+353-1-416-8900REST OF WORLD
+44-20-3973-8888REST OF WORLD
1-917-300-0470EAST COAST U.S
1-800-526-8630U.S. (TOLL FREE)


IoT's Promise and Opportunity in Retail

  • ID: 4755323
  • Report
  • June 2018
  • Region: Global
  • IHL Consulting Group
1 of 4

When you start to speak about the potential of IoT in retail the forecasts are all over the map.  Some include anything that has internet connectivity, others only count the view of emerging technology items.  In this study we focus on the IT spend aspect of IoT.  What are retailers spending in certain areas. 

We look at the following:

  • Rightsizing Inventory
  • In-Store Promotions
  • Layout Optimization/Traffic Patterns
  • Real-Time Intelligent CRM
  • Improved Staff Allocation
  • Improved Staff Priorities
  • Energy Management
  • Proactive Equipment Maintenance

But in the midst of this opportunity is also the minefield around customer privacy.  This study talks about best practices, how best to engage consumers to allow for the collection of data that really matters, and what you must do to compel consumers to use the systems.

The researcher looks at trends, barriers, best practices and provide a forecast for each of the technologies included worldwide, the size of the IT opportunities to solve these issues, and the major vendors competing in the space.

The report is designed for use by Retailers, Hardware Providers, Software Providers, Service Providers and others who might have a vested interest in the worldwide retail IT market.

Note: Product cover images may vary from those shown
2 of 4

1.0 Management Summary

2.0 Introduction and Background

3.0 Trends, Drivers, Barriers

4.0 Retail IoT Spend Forecasts

5.0 IT Spend Influenced by IoT

6.0 Retail IoT Use Cases and Forecast
6.1 Rightsizing Inventory
6.2 In-Store Promotions
6.3 Layout Optimization/Traffic Patterns
6.4 Real-Time CRM
6.5 Improved Staff Allocation
6.6 Improved Staff Priorities
6.7 Energy Management
6.8 Proactive Equipment Maintenance

7.0 Major Vendors and Capabilities

8.0 Retail Recommendations

10.0 Methodology

Note: Product cover images may vary from those shown
3 of 4


4 of 4

General 5 step process for all research.

Step 1 – The WorldView IT Sizing Forecast Model is used by the analyst as a leverage as a sizing and forecast tool for over 300 retail Hardware, Software, SaaS and Services categories is leveraged within this research. The analyst has been sizing and forecasting the retail/hospitality market worldwide by solutions for over 10 years. This provides the upper bounds of the market data and total market size.

Step 2 – This is then combined with a Sophia Data Service that tracks over 4,500 enterprise retailers and hospitality providers (with a minimum of 50 locations) in terms of which vendor’s technology a given retailer/hospitality provider has installed, the total lanes/licenses, the timing of those installations and when they are due to be replaced.

Step 3 – If it is part of an end user study, the analysts will do customized web surveys and phone calls with key retail industry leaders several times a year. This data is then leveraged for several different research reports if applicable. When combined with the IT Sizing in step 1, the detailed installs by retailer in step 2, and then the vendor and customer interviews in step 4, the research data comes from several angles to provide the most insight to readers.

Step 4 – The installs and business sizing for each vendor is validated through public records and vendor/channel interviews. Customer service/traction is validated through existing customer interviews and surveys.

Step 5 – All of this is then merged together into a singular view that not only provides total market size, but also market share and scale of difference between vendors.

Where many research companies provide a top level of insight with just the facts, these reports go a bit deeper through the use of cross-tabulation and sources to answer the questions about “So what?”, not just the data, but what it means and how you can react to the market as a result of this data.