case study: square meal - how to use intelligent data to implement successful recommendation...

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This slide share presents the benefits of using intelligent data to implement successful recommendation campaigns. Looking specifically at email and web recommendations highlighting the benefits personalisation can provide when delivering the right message to the right person at the right time.

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VIENNA • LONDON • MUNICH • ZURICH • BERLIN • PARIS • HONG KONG • MOSCOW • ISTANBUL • BEIJING • SINGAPORE • DUBAI

How to use Intelligent Data to Implement Succesful

Recommendation Campaigns, a Square Meal Case Study

Daniel Hagos – Client Solutions Manager, Emarsys

Ed Butcher – Head of Online, Square Meal

Talk with us @Emarsys @SquareMeal

#totallyengaged

Before we begin…

About Emarsys

About Emarsys

Email Service Provider

The Customer Engagement Company

4 key questions for successful customer engagement

How to choose the right Product?

Marketers aims

Personalized and Targeted Communication

88% of business leaders said being closer to

their customers was the top priority for realizing

their strategy over the next five years

IBM

29%

34%

38%

37%

Social media

engagement

Conversion rate

optimisation

Content

marketing

Targeting and

personalisation

2013

2012

44%

41%

66%

37%

39%

56%

44%

31%

Improving email

deliverability

Quantifying email

marketing ROI

Targeting recipients

with highly

relevant content

Both channels (32B2C)

Consumer channel (B2C)

Business channel (BB)

Which three digital-related areas are the

top priorities for your organisation in 2013?Most significant challenges to email mar-keting

effectiveness, by primary channel

39%

39%

39%68%

The reality

Are targeted emails being sent?

20%

20%

20%

19%

19%

25%

25%

24%

18%

18%

15%

9%Content

viewed on site

Up-sell

Abandonedbaskded

Subscription duefor renewal

Selling comple-mentary products

Lapsedcustomers

Win-back/reengagement

Shopping cartabandonment

Upsell/Crosspromotional

Date triggered

Event countdown

Post purchase

Activation

Triggered based onwebsite behaviour

Do you send out automated emails based

on any of the following triggers or behavior?

Do you use targeted email for the following

occasions?

In spite of consumer affinity for personalization, few

companies other than Amazon.com and Netflix

execute it in a turnkey, efficient, and

effective way.

Forrester

64% of CMOs have either an informal

or no process to manage their marketing

automation.

The Annuitas Group

25% 26%

Why Is There A Gap?

Many delegates focused on... the barriers they face

before implementing a marketing automation platform,

with the vast majority saying that they don’t know where

to start (especially in a very large organisation)

Econsultancy, 2013

Lack of know-how

…on the barriers they face before implementing a

marketing automation platform, ……or that internal

challenges prevent them from making any notable

progress

Econsultancy, 2013

“”

Internal challenges

(e.g. IT support, no resources)

Decision Tree Labs, 2013

“”

Lack of integration

IBM, 2013

Budget & ROI

The two biggest barriers are cost and lack of

certainty about ROI — both issues that are

becoming increasingly important in the marketing

domain

46 percent believe one of the top challenge of data-

driven marketing today is the inability to connect

data across multiple sources

Currently, what data do most marketers use to send segmented

campaigns?

What data is being used?

Purchase behaviour

Gender

Preference centre

Email behaviourMerchandising Teams knowledge

How do you know what a customer is

interested in now?

The Website tells us what a

customer is interested in now

The most

meaningful

interaction

with the customers is

on the website

10x more user data

generated on the

website compared to

email alone

The website is

always the most

up-to-date

point of expressing

interest

Challenge:

How can the website data be utilised to automatically create

unique and personalised content across various marketing

channels?

Recommendations : How do they work?

Captures:

• everything visitors do on

the website

CaptureAnalyse

Act

Applies:

• recommendation and

prediction algorithms

to the data

Provides:

• personalised content in

web, email and display

advertising

Multi-channel recommendations

Dynamic recommendation

widgets in real-time.

Boost website conversions

and sales.

Automatically personalise

every email you send.

Recommend products to

people.

Display AdRetargetng

WebsiteRecommender

EmailRecommender

Retargeting keeps track of

your website visitors and

displays your ad to them as

they visit other sites.

Recommendations… only for the big boys???

Who’s using recommendations effectively?

Now available to SMBs..

Who’s using recommendations effectively?

and many more…

electronics

real estate

job listings

toys

grocery

books

dating

Why do they work?

ROIRevenue

Brand loyalty

EngagementEngagement

CTR

Enabling personalised, highly relevant

1-to-1 product & content recommendations

Why do they work?

“Up to 20% of retailers revenue

could be attributed to product

recommendations”

“15% of consumers explicitly

admitted that they purchased

when they saw

recommendations on a page”.

(Forrester, 2010)

What percentage of revenue can be attributed to product recommendations??

Browsing Cart Purchase

Multi-Channel Recommendations across the Buyer

Cycle

2

Predict

Website

Predict

Email

Personal• 8% CTR• 2.5% revenue

Similar Items• 10% CTR• 4-10% revenue

Matching Items• 2-3% CTR• 1% revenue

AbandonedBrowse

• retarget aban-doned browse

In Cart• 4% CTR• ~3% revenue

AbandonedCart

• retarget aban-doned items

Re-Purchase• Increase

retention & ROI

Personal• 1.5-2x CTR

• 2-6x revenue

About Square Meal

• UK’s leading guide to restaurants & bars

• 2 print titles

• Big website, mobile site & apps

• 11,000 restaurants, 8,000 venues

• Active database of 250,000 users

• 2 trade shows

• 25 years

Square Meal Background

Square Meal Results from

Predict

43% higher click through

rate when Square Meal’s

emails have

recommendations

More customers can

discover new restaurants

and fewer leave without

booking

4 times more likely to

convert.

Before recommendations

• Open Rate: ~31.29% (max 48%)

• Click Through Rate: ~13% (max 22%)

• Click To Open: 40%

• Loyalty (LTV): increased 30%

Similar/Related Items

ALSO VIEWED widget offers

alternative products

• “Other products you may

be interested in”

• Generates 4%-10% of

total revenue

• Increases engagement,

average CTR 10%

• Square Meal: 4% of all

website bookings

revenue is generated by

Emarsys Predict

Learn the 3 key benefits of using a single platform

over disparate technologies

3:30 – 5.30pm

VIENNA • LONDON • MUNICH • ZURICH • BERLIN • PARIS • HONG KONG • MOSCOW • ISTANBUL • BEIJING • SINGAPORE • DUBAI

Thank You

Any Questions?

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