Data has been a hot top for a number of years and, with GDPR looming, it will continue to be a top priority for businesses. But its not just about wrangling big data, creating a unified or single view of the customer, its about building a data-driven culture. During Effectiveness Week back in November 2016, I spoke at the DMA's “Creating a Data Culture” on the merits and challenges of building effective data-driven cultures within different types of organisations; offering perspectives from working with big brands, agencies and startups.

1. DMA: Creating a Data Culture | 3 November 2016
Pipa Unsworth @peepa @verveiq

3. AGENCIES
We work with digital,
integrated and media
agencies looking to create
or upgrade their customer
engagement and CRM
capabilities.
BRANDS
We work with innovative
brands looking to transform
their business and
modernise their CX/CRM
strategy and data-driven
marketing activities.
3
STARTUPS
We work with pioneering,
early-stage companies that
are seeking to find their
product-market fit, engage
with their audience and
scale their business.
VerveIQ is strategic growth consultancy that helps brands, agencies and startups build meaningful
propositions and valuable relationships that deliver sustainable growth.
www.verveiq.com

4. The most significant culture shift today for marketing teams is
adopting a data-driven marketing approach.
Companies may be thinking differently about their data but are
they acting differently based on what the data is telling them?
We’ll spend the next 20 mins looking at different approaches to
building a data-driven culture and how agencies, brands and
start-ups can all learn from each other.
DATA CULTURES: AGENCIES, BRANDS & STARTUPS

5. CREATING A DATA-DRIVEN CULTURE

6. THE STATE OF PLAY
Many marketers admit their firms has yet to fully embrace the ‘criticality of data’:
§ 35% have a data strategy in place - but it is not embraced by the entire team
§ 23% said that no strategy exists at all
§ 43% have yet to fully embrace data as a critical operational requirement
§ 43% said it was too hard to get the entire organization to agree on a data strategy
Source: http://www.fiercecmo.com/data-analytics/23-businesses-lack-data-centric-marketing-strategy

7. Sour e: http://www.forbes.com/sites/emc/2014/06/06/5-steps-to-a-data-driven-culture
Limited access to data
Difficulties in performing analysis
Lengthy delays inherent in their analytic systems
Data is siloed in multiple departments
Many tools used to generate insights are not intuitive
Insights are often delivered too late, reducing their value
TYPICAL CHALLENGES

8. WHY BOTHER?
Source: http://www.forbes.com/sites/emc/2014/06/06/5-steps-to-a-data-driven-culture
Revenue
year-on-year increase
Efficiency
process cycle times
Costs
reduced operating expenses
27% 83% 12%
7% 39% 1%

9. WHAT DOES GOOD LOOK LIKE?
Data-driven have several things in common:
1. Data-oriented mindsets and to processes to support (and use) KPIs
2. Data is up-to-date, organised and centralised
3. Formal policies that govern data access
4. Data access is widely available but layered
5. Analytics are integrated into innovative and intuitive tools
* Better employee understanding of the value of data & how to apply it to decision-making
* Widespread commitment to backing up ideas with data & measuring outcomes
Source: http://www.forbes.com/sites/emc/2014/06/06/5-steps-to-a-data-driven-culture
Source: http://www.ngdata.com/creating-a-data-driven-culture

10. “NOT EVERYTHING THAT CAN BE COUNTED COUNTS.
AND NOT EVERYTHING THAT COUNTS CAN BE COUNTED.”
Albert Einstein

11. AGENCIES
Winning new clients
Growing client revenues
Managing costs
BRANDS
Digital transformation
Customer experience
Unified customer view
STARTUPS
Getting traction
Getting growth
Getting investment

12. AGENCIES
Winning new clients
Data as a differentiator
Make it easy
(product vs bespoke)
Use stories to
convey data insights
Growing client revenues
Provide dashboards as part
of account management
Platform + People
Add value through
benchmarks
Better work
Humanise the data to
inform the creative brief
Project/campaign
post-mortems
Shared learnings

13. BRANDS
Digital transformation
Using data to change
the status quo
KPIs shared across
the business
Widespread access to
intuitive information
Customer experience
Use data to break down silos
Reward collaboration
Drive results from data
(personalisation)
Unified customer view
Invest in the right tools,
process and people
Standardise taxonomies
Appoint data champions

14. STARTUPS
Soure:
Getting traction
Data vs. gut instincts
Build in tracking
from the start
Automate reporting
(real time dashboards)
Getting growth
Actionable insights
Justify product development
& prioritise roadmap
Keep growing team focused
on performance
Getting investment
Know your numbers
Solid business case
Model growth scenarios
and ROI

15. LEARNINGS
#1 A data culture leverages an organisation’s two greatest assets; its people and its data.
#2 Focus on data that supports decision-making and improving performance.
#3 Humanise the data. People always want to know,“What does this mean for me?”
#4 Find quick wins and champions to get buy-in and demonstrate value.
#5 Visualisation goes a long way. So does automation.
#6 Be patient; culture change takes time.

16. @peepa @verveiq
https://uk.linkedin.com/in/pipaunsworth
pipa@verveiq.com