Ten years after the term ‘Big Data’ infiltrated the world of marketing, why is it still complex to embed it in the decision-making process? In this webinar, we delve into exploiting data and analytics in favor of your business.
6. August 16, 2018
Big data is like teenage sex:
everyone talks about it,
nobody really knows how to
do it, everyone thinks
everyone else is doing it, so
everyone claims they are
doing it.Dan Ariely
6
7. August 16, 2018 7
53%
Implementing data
and analytics
On being data
informed
On having analytics
solutions in place
Fortune 500 companies
88%
Understand the
importance
91%
Struggle
8. August 14, 2018
Eight years earlier…
8
Promised diamonds from mining data but, it turned out to be
harder than anticipated.
9. August 14, 2018 9
We wanted
Data
driven
culture
Ended up with
Capture data
and prey
culture
11. August 16, 2018 11
Difficult to access - systems require nuanced knowledge of implementations
in previous years
Combining data sets into something meaningful is overly complex and time
consuming
Unknown data, especially by those who should use (marketing, strategy,
creative)
Access is restricted to those with skills / “need to know”
Making decisions from data is a slow, resource intense exercise resulting in
redundant information
Lack of ownership & cost centres to improve. IT? Tech? Analytics? Finance?
Where are we now.
12. August 14, 2018 12
CAN DO SOMETHING WITH
DATA TODAY, DESPITE THIS.
Or, work within
current constraints
13. August 16, 2018 13
• Prove ‘x’ is working
• Engagement
• Acquisition
• Channels
• Messages / offers
• Optimise £ / offers / creative
• Increase efficiency
• ROI
Understand consumers /
Predict behaviour
Change consumers
experiences
Monetisation of dataMeasure performance
Be specific.
Identify what data and
analytics should do.
Difficulty / complexity in deploying increases
• Target consumer who could
churn (retention)
• Prioritise valuable (future)
consumers
• Identify new opportunities
• Aquire the right consumers
• Personalisation (3 Ps)
• Prioritisation
• Personalisation
• Precision
• Experience embedded
• Product /brand placement
• R&D
• Partnerships
• Loyalty
• Cost reduction
14. August 14, 2018 14
• Prove ‘x’ is working
• Engagement
• Acquisition
• Channels
• Messages / offers
• Optimise £ / offers / creative
• Increase efficiency
• ROI
Understand consumers /
Predict behaviour
Change consumers
experiences
Monetisation of dataMeasure performance
Be specific.
Identify what data and
analytics should do.
• Target consumer who could
churn (retention)
• Prioritise valuable (future)
consumers
• Identify new opportunities
• Aquire the right consumers
• Personalisation (3 Ps)
• Prioritisation
• Personalisation
• Precision
• Experience embedded
• Product /brand placement
• R&D
• Partnerships
• Loyalty
• Cost reduction
Difficulty / complexity in deploying increases
15. August 14, 2018 15
Avoid boiling
the ocean.
Then ask. What could
I do today?
16. August 14, 2018 16
Identify one or two
metrics that tell you
something (you
actually need to know).
One. Can you access this easily?
Three. Will this give you useful information, driving action
(observed y, we should do x)
Two. Can you access this weekly?
17. August 14, 2018 17
Identify one or two
metrics that tell you
something (you
actually need to know).
One. Can you access this easily?
Three. Will this give you useful information, driving action
(observed y, we should do x)
Two. Can you access this weekly?
No? Is there something similar that is?
No? Start again
No? Is there something similar that is?
18. August 14, 2018 18
Identify one or two
metrics that tell you
something (you
actually need to know).
One. Can you access this easily?
Three. Will this give you useful information, driving action
(observed y, we should do x)
Two. Can you access this weekly?
No? Is there something similar that is?
No? Start again
No? Is there something similar that is?
All yes?
1. Look weekly / monthly
2. Determine actions which will improve the result
3. Repeat
20. August 14, 2018 20
Know your gaps.
Change consumers
experiences
What do you need to fully deploy data and analytics?
What do you have now?
What could you have in 1 month?
What could you have in 6 month?
Are there dependancies?
