. It’s being used to process huge amounts of data and turn this into actionable insights. 

Expect there to be many discussions around AI, automation and it’s ability to put the customer at the centre of the brand experience. 

 

Data is increasingly important to achieve digital marketing goals

Many companies are using data effectively in their digital marketing. The relationship between consumer data and consumer needs is more in focus than it has been in previous years. 

The potential of data in digital marketing is huge. Brands realise this but often struggle to maximize this potential. 

To do more with data companies will need to be smarter about how they source their data and be much better at turning the data into actionable insights.

Expect many workshops and talks that look to explain how to use data effectively. Learn about new data sets and how your organization can use these to meet its goals.

DMEXCO 2019

These are the main digital marketing trends that will be aired at the conference. Digital marketing in 2019 seems to be focusing on how to get the right balance between privacy and providing true value for the consumer. 

For all your data and personalisation needs, speak to Tamoco. We’ll be DMEXCO and would love to hear your take on the biggest challenges facing digital marketers. 

 

Categories
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.

Categories
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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Categories
Retail

Big Data In Retail – How Data Analytics Can Transform Retail

The retail industry is evolving rapidly. The way that consumers shop is changing. The line between online and offline is blurring and more retailers are adopting a data first strategy, helping to understand how their customers are behaving and ensuring that they can match the right person the best product.

Retail data analytics is the new normal. The brands that have access to high-quality data, and know how to use it, are the ones that will deliver unprecedented value to their customers. Let’s look at how big data can be used in retail analytics to gain a powerful competitive advantage in a highly competitive space.

 

Complete understanding of customers

Big data analytics can help retailers understand customer trends in great detail. Behavioural analytics help retailers to predict what the next big trend will be based on these data sets. This kind of insight can have a positive impact across the retail business strategy.

This helps brands identify new preferences much quicker, helps them to avoid churn and ensures that acquisition costs are kept to a minimum. Data sets based on how consumers behave online can help retailers to predict what will be the next must-have items, for example.

Other predictive datasets include location, which provides an understanding of the demographics that visit your stores. This allows retailers to adapt to their changing customer base. For example, there might be a growing number of millennials visiting your stores. Learning this in real-time allows retailers to be proactive. This could be in terms of the in-store experience -it could make sense to open a specific area with products relevant to these demographics.

 

Customization and personlized promotions

Retail marketing means matching customers to a product like never before. Big data is making this easier than ever before. Predictive analytics can help you to find the right customer for your product with incredible accuracy.

Data sets that include location can help you understand exactly how consumers behave. This helps retailers to create a better understanding of their customers and create better targeting solutions that provide value and personalize communications.

In-feed targeting can be a hugely effective way to reach the right customer with the right message when the right data sets are used. Data sets that can tell you how customers interact with your brand online and offline allows retailers to provide highly contextual communications.

This level of personalization also helps to optimise media spend and ensure that you are reaching the right consumers with the right message.

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Get in touch to see how data can transform your retail strategy

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Physical store layout

Personalisation also includes the in-store experience. Big data provides retailers with high-level insights around how consumers move in their retail stores.

These datasets allow brands to analyse store behaviour and measure the impact of marketing spend in store.

Big data in retail stores can provide a competitive advantage in cross-selling and it can significantly boost the power of in-store promoting.

As well as this it can provide a powerful method of understanding how to layout physical shopping experiences to maximise engagement and ensure that consumers are provided with optimal smart shopping experiences.

 

E-commerce marketing strategy

E-commerce is a huge part of the modern retailer’s arsenal. It’s vital that brands can leverage retail data analytics to help make the experience seamless.

Customers want an online shopping experience that follows on naturally from their store visits. They want the two to work together without any issues. Services like click and collect as well as abandoned baskets messages are seen as a something consumers expect from top brands.

Big data can help to fill in the gaps that allow retailers to link the Ecommerce world to the physical retail store and provide a seamless shopping experience for consumers. Linking Ecommerce to the physical store and ensuring that consumers can find solutions easily is a major benefit of big data in retail.

 

Order management

Behind the scenes, big data can help to inform the supply chain and optimize production. This means that customers aren’t disappointed when a trend takes off and the product is out of stock.

