3 approaches to personalization (case studies) using google analytics, vibetrace and marketizator

Guerrilla Marketing
Techniques for e-Commerce
using Google Analytics
some case studies about showing the right
message to the right audience in the right moment

23.01.2014

http://liviutaloi.ro
http://twitter.com/ltaloi
http://www.linkedin.com/in/LiviuTaloi
http://facebook.com/ltaloi/

2/55

Co-Founder of the most important
e-commerce resource in Romania

Community Manager for the biggest
e-commerce group/event in Romania


3/55

GMT for e-Commerce using GA
Workshop Agenda
•
•
•
•

04:
12:
25:
39:

Introduction
1st Experiment (do-it-yourself)
2nd Experiment (Vibetrace)
3rd Experiment (Marketizator)


5/55

Introduction
• CRO is not the Holly Grail
• Showing the right message to the right audience in the
right moment is the key to success – personalization
• Track / investigate / segment / hypothesis / test /
evaluate kpi’s / choose(challenge) the winner – always
be testing
• Always compute the cost of experiment – the smallest,
yet profitable segment

6/55

Personalization Profitability
• 1 Fashion site: 1.8% ecommerce conversion rate, 33
euros AOV, 10,000 users/day
• You want to improve a segment of 1000 users/day,
0.5% conversion rate, 30 euros AOV
• Expected improvement = 15%, 0.5->0.575%
conversion rate
• Expected +revenue = 630 euro/month
• Margin 30% => 189 euro/month

• Costs (developers/tool) = 150 – 450 – 950 euro/month

7/74

One possible approach to
personalization
• Data about the user needs/desires –surveys + forms:
ask them what they want to see, what they want to
receive on an email/newsletter – direct answer
• Data about what they wish to buy – wishlists +
abandoned carts – direct action (close to buy)
• Data about they are currently buying – the orders, the
products shipped.
• Data about their search process, their clickstream
navigation through the web shop

8/55

personalization
• WANT
– Survey->Analytics

More actionable

Less info
(old)

Less actionable

More info
(new)

• WISH
– Platform->Analytics

• BUY
– Platform + Analytics

• VISIT
– Analytics


9/55

personalization
Shopping
Sessions

week1

week2

Product 1

XXSSS SX XX

SB

Product 2

XX SS

SS

Product 3

SS

SS X

week3

week4

week5

week6

XXSB

XSSB

X = visit outside your site, S = visit on your site, B = buy
Shopping sessions: often interrupted, multi-device, multi-location, multi-channel


10/55

personalization
• You may monitor top 3 category + top 3 brands +
3 price intervals / category as the user browse
the site
• The rating score for each category is naturally
decaying (vibetrace)
• Different actions have different weights on the
score (the order matter also)
• .

11/55

3 experiments
• 3 months ago I started to prepare some
experiments
• 1 experiment is done using the team of
programmers behind the ecommerce platform
• 2 experiments are done using 2 CRO tools
developed in our country

• we are still collecting data… and changing things...

Experiment 1 – implemented into the ecommerce
platform by their developers


15/55

#1 – do it yourself
• Stage 1 – analyze, segment
• Stage 2 – prototyping the algo, making 1st
changes on some content areas (site,
newsletters)
• Stage 3 – analyze 1st results, changes on the
algo, starting again from stage 1
• .

16/55

#1 – do it yourself; Stage 1
• Establish what info do you need for
segmentation – granulation level user
–
–
–
–
–
–
–
–

category affinity
price interval for top categories
brand affinity
surveys for the “want” (categs + brands)
some demographics
amounts spent + number of orders
userid + mailid + clientid (not UA)
.


17/74

• You have to figure how to see this info into
analytics, into your reports (custom vars, UA:
custom dimensions)
• Then you may segment all users that have a
strong affinity with “Orient watches for
women”.
• Note that the segment is dynamic
• .

18/55

• Content to change: Newsletter
– Export a list of category affinity for each email
in your database from your analytics/platform
– Create an universal newsletter with boxes
dedicated to each main category (10-12
categories)
– At the time when the newsletter is distributed
one user may receive box1 and box5, other
user may receive box 3 and box 7..

19/74


20/55

• Content to change: Website
– An user is entering the site, having the
personalization cookie in place
– Based on categories score you show a widget
with products in the category with a high
score, in a price interval suitable for that user
– If the user is new you can show him some
tops (top sales, top rated, new products)

21/55

• You have a segment defined in your analytics
software
• You already showed some personalized
content to that segment, and that widget is
leaving some trails into analytics to monitor
• You look at some KPI’s and make changes:
algo, segment, etc

22/55

#1 – do it yourself; current stage


23/55

#1 – do it yourself; current stage


24/74


Experiment 2 – using a tool for CRO, personalization:
VIBETRACE


27/55

VIBETRACE
• They are computing a score for top X
Categories, score which is decreasing in time
without any activity from user
• They are using widgets for website and for
newsletter – easier implementation
• They have some big clients in Romania, they
are still working to improve the product
• .

