Empower Your Business With The Magic Of Machine Learning!
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Empower Your Business With The Magic Of Machine Learning!
These are the capabilities that companies need to develop to stay ahead. McKinsey
Personalisation is about using data from each channel to improve the customer experience in any channel.
Including physical stores.
The vast majority of retail sales are made in physical stores.
To achieve this, retailers need to coordinate many different data at high speed.
Of course, this is much easier said than done.
Something else that sets the leading retailers apart is how much they bring personalization to their stores.
This means that when the consumer enters the store you have to understand their needs and make them happy by guessing and suggesting what they want from you.
Leading companies in the world have achieved this and that’s why they remain leading.
Companies such as Sephora, Ulta and others have also been involved. Nordstrom , Home Depot and others.
Smartphones :The focus of personalization in the store !
Smartphones are the common thread that connects the entire consumer shopping experience with you.
From your e-shop to the store.
It is the tool that makes the transition without obstacles.
We read most of the emails on our phones, most people don’t go to the toilet without it, let alone to the store.
That’s why smartphones are the focus of personalisation in the store.
Shop employees work with consumer information that they have acquired themselves.
You have a lot more data than that.
This data sits in your e-shop and in your ERP
Imagine how powerful it would be if your Sales Associates had access to it.
If they knew the customer’s full shopping history, products they have browsed in your shop , their social media comments and all of this combined with recommended products and predictive models that determine what they are likely to buy and when from your recommendation engine mobiplus shopping recommendation platform.
it would give them the ability not to lose a customer coming into the store.
That’s where you need to improve the consumer experience with personalisation.
Consumers will ultimately choose to follow the retailers with the best experiences, which means a mix of physical and digital experiences.
To learn how the world’s top companies increase revenue up to 30% from existing customers using Recommendation Systems read the book below.
https://mobiplus.co/ebooks/customer-rediction/
Customer purchase data from your shop and ERP in close cooperation with the mobiplus shopping recommendation platform can provide you with a solution to the above.
You can offer personalized experiences to every consumer in your e-commerce and store through Annie intelligent shopping assistant , consumers smartphone trough a browser connect and through mobiplus app.
Based on Artificial Intelligence and Machine Learning it predicts what the consumer wants and recommends it.
Each time the consumer comes in contact with these recommendations within your store , Recommender learns better about their needs.
Annie is an intelligent digital in store shopping assistant which offers personal delightful experiences to consumers helping them to find the products they desire and collects rich shopping data that increase your revenues.
Annie Offers:
It can understand where in the store has sat , and what products looks !
Below we list some types of personalised recommendations for the consumer.
1.”Popular” is what all consumers want.
93% of consumers report that online reviews influence their purchasing decisions.
So it is important under each product to have data How many have bought to date, stars and consumer reviews.
That’s how you make the consumer’s decision easy.
Important also Like the Dislike so that the recommender learns more.
Also items like Follow this Brand under the product and are more important indication of interest.
And that’s how the Recommender learns better.
2.”What’s new” is also something important that consumers want.
This recommendation will help provide a new and engaging experience for your loyal customers, while providing another opportunity to attract newcomers.
Important information for all consumers.
4. “The customers who bought this also bought this”
Based on Collaborative filtering, which is a Recommendation Engine algorithm and exists in the mobiplus shopping recommendation platform.
It was first used by Amazon and is now a classic tool in Recommendation systems.
You can see them under the product page that the consumer now sees in your e-shop or on their mobile phone through the mobiplus app.
You can also see them under the shopping cart and there it gives significant help to the consumer as it also raises the purchase price.
It also works for consumers who have not logged in and gives them a significantly personalized experience.
5 . “ Recommendations based on purchase history “ .
These are very important and this is where Machine Learning and the mobiplus shopping recommendation engine work in depth.
It’s based on the consumer purchases you have in
It makes the consumer happy with the deeply personalized experience they have with you.
It makes you happy too because it comes back to the store again and again.
The more it comes to the store the better the algorithm gets and the cycle repeats.
mobiplus member Elevate Greece
Confirmed Innovation.
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.
