Category: Footfall & Retail

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Footfall & Retail

How Geospatial Data Transforms Online Retail Strategy

Understanding key geospatial data and using this resource to your advantage can play a key role in elevating your online retail strategy. Let’s start from the basics: geospatial data refers to information about the physical location and characteristics of objects or people, often represented by coordinates, maps, or digital images. 

This type of data is a powerful tool that informs decision-making across various industries. In retail, it offers invaluable insights into customer behavior and market trends. In this guide, we’ll explore how leveraging geospatial data can boost efficiency, personalization, and profitability in retail.

Optimizing Store Locations with Heat Maps

Heat maps are a game-changer for businesses. They offer an intuitive way to visualize data and make informed decisions about different regions in which your business operates and related demographics. Using heat maps, you can easily identify areas with high customer activity, allowing you to strategically place physical stores or concentrate digital marketing efforts. 

This data ensures you’re where your customers are, maximizing the return on investment and adjusting your offer to specific needs and expectations. By simplifying complex data into color-coded visuals, heat maps help you quickly grasp demographic trends, traffic patterns, and customer preferences. 

Enhancing Customer Targeting and Personalization

Understanding where your customers are and how they behave in different regions allows you to tailor your marketing and products to suit their unique needs. In turn, this ad hoc strategy can help boost engagement and sales. Here’s an example: imagine you’re aware of a surge in interest from a specific urban area. Thanks to this information, you can then tweak your offerings to cater to this demographic. 

Similarly, geospatial data allows you to understand different trends. For instance, if you’ve noticed that consumers in a certain area prefer a payment method over another, you can offer specific options, like Planet’s online payment solutions, in that region. Personalized experiences, right down to how customers pay, are key to building loyalty and user satisfaction.

Boosting Sales Through Location-Based Promotions

There are several strategies to visualize geospatial data, transforming complex information into graphs, maps, and charts that are easy to understand across your company—noy just by analytics experts! 

For example, feeding this information to your marketing team can guide your promotional strategy. If data shows interest peaking in coastal regions or within a certain customer group, your teams can run promotions targeting those regions or demographics. To reach customers effectively, consider utilizing online ads, geo-fencing, and targeted emails that are personalized and adjusted based on key data.

Improving Delivery Routes and Reducing Shipping Costs

With geospatial data, you can refine your delivery process to be both faster and more cost-effective. It helps in plotting the best routes, considering various factors like traffic, weather, and fuel consumption. This optimization minimizes delivery times and reduces costs. 

For instance, by understanding how regional demand spikes during different seasons or periods of the year, you can plan more efficient shipping schedules and routes, ensuring that deliveries are efficient and on time.

Gaining Competitive Advantage via Market Analysis

In the world of business, data is everything—and, in particular, geospatial data can be a treasure trove of insights that can place you ahead of your competitors! By understanding patterns of consumer behavior and market dynamics, you can adjust your strategies and remain relevant in a fast-changing landscape. 

For instance, identifying underserved regions could help you expand before your rivals do. Plus, analyzing competitors’ locations and customer bases enables strategic planning and better market positioning. 

Enhancing User Experience with Geo-Targeted Content

Delivering content that resonates with your audience is crucial, and geospatial data helps you do just that. By understanding where your users are, you can provide relevant and timely information through geo-targeted content. 

Whether it’s localized information, language adjustments, or product recommendations based on regional trends, personalization makes all the difference. A quick example is tailoring holiday promotions to cultural norms in different regions. When users feel like your brand speaks directly to them, they are more likley to engage with your business and become more loyal to your brand.

Staying Ahead with Innovative Retail Technologies

Keeping pace with technologies like geospatial data analytics ensures your online retail business is ready to adapt and remaining competitive as the market evolves. 

By actively monitoring trends and integrating new tools, you can stay agile in your strategy, ensuring your business doesn’t just survive, but thrives in a rapidly changing landscape.

Related: read more about how location data is used across retail and real estate.

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Footfall & Retail

Can Artificial Intelligence Benefit Retail Security?

While modern threats associated with cybercrime and data breaches are often talked about with regards to most major industries, for retailers, physical security remains a top priority. According to recently published data, retail crime in the US accounts for almost $126 billion in lost economic activity, with almost 80% of retailers listing physical crime as a top concern.

Developing effective retail security solutions and related organizational policies is central to the safe operation of all retail businesses. Not only as a way to reliably prevent the loss of key assets, but also to create a safe and welcoming environment for customers to enjoy. However, as retail theft rates rise, teams must find new ways to effectively deter criminality.

