Se ha denunciado esta presentación.
Utilizamos tu perfil de LinkedIn y tus datos de actividad para personalizar los anuncios y mostrarte publicidad más relevante. Puedes cambiar tus preferencias de publicidad en cualquier momento.

11 Steps to Analyze Data for Campaign Performance

7.017 visualizaciones

Publicado el

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

Publicado en: Marketing, Tecnología
  • Sé el primero en comentar

11 Steps to Analyze Data for Campaign Performance

  1. 1. Proprietary and Confidential | 1 HEADLINE EXAMPLE June 19, 2014 11 Steps to Analyze Data for Campaign Performance
  2. 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. 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. 4. Proprietary and Confidential | 4 How do we get to the Present Tense?
  5. 5. Proprietary and Confidential | 5 The Five Foundational Pillars of Success for Present Tense Marketing
  6. 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. 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. 8. Proprietary and Confidential | 8 Data Drives Contextual Experiences
  9. 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. 10. Proprietary and Confidential | 10
  11. 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. 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. 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. 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. 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. 16. Proprietary and Confidential | 16 Valuable Data Varieties
  17. 17. Proprietary and Confidential | 17 Step 4: Obtain the data Go forth and obtain the data in a form you can use.
  18. 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. 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. 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. 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. 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. 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. 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. 25. Proprietary and Confidential | 25 Headline Example Proprietary and Confidential Examples of Data Driving Success
  26. 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. 27. Proprietary and Confidential | 27 Data Drives a Contextual Welcome Series Day 0 Day 4 Day 8
  28. 28. Proprietary and Confidential | 28 41.83% Open Rate 29.00% Disengagement Rate Click-Through Rate 7.68% Open Rate Data Delivers Results
  29. 29. Proprietary and Confidential | 29 Real Estate Relevancy
  30. 30. Proprietary and Confidential | 30 Gathering Actionable Data
  31. 31. Proprietary and Confidential | 31 And, More Actionable Data
  32. 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. 33. Proprietary and Confidential | 33 DATA
  34. 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

×