Redefining the Role of Advanced Analytics
By embedding advanced analytic engines in core applications retailers can optimize every decision and improve every business process. For example, merchandise management can become more tailored, price management more profitable, inventory management more local, and customer engagement more personal.
The study finds a big majority of retailers (57%) are fully aware of this high-performance capability and rate the use of advanced analytics as being a major factor in achieving success. In fact, 20% of these retailers give advanced analytics the highest possible rating of “extremely important.”
However, the business benefit of using advanced analytics today has gone largely unrealized. The reason is only 3% of respondents have actually embedded advanced analytic engines in “most retail functions” and just 30% have them in “many retail functions.”
This means the vast majority of retailers are playing a game of catch-the-leaders in deploying advanced analytic technologies. This is not a game retailers want to lose in today’s fast-paced, turbulent marketplace.
In response, retailers are devoting a large chunk (23%) of their current IT budgets to deploying advanced analytic functions (including hardware, software, staff, consultants and cloud services). Many new projects are currently underway and many others are scheduled to go live in 2020, especially those focused on predictive analytics, which are covered in depth in a following section.
A big majority of retailers say advanced analytic technologies and services play a major role in their organization’s success.
Percent of a retailer’s
IT budget goes toward analytic technology for hardware, software and services including staff, consultants and the cloud.
Role Played by Advanced Analytics in Your Organization’s Success
Only a minuscule number of retailers say that advanced analytic engines have been embedded in most of their organization’s retail functions.
(other factors are
(other factors are
Maturity Level for Using Advanced Analytics
(a major factor)
Level 5 Advanced analytic engines used in most retail functions
Level 4 Advanced analytic engines used in many retail functions
Level 3 Advanced analytic engine used in at least one retail function
Level 2 Currently testing at least one advanced analytic engine
Level 1 No advanced analytic engine used or planned
Bringing Clarity to Business Drivers
Analytics is the fuel that powers the modern retail enterprise. Next-gen capabilities provide real-time insight into current market conditions, shopper behavior and overall organizational health and should be leveraged throughout the business to influence vital decision making. Analytics is a critical tool for every business unit, however some departments because of their increased reliance on data-fueled insight can significantly benefit from advanced analytic capabilities.
Merchandise management and store operations lead the charge with a whopping 56% reporting that those departments would most greatly benefit from advanced analytics. It is no surprise then that the biggest challenges that require investment in analytics to solve are increased price-based competition (63%) and the tight labor market (51%) followed closely by demand forecasting (46%) and demand management (42%).
The rise in off-priced and discount shopping coupled with the online leaders’ ability
to change prices at a moment’s notice, has driven pricing analytics to the forefront.
In addition, the ability to pinpoint demand and meet it requires an advanced analytic merchandising approach that many retailers report they are currently not equipped
Retailers recognize the need to up their merchandising firepower and named predictive analytics for modeling and forecasting (67%) and tightening control over inventory management (66%) as the biggest business opportunities driving analytic technology investment over the next year and a half.
Analytic Technology Investment
Top 5 Major
Over Next 18 Months
Predictive Analytics for Modeling and Forecasting
Dynamic Price Changes at Scale
Tightening Control Over Inventory Management
Developing Personalized Marketing Capabilities
Prescriptive Analytics for Recommending Best Course of Action
Top 5 Major
Over Next 18 Months
Tight Labor Market
More than half of
and store operations as
the departments most
in need of an
Departments That Can Benefit From Advanced Analytics
Building Blocks for High Performance Analytics
When planning is underway for an annual IT budget, smart CIOs assess their company’s technology fitness to meet customer and competitive expectations. During this process they look for key indicators to benchmark against.
Here is a good one to consider: three quarters of retailers (75%) plan to invest in predictive analytics between now and 2021. This could be a game changer in driving sales and profit performance for retailers making the investment.