Unfortunately, retail stores may always be vulnerable to physical threats like shoplifting due to the nature of the industry. With staff required to monitor large, over-crowded public spaces alongside carrying out other professional duties. But if some security tasks could be safely performed by smart technologies, retail security operations could be dramatically improved.

With this in mind, let’s look into the question: can artificial intelligence benefit retail security?

An overview of AI in retail security

The adoption rate of AI technologies among retailers on a global scale has been rising for several years, with the compound annual growth rate for such technologies sitting at almost 40%. While AI systems may not be exclusively used to benefit retail security tasks, the ability for teams to autonomously monitor assets and analyze data has likely driven adoption rates.

Across all the security practices in which AI can be beneficial, a few key operational factors remain present. In short, the ability for AI tools to perform real-time data analytics processes enables retailers to automate many key security tasks. At a time in which many retailers may be struggling financially, the adoption of AI systems can help to alleviate heavy workloads.

Supporting customer-facing employees and security teams by automating threat detection tasks allows retailers to both improve security processes and simplify the jobs of existing staff. Taking this into account, below are some examples of how AI benefits retail security.

Loss prevention

Research suggests as many as 90% of retailers have experienced instances of theft in their stores, with 83% believing retail theft to be a major issue. Whether these offenses are down to internal theft, shoplifting or a combination of the two, retailers must find a way to reliably deter criminality and to investigate reported incidents without overexerting human resources.

By integrating AI video analytics tools into existing store security systems, security staff can program automated responses to anomalous events. Installed cameras can continuously monitor high-risk areas in search of stimuli consistent with criminality, sending alerts to staff remotely for further investigation. Modern AI algorithms can also perform situational analysis of live footage, highlighting subtle indicators of criminality to improve incident responses.

Violent offenses

Tangentially related to shoplifting offenses, many retailers have recently shared concerns regarding a notable increase in instances of in-store violence. According to one report, 88% of retailers believe shoplifters to have become more aggressive in recent years, with almost 50% revealing they’ve observed much more violent behavior in retail environments of late.

In a similar sense to loss prevention solutions, AI analytics software can be deployed to help retailers better detect and address violent offenses. Object detection software can be used to autonomously identify contraband items, while video analytics tools can be programmed to detect suspicious behaviors like crowds forming in unusual locations. These stimuli can be used as triggers for wider security tools like alarms and locks to help staff mitigate threats.

Perimeter security

The benefits of AI with regards to retail security can also stretch into perimeter security, with specially designed analytics tools able to aid staff in preventing vehicular crimes. AI-informed cameras can use License Plate Recognition (LPR) software to continuously monitor parking lots, with systems configured to warn security staff of suspicious cars around the premises.

In addition, these same solutions can be used to prevent and address muggings, attempted vehicle theft and other physical crimes that may occur around stores. Staff can be alerted to suspicious events, provided AI cameras are linked to a cloud-based management solution, with options to immediately secure perimeter access systems and contact local authorities.

Fraud detection

Aside from physical security threats, one of the biggest challenges faced by retail security teams is the identification and prevention of fraud. The number of fraudulent transactions detected by retailers has increased significantly over the last few years, with 85% believing cases of credit card fraud rose in 2023 and 70% seeing an increase in check payment fraud.

Once again, the analytical abilities of modern AI systems can be used to detect and prevent suspected instances of fraud before such transactions can impact retailers. Dynamic AI tools can detect fraud by analyzing payment data in search of patterns consistent with fraudulent activity. If an anomaly is detected, systems can immediately alert stakeholders, reject false payment methods and contact authorities or financial institutions to enact further responses.

Cyber security

Finally, while the number of cyber threats targeting most industries has risen in recent years, retailers appear to be among the most commonly impacted organizations. According to data published in 2022, 77% of retailers were hit by ransomware attacks during the previous year, an 11% increase when compared to cross-sector averages observed over the same period.

AI threat detection solutions are well-positioned to help retailers prevent these threats. With tools like endpoint detection and response programs able to continuously monitor devices and digital systems, automatically addressing cyber threats as and when they occur. Using AI in this way has been shown to help teams cut data breach costs by almost $1.8 billion.

Summary

With research suggesting retailers may be facing elevated risks with regards to both physical and cyber crimes, modern organizations must find new ways to improve security responses. While investing in more security personnel may seem like the most obvious solution to these issues, an alternative may be to better support existing teams using smart security solutions.

The ability for modern AI tools to continuously monitor high-risk locations both effectively and efficiently can help retailers to improve threat detection processes, supporting existing teams and reducing the impact of common threats. By developing smart security systems designed to suit unique commercial environments, artificial intelligence can benefit retail security.

