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How to Develop a Personal Shopping Assistant App

How to Develop a Personal Shopping Assistant App


The more responsibilities we have to take care about and the busier we are, the less time we have for ourselves. We live in the era of digital information and it changes the world extremely fast. Luckily, the progress is on our side so newest technologies are being developed according to our demands.

Shopping has become the new religion in modern consumer society so mobile technologies come in handy with personal shopping assistant apps. Huge marketplaces like Amazon or EBay make our shopping more convenient but it can take a lot of time to surf for goods in such variety of propositions. They need something like online shopping assistant to help people to find the best solution for less money.

How to Develop a Personal Shopping Assistant App Powered by Data Intelligence and Humans

Reasons to create a personal shopper app

As always, mobile developers have taken care about everything. It was a brilliant idea to create a consultant people can carry everywhere. The market of shopping assistants evolves from year to year because everything that saves time and money gains a lot of popularity.

Personal shopper apps also help people to avoid unsafe purchases by notifying them. App offers you the most profitable solution with real reviews and ratings. It can also prevent you from impulse inspired purchases because it displays the best choice according to your preferences.

Personalized service is not new, a lot of online marketplaces use it for a long time. But shoppingassistant apps have propelled it to the next level by offering users to have a look at things they should like. App remembers all the propositions people watch and using tags and offer them something related according their style. This can be done by artificial intellect of the app or by human consultants. The question about what way is better is a bit philosophic so we will return to it later.

And, of course, no shopper assistant avoid the common retail features like bonusing, offering discounts and first-entry gifts.

How to Develop a Personal Shopping Assistant App Powered by Data Intelligence and Humans

Humans VS Machines

Most of shopping assistant apps use both human and artificial intellect. So if you don’t want interact with people, there is a set of data intelligence algorithms that could help you.

  • Coupons. Apps automatically send users coupons provided by the store and. in addition, its own ones. So shopping becomes even more enjoyable.
  • Alerts. If the product you want to buy is unsafe, app notifies you about it. As a developer, you can also implement Consumer Product Safety Commision database.
  • Price comparison. The best advantage of personal shopping assistance. App can automatically recognize the product user is looking at and notifies him if there is a better deal in other stores.

At first sight, there are no disadvantages in using a data intelligence. But AI still can’t overpower human brain so live consultants can benefit in some situations.

  • Full service customization. Human consultants are still better when it comes to customers that haven’t actually decided what they want. Human-human interactions can also lift the spirit of a customer.
  • Adaptation to each separate user. There’s no better consultation than personal one. Despite machine algorithms evolve, humans perform 100% adaptation to all users’ needs and preferences so they provide the best solutions according to users’ style and wallet. Speaking about clothes, machines don’t stand a chance comparing to humans.

So as we can see, both humans and machines have their advantages and in isolation from one another they can be less efficient. So their combination is the best solution.

How to Develop a Personal Shopping Assistant App Powered by Data Intelligence and Humans

The best shopping apps

Mona is a great example of successful human-machine collaboration. The key of their success is that developers have a placed a bet on personalization. The idea was to shift the shopping paradigma to the side of a customer. It makes itself felt when it comes to the key feature of Mona; the more you use it, the more it knows about you (but not like in Terminator).

In order to make recommendations, Mona requests an access to user e-mail. There is seeks for some e-commerce information to learn users’ style. Customers can also additional filters like their measures, brand or colour preferences, price range and so on.

Mona has only two disadvantages that developers have to avoid in future. The first one is that Mona is available only for IOS devices. In 2017 there is much more demand on cross-platform software. And the second one is an absence of its’ own payment system. When you click “Buy” button, you are automatically redirected to the website of a saler. However, Mona developers promise to implement payments in a short time.

PS Dept. It’s a personal shopping app that makes life of busy customers more convenient. It provides a combination of human-to-human interactions and a nimble artificial intellect.

PS Dept works in a very creative way: users send an image and a short description of a product they want and get an instant response with all the solutions from human consultants. They can also hold a parley with some stores. This app is created for users that already know what they want. In that way, PS Dept users usually look for something rare or specific, something that you can’t buy in the nearest Walmart. And that’s why it uses a bit old-school human-to-human consultation.

Unfortunately, PS Dept is also an IPhone exclusive.

Sure enough, personal shopping assistants will evolve in the next few years and PS Dept and Mona are not the only ones (don’t forget about Wish). Surely we will see new players in this game.

As a result, we will see a lot of demand on this kind of software so you can now start the development and catch the wave. So don’t hesitate and evolve your idea. Contact us and together we can make a new high quality product.