Determine who will manipulate the data (analyst)
Somewhere the data can live (i.e. web
analytics platform, email data platform)
A method the data can be shared with
non-analysts (Excel is fine)
Agreed process to make decisions,
implement action, have accountability
3
4
5
2
Identify the data you need to capture1
21. August 14, 2018 21
Identify the data you
need
Direct Entry
Research
WIFI, POS/PIM,
Unique ID
Ad, site, app,
content, MA
programs and
tracking tools
Cookies, Apps,
3rd Party
Linked Social
Accounts (or
scraped)
3rd party
enhancement,exc
hanges, DMPs
etc
Created
BI/AI/ML Tools
Created
BI/AI/ML Tools
Profile,
preferences,
surveys
Time, place,
contents of
purchase or
engagement.
Interests (brand,
offer or in
general) demos,
values, etc.
Surfing
behavior, Geo
location,
hardware and
software
Friends, Interests,
Affinities, etc
Interests,
Behaviors,
Demos,
Cross-Device
Inferred
preferences,
interests,
tendencies,
values, basic
CLTV and
lookalikes
Micro-Target
existing
audiences +
advanced CLTV
and lookalikes
DATATYPESOURCESEXAMPLES
Declared Transacted Device Appended Mined PredictedSocialEngagement
22. August 14, 2018 22
Find someone to
manipulate the data
(analyst)
With the proliferation of data,
there has also been an increase in
the different types of analysts.
Who do you need?
Web Analyst
Statistician
Data Scientist
Data Engineer
Analyst
Data Curator
23. August 14, 2018 23
Make analysts part of
the process.
Change consumers
experiences
Within Ogilvy Outside Ogilvy
All regions have an analytics hub covering the full
skills remit.
Many companies are expanding these analytics
capabilities. However, if they don’t exist, reach out
to Ogilvy
If it’s outside their remit, they can help find the right type of analyst.
25. August 14, 2018 25
SOMEWHERE DATA CAN LIVE
• Pull in only what’s required
• Automate as much as possible
with APIs, FTPs and other scripts
• Clean, process and merge
• Aggregate and manipulate for
reporting
26. August 16, 2018 26
Sharing with non-analysts
While Excel does the job, your analysts may
suggest using something more advanced /
powerful such as Tableau.
27. August 14, 2018 27
TO TURN THIS ALL INTO
ACTION.
Process to
review & make
decisions
Create
accountability in
the greater team
29. August 16, 2018
WEEKLY
29
ONLINE SALES DATA
DATA BASE
DATA PROCESSING OUTCOME
3RD Party
data
vendors
Retailers data
1
2
Other
sources
- Target
- Benchmarks 3
DAILYDIGITAL
CAMPAIGNS
Somewhere the data can live A method the data can be sharedIdentify the data you need to
3 41 2
30. August 16, 2018 30
Process to make decisions +
Accountability
Monday Tuesday
Tasks Topics Attendees
1. Dashboard updated
with previous weeks
data and shared online
1. Review of last weeks tasks (and actions taken / completed / outstanding)
2. Review of dashboard and key take outs & analysis & discuss impact
1. Group agree recommendations & actions for demand generation and content
2. Update demand generation plan
3. Update content and /or write brief
4. Data set up changes/ adjust benchmarks & KPIS
3. Update action plan for following week following analysis recommendations:
1. Owners
2. Expected delivery date
3. Expected impact
4. Brand marketing and activity updates
5. Update tasks and deadlines for the week (outside analytics)
Agency:
• Growth Hacker
• Data Analyst
• Cross-channel lead
• Content lead
• Other specialists as needed
•
Client:
• Digital Lead
• Brand Manager
• Brand Managers
• Sales Manager
5
31. August 14, 2018 31
RESULT =
CONSISTENT
SALES GROWTH
£-
£60,000.00
£120,000.00
£180,000.00
£240,000.00
March '18 Apr '18 May '18 June '18 July '18
Revenue
0%
10%
20%
30%
40%
Apr-22 May-22 Jun-22 Jul-22
30%
29%
38%
£££
33. August 14, 2018
Summary.
33
• Clients (and agency) are still struggling with ‘data’
• Know what you want data and analytics to do
• Start with something tiny you can do without a team supporting you
• Identify your data gaps and what you need in order to achieve your data
and analytics goals (and realistically, when you’ll have them)
• Find the right analyst, integrate them fully
• Create a process to ensure you start using data to make decisions!
34. Do you
want this
deck?
It will be available for download
shortly after the webinar on:
slideshare.net/socialogilvy
Ogilvy staff: It’s also on
The Market!
themarket.ogilvy.com