Digital summit Dallas 2015 - Research brings back the 'human' aspect to insights
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The document discusses the importance of research and analytics in understanding customer needs and driving decision-making in organizations, particularly focusing on the integration of data insights into marketing strategies. It highlights the differences between research and analytics, emphasizing the need for a structured approach to gather and interpret data effectively. Additionally, it outlines key trends, methodologies, and a framework for enhancing research engagement, while stressing the significance of aligning these practices with corporate goals and customer preferences.
Digital summit Dallas 2015 - Research brings back the 'human' aspect to insights
- 1. Intended for Knowledge Sharing only Research is to Human Learning, what Analytics is to Machine Learning Digital Summit Dec 2015
- 2. Intended for Knowledge Sharing only Disclaimer: Participation is purely on a personal basis and does not represent VISA,Inc. in any form or matter. The talk is based on learning from work across industries and firms. Care has been taken to ensure no proprietary or work related info of any firm is used in any material. Director, Insights at Visa, Inc. Enable Decision Making at the Executives/ Product/Marketing level via actionable insights derived from Data. RAMKUMAR RAVICHANDRAN Data Analytics Engineer. Data Architecture & Reporting Solutions to enable Decision Making NIRANJAN SIVARAMAN
- 3. Intended for Knowledge Sharing only Quick recap of what it is Intended for Knowledge Sharing only What makes a Company Iconic?
- 4. WHAT MAKES A COMPANY ICONIC Intended for Knowledge Sharing only 5% Brand 50% What they want before they know it 15% What they need 5% Sales & Service 20% What they want 5% Product Good Great ICONIC
- 5. IN HIS OWN WORDS… Intended for Knowledge Sharing only https://www.youtube.com/watch?v=2U3w5Blv0Lg
- 6. WHY IS RESEARCH NOT AS SEXY AS DATA SCIENCE Intended for Knowledge Sharing only Customers sometimes may not know what they want You cannot satisfy everyone all the time Low Response rates, since no incentive for the Customers What they say vs. what they do Don’t always understand the questions correctly Not easy to scale Legal/privacy issues
- 7. HOW CAN WE HELP? Intended for Knowledge Sharing only Product Sales & Service Brand What they want What they want before they know it What they need Analytics Monitoring A/B Tests Research Reports + Analytics + Research + Testing + Mining Active listening & pattern analysis could reveal unexpected opportunities…
- 8. Intended for Knowledge Sharing only Quick recap of what it is Intended for Knowledge Sharing only Really, how can say so?
- 9. RESEARCH VS. ANALYTICS Intended for Knowledge Sharing only RESEARCH ANALYTICS Cost/Speed of doing it Ease of Analyzing (Structure) Sample Size Type of Insights Attitudinal Behavioral Attribution Inferred Direct Greatest strength? Finding out a hypotheses! Testing the hypothesis Analytics is the yang to the Research’s yin…
- 10. Intended for Knowledge Sharing only Quick recap of what it is Intended for Knowledge Sharing only What can we do about it?
- 11. THE BIG TRENDS Intended for Knowledge Sharing only Cost & ease of storing and analyzing unstructured data going down Need for “Causal” answers vs. “Correlated” insights Increased investment & avenues for getting Customer feedback – Social; Transactional; Voice Text Analytics is maturing and getting integrated into Analytics suite More executive sponsorship and incorporation of metrics like NPS into Corporate goals
- 12. LISTENING AS PART OF ANALYTICS MATURITY CYCLE Intended for Knowledge Sharing only Inform Act Listen Predict Optimize Maturity phases of Analytics Practice ValueAddition Envision Mine
- 13. TREAT CUSTOMER RESEARCH INTERACTION LIKE ANOTHER TRANSACTION Intended for Knowledge Sharing only 1 Record: Store every Research interaction and make it a “Profile” field to be used in predictive modeling Relevant: Customize Research by the type and engagement level of the customers2 UED: Gamify the Research (not just financial incentive), make it easy/contextual/timely/deviced 3 Accountability: If a user feedback went into new product design, “thank and inform them” 4 Quantify: Has the customer satisfaction improved over time? Is it different across product types? Did the Lifetime Value go up? 5 …Analysis & optimization of Research funnel mandatory to improve data and insight collection progressively
- 14. STRATEGIC EXECUTION OF RESEARCH Intended for Knowledge Sharing only • Objective: Exploratory, Target, Monitoring • Target Customers: Engaged/Inactive, etc. • Where and how will it be shown: Focus/Trigger/Deferred, etc. • Success metric & criteria • Minimum sample size needed & time to run • Expected Corporate KPI bucket STEPS Strategy Measure Analyze Planning • Metrics instrumentation & logic(Conversions/Satisfaction/Share of Voice/Brand Awareness/Sentiment & Open/Click/Complete rate) • Dimensions: Engagement Bucket, Devices, Time to Survey, Type of Survey, Geo, Type of Customers, Profile DESCRIPTION • Analysis of Survey response, the insights readout & recommendations (Sizing of opportunity, consistency vs. statistical significance) • Text Analytics on the open commentary section – Entity extraction, theme identification, categorization, pattern identification, time series, structural analysis • Vetting, validation & storyling across various sources. • Additional research – in house/labs focus groups • Feature/Product planning & prioritization • A/B Testing
