Date post: | 07-Jan-2017 |
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MRMW
Online
Mobile
F2F
Old War vs New War2 2016 Borderless Access
Social media,Mobile online2
3 2016 Borderless Access
Our ApproachOur FindingsConclusionsOur ApproachOur FindingsConclusions
The Hypothesis : Does methodology impact -4P.S: The margin of error for both the options i.e.800 and 1600 is more or less similar. However, the difference is observed while analysing the data at city level 2016 Borderless Access
Accuracy of claimed behaviorThe Target Audience reachedResponse Patterns
Our background research5P.S: The margin of error for both the options i.e.800 and 1600 is more or less similar. However, the difference is observed while analysing the data at city levelOther research papers:
Differences in data captured across methodologies existBut, the impact on the business decision is not significant 2016 Borderless AccessBA Research Papers
We are poor witness to our own behaviorInvoluntary and voluntary lying existsUnderstanding of this behavior is important for clients and researchers
Our Approach: Target Audience6 2016 Borderless Access
Online
Mobile
F2F
Bangalore
JakartaPopulation: General 18+Gender: Male and FemaleCountries: India (Bangalore)Indonesia (Jakarta)
Target Audience6565653535351006565--353519510523070MeterNon-meterBangaloreJakarta
Our Approach: Data Analysed
Primary10 minute quant interview on lifestyle & purchase behavior. Questionnaire conducted via three methodologies
Behavioral DataBenchmarked the data captured against mobile meter data (amongst all 3 methodologies)Analyzed SmartSight data to understand and explain some results
10 minute Research Instrument7 2016 Borderless AccessHousehold & Personal Care GoodsReady to eat FoodMobile accessoriesFinancial transactionsOthers
Demographics
Commute timings
Purchase behaviour
App usage
Household & Personal Care GoodsReady to eat FoodAcross categories including ShoppingUtility appsAge, Gender, IncomeCommute timings for working and studentsApp behaviour
8 2016 Borderless Access
Our ApproachOur FindingsConclusionsOur ApproachOur FindingsConclusions
The Survey Hangover - by methodology9 2016 Borderless Access
F2F
Online
Mobile
Survey TakenNext Survey5 Days10 Days15 Days
15 Days
5 Days
3 Days
Productive field time by Methodology10
F2F
Online
MobileBetween12-5 PM : 65%Post 5:00 PM: 60%Throughout the day (25% each time slot)IndiaProductive Field time
Between 3-8 PM: 70% Men and 50% womenMen: evening and Night (66%)Women: Through out the day (25% in each slot)Throughout the day (25% each time slot)Indonesia
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Target Audience Reached by Methodology11
F2F
Online
Mobile35+ Women: 75%Homemakers & Retired (73%)SEC: SEC A, but lower income bandsWell Distributed on age and gender Working/self employed: 60%SEC: SEC A, but medium to high income bandsWell Distributed on ageWell represented on profession: 62% working/self employedSEC: SEC A, but medium to high income bandsIndiaTarget Audience
Usually older: 45+ YOEmployed: 70%SEC: SEC A, but lower income bandsUsually younger: 25-34 YOEmployed: 80%SEC: SEC A, but medium to high income bandsUsually younger: 25-34 YOBiased towards working population: 84%SEC: SEC A, but medium to high income bandsIndonesia
2016 Borderless Access
Purchase differences Consumer and Household Products12 2016 Borderless AccessBig Basket67%Grofers42%Natures Basket17%Kiranawalla12%Just Eat7%Pepper Tap7%Reliance Fresh Direct3%
Top Apps and install base among Metered Consumers in India
*Data will not add to 100% as multiple product categories have been added: Groceries + Personal Care + Clothing + Electronics + Books + Music
Purchase differences Food Delivery13 2016 Borderless AccessTop Apps and install base among Metered Consumers in India
Zomato37%Foodpanda28%Klik-Eat18%Sajian Sedap17%Toresto17%OpenRice15%Makan di Mana12%MakanLuar11%KFC7%
Customers are moving towards online & mobile purchases Irrespective of methodology
When asked What is the average time spent on phone using various apps14 2016 Borderless Access
Actual Time: 70 minutesPerceived Time: 350 minutes
15 2016 Borderless AccessMondayTuesdayWednesdayThursdayFridaySaturdaySunday
MondayTuesdayWednesdayThursdayFridaySaturdaySunday
12AM1AM2AM3AM4AM5AM6AM7AM8AM9AM10AM11AM12PM1PM2PM3PM4PM5PM6PM7PM8PM9PM10PM11PM
Hrs12AM1AM2AM3AM4AM5AM6AM7AM8AM9AM10AM11AM12PM1PM2PM3PM4PM5PM6PM7PM8PM9PM10PM11PM
Hrs
Online
MobileSurvey response pattern (SmartSight)People take email surveys when they reach work & mobile surveys when they leave work
Response by location Age (India)16
18-2516%44%30%10%26-3524%16%55%5%36-4538%7%34%21%Elsewhere in the galaxy
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44%55%38%
Response by location By Device (India)17
F2F71%--29%--PC/Laptop32%6%55%2%Mobile26%34%19%21% 2016 Borderless Access
Elsewhere in the galaxy
18-2571%55%34%
Without Time/LocationTargeting
With Time/LocationTargeting
Response Density in Sample by Methodology18
Response
Complete
Dropout
F2F
Online
Mobile 2016 Borderless Access
+23%
+63%
+40%
19 2016 Borderless Access
Our ApproachOur FindingsConclusionsOur ApproachOur FindingsConclusions
Conclusions from our research20 2016 Borderless AccessThere are differences that emerge from different research methodologies. But the differences are more significant in
Both impact the field time, cost & effort to achieve a representative sample especially in the case of F2F research.
The target audience reached
The productive field time
Conclusions from our research21 2016 Borderless AccessIf we can target the customer using time & location data via passive metering, the response received is higher and richerIn terms of online & mobile behaviour there are no major differences on stated behaviour vs actual behaviour across demographicsVery clearly, customers are moving online/mobile for many of their day to day activities making a strong case of conducting research where the customer is i.e. Mobile or Online
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2016 Borderless Access22
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