eRetail 2011 - Guido Fambach - comScore

Unlock Your Data. Deliver Results.

March 2011

2© comScore, Inc. Proprietary.

Customer value strategies


Who is in the analyses?

Challenge 1


The multiscreen customer

CAMPAIGNS

SALES

Awareness…. Consideration…. Preference….. Purchase…. Retention


Do we know whom this cookie represents?

1 customer

Valuable customers Considering prospect

4 customers

?


Do we really know whom this cookie represents?

:: 48 years old :: Male

:: 26 years old :: Female

:: 23 years old :: Male

:: 38 years old :: Female

?


Integration of Audience

Know your Audience, know your business!

What is the demographic profile of those converting on my site?

Is my new search campaign attracting my target audience?

Is my advertising inventory aligned with the audiences

visiting my site?


Make your users known

Digital Analytix lets you see and understand the breadth of your audience.

:: 48 years old :: Male:: First time browser to your site:: Search referral

:: 26 years old :: Female:: Frequent browser

:: 23 years old :: Male:: Return browser from your latest Ad Campaign

:: 38 years old :: Female:: Return browser from her first visit on a targeted page


Data Collection

Challenge 2


What data to collect?

Campaigns effectiveness

Prospect and customer behavior

Basket mutations

Browser engagement

Product placement

Sales drivers

And much more


Tags, Tags, Tags … Too Many Tags!


ONE Tag … TWO Purposes for Turnkey Implementations

Web Analytics Audience Measurement


Flexibility in custom attributes

Measurement metadata that make sense to you

Measurement metadata aligned with existing intelligence data

Easy re-writing of attributes to align with your business

Your own product names, id’s

Product placement codes

Server side enrichment

Resulting in faster website

No browser constraints

No limitations in metadata


Example questions about shopping baskets

V0910

Are my browsers going to the basket?

If they are, what products do they store there?

And finally do they purchase?

What average value does a basket have?

Total value of abandoned baskets?

Top products in baskets in comparison to order?

Most deleted products in baskets?


General Assumptions

V0910

In comparison to order measurement the basket measurement is a highly dynamic task

There is no clearly defined time to measure a basket in its final configuration

There are products added over a session or other mutations do happen like deletion of a product

To cover this, one needs to create a set of labels is sent, any time a basket mutation or view happens


Labels for Basket View

V0910

Set of labels to accommodate every basket view

Dimension Label Example Value Basket-Tag prefix_bid AcCEdF87654 Basket Event prefix_bev view Article ID prefix_bart 86085574,88071234,86074321 Colour prefix_bartc blue,no,grey Quantity prefix_bartq 1,2,1 Price in Euro prefix_bartp 45.00,9.95,12.00 Orderline prefix_bartl 1,2,3


Labels for Basket Mutation

V0910

Set of labels to accommodate every basket mutation

Dimension Label Example Value Basket-Tag prefix_bid AcCEdF87654 Mutation ID prefix_bmid 12 Basket Event prefix_bev add, del, mut Article ID prefix_bart 88071234 Colour prefix_bartc no Quantity prefix_bartq 1 Price in Euro prefix_bartp 9.95 Orderline prefix_bartl 2


Determine Abandoned Baskets

V0910

Make sure that the basket tag will be available on the confirmation page as well

Allows to determine information about the status of baskets: abandoned baskets

Note: The solution works as long as a basket does not exist longer than the session.


Data quality

Challenge 3


Sampling or not

Sampling is cost saving at first sight

Volume of site traffic

Trends in behavior

Good is in the details

Analyze actual numbers

Long tail analytics

Explain differences between web data and order intake


Example

1.000.000 browsers are visiting your website

Sample 1:10 trend analytics in behavior of browsers (f.k.a. visitors)

Sample 1:10 risk of inaccurate re-presentation of long tail products and order value

You’re selling 500 swatches and 1 expensive Rolex. Based on sampling

you risk to report the wrong numbers there

goes your commission…


Simpsons paradox: What would Homer do?

Which campaign is performing best?