- 15. RESEARCH METHODOLOGY MATRIX Intended for Knowledge Sharing only Research Methods • Attitudinal vs. Behavioral – What do Consumers say vs. What do they do • Qualitative vs. Quantitative – Direct data gathering (surveys) vs. Implicit data inferences (Logs) • Context for Product Use – Lab vs. close to real life
- 16. RESEARCH METHODOLOGY MATRIX Intended for Knowledge Sharing only Method Description Factors Speed Cost Inference Dev Stage Prototyping Usability Studies Focus Group Surveys & Feedback Pre-Post A/B Testing Create & Test prototypes internally (external, if needed) Standardized Lab experiments – Panel/s of thought-leaders; Employees; Influencers In-depth interviews for Feedback Email/Pop-ups Surveys Roll-out the changes and then test for impact Different experiences to users and then measure delta Quickest (Prototypes) Quick (Panel, Questions, Read) Slow (+Detailed interviews) Slower (+Response rate) Slower (Tied to Releases) Slowest (+Sampling+ Profiling+ Statistical Inferencing) Inexpensive (Feedback incentives) Relatively expensive (+Lab) Expensive (+Time) Expensive (Infra to send, track & Read) Costly (+Tech resources) Very Costly (+Tech +Analytics +Time) Directional +Consistency across users +additional context- Why? +scale +Rigorous (Statistical Significance). *Risk of bad experience. *Risk of bad experience reduced. Ideation Stage Ideation Stage Ideation Stage Ideation/Dev/ Post Launch Post Launch Pre Launch (after Dev)
- 17. Intended for Knowledge Sharing only Quick recap of what it is Intended for Knowledge Sharing only A note on Social
- 18. CONSIDER SOCIAL… Intended for Knowledge Sharing only 1-in-7 are Mobile-Social daily and spend more than half hour a day! Every 1-in-6 page goes Viral! Social is cheap and easy! Personalized! 1-in-5 people in the world are Social!
- 19. …BUT WITH CARE Intended for Knowledge Sharing only Metrics may obfuscate reality Like/follow & forget Not always actionable or relevant (don’t always know fan vs. customer) When it’s good, it’s difficult – lingo, emoticon, dialect, sarcasm Bad data-spam/gaming/bad behavior …it’s mostly reinforcement, not always influential (friend vs. expert)
- 20. Intended for Knowledge Sharing only Quick recap of what it is Intended for Knowledge Sharing only Putting it all together
- 21. MAY PLAY A ROLE ACROSS THE BOARD Intended for Knowledge Sharing only Product Marketing Operations Fraud Strategy 1. Monitoring throughout PLC 2. User Experience issues 3. Personalization – FB Connect 1.Promotion effectiveness 2.Brand/Public Relations initiatives 3.Cross & Up-sell/Campaign designs 1.Platform uptime 2.Conversion 3.Quicker sales 1.CRM Effectiveness 2.Proactive solutions 1.Brand Awareness, Share of Voice 2.Engagement 3.CLV 1.Needs assessment & roadmap 2.Competitive assessments 1.Fraud/gaming 2.Information Security 1.Reduced incoming calls & response times 2.Relational NPS 1.Fraud rates 2.Complex pattern identifications 3.Post incident response 1.Industry and consumer pulse 2.Consumer relationship stickiness Function Possible applications Possible metrics that it can help
- 22. NEEDS FOR IT TO BE SUCCESSFUL… Intended for Knowledge Sharing only 1 Alignment with Strategic Goals and Outcome Focused approach 2 Thought through Research Design –Strategic goals, success criteria, KPIs, initiatives, budget, executive ownership and cross checking with other information sources. 3 Customized by Customer Type (Influencer/Engaged/Inactive/Prospect), context, device & a Strong Value Prop for customers to respond 4 Record & profile users and analyze Research funnel and improve the response rates and quality of feedback and insights. 5 Establish “Text Analytics” practice that translates findings into recommendations with estimated impact sizes that helps prioritization. This also helps in connecting dots across the organization (Analytics, Research, Reports, A/B Testing, etc.) …Executive Support & sponsorship is assumed as a default necessity
- 23. SUMMARY 23 • “Know” that Research & Analytics each complete one half of the picture • “Must have” goals, success criteria & tie up with Corporate KPIs • “Ensure” Value Prop for consumers to respond • “Develop” ‘learn-listen-test-learn’ framework • “Prepare” for ever more increasing personal-mobile-social world and the possibilities & challenges of the new era. Intended for Knowledge Sharing only
- 24. Intended for Knowledge Sharing only Quick recap of what it is Intended for Knowledge Sharing only Appendix
- 25. THANK YOU! Intended for Knowledge Sharing only Would love to hear from you on any of the following forums… https://twitter.com/decisions_2_0 http://www.slideshare.net/RamkumarRavichandran https://www.youtube.com/channel/UCODSVC0WQws607clv0k8mQA/videos http://www.odbms.org/2015/01/ramkumar-ravichandran-visa/ https://www.linkedin.com/pub/ramkumar-ravichandran/10/545/67a RAMKUMAR RAVICHANDRAN 25 https://www.linkedin.com/in/niranjansivaraman NIRANJAN SIVARAMAN