Using big data in retail supply chains is instrumental in predicting trends and ensuring stock is in the right place. When big retail events hit, such as Black Friday, data set such as location insights can be instrumental to monitor areas where there is increased demand to allow retailers to react to changing demand and trends.

 

Big data in retail helps brands to answer questions that are crucial to growing a modern retail business. It helps you to answer these questions quicker than ever before:

  • Who are your customers?
  • What motivates them to visit?
  • What engages them?
  • How do they behave outside of your store?
  • How can you target them?
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To find out how location data and location intelligence can help your business please get in touch with our team.

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Categories
Apps News Privacy

Android Developers Can Use Google AdMob And Comply With GDPR

Google is asking app developers who publish apps on its play store to obtain consent for data use and for ad personalisation through its AdMob platform. 

Due to the coming GDPR legislation which comes into effect on the 25th of May. Any business based in the EU will need to gain opt-in consent to collect or use any of their user’s personal data. 

This news places the responsibility of obtaining consent for Google’s services that are running in the background (such as AdMob targeting) on the shoulders of the publishers. Android developers are expecting to see some kind of software kit to help them obtain and manage this consent. As of now, and up until the new legislation kicks in, Google has not announced any SDK or toolkit that could solve this headache for Android developers. 

Many developers lacking the time or manpower to create such a kit are weighing up their options ahead of the legislation. Some have even hinted at switching of these third-party services for users int eh EU. 

 

The problem

Breaches of the legislation carry with it the threat of huge fines. User consent has always been an issue for app publishers. Creating a solution for obtaining consent and then managing this consent is no easy feat. Integrating this consent with third-party integrations (such as advertising solutions) adds another layer of complexity. 

For Android developers, the problem is a little more pressing as AdMob revenue is what keeps them afloat. Developers may find themselves stuck between a rock and hard place – turning off AdMob would instantly create a big hole in their revenue. However, keeping it on and exposing themselves to potentially destructive fines doesn’t seem like a viable option either. 

 

So what’s the solution?

With the right toolkit developers wouldn’t have to change their business model too much. Letting users opt out of ads might lose some revenue but it’s a necessary step to take to comply with the changing mood around privacy and transparency. 

Controlling user data in a responsible way makes sense because it builds trust and in the long term it will be beneficial for developers. 

Luckily for developers, there’s a toolkit that is addressing this problem. Via a dedicated SDK app, publishers can continue to use third-party ad integrations, such as AdMob. The toolkit obtains and manages user consent to help developers comply with regulations such as GDPR.

As well as this the toolkit will sync user consent across devices. All consent preferences are stored in a secure audit trail so that developers can call on consent history of their users. The audit trail also contains information on consent preferences that have been replayed to third parties. In the AdMob example when a user opts out of personalised ads in their app the consent SDK will relay this to Google. The audit will register this along with a timestamp and other relevant details.

The SDK provides this functionality for first-party app features as well as third-party integrations. It’s a comprehensive toolkit to take control of your user consent. 

This toolkit doesn’t need to only apply for Admb or even android. A wider conversation about the role of consent in mobile applications needs to be had. Developers should look at how consent is obtained, managed and communicated to third parties. 

Complying with GDPR is a shortsighted approach. Developers need to put their users first and think about how they can put these users back in control of their data.

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Categories
Apps

App GDPR Toolkit – How Developers Can Prepare Apps for GDPR

When GDPR is concerned, developers can’t afford to overlook app user privacy, consent and opt-in preferences. Here’s five tips that will get you compliant.

It’s a huge problem for app publishers. How can you comply with intimidating privacy legislation and maximise the number of users that are opted into your app services?

By some estimates over 50% of current apps are not compliant with the new GDPR legislation.

That’s because apps have multiple third parties and SDKs integrated. Many of these are asking for data on users.

It’s difficult for publishers to keep track of this. But it’s now the law to be in control of this data.

It shouldn’t have to be this difficult to comply with privacy regulation. And it shouldn’t be hard for your users to opt-in and out of individual preferences.

Lucky we think we’ve found a solution for developers to manage, sync and audit consent in their suite of mobile apps. 

 

Asking for consent and getting your users to opt-in

Complying with privacy legislation isn’t the most straightforward process.

