use cases

Personalized Recommendations

Recommending the right products or services to your customers or stakeholders using machine learning

What are personalized recommendations?

Personalized recommendations has several denominations : predictive marketing, hyperpersonalized marketing, individualized marketing...It consists in improving customer journey and increasing conversions by showing to customers products recommendations that are relevant to them. In Machine Learning terms,this is called a recommender engine.

Why use personalized recommendations?

Whether in B2B or in B2C, predictive marketing is becoming more and more common for companies that have large pools of products or customers. Hyperpersonalization is about promoting the right product or service to the right customer at the right time.

Business Benefits

Increase cross-sell

Cross-selling is the action or practice of selling an additional product or service to an existing customer. AI can help you increase the value of a customer or customer basket by recommending new products to an existing customer.

Increase upsell

Upselling is the practice of encouraging customers to purchase a comparable higher-end product than the one in question. AI can help you increase crosssell to certain customer segments or markets.

Improve customer journey and retention

Studies show that customers are looking for personalization in their journey. Helping a customer find something that she/he may like, through relevant product recommendation, increases customer satisfaction and retention.

Develop new business models

What if you could use product recommendation to provide additional services to your clients, suppliers or partners? This is the case for some companies who develop new business models or extend their business model so they can find an additional lever for their data.

Kantify's approach to personalized recommendations

Kantify has developed a performing AI solution that can be tuned to your needs and business objectives. Before initiating the development work, we usually start a new predictive marketing project by helping you frame and refine your objectives. In that way, we ensure that your recommender engine (the predictive marketing solution) will be a long term growth vehicle for your company. The development of the solution can be performed autonomously or in close collaboration with your teams. The final solution, once tested, is conceived to be easily deployed and embedded in your testing systems, websites or apps.

Case study on Predictive Marketing

One of our latest case studies is a recommender engine for a lunch benefit company, Monizze. Monizze is a growing Belgium scaleup, part of the Up Group, that uses technology as a vector of its growth and competitive advantage.

Challenge

The challenge was to create a solution to provide the users of the Monizze mobile application with relevant restaurant recommendations at all points of the day and in the whole of Belgium.

Solution

Kantify has developed a personalised recommender engine that can define in real time what will be the relevance of a restaurant for a specific user. The customer gets a feeling of ‘serendipity’ (i.e find something that you like, by chance). His satisfaction and etention are increased through the relevance of the restaurant recommendations.

Insights

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Find out why customer retention and loyalty are so valuable, anticipate challenges in improving retention and know how to calculate the value of your customerRead More
Predicting Churn with Machine Learning
Predicting churn with Machine Learning: the essential steps in terms of data collection, machine learning techniques, and evaluation.Read More
What is hyperpersonalized marketing, and how it creates value
Hyperpersonalization of marketing has now become a trend. Read how it works and how companies can leverage it to create value.Read More
Facebook open-sources DLRM, a deep learning recommendation model
This recommendation model needs to help the AI community tackle challenges presented by recommender engines.Read More
Amazon launches AI-powered ‘Shazam for clothes’ fashion search
Amazon continues to dominate the e-commerce retail business and introduces a new feature that will enable customers to find similar clothes online.Read More
Can AI Nudge Us to Make Better Choices?
Human behaviours are more predictable and sometimes influenceable that we would like to admit. AI can remove this factor and help us make better choices.Read More
How The Times is achieving hyper-personalisation with “JAMES, Your Digital Butler”
JAMES uses data to get to know the habits, interests, and preferences of readers and will use this information to act as a digital butler.Read More
Online ads can be targeted based on your emotions
The New York Times is now able to sell ads based on the emotion the reader will most likely feel while reading an article.Read More

News

Kantify selected as Belgian Digital Champion by the Belgian Association of Marketing
Our CEO, Segolene, presented our solution in hyperpersonalized marketing at the BAM event on Belgian Digital ChampionsRead more
Kantify explains hyperpersonalized marketing on Radio La Premiere
Our CEO, Segolene, was interviewed by RTBF - La Premiere, concerning hyperpersonalized marketing.Read more
Kantify is a proud international representative of Belgium’s AI industry
Kantify has been selected by the Belgian Foreign Trade Agency in its yearly publication about Belgium's leading companies.Read more
Kantify algorithms make marketing intelligent
Our CEO, Segolene, has been interviewed by DataNews concerning the impact AI can have on marketing.Read more