Related: read more about how location data is used across retail and real estate.

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Footfall & Retail

These 3 Top Retail Analytics Trends Are Revolutionizing the Industry

Retail analytics involves collecting, analyzing, and interpreting retail operations and consumer behavior data. It uses various data sources, such as sales transactions, customer interactions, inventory data, and market trends, to gain insights and make informed decisions that drive business growth and optimize retail operations.

Top Trends in Retail Analytics

Here are three top retail analytics trends that are revolutionizing the industry.

Predictive Analytics: 

Predictive analytics controls past data, machine learning algorithms, and statistical models to predict imminent results and tendencies. In retail, predictive analytics helps businesses make informed decisions regarding demand forecasting, inventory management, pricing optimization, and personalized marketing campaigns. It enables retailers to anticipate customer preferences, optimize product assortments, and enhance operational efficiency.

Customer Journey Analytics

Customer journey analytics provides insights into the end-to-end customer experience across various touchpoints and channels. By analyzing customer interactions, behaviors, and preferences, retailers can comprehensively understand their customers’ journeys. It helps identify pain points, optimize customer engagement strategies, personalize experiences, and drive customer loyalty and retention.

Artificial Intelligence (AI) and Machine Learning (ML)

AI and ML technologies are transforming the retail industry by automating processes, enabling personalization, and driving intelligent decision-making. AI-powered chatbots and virtual assistants improve customer service and support, while recommendation engines provide personalized product recommendations based on customer preferences and behaviors. ML algorithms help retailers analyze large volumes of data, identify patterns, and uncover insights that drive strategic business decisions.

Key Areas in Retail Analytics

Retail analytics leverages data visualization, dashboards, machine learning, and predictive modeling tools to transform raw data into actionable insights. By utilizing retail analytics, businesses can make data-driven decisions, enhance operational efficiency, personalize customer experiences, optimize pricing and inventory management, and ultimately drive growth and profitability in the competitive retail landscape.

Sales Analytics 

Sales analytics analyzes sales data to understand patterns, trends, and performance metrics. It involves examining sales by product, category, store location, time period, and customer segment to identify top-selling items, peak sales periods, and areas of opportunity for improving revenue and profitability.

Inventory Analytics

Inventory analytics analyzes inventory data to optimize stock levels, minimize out-of-stock situations, and reduce excess inventory. It involves monitoring inventory turnover, identifying slow-moving or obsolete items, and forecasting demand to ensure optimal inventory management and reduce carrying costs.

Customer Analytics

Customer analytics includes customer data analysis to get insights into customer behavior, inclinations, and buying patterns. It helps retailers understand customer segments, identify high-value customers, personalize marketing efforts, and improve customer engagement and loyalty.

Pricing Analytics

Pricing analytics involves analyzing pricing data, competitor prices, and market trends to optimize pricing strategies. It helps retailers determine optimal price points, assess price elasticity, and develop dynamic pricing models to maximize revenue and profitability.

Market Basket Analysis

Market basket analysis examines transaction data to identify associations and relationships between products frequently purchased together. It helps retailers understand customer buying behavior, improve cross-selling and upselling strategies, and optimize product placement and promotions.

Supply Chain Analytics

Supply chain analytics focuses on analyzing data related to the supply chain, including supplier performance, transportation, and logistics. It helps retailers optimize supply chain processes, reduce costs, improve inventory flow, and ensure timely and efficient product delivery.

Store Operations Analytics

Store operations analytics involves analyzing data related to store performance, including foot traffic, sales per square foot, conversion rates, and customer satisfaction. It helps retailers optimize store layouts, staffing levels, and merchandising strategies to improve customer experience and drive sales.

Importance of retail analytics

Retail analytics plays a crucial role in the success and competitiveness of retail businesses. Here are some important reasons why retail analytics is important:

Data-Driven Decision Making

Retail analytics allows retailers to make informed, data-driven decisions instead of relying solely on intuition or guesswork. By analyzing and interpreting data, retailers can identify trends, patterns, and insights that guide strategic planning, optimize operations, and drive business growth.

Understanding Customer Behavior

Retail analytics provides valuable insights into customer behavior, preferences, and buying patterns. By analyzing customer data, retailers can understand their target audience better, identify customer segments, personalize marketing efforts, and deliver exceptional customer experiences. This understanding helps build customer loyalty, attract new customers, and increase sales.

