Empower Your Business With The Magic Of Machine Learning!

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We are now living in the Artificial Intelligence revolution with great application in the retail sector.

The way ecommerce and Retail businesses sell, advertise and market their products today will change dramatically in the next 10 years.

We no longer wait for the consumer to look for us but we predict what they will buy next week, using shopping recommendation engineering , recommend it and bring them to the physical or online store to buy it.

To get a taste of the future see here…

The father of modern marketing Philip Kotler in a major presentation in China on 22 Oct 2019 on The Future of Marketing said:

Marketing now with the use of technology will change dramatically!

Companies using technology will be able to automatically predict what products customers want and sell it  to them!

But this whole revolution is based on your company’s Data.

Artificial Intelligence is nothing new.

It has been a course in Computer Engineering since 1980.

What is strikingly new and is the fuel of AI is the Data you have in your retail business and elsewhere.

From this data the Artificial Intelligence with mobiplus shopping recommendation   can predict with considerable accuracy what the customer will buy next week.

The data that is gold for the business is the data related to customer transactions.

Loyalty Club.

Many companies have a Loyalty program with a privileges card that records all customer transactions.

There is important data there about his buying habits.

There you can find , using AI and shopping recommendation behavioral patterns , then find consumers who have the same patterns and predict for each of them individually what they will buy in the next period of time.

A company usually has a Loyalty program for about 10 years , with 20.000 users , with customer data and emails , which gives good data to start shopping recommendation!

Data from stores.

Stores issue receipts and many chains  link receipt  to  the customer.

Other chains do not link  receipts and  customer’s items.

Even  without customer  identification  you can see what products are bought together and you can use mobiplus shopping recommendation to predict what products you could sell together in the future.

And without the customer’s details you can see what products are bought together and find out by using the mobiplus shopping recommendation predict what products you could sell together in the future.

Also what products should be placed near each other in the store since they are bought together.

Or the opposite!

Your ERP records all these transactions which are gold for increasing revenue for the business.

Usually Retail businesses have ERP from 2000-2010 where your data is there and can be utilized in shopping recommendations.

Usually there you have 1 to 5 purchases per year per customer depending on the business you belong to and in other cases like supermarket one purchase per week.

You have an average receipt of 40 euros and you keep the customer for 6 to 7 years.

With this data you can predict who will buy  what and bring  them to  e-shop or stores to make the purchase.

You can predict what products they will want to buy next year and plan your production or purchases accordingly!


Many businesses have created eshops and sell their products and services online.

They have   an e-shop since 2010 , with 30,000 customers, 3 purchases per year per customer.

The customer here has 7 years  lifetime value  with average  basket 35 euros and  1 to 3 products inside.

You have 2000 visits per day and you have a revenue of 1m euro.

Every click the consumer makes on your product must be recorded.

Also the time they sit on the product  page….is it  10 seconds or  1 minute…this has  different weight for the prediction engine.

You certainly have the purchases that every user makes and that’s gold.

From the purchases made by this user you can predict what he will buy the next time, to notify him and bring it to the physical or online store for purchase.

From this user’s purchases, you will be able to find other users and predict what they will buy next week!

This is the data of an average shop and the above data can be used to help predict what the customer will buy next week and recommend it.

So increase your revenue up to 30% like the top players in the industry do.

Also your e-commerce platform and your intelligent instore shopping assistant will  recommends  products that each customer wants to buy  when they enter ,  differently for each customer

This will ignite up take your business to another level by giving an impressive customer experience.

To learn how the top companies in the world increase revenues up to 30% using Artificial Intelligence and prediction engineering read  the following book.


Download and read our ebook on how in store Shopping Data make Retailers profitable

Contact us now to increase your e-shop and in-store revenue  by 30%!

How to create a personalised e-shop. Household Equipment  with Artificial Intelligence and increase revenue by 30%?

Get 750 extra products in your basket in 10 days!

mobiplus  member  Elevate Greece
Confirmed Innovation.

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