And how do you make sure that you don’t spook your users into opting out of all services? User opt-in is important to obtain as it can be a great tool in which to drive engagement and retention, not to mention monetization.

You need to ask user to opt-in at the right time. And you need to be clear that they are in control. We tried to solve this problem by designing our consent toolkit to help developers obtain and manage user consent.

Many apps get opt-in timing wrong. Don’t ask for all permissions the first time that the user opens the app. Explaining the value that users will get in return for opting in for certain permission will mean that the user is better educated about what their data is being used for.

Make sure that your opt-in process is clear and be upfront with your users.

 

Manage user opt-out requests respectfully

Under new legislation is just as important to ensure that users can opt out as it is to obtain consent properly in the first place. To do this publishers must have a system in place that can allow their users to opt out of some or all of the permissions that they have previously opted in for.

This was one of the fundamentals that shaped the way our consent module works. We wanted our toolkit to make it as easy for users to opt-out and it is to opt-in. This needs to be done in a way that doesn’t just put the user in control of their data but allows them to choose which kinds of data is used by publishers.

 

Make sure you can manage consent across devices

Consent and user opt-in management are difficult enough to get right as it is. But this can be made nigh on impossible when you consider the fact that app users are constantly deleting apps and changing devices. 

Syncing user settings are important because if a user has revoked a permission on one device then to continue to use this could be a breach of privacy regulation. Also, if a user requests that all their data be deleted, this is difficult to do unless you can identify everywhere that the user has given access to data.

That’s one of the problems that the consent toolkit was built to solve. By using a series of unique identifiers it’s possible for developers using the toolkit to sync consent preferences. In this way, the consent toolkit manages a users consent and opt-in/opt-out preferences whenever they interact with an app or service.

This is especially useful when a user requests their data be deleted (or in GDPR terms – right to be forgotten). Having a toolkit that syncs across devices allows publishers to remove this data and stop collecting it wherever the user is seen in the future.

Sometimes it’s a messy infrastructure. What happens if a user updates consent preferences in one app, but uses other apps from you? Make sure you can sync this preference across your real-estate.

 

Integrate user consent with third parties

Apps rarely run in isolation. You might have third party services, or other SDKs that have access to our user’s data.

These need to be kept in sync with the user’s opt-in preferences. If your user says no to communication, this needs to be updated with third-party advertisers for example.

At Tamoco, our consent module allows apps to instantly update third parties with new user preferences. If a user asks for all of their historical data to be deleted this information needs to be relayed to third parties.

The consent SDK communicates this to third parties automatically when a user’s preferences are updated.

Information of this is then secured in a secure audit trail. The consent module will automatically ask third parties to confirm that they have received these requests for changes in a users preferences. When this is (or is not) received this is saved in the audit trail, along with timestamps and relevant information.

This means that developers can ensure that their users’ opt-in preferences are respected in third-party integrations. It’s important to be able to follow an audit trail to prove that this information was relayed to third-party partners and integrations such as SDKs.

 

Make sure you have a secure audit trail

With the correct procedure in place, developers don’t need to worry about manually managing consent. But what happens if you ever need to prove that your app has protected user data.

App developers need a way of storing the history of user consent. It should be easy for developers to prove that historical consent has been obtained.

In our consent toolkit we provide developers with an audit trail to do just this. Everytime a user changes their consent preferences then the SDK automatically records this with time stamp.

This ensures that app publishers are always covered. This information is easily viewed and provided for reference. Third-party consent is also stored in the audit trail. All requests for opt-out are sent to third parties and the record of this is then stored in the audit.

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Categories
Marketing & Advertising

Best Guide To Location-Based Marketing & Advertising 2021 + Examples

So as a marketer you want to know how location-based marketing can help you to reach your marketing goals?

It’s time to take a serious look at location. Big data is tearing up the rulebook in a number of different industries. This trend continues with data-driven marketing becoming the new normal. Mobile has changed many things, but it’s having a huge effect on the way that markers are using data to reach their goals.

The missing link in this equation is location data. The rise in mobile adoption has provided a much better and accurate understanding of how audiences behave in the offline world. This location data is allowing marketers to do incredible things, based on cold hard evidence.

We’re going to look at some examples of location-based marketing. Get ready to see how you can use location-based marketing to create effective campaigns. Learn how to use location data to provide powerful insights and measure attribution with precision.

