Empower Your Business With The Magic Of Machine Learning!
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- Aristotelous 83, Athens 163 43
- contact@mobiplus.co
Empower Your Business With The Magic Of Machine Learning!
Have you never imagined that while you have thousands of products in your eshop and in store, consumers don’t have time to discover and see them.
Artificial intelligence , machine learning and mobiplus shopping recommendation platform utilizes your shopping data from e-commerce and instore and understands the journey that every customer has within your business.
It predicts what products will buy next and recommends it in store and e-commerce.
The consumer has been inside your business different times , to find products , prices , offers , new arrivals , colors , e.t.c .
This journey has been recorded in your data.
There are hundreds or thousands of different journeys within your data and your business.
Artificial intelligence with prediction engineering finds these journeys within your retail business , sees what customers purchase and then create the rules, based on your shopping data, what each customer will buy next.
When a new customer enters your business , mobiplus shopping recommendation platform can tell in real time in which journey this particular customer is in.
It can also figure out at which specific point of the journey is in by seeing what products he clicked on or purchased lately.
It can also predict which products this consumer would like to see and buy next.
So you can predict which product this consumer would want to see and buy next.
It may sound like a work of science fiction to you, but this is being done today by thousands of the world’s top companies.
Having thousands of products in the ecommerce environment or in your company’s stores, the consumer sees a very small part of them!
You are thus missing valuable opportunities through the products you have chosen to have in your business , having spent a lot of time to find them and advertising them.
You have to show the right product , to the right consumer at the right time!
Today Artificial Intelligence and machine learning in retail together with mobiplus shopping recommendation platform can help you offer personalized experiences to each customer in store and e-commerce..
For every consumer who enters your retail business immediately predicts what products will buy next and recommends it.
It thus makes his life better having discovered something he wanted to find.
And makes you happy by increasing your revenues up to 30%.
Also you take your business to another level offering personalized experiences in store and e-commerce.
A level that predicts what the customer want to be happy.
In the case study below you will see how customer shopping transactional data within your retail business can give your customer an engaging and personalized experience and increase your revenues by 30%.
It is based on real consumer shopping data in an e-shop and stores of a large Greek company in the food delivery business , Lartigiano https://www.lartigiano.gr/
The architecture of the mobiplus shopping recommender is based on
After running the machine learning algorithms the recommendation engines are created , and then connected to your e-shop or instore through an API.
Let’s look at some real examples for a consumer who is looking now
‘Club Sandwich Bacon’
Recommended items user:
Club Sandwich Chicken Sandwich
Club sandwich ham
Club Sandwich Smoked Turkey
Burger Classic with cheddar,
cheddar cheese, bacon and fries
Coca-Cola 330ml
Burger Classic with cheddar cheese and fries
So content based recommender has discovered , using lartigiano shopping data ,what products to recommend to a user that is looking ‘Club Sandwich Bacon’ right now.
User based recommendations. A user now is logged in and using shopping data from users in the same cluster we can predict what other producst this particular user he would like.
Item to Item based recommendations .A user now has put ‘Club Sandwich Bacon’ on his cart and we are using shopping data what other users have bought when they put ‘Club Sandwich Bacon’ in the cart.
And the recommendations are:
Recommended items session:
Coca-Cola 330mlCoca-
Coca-Cola 330mlClub
Sandwich Chicken
Club sandwich ham
Coca-Cola Light 330ml
Club Sandwich Smoked Turkey
Fanta red 330ml
But we are surprised to see that a significant number of consumers who bought ‘Club Sandwich Bacon’ also bought Club Sandwich Chicken in the same order.
Let’s look at another real-life example.
Product on Product page.:
‘Spaghetti Carbonara’
Recommended items under it:
Rigatoni Chef
Bolognese
Spaghetti Amatriciana
Cesare
Tagliatelle Caruso
Al Pesto
Pollo al forno
Recommended products on cart:
Product on cart
‘Spaghetti Caronia’
Recommended products
Spaghetti Amatriciana
Bolognese
Spaghetti Bolognese
While he is in our eshop and puts in his basket ‘Spaghetti Caronia’ we recommend Spaghetti Amatriciana.
The above is a real pattern, as unbelievable as it may seem to you that someone who buys a ‘Spaghetti Caronia’ would also want a Spaghetti Amatriciana
The above predictions and shopping recommendations are dynamically generated within the ecommerce environment differently for each customer.
So imagine the thousands of combinations that your mobiplus shopping recommender calculates in real time.
You thus serve each customer personally by understanding their needs , and giving them new experiences , taking your business to a higher level.
So we have 3 levels of recommendations
1.Recommended for you!
First level on the main screen of the eshop-
Based on the user’s history we recommend items that they want
2.Maybe you want this!
Second level when it’s in the cart.
Based on the items in the cart and the user’s history.
3.Relevant products
Third level recommendations when user is the producta page recommend relevant products to help him choose
Sometimes we buy products that are completely outside our history.
Maybe a friend influenced us, we saw an advertisement , tried something new, something changed in our life.
At that moment the recommender recommends products to buy along with the product he put in the card.
If such a product exists in our business and in your transactional data.
All patterns are in the data in your business.
These patterns will be discovered by artificial intelligence , in your ecommerce environment , using mobiplus shopping recommender.
Lartigiano increases revenue and cart using Artificial Intelligence!
750 additional products in cart in 10 days!
See how the Lartigiano chain increases revenue and cart using Artificial Intelligence and mobiplus shopping recommender !
Test out the Recommendation Engine for up to 20.000 euros in revenue from recommendations. No credit card required. Just enter your company information and we’ll contact you with all the details.
