This document discusses tailor-made personalization and recommendation solutions provided by Sailendra. It describes Sailendra's 15 years of research experience in artificial intelligence and machine learning. Several case studies are presented, including increasing conversion rates for an e-commerce site through recommendations on product and basket pages, and improving sales and customer relationships for a B2B drinks distributor through cross-channel recommendations. Recommendations are also discussed for an online bank to simplify navigation and predict customer intentions. Sailendra provides customized recommendation solutions tailored to each client's specific business needs and goals.

1. Tailor-made personalization and recommendation
Sailendra
Tailor-made personalization
and recommendation
Tailor-made personalization and recommendation
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2. Tailor-made personalization and recommendation
Sailendra
15 years of research in AI
Collaboration:
INRIA and LORIA
Artificial intelligence
Machine Learning
Behavioural analysis
Recommendations
Activity sectorScientific experiences
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Behavioral analysis and recommendations
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Basics of solution
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• Collect users’ traces from client website:
• Navigation
• Visited pages (category page, product page …)
• Sales, add to basket, …
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• Convert traces into user-item digital rating

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Basics of solution
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• Choose the appropriate algorithm and adjusting it:
• User based
• Item based
• Hybrid algorithms
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• Add new algorithms that fit to client activity
specifications
• Marketing filters

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Costumers cases presentation
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E-commerce
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e-Business

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Paraforme
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Activity area : Online sales of parapharmaceutical
products
Problem : low users conversion
Objective : Realize additional sales
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Recommendations on product page
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METHOD
• Generate recommendations using
differents algorithms according to the
visited page

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Recommendations on product page
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Proposing alternative options to
augment satisfaction
- Cascade hybrid recommender
 Content based similar item
 Item based collaborative filtering
 Products usually bought with the
current product
GOAL
METHOD

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Recommendations on basket pageParaforme
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Incite user to complet his basket
• Cascade hybrid recommender
• Products usually bought with the
current product
• Popular products within the
community of the active user
GOAL
METHOD

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Recommendations on basket pageParaforme
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RESULT
• + 20 % of conversion

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E-commerce
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Business to Business

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J. Milliet
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Activity area : drinks distributor for restaurants and
bars
Problem : low conversion on sales channels
Objective : Increase sales
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Cross canal recommendations
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METHOD
• Personalized recommendations in the CRM and on commercials’
tablet
• Development of tailor-made filters

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Cross canal recommendations
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• Customers knowlegde
• Developement of customers proximity
• Sales increase
• Propose innovative recommendation despite the presence of
many strict rulesRESULTS

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Banque
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Online Bank

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BforBank
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Activity area : online bank
Problem : No direct relation with customers
(100% online)
Objective : Simplify and understand users’
navigation paths, and predict their intentions
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Sales channels recommendations
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METHOD
• Analysis (clustering) of stream based on behaviors
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RESULTS
• Optimize user navigation and simplify his path
• Predict user intentions and their time
• Anticipate costumer attrition and alert the bank
• Adapt marketing and communication strategies by community
Sales channels recommendations
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Other domains

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Other domains
e-Health: Satelor
• Goal : secure sick and old people in
their place
• Way : A robot and a tablet application
to monitoring user daily activities
• Sailendra:
– Personalizing the tablet interface
– Pushing personalized behavioural
advices to improve health
e-Learning: Périclès
• Goal : recommend personalized
pedagogic resources for students
• Way : an integrated framework within
the web-site of the university
• Sailendra:
– Participation in the conception and
parametring recommendation algorithm
– Industrialization of algorithms stemming
from the project
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Conclusion
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Conclusion

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Personalized and strategical support
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Tailor-made support in relation with:
Sector of activity Structure of the
website
Webmarketing
strategy
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Any questions ?
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www.sailendra.fr
regis.lhoste@sailendra.fr
+33 (0)3 72 47 03 37
@SailendraSAS
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