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Oh shit, Analytics.Huge
October 13, 2015
About Huge.
What we do:We help transform brands and
grow business.
Our Culture:Make something you love.
Hire the best people. Work on incredible projects.
Have fun.
1,200 employees worldwide.Our offices.
Research & analytics.Focus groups & surveys
Ethnography & usability studies
Social listening & trends spotting
Website, social & campaign analytics
Data platforms.
Strategy & planning.Brand planning & marketing
Product strategy & business consulting
Communications planning
Search strategy (SEO, SEM)
Discipline specialists (e.g., CRM, mobile)
User Experience.Content strategy
Information architecture
Interaction design
Mobile experience
Creative.Visual Design
Copywriting & editorial
Campaign development
Mobile, emerging & in-store digital
Technology.Ecommerce
Technical leadership/architecture
User interface development
Mobile & emerging platforms
Social platforms
Rapid & enterprise development
Quality assurance & deployment
Social engagement.Content strategy
Information architecture
Interaction design
Mobile experience
Studio.Photography
Motion
Video creation & production
Animation & illustration
Production
Media.Media planning
Media buying
Campaign management, optimization & analysis
Media partnership development
Program Management.Project management
Planning & roadmap development
Resource management
Risk mitigation
Enough shameless self
promotion.
What is analytics?
What is analytics? Data.
Data is the right experience for the right people
time
place
Data is the right experience for the right people
time
place
ROI
A small piece.
But let’s step back.
1. Business Goals. Why does this experience exist?
2. Objectives. Specific strategies utilized to accomplish business
objectives.
4. Metrics. Numbers.
3. KPIs. How are we doing against objectives?
Good relationships start with good planning.
Measure
Analyze
Socialize
Test
Refine
InsightImpact
Collect.Integrate online and offline data collected throughout
the user journey.
Store.Implement best of breed
data stores and data management platforms.
Model.Execute goal and need
driven segmentation and predictive algorithms.
Target & Personalize.
Optimize the ecosystem to drive
positive KPIs.
Visualize.Creating interface and
user experiences through data.
Communicate.Build a CRM based
communication loop to improve customer value.
Analyze.Drive business insight
based on user behavior.
Syndicate.Expose API to increase
secondary monetization opportunities.
REACH.
LAND.LEAD.
CONVERT.
SCORED RETARGETING
INCREASE TRAFFIC
AttributionMarketing analyticsSEO Optimization
INCREASE ENGAGEMENT
TestingWeb analyticsContent & offer optimization
INCREASE SALES
Lead scoringCRM analytics /data miningEmail testing and optimizationBuy-flow optimization
LOOKALIKE TARGETING
ENGAGE.
PERSONALIZATION
DATA
ANALYTICS
CALL CENTER.
CRM
OUTBOUND EMAIL PERSONALIZATION
3rd PARTY DATA
Help me know.
That’s all well and good Jon…but now I have these guys sitting in my office.
You and your analyst..
(Feed and caring directions for your new pet).
You don’t know what you’re talking about.
We don’t know what we’re talking about.
You?
Us.
Us.
You kind of know what we’re talking about.
We kind of know what you’re talking about.
Find common ground through beauty. We’re all here for the same reason. It is very easy for data folks to prejudge creatives’ decisions as opinion-based and without any empirical basis. Similarly, creative teams look — often rightfully — at analysts as mathematicians who want to optimize the soul out of their ideas. The truth is that analysts that end up at creative agencies are there because they like creativity. Analysts need to remember that they’re there to help create make beautiful experiences, not just a perfectly A/B tested wireframe. And creatives need to remember that optimization need not mean losing their vision any more than a tailor destroys the vision of a beautiful suit: The goal is to create a perfect fit for the end user.
Creative instincts are analytical hypotheses in the making. OK, basic rule: No patronizing each other. Creative teams, instead of asking for a specific analysis, ask a question you need answered and make it clear why it’s so important. Asking for specific analysis constrains in the analyst’s own creative instincts (yes, these do exist). Analysts need to keep in mind that there are no stupid questions in a creative process. You might think that the answer to something is self-apparent: It’s not, or your colleague wouldn’t be asking about it. There are connections between things like design and UX it’s hard for analysts to see because they tend to removed from the creative process. And while it’s an analyst’s job to be objective, it can also make it easy to get all judgmental about the simplicity (or lack there of) of a specific need.
Don’t get pissed off. No one wants to be told that their baby is ugly. That is equally true for both creatives and analysts. It is very easy to be defensive if someone criticizes your work, particularly if that criticism is coming from someone with a fundamentally different worldview. In the early part of projects, we build hypotheses built on instinct and experience. The job of an analytics team is to test those ideas through a formalized process (we do love a good process formalization). Sometimes those hypotheses need modification in order to adhere to user needs that might be unanticipated. It’s important to give yourself the allowance to incorporate challenges to your core assumptions. Analysts need to keep in mind that data does always tell the full story. Not even close. Your ideas and analysis are no more precious than those of your creative peers. Accept that the role of creative teams is to take your analysis into account alongside multiple other inputs. My rule of thumb is that typically one-half to one-third of my most brilliant analysis will ever be used in a specific project. Yeah, it sucks to spend hours in your data-crunching package of choice and then find out that much of it gets left on the cutting-room floor. You know what? That happens to creatives, too.
Three people.
28 people.
3 years ago. Now.
What happened?More clients.New types of work.Deeper relationships.More offerings.
Relationships not projects.
Data Science offerings.
Digital & media analytics: Planning, implementing, using, reporting.
Personalization & Targeting: Planning, platforming, algorithms, execution, testing.
Enterprise data systems:Strategy, platforming, analysis, visualization, modeling.
Some lessons from mistakes.
Unless you are super cheap analytics cannot be sold as a stand
alone service.
Shoot big to get little.
Your clients need to know that no one owns data.
A lot more money is made on strategy than analysis.
Someone will call you on your bullshit. But not that often.
But seriously, it’s a big deal.
On to the discussion....