Presentation from Mike Baxter on data triangulation in ecommerce - over 10 years of consultancy experience with real-world ecommerce data.
'Data overload' is the term increasingly used to describe the biggest challenge and frustration for online retailers. Tackling this data overload issue head-on is what this breakfast seminar is all about - how to leverage just the data you need to maximise profit.
How to focus on the metrics that matter.
Data-driven strategies for maximising profit.
Matching the right products with the right customers.
Accelerating ecommerce performance.
Beginners Guide to TikTok for Search - Rachel Pearson - We are Tilt __ Bright...
Data triangulation - Driving Profit form Data in Ecommerce
1. Data Triangulation
Driving Profit from Data in Ecommerce
Welcome to Ometria’s Breakfast Seminar
http://www.ometria.com - @OmetriaData
2. 2
The Ometria Team
Ivan Mazour
CEO
James Dunford Wood
COO
Dr. Alastair James
CTO
Edward Gotham
Head of Ecommerce
Victoria Elizabeth
Content Marketing Manager
Alexander Gash
Business Development Executive
http://www.ometria.com - @OmetriaData
Djalal Lougouev
CFO
Tomislav Bucic
Business Development Executive
3. 3
How Ometria Sees Ecommerce
Profit Models
The value of data
Product Models
Integrated
Ecommerce Analytics
Customer Models
Attribution Models
Goal Funnels
2000
2005
http://www.ometria.com - @OmetriaData
2010
2015
2020
6. 6
The Principle of Data Triangulation
Profit
Products
http://www.ometria.com - @OmetriaData
Customers
7. 7
Vilfredo Pareto
1848 – 1923 Born in Paris, Italian national, worked mostly at
University of Lausanne in Switzerland
80% of land is owned by 20% of people
80% of peas come from 20% of pods
The Pareto Principle / The Law of the Vital Few / The 80:20 rule
http://www.ometria.com - @OmetriaData
8. 8
The Pareto Curve – Long Tail
20% of customers account
for 80% of sales
Sales
20% of products
generate 80% of sales
Sales
Customers
http://www.ometria.com - @OmetriaData
Products
10. 10
The Principle of Data Triangulation
Most profit
Where is the sweet-spot in your
business where selling your best
products to your best customers
generates the most profits?
Best products
http://www.ometria.com - @OmetriaData
Best customers
11. 11
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
http://www.ometria.com - @OmetriaData
12. 12
The Principle of Data Triangulation
Most profit
Your best products:
1.
2.
3.
4.
Clicked most often
Bought most often
Highest order revenue
Encourage most return visits
http://www.ometria.com - @OmetriaData
Best products
Best customers
13. 13
The AIDA Model of Customer Journeys
Awareness
Interest
http://www.ometria.com - @OmetriaData
Decision
Action
14. 14
The AIDA Model of Customer Journeys
Awareness
Interest
for customers at this stage
of their journey …
http://www.ometria.com - @OmetriaData
Decision
Action
16. 16
Click-Propensity Products Clicked Most Frequently
Clicks as % of Impressions
26%
23%
21%
20%
18%
18%
16%
15%
14%
13%
http://www.ometria.com - @OmetriaData
17. 17
Click-Propensity Products Clicked Most Frequently
Clicks as % of Impressions
26%
18%
Action / Insight
23%
21%
20%
Attract new visitors to your site using high
click-propensity products
16%
http://www.ometria.com - @OmetriaData
15%
14%
18%
13%
18. 18
The AIDA Model of Customer Journeys
Awareness
Interest
For customers at this stage
of their journey …
http://www.ometria.com - @OmetriaData
Decision
Action
19. 19
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
http://www.ometria.com - @OmetriaData
22. 22
The Principle of Data Triangulation
Most profit
Where is the sweet-spot in your
business where selling your best
products to your best customers
generates the most profits?
Best products
http://www.ometria.com - @OmetriaData
Best customers
25. 25
The Principle of Data Triangulation
Most profit
Your best customers:
Best products
Best customers
http://www.ometria.com - @OmetriaData
1.
2.
3.
4.
5.
