Marketing solutions for B2C-brands · 2018-06-29 · 2 Search by data of loyalty cards, phones and...
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Printed Marketing solutions for B2C-brands Materials for discussion June 2018
Transcript of Marketing solutions for B2C-brands · 2018-06-29 · 2 Search by data of loyalty cards, phones and...
Printed
Marketing solutions for B2C-brands
Materials for discussion
June 2018
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Search by data of loyalty cards, phones and e-mails
Find data about the company’s clients in the Internet
▪ 60% of the clients ▪ 99,8%
accuracy
▪ Automatic search ▪ Securely on
client’s side
Double Data is one of the leading independent digital companies in Russia offering big data solutions for large B2C-companies
Double Data unique technologies allow to…
Restructure data from the open sources Develop strategic solutions for B2C-companies
Unstructured data from the users’ web pages
360о view for each client
27 out of 30 top banks in Russia
Financial industry
Brands and retail companies
3 out of 5 leading consulting firms, 4 out of 5 leading
marketing agencies
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Big data analytics helps companies in solving strategic objectives, but in this paper marketing objectives and solutions are in focus
Sales Product development Marketing
Risk management and operational efficiency
Effective scoring
Decrease in bad debt losses
Fraud prevention
HR automation
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Retail-companies spend >$80 bn per year on marketing
~5-7% is potential market of analytical instruments
B2C-companies have a need to know their clients as good as it is possible to be, because this have a direct correlation with effectiveness of advertising spendings
Standard solutions Solutions of Double Data
Why approach of Double Data is more effective: § Time: less time-consuming § Scale: large volume and detailing of data § Accuracy: work with current clients and their real purchases
Quantitative surveys
Focus groups
Interviews
Collection and analysis of clients’ data from open sources in the Internet
Consumers are sharing personal info and info about their preferences themselves on the Internet for the last 10+ years
Sources: АКАР, TNS
Market analysis
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Merging data between Retail and social networks will enable to generate detailed analytical reports about real consumers of any product
Data merging
Data about consumers (Current, competitor or potential ) ▪ Name / Surname ▪ Town ▪ Date of birth ▪ E-mail ▪ Phone ▪ Social_id ▪ Segment
Data about the identified social networks’ consumers: ▪ Profiles ▪ Subscriptions and likes ▪ Photos ▪ Check-ins ▪ Friends ▪ Publications
Consumers’ segmentation
Depending on business-tasks, presence and volume of sales data, it is possible to identify consumer segments by: ▪ Product categories ▪ Product brands ▪ Frequency of purchases ▪ Quantity of purchases ▪ Average bill ▪ Loyalty ▪ … and other characteristics by
agreement with client
Interactive analytical reports “Dbrief”
and
1 Sample of consumers for analysis DBrief can be formed entirely on consumer list shared by client or on agreed with client criteria, that can be extracted from open data in social networks, also it is possible to mix two of these approaches
CRM Bank Social
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“Dbrief” analytics are designed to increase efficiency of marketing activities
Content of analytical report Expected results for business
Socio-demographic characteristics Increased efficiency of ad creative
Improved targeting
Increased efficiency of promo-activities
Prioritization of partners for co-branding activities
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Selection of optimal set of media channels for ads
Cooperation with the most effective celebrities
Lifestyle
Media consumption
Brand attitude
Attitude to public places and events
Attitude to celebrities
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Analysis of basic social-demographic characteristics help to provide deeper understanding of consumer
SOCIAL-DEMOGRAPHIC ATTRIBUTES AND FACTS
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Example of interactive report1 about social-demographic characteristics of clients’ segment
Consumer type
City type
Тип 1 Тип 2
1 – interactive report is developed in Tableau and enables client to choose different analytical cross-sections as agreed
Age distribution Top 10 regions
Distribution by gender
Average amount of friends
Age median
Choose the segment
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How do my customers spend their spare time?
What are my customers interested in?
What are beliefs of my customers?