Improving Inventory Management

Effective inventory management is essential for retail success. Retail analytics enables retailers to accurately analyze inventory data, monitor stock levels, and forecast demand. It helps optimize inventory turnover, reduce stockouts and overstock situations, minimize carrying costs, and improve inventory management efficiency.

Enhancing Sales and Marketing Strategies

Retail analytics empowers retailers to analyze sales data, identify top-selling products, assess sales performance, and optimize pricing strategies. By understanding customer preferences, retailers can create targeted marketing campaigns, develop personalized promotions, and optimize pricing decisions to drive sales and increase revenue.

Competitive Advantage 

In a highly competitive retail landscape, retailers that leverage analytics have a significant advantage.

Cost Reduction and Efficiency Improvement

Retail analytics helps identify areas of operational inefficiencies and cost-saving opportunities. By analyzing supply chain, logistics, and store operations data, retailers can optimize processes, reduce costs, minimize waste, and improve overall operational efficiency.

Final Words

These trends showcase the growing significance of data-driven decision-making and advanced analytics in the retail industry. Connecting with the power of retail analytics enables the businesses to gain a competitive edge. It also helps to optimize operations and retain customers by delivering the best user experience in a dynamic retail landscape.

Related: read more about how location data is used across retail and real estate.

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Footfall & Retail

Big Data In Real Estate – How Location Data Is Transforming Real Estate

For real estate, there’s nothing more important than location Whether looking for a place to live or identifying the best place for commercial property – location is the most crucial factor.

Companies in the space are looking beyond simple location classifications like zip codes or areas. Instead, more robust modeling and new datasets have opened the door to understand how neighborhoods are changing and what the people who live in specific areas want from their location.

It’s no surprise to see that big data is transforming the real estate industry. At the center of this is location data.

Let’s look at how data is innovating the in real estate space.

 

Data for real-estate investment

Evaluating and investing in new real estate opportunities requires extensive research and due diligence.

It pays to be the first to identify an up and coming area, but many companies have access to the same resources to try and understand where these hot neighborhoods are.

Emerging data sets, such as location are changing this. Movement data is giving real estate investment companies a head start, allowing them to understand the potential of a neighborhood before the competition.

Big data is allowing companies to answer the difficult question such as:

  • How to identify new neighborhoods or areas that are good prospects for investment
  • How to understand regional risks when investing

Location data is incredibly valuable in this area, not just because of the geographical nature of real-estate, but because the value of a property or area is determined by what happens in the surrounding area.

Real-estate value is closely linked to social and economic conditions – concepts that can be understood by using device location data. So the better your data, the better your insight into the investment potential of a specific region or area.

Utilizing location data alongside real estate demographic data and other third-party data sets allow real-estate to identify an investment opportunity early and measure and analyze the investment that you have already made.

 

Planning and development

For commercial real estate, the power of data is just as impactful as in the residential sector. Forget about costly to integrate footfall management systems. Location data can understand footfall across all real-estate properties, including your competitors. The most successful companies are using these real estate data analytics to adapt and plan in real-time.

 

Identify the most valuable spots

Location data can identify footfall in retail properties, both passing by and entering. Detailed metrics into visits and visit length can help understand the value of each location.

These insights can even lead to dynamic rent pricing or could also function as an add on product for tenants wanting to understand the benefits of their commercial property.

 

Increase operational efficiency

Real estate data can also help to improve operational efficiency. For commercial properties with vast amounts of footfall, such as airports, understand patterns around movement can significantly contribute to enhancing operations and optimized unused space.

These insights can be extended when developing new properties and planning from the initial placement of the project, to individual placement of retail booths inside. Predictive analytics in real estate is now commonplace and is having a huge effect on planning and development in the industry.

 

Advertising and marketing

Data isn’t just for planning and investment. Data has transformed the world of advertising and marketing, and this is true for the real estate industry.

Over 90% of home buyers start their search for a house online. Data is filling in the gaps between what the consumer wants and the ads that real estate delivers to these potential customers.

Datasets are making marketing and advertising more personal for these prospective customers. Ads can be targeted to those who have visited estate agents or personalized based on regular behavioral patterns. All allowing the real estate company to engage with a new audience in a personalized way.

This behavioral data can also be used to create a more engaging search process – where results are tailored to the user. This extends through to any consultation process, with the rise of chatbots, such as WhatsApp Chatbot and automation solutions requiring powerful data to be more productive.

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Related: read more about how location data is used across retail and real estate.

