# data[].attributes.headline
need to collaborate and work together as an org more

# data[].attributes.subject
need to collaborate and work together as an org more

# data[].attributes.body
What drives decisions? So many blind spots. E.g., print advertising. What are the right drivers and deploy marketing dollars the best way.

# data[].attributes.headline
something may catch your eye that doesn't catch my eye.  Instagram in our mktg dept helps curate ideas

# data[].attributes.subject
something may catch your eye that doesn't catch my eye.  Instagram in our mktg dept helps curate ideas

# data[].attributes.body
What is driving customer's purchase. what makes her tick. How do we serve that?

# data[].attributes.body
what should you pay attention to vs. not? what are the trends that matter?

# data[].attributes.headline
I appreciate the weekly trend roundup my agency provides that I can share with my team

# data[].attributes.subject
I appreciate the weekly trend roundup my agency provides that I can share with my team

# data[].attributes.headline
Challenge: be both strategic and tactical

# data[].attributes.subject
Challenge: be both strategic and tactical

# data[].attributes.body
Have a plan yet be flexible and able to change.

# data[].attributes.body
Have an instagram board to share on our team

# data[].attributes.body
insta group where they post stuff they find….good curation tactic

# data[].attributes.headline
need to collectively work together to create successful marketing programs

# data[].attributes.subject
need to collectively work together to create successful marketing programs

# data[].attributes.headline
The interviews is consistent with feedback I get from marketers about their challenges and use cases for marketing analytics--Tina

# data[].attributes.subject
The interviews is consistent with feedback I get from marketers about their challenges and use cases for marketing analytics--Tina

# data[].attributes.headline
how do we layer the right data on top of each other? need a tool to bring data together

# data[].attributes.subject
how do we layer the right data on top of each other? need a tool to bring data together

# data[].attributes.body
curating input to stay current

# data[].attributes.body
Free up time from excel and spend more time analyzing data

# data[].attributes.headline
20 different newsletter sources -- how do you aggregate data to spot trends and see what you need to pay attention to?

# data[].attributes.subject
20 different newsletter sources -- how do you aggregate data to spot trends and see what you need to pay attention to?

# data[].attributes.headline
Need to feel like I'm not missing anything

# data[].attributes.subject
Need to feel like I'm not missing anything

# data[].attributes.body
Subscribe to 20 newsletters -- how to stay on top of trends, really know what is going on in the retail industry, sharing out, communication is key

# data[].attributes.headline
Private group (internal marketers) on Instagram

# data[].attributes.subject
Private group (internal marketers) on Instagram

# data[].attributes.body
to store all that inspiration in 1 place.

# data[].attributes.body
what are the "right' tools? and how do you marry the information together?

# data[].attributes.headline
Need to know what to pay attention to (and what to tune out)

# data[].attributes.subject
Need to know what to pay attention to (and what to tune out)

# data[].attributes.headline
how to aggregate all of the different data sources to drive effective marketing

# data[].attributes.subject
how to aggregate all of the different data sources to drive effective marketing

# data[].attributes.body
media mix decisions

# data[].attributes.headline
How do you best layer all the types of data on each other in a meaningfully action oriented way

# data[].attributes.subject
How do you best layer all the types of data on each other in a meaningfully action oriented way

# data[].attributes.headline
ability to understand in store vs digital

# data[].attributes.subject
ability to understand in store vs digital

# data[].attributes.body
need to increase transparency within the team so they can collaborate

# data[].attributes.headline
Media planning agency sends round up, but sales is not seeing those

# data[].attributes.subject
Media planning agency sends round up, but sales is not seeing those

# data[].attributes.body
Communication is key, work together to create programs.

# data[].attributes.body
media agency does a trends roundup each week, very helpful!

# data[].attributes.headline
layer all the data sources on top of each other

# data[].attributes.subject
layer all the data sources on top of each other

# data[].attributes.headline
how do we layer the data on top of each other?  what is the best source of data?

# data[].attributes.subject
how do we layer the data on top of each other?  what is the best source of data?

# data[].attributes.headline
data should be visible to broader org so there is transparency around who the customer is, and there can be a dialogue about how to reach her

# data[].attributes.subject
data should be visible to broader org so there is transparency around who the customer is, and there can be a dialogue about how to reach her

