Location-Based Analytics Yield Customer and Inventory Insights

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Location-Based Analytics Yield Customer and Inventory Insights

By Margot Myers, Director, Global Marketing & Communications, Platt Retail Institute - 10/19/2015
Evolving consumer digital shopping behavior is driving retailers to seek consistency in their operations across channels. A new research article from the Platt Retail Institute, sponsored by Tyco Retail Solutions, explains how changes in shopping behavior are driving retailers to adopt integrated information platforms to become data-driven organizations.
 
Digital Shopping
 
Consumer expectations for an immersive, digital, omnichannel shopping experience are a direct result of information accessibility, which has had a major impact on shopping behavior. Digital devices, regardless of where accessed, provide a wealth of instant access to price and product information, product reviews and demonstrations, and the ability to make purchases and track orders instantaneously. Wherever a retailer is communicating with customers, consistency in the brand presentation and shopping experience is expected.
 
Recognizing the implications and opportunities, retailers are making investments to integrate systems to support changing consumer behavior. Technology advancements are enabling the collection and processing of vast amounts of information to produce analytics for competitive advantage.
 
Defining and Valuing Information
 
Before implementing an integrated information platform on the path to becoming a data-driven retailer, a common understanding of what information is and how it will be valued is instructive.
 
Information provides an organization with a goal-seeking system to decide and/or control. This definition ties the achievement of established objectives to the process of selecting from among available alternatives and determining the necessary actions required to achieve an objective.
 
In the abstract, the value of information (VOI) may be thought of as its economic contribution, but it should be distinct from a determination of the return on an investment in information technology. One approach to the VOI that is flexible in its consideration of a company’s objectives seeks to define four value dimensions, including expense containment, process improvement, customer advantage, and talent leverage, and then link them to specific outcomes.
 
Retail Analytical Objective
 
The retail analytical objective is to make better operating decisions and improve the shopping experience through the intelligent use of information. This occurs by providing management with information that supports the best possible decision based on numerically measurable business outcomes that are consistent with the goals and objectives of the organization.
 
Value of Analytics
 
Research supports the general proposition that an investment in building an integrated data platform capable of producing analytical insights can justify such an investment. For example:

Research conducted by McKinsey and the Massachusetts Institute of Technology found that companies that inject big data and analytics into their operations outperform their peers by 5 percent in productivity and 6 percent in profitability.

An IBM study from 2014 found that organizations using big data and analytics within their innovation processes are 36 percent more likely to beat their competitors in terms of revenue growth and operating efficiency.
     
It has been found that a retailer’s financial performance will increase as its
customer analytics deployment increases, and that retailers will benefit more
from increases in customer analytics deployment than other industries.
 
Customer and Inventory Location-Based Analytics
 
Advancements in technology have improved the ability to collect consumer location-based and inventory location-based data. When combined with other information, the analytics produced provide a retailer with a broad range of in-store customer and operational insights, analogous with those that have been available to online retailers for some time. This knowledge provides a retailer with a more granular level of store visibility.
 
Customer location-based analytics yield detailed information regarding store traffic, store traffic patterns, in-store location dwell time, store penetration rate, repeat visits, sales conversion and productivity, and staff availability. Inventory location-based analytics have many uses, include creating upsell opportunities and addressing issues surrounding inventory distortion, among other things.
 
Online – In-Store Behavioral Bonding
 
Considerable research has been undertaken to aid in understanding consumer shopping behavior, though generally it has been focused on a specific channel, such as online or in-store. Little has been directed at understanding the influence of an online stimulus, such as advertising, on in-store behavior. This is important, as more than fifty percent of in-store purchase decisions are influenced by online behavior. The Research Article introduces the Online – In-Store Behavioral Bonding Model, which aligns online and in-store shopping behavior. The Model represents an important first step in understanding how online messages impact in-store purchases.
 
To learn more, download the full PRI Research Article, “Customer and Inventory Insights Generated by Location-Based Analytics, and the Introduction of an Online – In-Store Behavioral Bonding Model” here.
 
Copyright Platt Retail Institute 2015. All rights reserved. See the entire PRI Resource Library at www.plattretailinstitute.org/library.