11 steps to analyze data for campaign performance
DESCRIPTION
To succeed in today's rapidly evolving marketing landscape, you need to understand how to collect, analyze, and leverage the massive and varied amount of data available. A system of data analysis, usable by data novices and ninjas alike, can unlock your campaigns’ performance potential. Hear from StrongView’s Senior Strategist, Catherine Magoffin, as she lays out a step-by-step, soup to nuts process for data analysis, focused on digital marketing performance. Key Topics * Why it is so important to begin utilizing your customer data, today * 11 Steps for harnessing your customer data into action * Real life examples of success from Cooking.com and RedfinTRANSCRIPT
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HEADLINE EXAMPLE
June 19, 2014
11 Steps to Analyze Data for Campaign Performance
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Welcome!
Today’s Topic:
11 Steps to Analyze Data for Campaign Performance
Presenter:
Catherine Magoffin, Sr. Strategist and Team Lead at StrongView
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Today’s Agenda
• Using Data to Drive Contextual, Present Tense Marketing Experiences
• Review of the 11 Step Methodology for Data Analysis
• How Data Translates into Contextual Consumer Experiences and Marketing Results
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How do we get to the Present Tense?
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The Five FoundationalPillars of Success for
Present Tense Marketing
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Present Tense Marketing Pillars of Success
1) Acquisition & Revenue
2) Context Awareness
3) Data
4) Efficiency
5) Channel Integration
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Beyond Lifecycle = Present Tense Marketing
Present Tense Marketing
Single Channel Multi - Channel Cross -Channel
Evolving the Dialog to the Constantly Connected Consumer
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Data Drives Contextual Experiences
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Today’s Marketers Need Insight + Action
Insight Action FASTER TIME TO
INSIGHT
UNPRECEDENTED VISIBILITY CROSS-CHANNEL ORCHESTRATION
AUTOMATED INTERACTION
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1. Define the question 2. Define the ideal data set3. Define what you can access4. Obtain the data5. Clean the data6. Conduct exploratory data analysis7. Deploy statistical/predictive modeling8. Interpret results9. Challenge results10.Document results and recommendations11.Outline ongoing data analysis plans
The 11 Steps
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Objective: Clearly specify the general and specific question you need to answer. This is the MOST IMPORTANT STEP.
Step 1: Define the question
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Any question may be a good question . . .
If it supports your business objectives and program optimization goals. Think about questions relating to:
Channel Engagement Device & OS Activity Location Time Demo-Socio-Psycho-Graphic Purchase History Lifecycle Stage Content Preferences Permissions Source Loyalty levels
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Step 2: Define the ideal data set
Assuming you have access to anything and everything, define the ideal data set to answer the question.
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Step 3: Define what you can access
Realizing you may not have access to every data point desired, what can you get? Think about where it resides, how you can get it and how you can consume it.
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Valuable Data Varieties
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Step 4: Obtain the data
Go forth and obtain the data in a form you can use.
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Step 5: Clean the data
Manipulate the data to be usable in your analysis tools.
Remember to keep a clean copy of the original data you obtained and to describe how you changed it in writing.
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Step 6: Explore the data
Begin to review basics of the data:
• Do you have the data elements needed to answer the question?
• Is it accessible by key segments and attributes, such as:
• Program response• Specific timeframe• Brand or product category• Region• Past purchase or Loyalty Level• Source
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Step 7: Deploy statistical/predictive modeling
Once you have a basic understanding of the data set, begin to describe the process, relationship or trends the data is revealing. What story is it telling? Where necessary, apply statistical modeling techniques to better assimilate the data.
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Step 8: Interpret results
Once you understand the data model or relationship, what does it tell you about the broader question? Can you answer the question now? How does the data answer the question?
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Step 9: Challenge results
Before presenting the results to stakeholders, have a data hackathon of sorts -- try to poke holes in the data and your analysis. Do this yourself and have other colleagues provide their input and challenge the results.
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Step 10: Document results & recommendations
Finally, present your results, interpretation of the data and recommendations to key stakeholders. Decide on next steps and a plan of action.
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Step 11: Document your process
Make sure someone else can come back and consistently replicate the process. Document all steps, save all files and make them available for future reference.
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Headline Example
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Examples of Data Driving Success
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Analysis and Insight
Analyzing purchase behavior, demographics, location, interests, buyer scoring and other dimensions to assess the impact on purchases.
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Data Drives a Contextual Welcome Series
Day 0 Day 4 Day 8
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41.83%Open Rate
29.00%
Disengagement Rate
Click-Through
Rate7.68%
Open Rate
Data Delivers Results
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Real Estate Relevancy
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Gathering Actionable Data
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And, More Actionable Data
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1. Define the question 2. Define the ideal data set3. Define what you can access4. Obtain the data5. Clean the data6. Conduct exploratory data analysis7. Deploy statistical/predictive modeling8. Interpret results9. Challenge results10.Document results and recommendations11.Outline ongoing data analysis plans
The 11 Steps Recap
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DATA
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Questions?
• Go to www.strongview.com• Whitepapers• Research• Case Studies• Webinars• Expert Advice & Blogs• Twitter: @strongview• Facebook.com/strongview
Catherine MagoffinSr. Strategist and Team [email protected]