28/74


29/55

VIBETRACE – (1) new subscriber
• For any visitor we don’t
recognize (we don’t
know his email address)

• Rules to display the
email collector


30/55

• December, total addresses = 1800
• 9% conversion rate (Popup display -> subscriber)
• 7000 daily visits on average


31/55

• email retargeting
possible campaigns

• trigger event puts a
schedule after 1 day
if the following conditions
will be met


32/55

• Remarketing after subscribing to newsletter

trigger event

first condition, must viewed
at least one product page

second condition, did not
purchase after trigger event

33/55

Cart abandonment


+

Remarketing after NL

34/55

• Results for transactional (emails) campaigns
• Average ecommerce conversion rate = 0.67%


35/55

(2) onsite recommendations


36/55


37/74


38/55

(3) newsletter recommendations
• Without VT

• With VT


Experiment 3 – a tool for CRO, real-time marketing:
MARKETIZATOR


40/74


41/55

MARKETIZATOR
• Specialized on real time marketing, using
interactions (popups, content layer) based on
rules, A/B testing, surveys
• They managed to rise conversion rates to
some of the well known online shops in
Romania
• They are improving the product constantly
• .

42/55


43/55

MARKETIZATOR - interaction


44/55



45/55



46/55



47/55

MARKETIZATOR – A/B Testing
experiment V2 + segment direct new

• Version A(#2)


48/55


• Version B(#3-2)


49/55

• CR = CTRL > B – 2.26% vs 2.16%...
• AOV = CTRL < B – bigger revenue


50

Thank You!
Send me an e-mail for this presentation.
• http://LiviuTaloi.ro
• Liviu.Taloi@SiteAudit.ro; Liviu@LiviuTaloi.ro
• I am active on Twitter, Facebook, G+ etc.

–ECOMpedia.ro
– http://twitter.com/ltaloi
– http://www.facebook.com/ltaloi
– http://slideshare.net/ltaloi/

Not enough time spent on questions?
Did you have more questions on your list?

Go online on ECOMpedia.ro
and ask questions that you want answered
usability, marketing, seo/ppc, e-commerce


52

About Liviu TALOI
•

Liviu Taloi was part of the team who worked for the most powerful Romanian online store –
eMag.ro during the first years of existence, where he was a PR Manager for 3 years.

•

Since 2005-2006, Taloi founded the company WebAudit specialized in providing
consultancy in electronic-commerce for Romanian online shops. As a consultant, Taloi was
practically a Project Manager for each client, his main activities regarding: analyzing and
solving usability and functionality problems, growing and optimizing conversion rate, testing
consumers behavior with website optimizer tools, administrating all the departments of an
online shop and creating online advertising/marketing campaigns, measuring the return of
investment and other KPI’s.

•

Together with Andrei Radu, Liviu Taloi developed the methodology and organized the
usability tests for Romanian eCommerce Awards Festival (GPeC) since 2007 until now (first
ones held in Romania). Based on international standards, the purpose of usability tests was
to identify main problems faced by regular users when they are trying to buy something
online.

•

In the last years, Liviu Taloi offered consultancy to more than 100 Romanian online shops.
Most of them are now leaders on their market niche.

•

Except consultancy and running usability tests, Taloi is also a speaker at conferences and
e-commerce workshops, being very appreciated by audience. He also writes articles and
market analysis for different online and printed publications. In 2008, Liviu Taloi was lecturer
at the first Romanian E-Commerce workshop called “iSell” and also he was lecturer at the
first Online workshops called “WebSell” – a series of 7 webinars regarding major problems
of an online shop.

•

Taloi was part of the team who developed the E-Commerce Study requested by ANCOM
(government agency) in October 2008 and the Romanian E-Commerce Study in 2006 at the
request of MCTI (ministry of IT&C). He repeated the study with private funding in 2010.



3 approaches to personalization (case studies) using google analytics, vibetrace and marketizator

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (6)

En vedette

En vedette (8)

Similaire à 3 approaches to personalization (case studies) using google analytics, vibetrace and marketizator

Similaire à 3 approaches to personalization (case studies) using google analytics, vibetrace and marketizator (20)

Plus de Liviu Taloi

Plus de Liviu Taloi (18)

Dernier

Dernier (20)

3 approaches to personalization (case studies) using google analytics, vibetrace and marketizator

Notes de l'éditeur