 

What is location-based marketing and big data marketing?

Location data can be seen as a branch of big data. When the term big data is used people generally think first about quantity. Whilst this probably has to do with the reason that the terms exist, big data isn’t really about quantity.

We think that data is big in the sense that the impact is big. We think of location data as big because of it’s quality in both application and insight.

With that in mind, we can define big data as the collation of data from multiple sources. To inform better decision making, powerful targeting, and improved attribution.

Location data is big data that uses information about a person or group of people’s movement or behavior. This is used to understand wider trends and patterns. Location-based advertising and marketing use this data to fine-tune marketing efforts. But it is also used to generate better engagement and get valuable insights into customer behavior.

 

How can my business use location data and location-based mobile marketing

For marketers, it has sometimes been difficult to understand the benefits of location data. Especially whilst trying to get around the technical side of how it works. In the beginning, many companies had inaccurate data sets. But now the science behind location data has advanced greatly. This enables marketers by providing quick and reliable results. All by incorporating location data into their marketing strategy.

These uses are now much more accessible and easily combined with existing marketing efforts. Plug and play location-based marketing is now available. With this in mind let’s look at some of the key marketing practices that benefit from location data.

 

Location-based segmentation

Audience segmentation is a key challenge for any marketer. In order to optimize marketing dollars, it’s important to make sure that you are reaching the right people. It can sometimes be difficult to get this right, and often involves a lot of hypothesizing and testing as well as optimization.

Location can help to build powerful audience segments as it’s a key indicator of intent. For example, let’s say you make the active decision to walk into a specific location in a shop. It is then likely, at some level, for you to be interested in some of the products in that location.

Location can also be used to build historical audiences based on location history. This means that you might target a group of people who are health nuts. You’ll have many ways of doing this currently. But location adds something that isn’t possible through traditional targeting options.

You can build an audience of people who visit gyms twice a month and have been to a dedicated health and fitness store in the past three months. If you have a strong idea of the type of target audience your product sits well with then location is a powerful tool for identifying custom segments.

An important point to make is that these audiences can then be used in the way that best suits your needs as a marketer. You can target them through social media ads or send the data straight to a trading desk, DSP, DMP or other ad network. You can use it to overlay custom audiences to understand overlap. You can even use location to see the accuracy of your existing audiences and targeting.

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Improve your audience segmentation

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Location-based targeting

Location tech is valuable for marketers because of the instant nature of data. Real-time insights allow targeting to occur in the moment, especially on mobile.

Location-based targeting is a powerful tool in any marketers arsenal. For targeting when users are in the right frame of mind for conversion, location is effective in driving engagement.

But location-based targeting is great for physical businesses with products in the real world. The ability to target audiences when they are either geographically close or in the right moment, location can be very effective in driving footfall or driving brand engagement.

An example is a location-based campaign that targets users when they are close to a physical store of venue. When the user enters a pre-defined location they are given a message that informs them of the CTA that is nearby.

This can be in the form on a push notification via a third party app on their phone. But it’s also possible for marketers to feed this real-time data into existing media buying tools that can deliver ads via other programmatic media. As long as this is real-time the audience is still in the relevant moment and therefore effective.

These kinds of campaigns get much higher engagement and conversion rates. Marketers can use location data to ensure that their real-time targeting is effective. With location, you’ll also get insight from these kinds of campaigns. These insights can help you to optimize your entire marketing department.

 

Location-based attribution

This is an area where location data is offering unique insights for marketers. The ability to measure the effect of advertising in the offline world is a relatively new concept. Especially at a level that rivals the detailed insights that are readily available in the digital realm.

Location-based advertising attribution is helping marketers to understand the complete effect of their efforts in the real world. Offline attribution is effective in a number of ways:

 

Measuring OOH

OOH, real-word adverts are big business for marketers. But there’s always been a problem – how do you measure the results? It’s difficult to attribute store visits or purchases to OOH. It’s also difficult to understand exactly how many people are exposed to advertising in the first place.

Location data makes these insights accessible. By listening to areas around OOH it’s possible to measure how many people have passed or remained close to the OOH advert. From this data, you can create insights on how many people have been ‘exposed’ to the OOH ad. Of course, this isn’t perfect as there’s no guarantee that everyone walking past saw or understood the message.

