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Data	Is	Not	Enough:		
It	needs	to	be	turned	into	
insights
“The	key	to	good	decision	making	is	not	
knowledge.	It	is	understanding.	We	are	
swimming	in	the	former.	We	are	
desperate...
Data	vs.	Insight	
Data	=	facts,	either	quan@ta@ve	or	qualita@ve	
	
	
	
	
Data	is	easy,	quick,	one-dimensional	
	
Response	...
Just	geKng	data	is	like	going	to	a	restaurant	and	the	waiter	plops	all	the	raw	
ingredients	of	your	dish	on	the	table.	
Da...
Data	vs.	Insight	
Insight	=	outcome	of	a	process	that	combines	facts	
with	business	knowledge,	observa@on	and	
experience....
How	to	turn	data	into	insights	
1.  Know	the	business	ques@on	you’re	trying	to	answer	
2.  Study	the	business	
3.  Analyze...
1.	Know	the	business	ques@on	you’re	
trying	to	answer	
	
It’s	not	enough	to	just	field	a	study	or	look	up	an	answer	
to	a	q...
2.	Study	the	business	
	
Look	to	understand	the	bigger	picture.		How	
does	the	business	challenge	or	ques@on	relate	to	
th...
3.	Analyze	the	data	available	
	
	Now	you	have	a	pile	of	data	from	either	a	study	you	
fielded	or	secondary	searching.		Rea...
4.	Bring	the	data	to	life	through	
visuals	
	
	
	
It’s	oden	easier	to	see	the	most	relevant	points	
once	is	visualized.		T...
5.	Look	for	themes	in	the	data	
	
	Now	that	everything	is	visual,	it’s	easier	to	see	how	
the	data	relates	to	each	other.	...
6.	Combine	with	other	knowledge	and	
determine	insights	
	
	By	this	point,	the	data	should	be	making	sense.	You	
know	what...
Data	 Insights	 Recommenda@ons	
Data	alone	is	not	enough.		You	have	to	take	it	to	the	next	level	for	it	to	
be	useable.		D...
The	brand	story	your	clients	think	they	have	may	not	be	the	same	one	that	their	customers	are	
thinking.		This	is	where	Lo...
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Data is not enough

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How to move from data to insights to recommendations. Make sure you get more out of your agency or marketing research support.

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Data is not enough

  1. 1. Data Is Not Enough: It needs to be turned into insights
  2. 2. “The key to good decision making is not knowledge. It is understanding. We are swimming in the former. We are desperately lacking in the la;er.” - Malcom Gladwell, Blink
  3. 3. Data vs. Insight Data = facts, either quan@ta@ve or qualita@ve Data is easy, quick, one-dimensional Response Rates Top Two Box Impressions Likes Likelihood to Purchase Page Views Click Through Rates Importance
  4. 4. Just geKng data is like going to a restaurant and the waiter plops all the raw ingredients of your dish on the table. Data Insights vs.
  5. 5. Data vs. Insight Insight = outcome of a process that combines facts with business knowledge, observa@on and experience. Insights are more @me intensive and mul@-dimensional and you have to know the business ques@on and the business in order to create insights.
  6. 6. How to turn data into insights 1.  Know the business ques@on you’re trying to answer 2.  Study the business 3.  Analyze the data available 4.  Bring the data to life through visuals 5.  Look for themes in the data 6.  Combine with other knowledge and determine insights Data Insights
  7. 7. 1. Know the business ques@on you’re trying to answer It’s not enough to just field a study or look up an answer to a ques@on that is thrown at you. You need to know the background. What led to this ques@on or project? How does it fit into the bigger picture? What will you do with this informa@on? All of this informa@on will help you obtain the right facts that will lead to insights. Example: Some of our bank branches are more profitable than others. We want to know if it is the customers, loca@on, or sales team.
  8. 8. 2. Study the business Look to understand the bigger picture. How does the business challenge or ques@on relate to their plans or the industry they are in? Talk to people about the impetus for the request. How does your project fit into the overall strategic plan? What problem is it solving? In other words – do your homework and get smart about the business. Use this informa@on when crea@ng insights. To Do: Read the annual report and exis@ng strategic plans or other background informa@on about the company, industry, and compe@@on.
  9. 9. 3. Analyze the data available Now you have a pile of data from either a study you fielded or secondary searching. Read through it. What is it telling you? If it’s a dataset, run your sta@s@cal analysis on it. Look at significant differences across various groups. All of this analysis will lead to addi@onal ques@ons. Try to find the answers to those ques@ons. Fill your mind with as much data and informa@on as possible. Look at: Addi@onal resources can help the ques@ons that will come up. Google searches, secondary research and past primary research are great here. Also talk to individuals at the company to see if they have answers.
  10. 10. 4. Bring the data to life through visuals It’s oden easier to see the most relevant points once is visualized. This can take many forms from a simple pie chart to a more complex chart incorpora@ng mul@ple data points. The main point here is that the visual accurately shows the data and that it is easy to understand. While words should always be included to explain it, the graph should be able to stand on its own if needed. Think about: What is the best way to help the reader understand the meaning of the data in the quickest and most complete way possible?
  11. 11. 5. Look for themes in the data Now that everything is visual, it’s easier to see how the data relates to each other. Spend some @me looking for similari@es and disconnects among the data points. What does the data tell you? What stories are beginning to form in your mind from the data? What are the most impaceul data points? Do they all relate to one area? Look For: Trends, anomalies and outliers. What’s different, what’s the same? Are there rela@onships? Develop a hypothesis as to why the data looks the way it does and think of ways to test your theory.
  12. 12. 6. Combine with other knowledge and determine insights By this point, the data should be making sense. You know what it is saying. The key now is to combine it with other research, business knowledge and experience to help form the insights. Once you’ve combined some points, think about what it’s really telling you about the business. Now star@ng wri@ng them out. Combine these and add to them. Now you have insights. Tip: Step away from all the work for a bit – go for a walk or sleep on it. When you come back with a fresh mind or new perspec@ve, you might see new things and also determine the most impaceul insights. These should be used to build recommenda@ons.
  13. 13. Data Insights Recommenda@ons Data alone is not enough. You have to take it to the next level for it to be useable. Data to insights to recommenda@ons wins every @me!
  14. 14. The brand story your clients think they have may not be the same one that their customers are thinking. This is where Long & Short of It can help. We use insights based solu@ons to provide clear strategic direc@on. Branding Brand elements connect the internal vision with the external brand expression. Strategic Planning Measurable objec@ves, insights, strategy and tac@cs to achieve the desired outcome. Idea8on Structured brainstorming yielding many ideas and then dis@lled into a short list to be tested. Innova8on Design thinking process, tools, and methodologies to help create new products, system, or solu@ons. Customer Insights Research to determine what customers are thinking, feeling and doing. Research The cornerstone of everything; we employ all qualita@ve and quan@ta@ve methods. www.lasoi.com

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