However, if your organization is not currently up to date or planning to do a major upgrade in predictive analytic technologies within two years then you are in imminent danger of falling behind 75% of the marketplace.
According to the study, retailers are pouring more money and resources into predictive analytic capabilities than any other technology. In a distant second place is price optimization, where 60% of retailers plan to invest by 2021.
Other areas of analytic technology where major investments are flowing include: campaign optimization (the number one investment in 2020), in-store tracking analytics (number three in both 2020 and 2021), and machine learning/artificial intelligence (number two in both 2020 and 2021).
One final area where retailers are investing in advanced analytics to drive sales and improve margins is personalized marketing. The study finds that 65% of retailers say advanced analytic technology is a major factor in optimizing personalization efforts and, of these, 26% say it will be decisive.
Over the next three years (2019 to 2021) three quarters of retailers plan to invest in predictive analytic technologies to increase accuracy of modeling and forecasts. This trend promises to be a game changer for achieving business performance goals on macro (overall) and micro (individual store, channel and SKU) levels.
Nearly two thirds of retailers say advanced analytic technologies are a major factor in optimizing personalization efforts to improve margins and increase sales and of these, 26% say advanced analytic engines will be decisive.
Role Played by Advanced Analytics to Optimize Personalization
(a major factor)
(other factors are equally important)
(other factors are more important)
Top 5 Analytic Tech Investments for Today, 2020 and 2021
1. Predictive Analytics.................
2. Category Analysis....................
3. Price Optimization...................
4. Competitive Analysis...............
5. Prescriptive Analysis................
1. Campaign Optimization.............................
2. Price Optimization.....................................
3. Predictive Analytics..................................
4. Machine Learning/Artificial Intelligence...
5. In-Store Shopper Tracking Analytics........
1. Predictive Analytics..................................
2. Machine Learning/Artificial Intelligence..
3. In-Store Shopper Tracking Analytics.......
4. Price Optimization....................................
5. Prescriptive Analytics...............................
This benchmark study of the analytic maturity of the retail industry draws data from regional and national chains. Data was collected in August 2019 from 61 respondents that hold executive positions within their companies that gives them significant influence on technology strategy, project selection and budgets. Sixty percent of those surveyed hold director positions and the remaining 40% are VP-level executives or higher.
With sales on the rise, savvy retailers are not simply pocketing the increased earnings, but rather reinvesting in their technological prowess. The research field reports that spending on technology has increased 19% on average, with 23% of the overall technology budget allocated to analytics.
Increased 5% - 9.9%
Year-Over-Year Sales Performance
$100 Million - $249 Million
$250 Million - $999 Million
$1 Billion - $4.9 Billion
Revenue for Last Completed 12-Month Period
Direct about a quarter of your IT budget toward analytic technology for hardware, software and services (including staff, consultants and the cloud) to match the industry average of 23%.
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Focus on upgrading your predictive analytic technologies to keep up with 75% of retailers who plan to invest in them in the next three years.
Increase your analytics IQ in campaign optimization (the number one investment among retailers in 2020), machine learning/artificial intelligence (number two in 2020 and 2021), and in-store tracking analytics (number three in 2020 and 2021).
Invest in upgrading your price management capabilities, which 63% of retailers identified as one of their biggest challenges.
Seize business opportunities where other retailers are investing heavily, such as in the specific tactic of using predicitive analytics for forecasting and modeling (67%) and tightening control over inventory management (66%).
By embedding advanced analytic engines in core applications throughout the enterprise retailers can optimize every decision and improve every business process. Three quarters of retailers plan to invest in predictive analytics over the next three years, however we know some will postpone their plans and others will cancel them for various reasons. This will not work out well for these retailers because predictive and prescriptive analytic engines will be a game changer for those who adopt the technologies.
Findings indicate the retail industry continues to grow, with 72% of those surveyed reporting revenue increases over the past 12 months. What’s more, 15% report sales have swelled more than 10%, with just 13% tallying revenue reversals year-over-year.