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Best Things To Look For When Looking At Real Estate

Thailand is a destination appreciated by many foreigners. The contrast of cultures and behaviors amazes and forces citizens of other countries to join the celebration of life and resort lifestyle. Here the ancient temples neighbor exotic shows, and daytime spiritual practices are replaced by grandiose night discos. Mild climate, endless beaches and low cost of living in Thailand attracts thousands of foreigners wishing to buy property in this paradise corner. Ownership of property by the sea in Thailand is a fairly safe and solid means of growing your fortune. 

Real estate for sale in Thailand 

Monitoring the real estate market of Thailand, you may notice that it offers housing objects for every taste and budget. You can choose a modest apartment somewhere on the outskirts or a spacious apartment of several rooms in the capital`s center. 

Besides, whether you intend to invest in a home of your own or to rent it out for tourists, you will not face any shortage in real estate of the luxury segment at reasonable prices. 

Those wishing to purchase a relatively inexpensive apartment or private home, choose Pattaya. For fans of luxury – a wide range of real estate on the fashionable resorts: Phuket and Samui. New buildings and secondary housing in Bangkok also attract buyers, but mostly in the Thai capital investors are more interested in commercial real estate.

The most reliable method of real estate purchase 

The government of Thailand used to approve several ways of acquiring ownership of real estate by foreigners. The establishment of a Thai company was the most popular and the easiest one. However, most investors have understood the risks of such a deal and abandoned it. Today there remain two legitimate ways to buy real estate – the purchase of shares in the condominium or a long-term lease, the maximum recorded period of which is 30 years. But many foreigners are not willing to invest in condominium projects, especially in areas such as Phuket, Samui, Pattaya or Koh Chang, where preference is given to the resort-style properties, particularly villas.

For this reason, leasehold appears to be the safest method of obtaining real estate in Thailand. To get the profitable investment in the foreign real estate market, it is advisable to evaluate the profits and estimate the risks. 

Profits of buying real estate in Thailand 

When it comes to buying real estate in Thailand, there is an ocean of opportunities and a whole pack of benefits. Foreign investors are looking for a way to provide a reliable cushion for seasonal or unexpected fluctuations in revenue and they find it in Thailand. 

  • High return on investment. 

Real estate in Thailand is a rational choice if you want to have solid investment options. There is no decrease in prices on Thai property is foreseen in the near future. The resort location of the country welcomes tourists or so to say potential tenants all year round. This is why real estate in Thailand has a huge demand among both local and foreign investors. 

  • The constant development of the country. 

Thailand is characterized by a well-developed transportation system that connects major commercial, residential and industrial centers. Besides, the government works on reducing the number of traffic jams on the main roads and decides on more advanced means of transport. 

The kingdom is also known for high quality medical services, fast internet connection, good business opportunities, and multiple variants of comfortable accommodations. 

  • Relatively low cost of living.

The cost of living in Thailand may be called relatively low as here you need less money than in other resort destinations. Besides, the level of life and the prices differ depending on the region, so a resident with any income can find the suitable option. Of course, over the past few years, the cost of living in Thailand has increased, but the prices of many services, seafood, vegetables, fruits and rent are relatively democratic. A studio or one-bedroom apartment in Thailand can be rented for an average of $200-400 (per month), depending on the region. 

Risks when buying real estate in Thailand

Any purchase of real estate is followed by certain risks. Therefore, it is advisable not to be blinded by appealing advantages, but be ready to face the responsibility. 

  • Legal risks. 

There are myths that in Thailand there is no private property as all land belongs to the King. However, this information is wrong. The amount of foreign capital in the country perfectly shows that most of the land belongs to companies and individuals. 

  • Risks in the process of construction. 

If you invest in real estate under construction, it is important to be aware of some possible issues, like delay of the delivery or absence of the EIA. To avoid purchasing a property without the Environmental Impact Assessment or EIA, check the documentation provided by the developer and ask a professional for help. The delay of construction finishing is rather an exception, and in this case a developer has to pay fines to the buyers. 

  • Risks of obtaining less income than expected. 

The marketing risks appear when some estimation mistakes have taken place on the stage of creating the project. It means that the delivered real estate will not bring as much profit as it intended. However, with the responsible approach to selection and sufficient consideration, these risks are easily avoided. 

The final word 

All the risks can be eliminated and all the profits can be increased if you select property with the help of the correct resource. The major aggregator Thailand-Real.Estate cooperates with the trusted Thai developers to offer the reliable housing units. An ocean of accommodation variant to any taste and money are available on the website. 

On the whole, due to the uncertain economic situation in the world, the purchase of real estate abroad may be the furthest thing foreign investors think about. But what if this option is the best way to establish balance and even force growth of your capital nowadays? The statement definitely needs to be carefully thought out.

