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Creating a Data Culture
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Transcript of Creating a Data Culture
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DMA: Creating a Data Culture | 3 November 2016
Pipa Unsworth @peepa @verveiq
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AGENCIESWe work with digital, integrated and media agencies looking to create or upgrade their customer engagement and CRM capabilities.
BRANDSWe work with innovative brands looking to transform their business and modernise their CX/CRM strategy and data-driven marketing activities.
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STARTUPSWe 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
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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
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CREATING A DATA-DRIVEN CULTURE
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THE STATE OF PLAYMany 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 strategySource: http://www.fiercecmo.com/data-analytics/23-businesses-lack-data-centric-marketing-strategy
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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
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WHY BOTHER?
Source: http://www.forbes.com/sites/emc/2014/06/06/5-steps-to-a-data-driven-culture
Revenueyear-on-year increase
Efficiencyprocess cycle times
Costsreduced operating expenses
27% 83% 12%
7% 39% 1%
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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
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“NOT EVERYTHING THAT CAN BE COUNTED COUNTS. AND NOT EVERYTHING THAT COUNTS CAN BE COUNTED.”
Albert Einstein
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AGENCIES
Winning new clients
Growing client revenues
Managing costs
BRANDS
Digital transformation
Customer experience
Unified customer view
STARTUPS
Getting traction
Getting growth
Getting investment
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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 partof account management
Platform + People
Add value through benchmarks
Better work
Humanise the data toinform the creative brief
Project/campaignpost-mortems
Shared learnings
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BRANDS
Digital transformation
Using data to changethe status quo
KPIs shared acrossthe 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
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STARTUPS
Soure:
Getting traction
Data vs. gut instincts
Build in trackingfrom 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 scenariosand ROI
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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.