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The Retailer's Guide to Big Data

The Retailer's Guide to Big Data

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Retailers already know how to use customer data to run their brick-and-mortar operations. And they've been digging through reams of website analytics for at least a decade now. But data didn't really get "big" until an explosion in smartphone use and social media addiction, resulting in the need for more agile, relevant marketing The Retailer's Guide 10 BIG DATA Retailers already know how to use customer data to run their brick-and-mortar operations. And they've been digging through reams of website analytics for at least a decade now. But data didn't really get "big" until an explosion in smartphone use and social media addiction, resulting in the need for more agile, relevant marketing. WHAT MAKES BIG DATA SO BIG? 6 BILLION 87% mobile subscriptions worldwide of the world's population f 1.01 BILLION 604 MILLION Facebook users worldwide users log-in monthly from mobile devices 90% 400 MILLION 84 MILLION of the world's data has been created in the past two years! Tweets per day users access Twitter via mobile And Big Data will only get bigger as traffic from smartphones and tablets outpaces traditional devices. Percentage of Web Traffic by 2016: Volume of Digital Content: 7.9 zettabytes equals 9 MILLION galaxies eguals 61% 39% 2.7 18 Libraries of Congress zettabytes wireless wired devices devices 2012 2015 TAKING THE MYSTERY OUT OF BIG DATA In order to leverage Big Data, retailers first need to understand the different types of data generated, and then figure out which information they should collect and store. DATA DETAILS Retailers view Big Data along two different constructs. Structured: Semi-Structured/Unstructured: NAME Address PRODUCT REVIEWS TWEETS DATE OF BIRTH TRANSACTIONS IMAGES, ETC. AMOUNTS "Likes" Loyalty Points, etc. TOP DATA CHALLENGES DATA DISCOVERY FOR RETAILERS How much enterprise data does your company store? O Volume O Variety • Velocity 20% 32.8% 32.8% 24.6% 8.2% 1.6% Don't know Less than 51 to 500 More than 1 500 to 999 50 terabytes terabytes petabyte terabytes 46% How much of the data is unstructured? 24.6% 75.4% 34% Know the Don't know the percentage percentage CHALLENGES TO USING BIG DATA Given that nearly one-third of retailers are in the dark about their available data, it makes sense that silos are the primary hurdle in using this information. 51% 45% 42% 39% 29% Lack of sharing data is an obstacle to measuring marketing ROI Not using data effectively to personalize marketing communications Not able to link data together at the individual customer level Data collected too infrequently or not quickly enough Too little or no customer/consumer data GOALS FOR USING BIG DATA Based on where retailers are investing (or are planning to invest) their resources, they see the value in creating more sophisticated omnichannel marketing efforts. Retailers plan to focus their Big Data initiatives on improving: But they expect to deploy their first Big Data projects in: | 29.6% | 20.4% | 20.4% Merchandising | 62% Marketing Marketing 60% Ecommerce/Multichannel Ecommerce/Multichannel |44% Merchandising 29% | 25% Supply chain Store operations 13.0% Store operations Supply chain 9.3% Operations 14% Operations 3.7% HOW TO DEVELOP A BIG DATA GAME PLAN Keeping up with today's demanding customers and analytics-savvy competitors (it's not just Amazon and Expedia anymore) means putting data at the heart of the retail business. Get started with this five-step plan: Determine the maturity level of your company's 1 approach to Big Data, then implement proof of concepts to guide your ongoing investments. Make sure your data strategy encompasses customer 4 data/master data management, policy and process rules, and data collection usage and sharing. Zero in on business functions for which Big Data can drive the greatest improvement, and create detailed use cases for these projects. Three key areas to investigate first are pricing, segmentation, and marketing effectiveness. Anticipate the hiccups that accompany business process change, helping teams adjust to this new way of incorporating Big Data and analytics into decision-making. 2. 5. 3. Size up your data management and analytics capabilities, identifying gaps and developing the necessary recruitment and training plans. BIG DATA SOURCES: ASSOCIATED PRESS I CENTURYLINK BUSINESS I CISCO ENGINEERING I COLUMBIA BUSINESS SCHOOL/NYAMA I EDGELL KNOWLEDGE NETWORK I IBM I IDC I KEVIN CONLEY I MOBITHINKING I TWITTER I WINTERBERRY GROUP monetate Follow @Monetate en twittery

The Retailer's Guide to Big Data

shared by ColumnFive on Jan 09
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Retailers already know how to use customer data to run their brick-and-mortar operations. And they've been digging through reams of website analytics for at least a decade now. But data didn't really ...

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