But location data makes it possible for marketers to then measure how many of these people perform the desired goal. This may be that they visit a retail store associated with the ad. This is an effective tool for marketers to be able to measure, test and optimize OOH advertising.

 

Measuring experiential or other offline advertising

Of course, this tech can be used to measure other forms of advertising. Take experiential, for example. Usually, these campaigns end with the consumer leaving with a sample of some kind. But attribution doesn’t come easy and many campaigns end with the basic insights. These are usually how many people visited the experiential stand, or how many samples were handed out.

But location data enables marketers to then say, with great precision, this many people engaged with our experiential stand. You can then identify the percentage of these people that visited the store within a certain period of time.

These insights are invaluable. They provide marketers with the opportunity to get digital insights on traditional offline marketing campaigns.

 

Measure the effect of digital advertising on offline goals

Location data is a powerful tool to associate online digital advertising to offline conversions.

For example, if you have a Facebook campaign you will have an idea of how many people saw your ad and even how many of these clicked your ad. But if your conversion is in the offline world, ie visiting a physical store, then this is where your campaign traditionally ends.

Sure there are some things you can do to pick up customers on the other side, like offer codes or loyalty schemes. But none of these will offer the same precision or reach as location data-driven marketing attribution.

Using location data marketers can understand the offline effects of digital advertising.

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Do attribution better, with location

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Business intelligence and business analytics

For marketers, getting those insights on a micro and macro level are crucial when creating your strategy. In terms of insight, data is the new normal. You want to base your marketing decisions on data that is accurate and instant.

Understanding the customer is critical to any marketing department. Location intelligence is a powerful tool in the area of customer analysis. Try enriching customer data with demographic and anonymous lifestyle information. This allows marketers to create more effective databases and be better placed to predict where best to spend the marketing costs.

For brands with a physical venue or store location data can provide powerful insights into business performance. Understanding footfall and trends can help to inform on the ground business strategy. For example, retail location data can also help strategize how best to compliment physical retail stores with digital advertising.

Combine this with the ability to see data on competitors and other physical location and you have a powerful toolkit that marketers can use to put data at the centre of their decision making.

 

Personalization with location

For marketers, a key goal is to try and personalize the relationship between brand/product and the consumer/user. Of course, this can be difficult as it’s not always easy to completely understand your audience. It’s even more difficult to personalize your communications based on this, especially on a one to one level.

But analytical intelligence can be one solution to the personalization problem. Identifying the location of a customer can help brands and marketers to customize their message so that it is personal.

This could be a simple as including terms like welcoming back in your messaging. Or you can create entirely different communication for customers that are in different locations or have demonstrated previous patterns of behavior.

Communicating with your customers in this way can help to build stronger relationships and increase brand loyalty. This allows you to communicate with the right customer when they are in the right place with the right message.

 

How does location-based marketing work?

Location data is sourced from mobile devices. Sensors are used to understand and pinpoint these devices. This process is anonymized so that the user’s personal details are kept private.

These sensors come in a variety of forms – from beacons to Wi-Fi to geofences. Using a combination of sensors allows for greater accuracy and better scalability of data.

 

What is good location data?

You’ll need to make sure that your data provider is doing two things:

 

Can validate the accuracy of the data they collect.

This means you’ll need to understand what types of location data there is. Some are more precise than others. Some are real-time and others are delayed.

Generally, a data provider that can explain to you their methodology and is transparent about their data sources is a good start. Look for sensor-driven data sources such as beacons, GPS or wi-fi. First party data sources are much better than third-party, where the provider cannot validate the accuracy.

 

Can ensure that data is collected in a safe and secure way

Does your data provider have the correct opt-in procedures? Do they comply with current data collection legislation? These are all important questions that any good location-based marketing company will be happy to explain to you.

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Add location to your marketing today

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What is location-based marketing?

Location-based marketing, also named geolocation marketing, is a form of mobile advertising that is highly personalized based on where the consumer is or has been.

How does location based marketing work?

Location based marketing works by using real-time device location to build detailed prolifes of how consumers move and behave in the real world.

Is an app needed to engage with location-based marketing?

Not at all, even brands without a dedicated mobile app can start using location based marketing to engage with consumers.