Related: read more about how location data is used across retail and real estate.

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Footfall & Retail

Investing In Real Estate To Obtain Second Citizenship: A Guide

The real estate business is one of the most trusted segments of investment worldwide, as there are zero losses when you invest in real estate. However, in some cases, you might also witness property prices rise as many people invest their money to maximize returns.

Many countries offer citizenship to people who wish to invest in real estate and buy land. This helps the host country to inject money into the economy in return for providing citizenship.

There are many examples of countries giving citizenship, such as the St Lucian citizenship by investment program. Investing in real estate is the process through which the majority of foreigners who complete Saint Lucia’s citizenship application and due diligence process will immediately acquire dual citizenship.

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Follow the tips below to learn how to invest in real estate and get a second citizenship.

1. Quickest Way to Get Second Citizenship 

Investing in real estate is a shortcut for a new beginning in life, as it is the quickest way to get a second citizenship. On the other hand, if you move to a new place and use other means to get the visa, it might take years to conclude your application with no guarantee of a positive response.

Furthermore, no matter where you invest your money, real estate investment will make profits for you. In some cases, you might think that it is a time-consuming process, but usually, within five years, you can get a lot more profit than with a bank’s savings account. Due to the rise in population, there is an ever-increasing demand for properties, which is why the construction business is also booming.

Therefore, if you plan to invest your money, you should go for real estate.

2. Follow the Rules Of the Specific Country

It is essential to understand that you must follow the rules and regulations of investment when you want to obtain citizenship. For instance, if you invest your money in St Lucia, there is a minimum threshold of investment that means you must invest a minimum of 190,000$ to be eligible for permanent residency. In addition, your application may take 3-6 months.

After the process, you are free to use all the facilities like any other St Lucian citizen.

3. Clear Criminal Record

Copyright: Image by Freepik  I License: CC0 Public Domain

To apply for second citizenship, you must have a clean criminal record, and some countries might also require a character certificate from your current country of residence. It is important to be clear about your criminal past to reduce the risk of problems further down the line.

In some instances, this might be nothing more than minor grievances against you, as ups and downs are part of life. After a while, you can get a clean sheet from authorities.

4. Legal Source Of Income

Even if you are looking to open a bank account, you must provide a source of income for your funds. Similarly,  while investing in real estate, you must provide legal documents about your business and the funds you generate. The reason for doing this is to determine that the funds are not from any illegal activity and that it is safe to allow you to invest.

Moreover, this also helps the host authorities understand your sustainability and work.

5. Invest Money in Government (Approved Option)

You should remember that the main goal is to get a second citizenship. Therefore, you must take the process seriously; otherwise, all your efforts might go to waste, and you could lose your money.

To avoid such situations, you must invest in those real estate options the government provides you. There will be no risk, and everything will be done under the supervision of higher authorities. Moreover, the time it takes to get the visa might be minimized.

Another advantage of investing in such options is that there will be no chance of losing your money by investing in disputed options, and you will get a head start with your real estate business.

6. Tax Planning

For tax planning, dual citizenship could be helpful. You can save much of your money from taxation and invest it elsewhere. For instance, some nations only tax income produced within their borders and do not tax capital gains. As a result, investors can manage their capital more skillfully and successfully.

Obtaining Second Citizenship Can Increase Your Returns

In conclusion, citizenship by investment or simply buying a passport is becoming increasingly popular among citizens today. While it may be expensive, there are significant rewards associated with obtaining a second residency or even full citizenship in a different country. This includes access to better educational and health opportunities, global tax advantages, and job prospects. 

When you want second citizenship, you must be organized and take the time to look for suitable options with the suggestions mentioned above in mind. 

Related: read more about how location data is used across retail and real estate.

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Footfall & 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. Big Data Integration allows businesses to consolidate and analyze data from multiple sources, enhancing customer insights. Predictive analytics can help you 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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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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Footfall & Retail

How To Engage Your App Users And Improve App Store Rank

How to engage with your mobile app users and rank higher in the App Store. 

Location can improve app engagement. Creating a valuable relationship with your app audience should be the upmost priority for app developers. There’s no quick fix to acquiring millions of users, ranking highly and generating huge income than creating a great, engaging and useful app. 

 

If you take a look at the best ranked apps at the moment you might notice a common trend. They understand the importance of micro-moments and implement a strategy which utilises these moments to engage with their users. These are the specific interactions within a mobile app that create high value for the app user. If you get them right these can be the difference between a user becoming your biggest ambassador or deleting your app moments after downloading it. Location is the perfect toolkit to engage with app users, keep them coming back for more and ensure that your app keeps on shooting up the App Store rankings. 