# data[].attributes.body
such a wealth of info, hard to keep abreast of trends

# data[].attributes.headline
Marrying all their information together in a cohesive way

# data[].attributes.subject
Marrying all their information together in a cohesive way

# data[].attributes.body
how do you marry programs you're doing with someone else with what you have?

# data[].attributes.body
not getting siloed in ecomm; understanding how we should and can transcend boundaries

# data[].attributes.headline
still trying to figure out what are the best drivers so they can best deploy their marketing dollars

# data[].attributes.subject
still trying to figure out what are the best drivers so they can best deploy their marketing dollars

# data[].attributes.headline
Priority / Important: Getting everyone aligned

# data[].attributes.subject
Priority / Important: Getting everyone aligned

# data[].attributes.headline
challenge: which marketing trends are worth paying attention to? there is SO much information - where should marketers focus? 

# data[].attributes.subject
challenge: which marketing trends are worth paying attention to? there is SO much information - where should marketers focus? 

# data[].attributes.body
how do they layer the data sources to optimize for customer journey

# data[].attributes.body
Instore and outside of store

# data[].attributes.headline
Our target customer is a Millennial but we focus more on a psychographic vs. a demographic

# data[].attributes.subject
Our target customer is a Millennial but we focus more on a psychographic vs. a demographic

# data[].attributes.headline
challenge: how to marry data together when it comes from different sources? how to layer it in a meaningful way?

# data[].attributes.subject
challenge: how to marry data together when it comes from different sources? how to layer it in a meaningful way?

# data[].attributes.body
purest relationship is via our online assets ... b/c we can test and adjust

# data[].attributes.headline
We don't have free standing stores so our ecommerce site is the ultimate destination

# data[].attributes.subject
We don't have free standing stores so our ecommerce site is the ultimate destination

# data[].attributes.headline
How communicate insights across organization and offer transparency

# data[].attributes.subject
How communicate insights across organization and offer transparency

# data[].attributes.headline
how do we ultimate drive our customers' purchase behaviors

# data[].attributes.subject
how do we ultimate drive our customers' purchase behaviors

# data[].attributes.body
what are the right drivers and how do they deploy their marketing drivers to build sales

# data[].attributes.body
What is happening in store?

# data[].attributes.headline
Don't define customer by demographics alone

# data[].attributes.subject
Don't define customer by demographics alone

# data[].attributes.headline
we focus on pyschographics not demographics which leads use to social data.

# data[].attributes.subject
we focus on pyschographics not demographics which leads use to social data.

# data[].attributes.body
engage via social media channels

# data[].attributes.body
what is happening in store vs. not

# data[].attributes.headline
How aggregate all the data and trends and apply to specific marketing need

# data[].attributes.subject
How aggregate all the data and trends and apply to specific marketing need

# data[].attributes.headline
Take different consumer approaches based on channel, geography

# data[].attributes.subject
Take different consumer approaches based on channel, geography

# data[].attributes.body
social channels are a great way to engage with their customers

# data[].attributes.headline
Challenge: Tie data together and act on it

# data[].attributes.subject
Challenge: Tie data together and act on it

# data[].attributes.body
Hardest part. Getting alignment on who is doing what and who is providing direction. All disparate systems and data set. Refine the process. E.g., use MMM to set budgets. Hard to tell if the MMM is recommending a shift to digital. Where?

# data[].attributes.headline
challenge: what drives buying decisions in store and out of store? and, how to deploy marketing dollars to drive sales across multiple channels? 

# data[].attributes.subject
challenge: what drives buying decisions in store and out of store? and, how to deploy marketing dollars to drive sales across multiple channels? 

# data[].attributes.body
creative with the data

# data[].attributes.body
not just demographics

# data[].attributes.body
online is the purest relationship with the customers b/c they can underrstand exactly what she is doing

# data[].attributes.headline
Need to understand what is driving their target customer - what makes that person tick

# data[].attributes.subject
Need to understand what is driving their target customer - what makes that person tick

# data[].attributes.headline
need a technology to aggregate insights from all their systems/technology. ideal state would live with the data & analytics team

# data[].attributes.subject
need a technology to aggregate insights from all their systems/technology. ideal state would live with the data & analytics team

# data[].attributes.headline
How layer all the data on top of each other

# data[].attributes.subject
How layer all the data on top of each other

# data[].attributes.headline
need a technology to aggregate insights from all their systems/technology. ideal state would live with the data & analytics team - need them to stop doing manual reports to save time