▪ Leisure at home ▪ Public places visits ▪ Sport ▪ Active leisure
▪ Animals ▪ Auto and moto ▪ Family ▪ Finance ▪ Gadgets ▪ Healthy lifestyle ▪ Movies ▪ Music ▪ Series ▪ < … 10+ of other categories … >
▪ Alcohol ▪ Tolerance ▪ Social activities ▪ Religion
Question Categories of 1st level Categories of 2nd level Categories of level 3+
categories 100+
categories 300+
categories 50+
Leisure
Interests
Worldview
Interests analyzes helps to describe profiles of consumer segments, improve efficiency of ad creative and targeting
LIFESTYLE
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CASE STUDY: Analysis of interests among segments of football fans and search for triggers to attract new audience to the stadium
Case description Example of analysis
▪ Industry: Sport and leisure ▪ Client: Sport club ▪ Customer base source:
Loyalty cards
▪ Size of customer base: over 90 K
▪ Data type: Personal data (30%), phone (60%), email (100%) ▪ Identified in social
networks: 50% of fans
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Estimation of customer’s media consumption helps to prioritize selection of high-coverage advertising channels for promotion
MEDIA CONSUMPTION
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Internet media TV channels TV shows
Radio stations Pages of popular bloggers
>200 >50 >100
>30 >1000
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CASE STUDY: A search for effective promotion channels to activate consumer’s segments of a large drug-store
Case description Example of analysis
▪ Industry: pharmaceutical retail ▪ Client: large drug-store ▪ Customer base source:
loyalty cards
▪ Size of customer base: 500 K
▪ Data type: personal data (100%)
▪ Identified in social networks:
45% of customers
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Analysis of consumer’s attitude to popular B2C-brands and services helps to select optimal partners for co-branding activities
BRANDS
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Food and Beverages
Electronics and household appliances
B2C-services
Household goods
Beauty and self-care
Auto
Travel
…
…
…
…
…
…
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Children’s goods
Sporting goods
Pet products
Financial services
Computer games
Telecommunication
Internet services
…
…
…
…
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… www
Upon request of the client additional categories can be included for analysis
NOT EXHAUSTIVE
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CASE STUDY: Prioritization of B2C-services considered as partners for different cardholders of a large retail bank
▪ Industry: finance ▪ Client: large retail bank ▪ Customer base source:
cardholder data base
▪ Size of customer base: over 1 mln
▪ Data type: personal data (100%)
▪ Identified in social networks:
65% of customers
Affinity to popular B2C-services among the bank’s customer segments Services Customer segments
149% 114% 133% 107% 154% 122%
136%
87% 126% 116% 90% 111% 113% 95% 118% 108% 105% 119% 99% 84% 130% 99% 138% 107% 93% 80% 73% 88% 37% 77% 88% 57% 68% 84% 67% 79% 70%
173%
Aviasales Skyscanner
OneTwoTrip Booking Airbnb Ostrovok Foodfox Delivery Club Yandex Taxi Uber Gett Delimobil Belka Car 160%
Customers from segment are mostly interested in services for avia tickets purchase
Customers from segment are mostly interested in car-sharing services, unlike and segments
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Case description Example of analysis
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Estimation of customer’s attitude to places and events helps to prioritize public activities connected with them
PUBLIC PLACES AND EVENTS
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Health and beauty
Sports and fitness
Museums and theatres
Parks and public communities
Festivals
Restaurants and bars
Fast-food
Cinema
Concert halls
Education
NOT EXHAUSTIVE
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CASE STUDY: Selection of the optimal events for promo activities for different beer brands
Affinity to music festivals among different beer brands drinkers ▪ Industry: FMCG ▪ Client: beer producer ▪ Customer base source:
promo activities participants
▪ Size of customer base: 700 K
▪ Data type: personal data (90%), email (70%), phones (60%)
▪ Identified in social networks:
55% of clients
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Case description Example of analysis
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Analysis of consumer’s views on celebrities helps to choose the most efficient characters for advertising campaigns
CELEBRITIES
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Musicians Athletes Actors
Categories of celebrities analyzed by Double Data
Politicians TV stars Internet stars
NOT EXHAUSTIVE
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CASE STUDY: Search for the most efficient celebrity to participate in advertising campaign of the clothing brand
▪ Industry: FMCG ▪ Client: large mass market clothing brand ▪ Customer base source:
brand subscribers in social networks’ communities
▪ Size of customer base: over 500 K
▪ Data type: social network profiles
Affinity to celebrities among customers of different clothing brands
Gloomy АК-47, Ptakha and Basta – are for , fancy Timati is for , both of them are
audience is familiar with DOM-2 stars better than anyone
pay attention to fashion bloggers, but the interest of is 2 times stronger
Sergey Zhukov is most preferable by audience. and evenly like Nyusha and Egor Krid. Half brands in the category have interest to Olga Buzova
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Case description Example of analysis
