Modern life has turned into a rat race. People are busy with their daily responsibilities and rarely have time to do shopping. The digital era has shaped the world according to its demands representing digital stores and huge online marketplaces like eBay and Amazon making shopping as easy and convenient as possible.
On the other hand, online shopping can also take much time while surfing the net in search of a new dress or handbag. For this reason, mobile app developers have come up with a brilliant idea of creating your personal mobile shopping assistant you can always carry with you. It helps you compare the best prices and offers available on the web.
Reasons to Build a Shopping Assistant App
Developing a shopping assistant app is always a good idea due to several major reasons. First of all, such applications let people save time and money offering the best prices and a variety of options at short notice.
Snowed under with work and other responsibilities, we often do not have much time to browse through dozens of web shops. Such app would certainly be a lifesaver. At the same time, shopping assist application will prevent you from buying goods on impulse and save money.
Another good reason is a high quality of products you buy. You can choose from a range of goods based on real reviews and expertise.
Mobile apps are able to deliver a range of services integrated with your personal digital shopping assistant. They traditionally include:
Booking and reservation services;
Ticket purchase and delivery;
Bonuses, awards and last-minute gift options.
Another great benefit of shopping apps is that they may appear to be beneficiary for both users and developers. Publishers will have plenty of options how to make money on their award-winning applications. As a rule, shopping assistant apps are free to download and install. So, what are the most efficient ways to make a profit from them for developers?
Companies can opt for two major ways of earning money. The first and most popular one is advertising. Another strategy involves kickbacks any time a person proceeds with purchasing from a particular store.
Shopping Assistant App Algorithm
The app may include both artificial intelligence as well as the human element. For this reason, applications are traditionally divided into two main groups. The first group includes apps based on human insight in addition to data intelligence. They actually have real people who provide some of the best offers available.
The second group unites applications that are powered by artificial intelligence only. They feature specially developed algorithms that do not include any type of real people’s consultations. Such apps introduce a set of options and tools making it easy for users to opt for the right offer. These functions typically include:
Best Price Comparison – the idea of such function is to find the best price letting users benefit from a great deal. The application identifies the product you need and looks for the best price available online. The data can be obtained directly from digital stores as well as from retailers and partner stores that also provide information on additional bonuses and discounts;
Coupons – users may benefit from the best coupons provided by the app before checking out;
Safety Alerts – a user will be notified by the application in case the product is unsafe;
Shopping Records – users will be able to track the entire shopping list in the shopping history. It reveals all purchases and transactions using special tracking system;
Package Tracking – you can use your shopping assistant app to track the package as well as track the status of the shipment.
However, if you want to make your app as successful as possible with users, combining data intelligence with a human insight would be the best bet. Mona is a good example of such beneficiary combination. Developed by former Amazon teammates, the app provides a great shopping experience.
Of course, creating such app calls for the most precise and accurate approach. Developers will have to take into account numerous experiments as well as find out users’ preferences and dislikes, what products they prefer the most and why. Developers will need to create a huge database that will enable an efficient recommendation system. High-quality performance is guaranteed only in case of more data.
Mona – Example of a Great Shopping Assistant App
The key to success is to make the app as personalizes as possible. In other words, the more people use your application, the better it gets to know their likes and dislikes. Mona is a great example of such approach. It was initially launched as an integration to dozens of digital stores, retailers and websites including some major online marketplaces like Barney’s, Amazon and more. However, the main mission is to turn the app into a third-party marketplace following the example of Amazon.
The main goal is to establish an efficient communication between customers and application. For this reason, Mona users may provide access to their emails as well as any additional information that may come in handy for better personal recommendations. The data may include sizes, color, prices, brand preferences and many other useful details. Many positive reviews show that Mona is rather good when learning people's likes and dislikes. It does its best when choosing a product that suits users’ tastes. The only drawback is that this app is supported by iOS platforms only.
There is one more disadvantage according to users’ reviews. Mona is not able to proceed with transactions. Whenever you want to pay for the product, you will be automatically redirected to the brand or company’s website to complete the payment. On the other hand, Mona developers are about to fix that bug.
People VS Artificial Intelligence in Shopping Assistant App
If you are afraid of interacting with artificial intelligence, you may opt for some apps and programs like Cortana or Siri. These systems will let you feel like interacting with real people. Some applications consider hiring a real person to play a role of your personal assistant. Such approach comes with a set of crucial benefits:
Fully-Customized Service – Humans are still better when surprising users if compared with artificial intelligence. They are more likely to come up with a brilliant idea for a gift. Any algorithm will hardly do the same. Personal online consultants will offer a gorgeous look that meets your expectations and tastes;
Total Adaptation to Users’ Needs – Although machines can still learn like Terminator, humans will hardly face any difficulties when taking into account your preferences. They can perform 100% adaptation to your style and individuality offering some of the best products that would suit you best.
Both artificial intelligence and human insight come with some advantages and drawbacks. Whenever you want to build a good and high-quality shopping assistant app, combining both variants would be a good idea.
Personal Shopper Department or PS Dept for short is another good example of a great app developed for iOS platform. It is based on an algorithm that provides users with access to all stores located around the city. The key feature of the app is a combination of personal touch with a smooth-running and flawless mobile platform.
How PS Dept Works
The application is based on a so-called human-to-human interaction system that is shaped by mobile technology greatly. All you need is to send a short description of the product you need featuring its image. As soon as you are done, the app will provide a range of some best offers available on the web. All suggestions are sorted out and sent via a team of live experts. Some may say that such approach is a bit out-of-date. On the other hand, people behind the scene can negotiate the price and look for all available offers online as well as in real stores.
Both PS Dept and Mona are only pilot versions of shopping assistant apps. We should expect more applications that are similar featuring advanced options and algorithms. Moreover, the mobile technology will soon reshape the approach established by some major brands and retailers. It means that developers in the niche will be in a huge demand in the nearest future. So, get ready now nd work out your own concept of your own shopping assistant app.Previous Next