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11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
11 Steps to Analyze Data for Campaign Performance
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11 Steps to Analyze Data for Campaign Performance

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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, …

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 Redfin

Published in: Marketing, Technology
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  • Goal
    Bring it all together with the help of a specific example

    Sample Narrative
    Here’s an example of how the breadth and depth of data we talked about could influence how a marketer engages a customer. We start with a traditional approach where we target a consumer based on their profile data and some past purchase history.

    So, We have a fictitious consumer we’re calling “Pete”, who is a 35 year old male from Green Bay Wisconsin who recently bought a washer and dryer. Based on this limited set of data we have on Pete, we might conclude that he is a new home owner whose next purchase might be a refrigerator, and so I might target him with an offer for that appliance.

    But if I were able to supplement Pete’s profile data with his web browsing and search history as well as “Likes” from his Facebook profile, that would help paint a more complete picture of Pete. In this case, I would learn that Pete is a Packers fan, and that he’s been pricing comparison shopping 60 inch Samsung televisions. If I were to also factor in the results of last week’s play off games and the weather forecast for the week ahead that shows storms heading into Green Bay, I’d conclude that Pete is in a prime candidate to buy a TV now, and that the best offer would be Free Delivery and Setup of that new TV he wants so that he doesn’t have to deal with the storm that’s coming.
    This is the power of Present Tense Marketing.

    Questions for Audience
    Can you envision a scenario like this being effective with your audiences?
  • In response to how consumers engage with brands today, marketers need to engage audiences in the context of their current need or situation, which we call “state”. Our belief is that If you as a marketer understand and engage your audience in the context of their current state, then you’ll be more relevant and successful with them. Otherwise, it’s likely you’ll be ignored.

    StrongView has developed a methodology call PTM – which reflects the idea that marketers need better insight on the needs and intentions of their customers at specific moments in time, and they need to be able to take action in the context of those insights.

  • NOTE: As you do this, more questions will likely arise that may require you to access more data. Go back to Step 2 (Define) and continue to refine the ideal data set.
  • ANOTHER IMAGE?
  • Demographics (Age, Income, Net Worth, Household Composition, Occupation, Ethnicity, Religion, Voting)
    Residence (Location, County Size, Home Type, Home Value, Length of Residence)
    Purchase Behavior (Product Categories, Frequent Purchases, Lifestyle Segments)
    Interests (Hobbies, Music, Reading, Sports, Travel, Donor, Financial, Diet, Collectibles, Ownership, Shopping)
    Buyer Score—A measure of purchasing activity and capacity
  • Resource putting together buyers and sellers. Have been able to leverage profile data to serve more personal info and proactive – allowing customers / sellers to do price tests – Price Whisperers. Post-sale communication using weather in area – do need to clean gutters?
  • This is the second email in the series – it’s very powerful because it’s the only way we have for users to let us know if they’re buying and/or selling. When they click we send them to dedicated landing pages with our offerings, and we’re able to store that click for future targeting.
  • Often skip to four!
    Begin w/ end in mind!
  • Transcript

    • 1. Proprietary and Confidential | 1 HEADLINE EXAMPLE June 19, 2014 11 Steps to Analyze Data for Campaign Performance
    • 2. Proprietary and Confidential | 2 Welcome! Today’s Topic: 11 Steps to Analyze Data for Campaign Performance Presenter: Catherine Magoffin, Sr. Strategist and Team Lead at StrongView
    • 3. Proprietary and Confidential | 3 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
    • 4. Proprietary and Confidential | 4 How do we get to the Present Tense?
    • 5. Proprietary and Confidential | 5 The Five Foundational Pillars of Success for Present Tense Marketing
    • 6. Proprietary and Confidential | 6 Present Tense Marketing Pillars of Success 1) Acquisition & Revenue 2) Context Awareness 3) Data 4) Efficiency 5) Channel Integration
    • 7. Proprietary and Confidential | 7 Beyond Lifecycle = Present Tense Marketing Present Tense Marketing Single Channel Multi - Channel Cross -Channel Evolving the Dialog to the Constantly Connected Consumer
    • 8. Proprietary and Confidential | 8 Data Drives Contextual Experiences
    • 9. Proprietary and Confidential | 9 Today’s Marketers Need Insight + Action Insight Action FASTER TIME TO INSIGHT UNPRECEDENTED VISIBILITY CROSS-CHANNEL ORCHESTRATION AUTOMATED INTERACTION
    • 10. Proprietary and Confidential | 10
    • 11. Proprietary and Confidential | 11 1. Define the question 2. Define the ideal data set 3. Define what you can access 4. Obtain the data 5. Clean the data 6. Conduct exploratory data analysis 7. Deploy statistical/predictive modeling 8. Interpret results 9. Challenge results 10.Document results and recommendations 11.Outline ongoing data analysis plans The 11 Steps
    • 12. Proprietary and Confidential | 12 Objective: Clearly specify the general and specific question you need to answer. This is the MOST IMPORTANT STEP. Step 1: Define the question
    • 13. Proprietary and Confidential | 13 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
    • 14. Proprietary and Confidential | 14 Step 2: Define the ideal data set Assuming you have access to anything and everything, define the ideal data set to answer the question.
    • 15. Proprietary and Confidential | 15 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.
    • 16. Proprietary and Confidential | 16 Valuable Data Varieties
    • 17. Proprietary and Confidential | 17 Step 4: Obtain the data Go forth and obtain the data in a form you can use.
    • 18. Proprietary and Confidential | 18 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.
    • 19. Proprietary and Confidential | 19 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
    • 20. Proprietary and Confidential | 20 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.
    • 21. Proprietary and Confidential | 21 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?
    • 22. Proprietary and Confidential | 22 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.
    • 23. Proprietary and Confidential | 23 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.
    • 24. Proprietary and Confidential | 24 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.
    • 25. Proprietary and Confidential | 25 Headline Example Proprietary and Confidential Examples of Data Driving Success
    • 26. Proprietary and Confidential | 26 Analysis and Insight Analyzing purchase behavior, demographics, location, interests, buyer scoring and other dimensions to assess the impact on purchases.
    • 27. Proprietary and Confidential | 27 Data Drives a Contextual Welcome Series Day 0 Day 4 Day 8
    • 28. Proprietary and Confidential | 28 41.83% Open Rate 29.00% Disengagement Rate Click-Through Rate 7.68% Open Rate Data Delivers Results
    • 29. Proprietary and Confidential | 29 Real Estate Relevancy
    • 30. Proprietary and Confidential | 30 Gathering Actionable Data
    • 31. Proprietary and Confidential | 31 And, More Actionable Data
    • 32. Proprietary and Confidential | 32 1. Define the question 2. Define the ideal data set 3. Define what you can access 4. Obtain the data 5. Clean the data 6. Conduct exploratory data analysis 7. Deploy statistical/predictive modeling 8. Interpret results 9. Challenge results 10.Document results and recommendations 11.Outline ongoing data analysis plans The 11 Steps Recap
    • 33. Proprietary and Confidential | 33 DATA
    • 34. Proprietary and Confidential | 34 Questions? • Go to www.strongview.com • Whitepapers • Research • Case Studies • Webinars • Expert Advice & Blogs • Twitter: @strongview • Facebook.com/strongview Catherine Magoffin Sr. Strategist and Team Lead cmagoffin@strongview.com 650-226-6826

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