- Why e-shop needs recommendations - Magento recommendation out of the box - 10 best recommendation‘s strategies that is NOT Included in Magento - Cases & Examples

1. Personalized recommendations
How to help customers do the shopping in
your Magento +
www.quiosque.pl Case Study

2. • Why e-­shop needs recommendations
• Magento recommendation out of the box
• 10 best recommendation‘s strategies that is
NOT Included in Magento
• Cases & Examples

3. E-­commerce manager pain
How to help customers buy any product?
• How to increase conversion rate?
• How to maximize cart value?
• How to speed up my IT?
• How can I have more time?

4. Personalized recommendations
WHEN YOU HAVE 1M VISITORS ONLINE,
YOU SHOULD HAVE 1M VERSION OF YOUR E-­
SHOP

5. How we define recommendations
Showing additional product to e-­shop
buyers when they are shopping
UpSelling, Related products, Cross-­selling,
Similar, Alternative, trending, bestsellers,
personalized, sold-­out, long tail

6. Similar products
recommendations
Related products
recommendations

7. Up-­Selling
Products you wish to your customer to buy instead of the
product that they are viewing
They might be
-­ More expensive
-­ Higher margin
-­ Regular price

8. Cross-­selling
Products to be
purchased in addition
to the product being
view or added to the
cart

9. Magento out of the box
recommendations
Product Page
-­ UpSelling
-­ Related (cross-­selling)
Cart Page
-­ Cross-­selling (impulsive)

10. Manual recommendation settings

11. Recommendations can be
automated

12. Machine Learning algorithms
Collaborative filtering
Content based filtering
Association rules
Neural Networks
Black Box engine
algorithms
BIG DATA
Real time
personalization
algorithms

13. Visitor browse e-­shop webpage,
each click does matter and is
collected by the reco engine.
AI smart mechanism learn
immediately the visitor
needs based on his
behavioral data.
Recommendation engine predict and
decide automatically what products
the customer might like and display
personalized offer to him in the real
time.
AI based Recommendations

14. What with Furby?

15. What with balaclava?

16. Strategies that work
1. Personalized landing page
2. Dynamic trends
3. Smart Cross-­selling
4. Smart Up-­selling
5. Similar products
6. Zero search recommendations
7. 404 – page recommendations
8. Add to cart cross-­selling pop-­up
9. Impulse Cross-­selling
10. Personalized promotions

17. Case study
How www.quiosque.pl is enriched with
personalized recommendation engine -­ QuarticON

18. Step 1 -­ Integration
<script type="text/javascript">
(function(){ upsParams = window.upsParams ||
[];
upsParams.push(['customer','xxxxxxxxxxxxx']);
var _qS = document.createElement('script');
_qS.type = 'text/javascript';
_qS.async = true;
_qS.src = '//rec.quartic.pl/qon.js';
(document.getElementsByTagName('head')[0]||doc
ument.getElementsByTagName('body')[0]).appendC
hild(_qS); })();
</script>
One script before </HEAD>
• Tracking user interaction data
• Product feed crawler
• Widgets displaying

19. Step 2 – strategies

20. Step 3 -­ The results
12% total sales
generated with
recommendations

21. Cross selling Pop Up – Must have
CTR 15%, Conversion 5%

22. Thank You
Paweł Wyborski, Founder at QuarticON.com
pw@quarticon.com