# data[].attributes.subject
need a technology to aggregate insights from all their systems/technology. ideal state would live with the data & analytics team - need them to stop doing manual reports to save time

# data[].attributes.body
scalabilty -- how to craft plan that incorporates from tactical to integrated and strategic plan

# data[].attributes.headline
we need to be more dynamic to what is changing on any given day

# data[].attributes.subject
we need to be more dynamic to what is changing on any given day

# data[].attributes.body
we put the consumer at the heart of what we do

# data[].attributes.body
Behavioral data shows higher engagement from certain sub segments, more narrow. "Fuzzy" now, beh data helps you sharpen

# data[].attributes.body
marketing is a balance of the art and science

# data[].attributes.body
Use the tools that exist to make decisions

# data[].attributes.body
data and analytics vs. planning teams now...but if the analyses can be more turnkey, then things are simpler and able to move faster

# data[].attributes.body
Planning data has been panel based. Now starting to tie in behavioral data. Just starting. 2019 planning.

# data[].attributes.body
Not always done

# data[].attributes.headline
Put the consumer in the heart and center of what they do

# data[].attributes.subject
Put the consumer in the heart and center of what they do

# data[].attributes.body
surprised at how important newsletters can still be important to understanding the landscape

# data[].attributes.body
harmonize the data

# data[].attributes.body
How to they create these including all their different vehicles

# data[].attributes.body
Still is a challenge to tag and layer in different types of data

# data[].attributes.headline
need understanding of what's happening in store vs. online

# data[].attributes.subject
need understanding of what's happening in store vs. online

# data[].attributes.body
Planning / media. Customer insights tool proprietary offered by agency. Media habits, consumption, behavioral characteristics. Bake into where they buy the media, past vs. gaps. What's planned and where that consumer actually is. Model diff scenarios - e.g., digital vs. TV

# data[].attributes.body
multi touch attribution; individual addressable basis -- all in different platform; how to synthesize (not manually)

# data[].attributes.headline
Needs are across board- from very tactical to VERY strategic marketing needs

# data[].attributes.subject
Needs are across board- from very tactical to VERY strategic marketing needs

# data[].attributes.headline
focus on psychographic rather than demographic views

# data[].attributes.subject
focus on psychographic rather than demographic views

# data[].attributes.headline
what are the key things we look at to key into?

# data[].attributes.subject
what are the key things we look at to key into?

# data[].attributes.headline
today synthesizing data is very manual and demands resources - ideally, want to have one quick, seamless way to integrate the disparate insights

# data[].attributes.subject
today synthesizing data is very manual and demands resources - ideally, want to have one quick, seamless way to integrate the disparate insights

# data[].attributes.headline
Want to analyze data- not create the excel files. Need a turnkey effort.

# data[].attributes.subject
Want to analyze data- not create the excel files. Need a turnkey effort.

# data[].attributes.headline
Working: Series of annual media and planning workshops with all key stakeholders

# data[].attributes.subject
Working: Series of annual media and planning workshops with all key stakeholders

# data[].attributes.body
Get everyone together, client and agency. What's planned and running. What oppy can we learn from other markets or look at data differently. Scenario planning. Get the right folks together for a few days and make decisions. Sets the path for the year. Check in regularly. Can see progress over 3 years. Takes time. Sets a baseline Allows for key dialogs.

# data[].attributes.headline
tying data together and getting alignment is the hardest piece

# data[].attributes.subject
tying data together and getting alignment is the hardest piece

# data[].attributes.headline
bringing different data sources and journey points together and activating on those insights is the hardest part

# data[].attributes.subject
bringing different data sources and journey points together and activating on those insights is the hardest part

# data[].attributes.body
No clear owner here in the organization. These are also all disparate systems and data sets.

# data[].attributes.body
getting everyone fully aligned and pointed in the same direction.

# data[].attributes.headline
Single solution to synthesize the data into single source

# data[].attributes.subject
Single solution to synthesize the data into single source

# data[].attributes.headline
behavioral data helps refine targeting/segments

# data[].attributes.subject
behavioral data helps refine targeting/segments

# data[].attributes.body
Would be great to have ONE source that aggregates relevant data and activates upon it.