The document outlines five strategies for using online recommendation engines to boost sales: personalizing the shopping experience, cross-selling complementary products, providing social proof, offering location-based recommendations, and upselling alternate products. It highlights the advantages of automated recommendations over manual methods and cites various studies demonstrating increased conversion rates and average order values. The conclusion encourages implementing these techniques for improved online sales performance.

1. 5 Ways an Online
Recommendation
Engine can
Increase Sales

2. According to a Forrester study,
15% of visitors admit to buying
recommended products.

3. HOW
can product
recommendations
help you increase
online sales?

4. Offer a personalized
shopping experience to
your visitors.
#1

5. Personalization leads to
greater conversions.
Recommendation engines must efficiently analyze on
site behaviour and understand visitor preferences.
73% of customers prefer
personalized
shopping experiences

6. Food for thought...
Manual recommendations cannot
personalize to the extent an automated
recommendation engine can.

7. WHY
are automated
recommendations better
for personalization?

8. Manual
Recommendations
Automated
Recommendations
● An intelligent algorithm that
tracks visitor behaviour,
uses collaborative filtering
etc.
● No manual intervention
● Accurate
● Allow merchandizers to pick
complementary categories
or specify recommendations
per product
● Laborious & time-consuming
● Inaccurate

9. Cross-sell
complementary
products to your
visitors.
#2

10. Recommendation widgets like ‘Frequently bought
together’, ‘People who bought this also bought’ etc.
show complementary products to visitors and boost
conversions.
According to Mckinsey,
cross-selling techniques
increase sales by 20% and
profits by 30%.

11. For example, Amazon shows related
products such as sandals, handbag
etc as recommendations for a dress.

12. Show
recommendations
that deliver Social
Proof
#3

13. Recommendation widgets like ‘People who viewed
this also viewed’ show recommendations based on
the wisdom of crowd and use social proof to engage
visitors.
‘Content sharing (reviews,
testimonials etc.) can influence
consumers more than price and
brand, and motivate people to
spend 9.5% more’.
Source: Smart Insights Blog

14. For example, for this handbag,
Zappos shows recommendations that
foster social proof.

15. Personalization
based on location &
time
#4

16. Some recommendation tools consider
location/weather/time to further personalize the
shopping experience.
Location-based
recommendations make
product suggestions more
relevant and contribute to
higher conversions.

17. For example,during summers it
makes sense to show
recommendations for summer
dresses.
You would show different top-
sellers in Miami than the ones you
show in Alaska primarily because
of location/weather differences.

18. Upsell alternate
products to your
visitors
#5

19. Recommendation widgets like ‘More like these’/
‘Similar products’ are used to upsell products that
helps increase conversions significantly.
Amazon reported that 35% of
its revenues were as a direct
result of it’s cross sales and
upselling efforts.

20. Upselling has two critical benefits
1. Product Discovery
Show more products and give better
options to visitors.
2. Increase AOV
Products with better features
encourage visitors to spend more
and increase the average order
value.

21. For example, Asos upsells with the
‘We recommend’ widget to show
similar products.

22. 1. Offer a personalized shopping experience to your
visitors
2. Cross-sell complementary products to your visitors
3. Show recommendations that deliver Social Proof
4. Personalization based on location & time
5. Upsell alternate products to your visitors
CONCLUSION

23. Key takeaways
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