Have bought recently
Buy most frequently
Spend most money
Recommend you to their friends
Leave distinctive data trails on their
way to becoming hero customers
26. 26
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 Libey
Available free online at http://www.e-rfm.com/Libey/Libeybook2.html
http://www.ometria.com - @OmetriaData
27. 27
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
http://www.ometria.com - @OmetriaData
28. 28
RFM Matrix
Recency of last order
0 to 6 months
Frequency
(orders/year)
6+
6 to 12 months
low
low
med
high
low
2 to 5
1st
order
low
low
high
med
low
low
high
http://www.ometria.com - @OmetriaData
med
high
med
low
Med = £50 to £100
High = over £100
med
high
Monetary value
(average order value)
Low = up to £50
high
high
med
med
high
high
med
low
med
12 months +
29. 29
RFM Matrix
Recency of last order
0 to 6 months
Frequency
(orders/year)
6+
2 to 5
1st
order
6 to 12 months
low
low
med
high
med
ActionhighInsight
/
12 months +
low
med
high
RFM analysis can often be distorted by the
categories used low recency, frequency and
for
low
low
med
med
med
monetary value
high
high
high
CHAID can be used to statistically optimise how
customers are categorised
low
low
med
med
low
high
med
http://en.wikipedia.org/wiki/CHAID
http://www.ometria.com - @OmetriaData
high
high
Monetary value
(average order value)
Low = up to £50
Med = £50 to £100
High = over £100
30. 30
RFM Matrix
Recency of last order
0 to 6 months
Frequency
(orders/year)
6+
6 to 12 months
low
low
med
high
low
2 to 5
1st
order
low
low
high
med
low
low
high
http://www.ometria.com - @OmetriaData
med
high
med
low
med
high
Heroes-in-waiting – test
them with hero-treatment
Lapsing heroes – invest to
get them back
Lapsing – regular attempts
to re-activate
high
high
med
med
high
high
med
low
med
12 months +
Hero customers – make
them feel loved &
cherished – turn them into
brand ambassadors
Lapsed heroes – last-ditch
big effort to re-activate
Lost cause – try … but
don’t hold your breath
31. 31
RFM Matrix
Recency of last order
0 to 6 months
Frequency
(orders/year)
6+
6 to 12 months
low
low
med
high
med
12 months +
low
med
high
high
Action / Insight
2 to 5
1st
order
low
low
med
low
med
Invest different amounts of time and moneymed
in
the customers that have different value to your
high
high
high
business
low
med
low
high
http://www.ometria.com - @OmetriaData
med
high
low
med
high
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
32. 32
The Principle of Data Triangulation
Most profit
Where is the sweet-spot in your
business where selling your best
products to your best customers
generates the most profits?
Best products
http://www.ometria.com - @OmetriaData
Best customers
33. 33
Different Types of Hero
Profile
Margin
Action
Recency: 26 days
Frequency: 6.5/yr
AOV:
£124
Revenue=£806
# discount items=1
Gross margin=£187.5
Regular contact – highlight brand
messaging, new products &
repeat purchases – added value
offers (e.g. gift-wrap) instead of
discounts
Recency: 33 days
Frequency: 8.3/yr
AOV:
£114
Revenue=£946
# discount items=14
Gross margin=£49.7
Regular contact – highlight
bundled offers and cumulative
refer-a-friend discounts
http://www.ometria.com - @OmetriaData
Good morning, I’m Ivan Mazour the CEO of Ometria, and a very warm welcome to our very first breakfast seminar. Other members of the Ometria team with us this morning include …
In the early days of the web, a hit-counter was a sophisticated analytical tool<click> Then, in 2005, along came Google Analytics. It wasn’t the first analytics solution, but there again, the iPhone wasn’t the first smartphone.<click> Google Analytics enabled ecommerce businesses to get huge value out of data – and it did so by providing a technology toolkit, giving people access to meaningful, action-able data AND ALSO thought-leadership – it, for example, <click> introduced the idea of goal funnels and attribution models to the ecommerce world.<click> One of the reasons we set up Ometria is because we believe the Google Analytics growth curve is flattening out – most of the value it has to offer has already been offered. <click> We believe it is time to ‘jump the curve onto a new growth curve - the Integrated Ecommerce Analytics curve. And, just as Google Analytics did before us, we believe that our success is going to be built on two things – great technology, giving access to meaningful and action-able data and thought-leadership – and it is the thought-leadership that brings us here today. Intro Mike …
Mike’s first slide
Tim Ferris became something of a legend as the creator of the 4-Hour Working Week – however, the story of how he came to live his pretty amazing lifestyle on 4 hours work per week is less well known. Essentially, he analysed his sports supplements business and realised that most of his customers and most of his products were contributing little or nothing to his profits – so he got rid of them.He was running a wholesale business so this was easier than in a retail business but the data is no less valuable