Since higher levels of engagement help your app to rank higher in the App Store (ranking is dependent upon activity and how quickly your app is deleted once it’s downloaded) you’d think that more publishers would spend more time figuring out how to reengage users. A huge twenty-five percent of apps are discarded after being used only once. It has never been more important to for mobile app publishers to encourage engagement, without this you won’t get new users, and you’ll quickly lose the ones you have already gained. Luckily, location might be the solution to both of these problems. 

 

Add context to your app experience

For a mobile app to engage users it must have a high value proposition. Increasingly, many developers overlook the fact that their app provides little benefit to the audience, or it does at the incorrect moment. As an example, let’s take a look at the push notification. 

Adding location to push notification strategy is a great example of reaching users in the right moment. Location technology allows you deliver a customised notification to your users based on their environment, location and behaviour. Interacting with your audience in this way is much more effective and engaging than sending push notifications blindly, without the insights provided by location tech.

This engagement helps you to rank higher in the App Store – ranking is dependent upon how often your app is engaged with and how quickly your app is deleted once it’s downloaded.  This is why it’s important to encourage engagement, without it, you won’t get new users. Location is pivotal to this engagement.

We know that nagging push notifications can have an adverse effect on app engagement. It’s important to ensure that your notifications are useful to the end user, rather than just encouraging them to open the app. Adding a location enabling SDK to your app can achieve this – by adding context to your notification delivery then you omit irrelevant communication and increase the value that your app provides to your users. They will thank you for this value by engaging more often with your app. 

This works by using highly precise location signals to trigger the delivery of notifications. For example, by segmenting the audience that receives the notification based on relevance. By understanding what your app user is doing, why they are there, app developers can create an effective engagement strategy. All app owners should be asking themselves these important questions – and location integration can answer them. 

 

Measurement, analytics and attribution. 

 

Adding a proximity SDK to your app allows app developers to create a measurement strategy which provides valuable insights into user engagement and behaviour. 

These insights are available with a simple integration, for example, Tamoco offers our partners real-time insights through our analytics platform. This allows apps to visualise their app engagement and understand and measure engagement strategies. Every app is different and will have varying KPIs, but location tech can help to measure these effectively. 

But it’s not all about insights, it’s also about attribution outside of your app. For example, if your app is a branded clothing app with a real-world store, you can measure physical store visits as well as successful e-commerce journeys through the app. This way you will receive a much more comprehensive ROI for your in-app marketing strategy. A good example is the looking at WhatsApp for Ecommerce.

The important part for app owners is that these insights are highly actionable and all ultimately help you to engage with new and existing users. For example, if you understand where most of your users are engaging with your notifications, and you can understand the context (perhaps they just left the local tube station). These insights tell you much more than just how many users opened your notification, they help to analyse why you are getting such a high/low engagement rate. This helps you to improve and create an effective engagement strategy. 

 

Monetise app engagement

 

Whilst improving app engagement, app publishers can provide some extra income by allowing third-party brands on our network to send notifications. This provides added value for your users as we ensure that your app only delivers relevant content in the right moment. 

For example, if you want to retain your mobile audience then you’ll want to provide them with value in your app, through relevant notifications and in-app experiences. 

Let’s say that you have a lifestyle app. If a third party brand that is relevant to your app audience is running a nearby event or offer then it could be worthwhile to allow them to advertise it through your app. Using proximity technology we only deliver this to relevant app users, based on their location. 

You’ll receive a cut of the campaign budget for allowing them to use your mobile app to reach this audience. You can define the number of notifications that each user receives, this means that you have complete control over what is delivered to your mobile audience. 

Tamoco, for example, has hundreds of clients on our proximity network who are willing to use third party apps to reach users. You could provide high value to your users and that will keep them engaged and ensure that they keep your app on their phone. This generates behavioural data around your audience. Information of this kind is very useful for app developers. They can gain valuable insights into their audience, understand their actions and understand

Before you know it you’ll be shooting up the rankings and that means more opportunities for background monetisation. 

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Footfall & Retail

Location data and retail – optimising OOH

Retail brands can utilise location data in order to optimise their OOH advertising and gain offline attribution based on store visits. 

 

What is location data

For retailers, it’s important to understand what is going on in and around your store.

This kind of retail insight is already available for online adverts. You can tell how many people view your advert, click it and purchase your product. But in the real-world physical store, the customer journey becomes more difficult to pin down. How can you determine the effectiveness of your out-of-home, physical advertising? Offline consumer attribution involves using accurate, proximity location data to understand how audiences react to your out-of-home advertising.

