data triangulation - driving profit form data in ecommerce

http://www.ometria.com - @OmetriaData

Data TriangulationDriving Profit from Data in Ecommerce

Welcome to Ometria’s Breakfast Seminar


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The Ometria Team

Ivan MazourCEO

James Dunford WoodCOO

Dr. Alastair JamesCTO

Djalal LougouevCFO

Edward GothamHead of Ecommerce

Victoria ElizabethContent Marketing Manager

Alexander GashBusiness Development Executive

Tomislav BucicBusiness Development Executive


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How Ometria Sees Ecommerce

2000 2005 2010 2015 2020

Goal Funnels

Attribution Models

Integrated Ecommerce Analytics

Customer Models

Product Models

Profit Models

The

valu

e of

dat

a


Data TriangulationDriving Profit from Data in Ecommerce

Mike Baxter


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££

Profit

What is Ecommerce

EcommerceProducts Customers


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The Principle of Data Triangulation

CustomersProducts

Profit


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1848 – 1923 Born in Paris, Italian national, worked mostly at University of Lausanne in Switzerland

80% of land is owned by 20% of people80% of peas come from 20% of pods

The Pareto Principle / The Law of the Vital Few / The 80:20 rule

Vilfredo Pareto


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The Pareto Curve – Long Tail

Products

Sales

20% of products generate 80% of sales

Customers

Sales

20% of customers account for 80% of sales


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Tim Ferriss


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Best customersBest products

Most profit

Where is the sweet-spot in your business where selling your best products to your best customers

generates the most profits?


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A Note on Examples & Data

Based on Ecommerce consultancy work over the past 13 years with businesses ranging from High Street brands to 2-person niche pure-plays

Using examples from JohnLewis.com – NEVER worked with them so no confidentiality issues – SO hypothetical data

But all data, trends and insights based on real examples presented to actual clients


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Most profit

Your best products:1. Clicked most often2. Bought most often3. Highest order revenue4. Encourage most return visits


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The AIDA Model of Customer Journeys

Awareness Interest Decision Action


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for customers at this stage of their journey …


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Which Products to Promote?


16Click-Propensity Products Clicked Most FrequentlyClicks as % of Impressions

26% 23% 21% 20% 18%

18% 16% 15% 14% 13%


17Click-Propensity Products Clicked Most FrequentlyClicks as % of Impressions

26% 23% 21% 20% 18%

18% 16% 15% 14% 13%

Action / InsightAttract new visitors to your site using high

click-propensity products


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For customers at this stage of their journey …


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Purchase Propensity

• 30 products in category (top 12 shown opposite)

• Null hypothesis – random-click, random purchase

• Within-category, each product = 3.3% CTR, 3.3% purchase

• Actual CTR & purchase shown as difference from null-expected


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Purchase Propensityover-viewedunder-sold

under-viewedover-sold


Number of times product was viewed as % of null-expected

Number of times product was bought as % of null-expected


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Purchase Propensityover-viewedunder-sold



Number of times product was viewed as % of null-expected

Number of times product was bought as % of null-expected

Action / InsightAdjust traffic flows through your site to

match product-views with product-purchase-propensity


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Most profit




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Highest Revenue Products

1st 2nd 3rd 4th 5th

6th 7th 8th 9th 10th


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Highest Margin Products

1st 2nd 3rd 4th 5th

6th 7th 8th 9th 10th

low margin high returns heavy discount

highest margin products


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Most profit

Your best customers:1. Have bought recently2. Buy most frequently3. Spend most money4. Recommend you to their friends5. Leave distinctive data trails on their

way to becoming hero customers


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Recency, Frequency & Monetary Value

The “father of customer analytics”

Worked in direct sales (mail-order and ecommerce) for over 30 years

Now facilitates the buying and selling of businesses, guided by their

customer performance

Donald LibeyAvailable free online at http://www.e-rfm.com/Libey/Libeybook2.html

http://www.e-rfm.com/Libey/Libeybook2.html

http://www.e-rfm.com/Libey/Libeybook2.html


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Recency, Frequency & Monetary Value

Recency: The freshness of the relationship between your brand and your customer; indicates when customers slip from active to inactive; the primary measure of business vitality

Frequency: The measure of demand; measured in # orders per period of time

Monetary Value: A measure of customer worth; measured as average order value


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RFM Matrix

6 +

2 to 5

1st order

0 to 6 months 6 to 12 months 12 months +

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

Recency of last order

Freq

uenc

y(o

rder

s/ye

ar)

Monetary value(average order value)

Low = up to £50

Med = £50 to £100

High = over £100


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RFM Matrix

6 +

2 to 5

1st order


low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high


Freq

uenc

y(o

rder

s/ye

ar)

Action / InsightRFM analysis can often be distorted by the categories used for recency, frequency and

monetary value

CHAID can be used to statistically optimise how customers are categorised

http://en.wikipedia.org/wiki/CHAID

Monetary value(average order value)

Low = up to £50

Med = £50 to £100

High = over £100




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RFM Matrix

6 +

2 to 5

1st order


low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high


Freq

uenc

y(o

rder

s/ye

ar)

Hero customers – make them feel loved & cherished – turn them into brand ambassadors

Heroes-in-waiting – test them with hero-treatment

Lapsing heroes – invest to get them back

Lapsing – regular attempts to re-activate

Lapsed heroes – last-ditch big effort to re-activate

Lost cause – try … but don’t hold your breath


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RFM Matrix

6 +

2 to 5

1st order


low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high

low med

high


Freq

uenc

y(o

rder

s/ye

ar)

Hero customers – make them feel loved & cherished – turn them into brand ambassadors

Heroes-in-waiting – test them with hero-treatment

Lapsing heroes – invest to get them back

Lapsing – regular attempts to re-activate

Lapsed heroes – last-ditch big effort to re-activate

Lost cause – try … but don’t hold your breath

Action / InsightInvest different amounts of time and money in the customers that have different value to your

business


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Most profit




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Different Types of Hero

Profile Margin Action

Recency: 26 daysFrequency: 6.5/yrAOV: £124

Revenue=£806# discount items=1Gross margin=£187.5

Regular contact – highlight brand messaging, new products & repeat purchases – added value offers (e.g. gift-wrap) instead of discounts

Recency: 33 daysFrequency: 8.3/yrAOV: £114

Revenue=£946# discount items=14Gross margin=£49.7

Regular contact – highlight bundled offers and cumulative refer-a-friend discounts


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Profit

What is Ecommerce

EcommerceProducts Customers

herocustomers

heroproducts

Right product to the right customer

at the right time

££


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Any Questions?

Address: 38 Park Street, W1K 2JF Website: http://www.ometria.com

Email: [email protected]: +44 20 7016 8383

Twitter: @OmetriaData