Dafiti presents how it uses Jetlore to provide product discovery experiences across its channels. The experiences are powered by Jetlore's real-time, unified, omnichannel customer profiles, predictive capabilities and presentation technologies.

1. The Latin King of Product Content:
How Dafiti Grew into a Top Retailer by Providing
Fresh, Engaging Content-Driven Experiences
Romulo Zarelli Costacurta
Head of CRM, Dafiti
Eldar Sadikov
CEO, Jetlore

2. About Dafiti
‣ Latin America’s largest fashion online retailer
‣ >$200M in online sales annually
‣ One of the fastest growing e-commerce
companies in Latin America
‣ Operates in 5 different countries with different
currencies and languages
‣ >100,000 SKUs
‣ Includes now 3 other ventures:
Dafiti Sports, Tricae, and Kanui
‣ Accessible by means of all device types

3. Dafiti CRM program
‣ Email newsletters (along with triggers) are
critical for customer retention and activation
‣ High customer engagement in email has a
dramatic impact on customer LTV
‣ User engagement/activation in email is usually
accomplished through category-specific
promotions and discounts
‣ Heavily relied on segmentation to ensure
featured promotions were relevant to users
‣ But it's not always easy for the customers to
discover products via promotions and price is
not the decision driver for many customers

4. How can we make email content
exciting and fresh everyday?
‣ We realized that product catalog is our best
content!
‣ But hand-picking product is painful and
suboptimal: different users want to see different
products
‣ Putting a carousel of last purchase or cart
abandonment recommendations may not reflect
the current fashion trends or customer’s tastes as
time goes by
‣ How can we create an engaging non-repetitive,
yet personalized product discovery experience?

5. We added a “product discovery” section
to our email
‣ The product collection is algorithmically merchandised at
email open time
‣ Takes into account:
- historical purchases
- browsing behavior
- passive observations (what products were displayed before)
- catalog product performance
- customer context
‣ The collections adaptively iterate as Jetlore learns more about
the customer without the need for constant manual updates
to product selection strategy

6. Jetlore’s logic ensures a fresh, diverse and
relevant collection to explore every day
Felipe has been
browsing shorts and
summer wear leading
to shorts being
featured top left

7. Felipe has been
browsing shorts and
summer wear leading
to shorts being
featured top left
Jetlore’s logic ensures a fresh, diverse and
relevant collection to explore every day
Felipe didn’t click on
Thursday’s Email, leading
to exploration of casual
shoes, a prior purchase
category. Hooded
sweatshirts were also
trending.

8. Jetlore’s logic ensures a fresh, diverse and
relevant collection to explore every day
Felipe didn’t click on
Thursday’s Email, leading
to exploration of casual
shoes, a prior purchase
category. Hooded
sweatshirts were also
trending.
Felipe browsed sweaters
and backpacks Saturday
morning before opening
the email, leading to their
inclusion that day.

9. Results:
Revenue Per Opened Email
14.6% 51.3%
All Days
(including days
with discounts on all
products)
Low/No
promotions
(one third of all days)
vs

10. Click to Open Rate: Higher and Steadier with Jetlore
ControlJetlore
Results: Click-to-open Rate is Higher and Steadier
11% CTOR

11. How were these numbers and
consistency achieved?

12. 1. Jetlore ensures diversity of
featured items spanning
multiple product categories
vs
This exposes users to a
variety of items and enables
exploration (studying user
behavior to see if they react
to the items)

13. 2. Jetlore keeps product content
fresh and constantly evolving
‣ Standard recommendation systems pivot
off the last shopping cart item or last
purchase and repeat the same products.
‣ Jetlore’s engine dynamically adjusts to the
user behavior:
- if the user does not take action, it will
iterate to offer new categories and
items
- if the user takes an action, it quickly
reacts by featuring more from that
class of items

14. 3. Jetlore immediately
incorporates new items and
trends
‣ Typical recommendation systems require a
bootstrapping time to start featuring each
item and, as a result, tend to over-focus on
the top/older items
‣ Jetlore immediately incorporates new
items without any bootstrapping time
‣ Jetlore automatically incorporates fashion
and seasonal trends via real-time
monitoring of product performance
Felipe’s profile
Shorts Summer wear
Backpack
Shoe
Ralph Lauren
Lacoste Casual
Navy BlueStripes
Ecco
Nike
Nike BackpackBlue
New
Arrival

15. What’s next?

16. Discovery is not limited to products.
It applies to promotions as well!
‣ In any given 2-week timeframe, we have 50-100
promotions created by Dafiti’s marketing team
‣ Each promotion is associated with a sub-catalog of
items (50-1000 items in each sub-catalog)
‣ Each user has a unique affinity to buy from a specific
sub-catalog
‣ Jetlore will select for each user the most relevant
promotions given the user profile at that point in time
- ensuring that promotions are not repetitive

17. Personalized discovery of
promotions and products across all channels
Web: Homepage Mobile App: Home ScreenEmail: Newsletters

18. Thank you! Questions?
Content in the form of promotions and products is your best weapon.
Use it to create personalized engaging discovery experiences.