When we talk about location data, we are talking about understanding how consumers move in and around your retail space. This is what we like to call the offline world. Understanding it is valuable for brands and can present information that can dramatically improve footfall and sales. According to a recent report, over 96% of surveyed marketers believe that location data is a key part of their mobile marketing strategy. My question is – what were the other 4% thinking?

 

An accurate solution to an old problem

Retail brands are beginning to realise that this is important and that it’s a crucial part in any successful retail marketing strategy. What brands might not realise is how accurate this data can be, and the effect this can have on OOH advertising. Location data is precise – and provides an accurate understanding of the customer journey. With the right proximity sensors, you can measure this journey with an accuracy of up to 1m. 

This accuracy is provided by the number and precision of the sensors on our proximity network. This delivers valuable insights into retail environments, and how consumers move. One application of this data is to measure the effectiveness of OOH and redefine how your OOH works. 

It’s currently quite difficult to measure how real-world adverts are performing. Attribution is key for the modern marketer and It’s not always apparent where footfall traffic is coming from. Location data solves this problem by allowing unprecedented insights into the journey to store and to purchase. 

 

Let’s look at how this could work for retail brands.

Using location data, you can understand when a user is in front of your advert. You can then use in-store sensors for attribution – to understand which users then visited your store because of the OOH. 

Very quickly this can give insights into how your physical adverts are performing. You can understand which customers respond best to your OOH and determine how much of your footfall traffic is being generated from these adverts. This provides an accurate ROI for physical advertising.

With the accuracy of proximity sensors it’s possible to even determine which area of the store users visit after viewing OOH. This kind of insight is unprecidented and provides numerous advanatages for brands that implement this strategy. 

These insights are highly actionable for brands. For example, using real-time location data marketers can adjust OOH advertisements in real-time depending on footfall data.

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Footfall & Retail

Retail, the IoT and the stores of the future

It’s a hot topic at the moment – how will retail adapt to the current challenges facing brick and mortar stores?

Online shopping is on the rise and customers are using stores as showrooms whilst purchasing elsewhere. Retailers are looking to bridge the gap between the growing digital world and the traditional in-store experience.

A recent report states that over 70 percent of retailers are now looking to invest in IoT tech to improve their in-store experience. Further, 90 percent are looking to incorporate mobile into their in-store experience. The IoT and proximity tech is becoming more popular in the retail space. Here’s how retailers are using it to find omnichannel solutions to the big retail problems.

 

Using the IoT to personalise the customer retail experience

Personalising the mall or store experience will boost in-store engagement rates. Deployed IoT sensors can measure where users are in real-time. Targeting users based on their location is one solution for retailers. These proximity campaigns create value for the customer. By receiving advertising content when it’s most relevant, shoppers are more engaged.

Proximity sensors are now accurate up to one meter. Combining these with the connected IoT delivers content to shoppers when they are in highly specific locations. Reaching consumers in this moment personalises the shopping experience and it also improves brand image. The retail store of the future will be an individual experience and the in-store experience will need to be adapted accordingly. One benefit of the IoT and proximity is that it works in real time. This means in-store content can update live, depending on who’s in front of it. It’s in these micro moments that retail personalisation will be most prevalent. This will create high value for retail brands.

Digital customer engagement will help create smart retail spaces. For example, using in-store location to order out of stock products. Or even using digital channels to order in-store products for home delivery. Some retailers are even trying to implement the delivery of in-store items to your car. Adding personalisation and convenience to the buying journey is key for retailers. The best way to achieve this is through the internet of things and its accompanying location enabled tech.

 

Leverage data from the IoT for insights.

Digitalising the in-store shopping experience isn’t where this story ends. Using proximity networks it’s possible to gain real-time insights into your customers. The IoT consists of millions of proximity sensors which can shed light on how your retail space operates. Customers make purchases on multiple devices and in many different ways. It’s important for retailers to understand these trends and incorporate them into their omnichannel retail strategies. It’s about understanding how your customers are interacting with your brand. The IoT makes it possible to understand where to reach customers elsewhere on the buying journey.

Using the internet of things to understand how your customers move and interact with your retail store must be high priority for retailers. Location data from proximity sensors can help inform this. This data provides insights on how advertising or promotions affect store visits in real-time. Marketing activity can be measured based on cost per visit. Or even to understand the performance of in-store promotions.

The internet of things is growing quickly. Along with the accompanying proximity tech it will change the retail landscape. Make sure your brand is on board.

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