Categories
Software Technology Uncategorized

How geolocation and big data can be used to the advantage of your business apps

Nearly all industries have improved their efficiency through the use of geolocation. When it is combined with big data it allows for greater client satisfaction including more individualized customer experience, better targeted marketing and enables you to learn more about your own company.

Geolocation Apps & Big Data

Geolocation is most commonly used in marketing for geofencing, which targets clients who enter a certain location or area. This is often seen in shop apps which recognize when a client is near one of their stores and will then send them special offers, discount coupons, or other promotional information.

In similar vein big data analyses purchases to change or improve offers to better suit the needs of the consumer and allows a company to make their own products more attractive than those offered by the competition. For example a retailer can send special promotions and offers to a client whilst they are shopping in a competitors store. Equally, offers with a small time window can be sent to customers who are currently shopping in one of the company’s own on-line stores. This last example utilizes Beacon technology which works like geofencing but on a smaller scale, i.e. tracking the exact location of a client in the shop.

geolocation apps

Transportation and Logistics

Geolocation is indispensable for transportation and logistics where it is able to get the most out of the huge amount of data produced. Applications utilizing geolocation collate information about traffic jams, road works, quickest routes and allow for the communication of current locations and delivery times between the customer and the service/goods provider. For example, the client can keep track of the person who is delivering his food, and conversely a restaurant can also know exactly when the customer arrives to collect their order. Even within companies it is possible to create more realistic schedules and production timelines based on geolocation information shared between employees.

Social apps

Geolocation has also become an integral part of many social apps allowing users to leave digital markers as they use restaurants, hotels, and bars so that they can  rate their experiences and leave comments for other customers. This also provides increased levels of user engagement as most recently exampled in the huge success of Pokémon Go which showed the possibilities of augmented reality making old forms of advertising suddenly come alive. The same technology can be applied to museums, galleries and other architectural spaces to create virtual tours and even help people negotiate other public facilities such as hospitals or government buildings.

big data apps

Summing up

Geolocation and its various applications are constantly improving, just as are the analytic tools used to interpret and apply the information produced by it. However, it is worth mentioning security concerns that are inevitably produced by the collecting and use of such data. In this regard we should only ask for information that we really need and we should be always transparent about how and when it is to be used. In this way users can always feel safe using our products and can make informed choices on whether or not to disable location on their app.

Want to know more about Espeo? Read about our services HERE.

See also:

Categories
Uncategorized

Machine Learning App: How To Implement AI & ML into your App

In recent years Artificial Intelligence, Machine Learning and Augmented Reality have taken mobile app development by storm. When it is reasonable to build Machine Learning App? With Apple and Google both encouraging and making it easier for developers to use these technologies, businesses can vastly benefit by increasing user satisfaction and engagement by utilizing AI and ML.

Are you wondering if you can implement AI for your business?

There are numerous uses for AI in web and mobile applications. The main goal is to implement a deep learning process into your app to recognize patterns and then apply these ‘learnings’ to solve various complex queries. Here are the most common uses of AI and ML for businesses.

Learning user habits

AI is great for dealing with complex data like analyzing preferences. Building products with user experience in mind is a priority for modern applications. Appealing visuals are not enough to keep your user base happy, but AI can help with that. While most people do not bother to customize or personalize their apps small things like choosing which screen appears first or discovering what color theme is the most popular, can make the user feel that the app is designed specifically for them. Apps where the user has to go through many steps to complete a task can also easily use AI to make it faster or reduce the cognitive load on the user.

Recommendations

We already have AI recommending products or services to us on a daily basis (i.e. Netflix, Amazon) and this is all thanks to algorithms. Learning what a specific type of user (based on age, gender, location, previous purchases etc.) usually buys is a good way to predict the best options for them without having to use annoying and badly targeted marketing. Knowing what someone’s preferences are helps to facilitate ease of use and keeps them engaged for a longer period of time.

This method works extremely well for entertainment apps or those that sell products, meaning we can guarantee that all new content will get to the right people.

machine learning app

Face recognition

Current mobile devices are now able to use the complex data of a human face to recognize who a person is. The correct algorithm and a large enough selection of a persons pictures can provide a high degree of accuracy using this method. This can be used for both fun and security. Although locking a device with a fingerprint is currently more secure than 2D face recognition as AI gets smarter and faster, 3D face recognition will be utilized by more applications to work along with, or replace completely, fingerprint scanners.

Making everything easier

The amount and sophistication of smart devices is constantly growing, controlling lights, heating and air conditioning systems and refrigerators, to name but a few, but it can be a little bit of a hassle individually adjusting all these. Smart home products and systems can incorporate AI to work ‘with’ the user and not just ‘for’ the user. Our phones can become our personal assistants by setting optimal temperatures, turning lights off when we fall asleep or reminding us that we don’t have milk when we are shopping. Further, Speech Recognition allows us to learn applications quickly and interact with other devices around us more easily.

Mobile camera

Computer vision is constantly improving, mostly thanks to Machine Learning. The most common combination of these two features are apps that recognize people, everyday objects like lamps, text or even works of art. Everything from scanning barcodes to detecting facial expressions on photographs works faster and with more precision using Machine Learning. Camera applications can add filters on photographs and videos by detecting and tracking certain points. We can interact with phones via gestures because it learns and detects them. Every application using a camera can be better and more engaging for the user with computer vision.

machine learning applications

Summing up

First impressions in app sessions are crucial for retaining new customers. With AI learning the behavior and preferences of the user you’re much more likely to make these sessions better and more memorable.

All the data companies get from their customers is extremely valuable and should be used to not only improve the user experience but increase the chances of future business.

It is also worth noting that AI can be used to solve staffing problems where certain kinds of work can be fully or partially automated.
Consequently progressive businesses are very quickly integrating AI into their mobile and web applications to create useful apps for their customers. As such AI is a highly exciting and lucrative area to be involved in.


Check out how we can help on your next Machine Learning App!

Want to know more about Machine Learning App and our recommendations?! Read this post: Al and machine learning Apps: What can we learn from big brands
[contact-form-7 id=”13387″ title=”Contact download_8_reasons”]