Off course that’s campaign B

Mail campaign Converted Non-converted Total Success rate

A 21100 900 22000 95,90%

B 20310 690 21000 96,70%

Total 41410 1590 43000


Simpsons paradox

Which campaign is performing best?

Low ticket conversions High ticket conversions

Uhh so campaign A is outperforming B? Yes if you care about value!

Converted Non-converted0

5000

10000

15000

20000

25000

30000

A

B

Converted Non-converted0

2000

4000

6000

8000

10000

12000

14000

16000

18000

A

B


Aggregated vs. unaggregated

• Reactive

• Faster standard reports

• Reporting focused

• Suits high level overview

• Proactive

• Standard and custom reporting at same speed

• Easy custom report building

• Fast and flexible segmentation

• Immediate access to granular data for analyses


Out of 1.000.000 products online, I want to know IMMIDIATELY:How many red skirts have we sold?

The aggregated approach : We sold a 1.000 red skirts

But what you really want to know is: What is beneath the red skirt…


Out of 1.000.000 products online, I want to know IMMIDIATELY:How many red skirts have we sold?

Unaggregated: We sold

Type 1: 100

Type 2: 300

Type 3: 50

Type 4: 0

Type 5: 150

Type 6: 400

Now that we’re at it, Do you want to know the size, value and segmented to male and female as well?


Evaluating a campaigns traffic volume on the fly

How many unique browsers did the campaign generate between February 3 2010 and February 27 2010 and can you compare that to the campaign that was running from January 18 to February 11, 2011?


Atomix Technology: Access to ALL of your data


Data integration

Challenge 4


Multi-channel customer

What channels with what demographics drive your most valuable customers in terms of CLV

Where do I need to tweak and tune?


Connecting through linking pin

Login

E-mail address

Client number

Phone number

Purchase code


Combining multichannel data: retention in Telco subscriptions

People that visit general terms and conditions page

People that are 3 months before end of contract

People that complain at the customer service center

People that visit general terms and conditions page and are 90 days from end of contract and complained at customer service twice this month

Same visitor but now you woke up, right?!


Conversion attribution

Challenge 5


Multichannel data: attribute online responses

General

– Sent out catalogue Spike in traffic

Targeted

– Specific product snail mailing Spike in specific product views and online sales


Multichannel data: attribute offline responses

General

– Traffic volume online (orientation) leads to sales offline in the proceeding period.

Targeted

– Online mailing on specific visitors (geo location) leads to sales offline in the proceeding period.


Attribution ModelDetailed measurement of each user action and flexible, insightful attribution model links action to conversion.

Campaign and Site EngagementMeasure your campaign and engagement across many metrics.

Advanced attribution models to measure campaign objectives


Attribution: last cookie counts


Attribution: based on visitor engagement


Campaign ,conversion en attribution

Advantages engagement based attribution

– Objective basis(engagement score)– Fair distribution– Including online direct channel (brand performance)– Improve budget allocation– Pricing model


I want it all and I want it now

Challenge 6


Mobile, Video and Site Measurement integrated into one view

Discover and optimize your site against the content that drives your users on mobile devices, PCs, Video, or rich media


Live Segmentation on the fly

How many unique browsers visit my website

Are these male or female?

Is the product video on the website driving sales or not?

I want to see 50 year old men, that bought a book last month and that visited my website twice in the last week using their iphone


Translate into effectiveness

Challenge 7


Digital Analytix™


Digital Analytix

Atomix™

FULLY Integrated Demographics

SINGLE Tag

Immediate Access to ALL of Your Data


Digital Analytix

Atomix™

Audience Page Stream Metadata Mobile Data Lookup Data Merge Ecom

PowerPoint GUI Your Partners Report Builder API Excel


Enable your customer value strategies


Make your users known

Know your audience.

Know your business.


Thank You

More information:

Guido Fambach

VP Professional Services comScore

[email protected]

mailto:[email protected]

eRetail 2011 - Guido Fambach - comScore

Documents

Transcript of eRetail 2011 - Guido Fambach - comScore