AI in Retail: The Ideal Weapon to Win the Battle for Profitable Growth

Prem Kiran
Founder and CEO
April 10, 2020

The next decade will be more crucial for retailers than ever before, with a significant operational shift from in-store to online and increasing new technology disruption. Obsessed with customer satisfaction and data-centricity, today’s most innovative retailers have given us a lot to learn from. Not only has technology given them a significant competitive advantage, but it has also changed the retail landscape forever.

What are the retail innovators doing right?

Undoubtedly, AI remains perhaps the most significant weapon in this battle. From customer support to product recommendations to delivery tracking – it’s everywhere. With the increasing expectations of personalized experiences, your customers are already enjoying some of the advantages of an AI-enabled experience.

But, how can you deliver that extraordinary experience when even the most trivial age-old back office functions around merchandising, marketing, finance and operational decisions take hours or days to make, and you’re surrounded by a variety of disparate legacy applications, siloed data sources, and a growing army of analysts to make sense of it?

If this is you, then maybe it’s time to harness the power of AI in retail, and benefit from more efficient and effective decision-making process in these areas too? After all, AI is merely a software that mimics and better automates the very tasks that humans have always done only faster and more accurately.

In this blog, we’ll discuss benefits of AI in retail, potential AI use-cases, and most importantly, what it takes for a business to be AI-ready.

Why are retailers turning to AI?

As per a survey conducted by Capgemini, AI in retail could help save $340 billion annually by the year 2022. By automating several processes and operations and making them more efficient, AI in retail isn’t just a stepping stone – using it right could help you ‘leapfrog’ your competitors.

Here are some of the benefits of AI in retail:

Faster optimization and implementation

As a retailer, you’re aware that consumer behavior is dynamic and ever-changing. By the time your analysts are finally able to get you the actionable report you really needed now, hours or days have passed, and the data is already stale. An AI platform can turn hours or days into seconds, allowing you to act fast and stay ahead.

Democratic access to data

What is needed for sales or merchandising is dramatically different than what is needed for marketing, or store-operations, even if there are similar data points. With an AI-powered decisioning platform, every decision-maker, whether in stores, various departments and executive management – can access relevant data explicitly stitched together for them with no technical knowledge required!

Better decisions, right timing

One decision can make or break your business strategy. AI in retail allows you to leverage each and every data point to ensure that the decisions being made by your company’s various leaders will be based on more than just their “gut instinct.” After all, a bad or late decision is a huge, often hidden cost to the company, or worse, an unrealized opportunity gone by.

To put you at the peak of your decision-making efficiency, here’s how AI in retail optimizes critical workflows.

AI transforms retail workflows forever

AI-powered Demand Forecasting

AI in retail can help you accurately predict your sales, item movement, and pricing while considering demand-driving factors such as pricing, promotions, assortment, seasonality, and weather amidst other demand influencing factors. AI-powered demand forecasting can be significantly faster and more accurate than non-AI regression-based approaches.

Intelligent Pricing and Promotions

Evaluate the effectiveness of your pricing and promotions with an awareness of competitor intelligence, item cost changes, and anticipated shopper sensitivity to price or promotional changes. Intelligent pricing and promotions can help to grow profitable revenues by 2-5% in most retail formats.

Market Basket Analytics

Understand the relationship between items. You can ask your AI system questions like “What is the effect of wine sales on cheese?” or “Which other products are most likely to sell when I put hot dogs on sale?” Anticipate how you can increase your sales dramatically with complementary product recommendations.

Production Planning

With AI in retail, you will be able to prepare and produce bakery, deli, or food service items in correlation with actual customer demand for those items by time of day and day of week. This intelligence can materially reduce spoilage by 10-25% by avoiding over-production or production that occurs too early. This same capability can also reduce lost sales attributed to out of stock of prepared foods that customers would have otherwise purchased if they were available.

Assortment Evaluation

Evaluate item additions and deletions based on their contribution and impact to a category or subcategory. Intelligent assortment evaluation allows retailers to understand which product additions will actually create profitable growth while avoiding cannibalization of sales on other items. Poorly performing items can be delisted and removed from the assortment to free up working capital previously tied up in inventory of these items that sell poorly.

Test and Control

When rolling out new initiatives, test them in a set of stores and measure their impact. This capability can be used to evaluate potential promotions or assortment changes. Allow AI to help you test your approach, learn, and fine-tune high-risk decisions to ensure maximum benefits.

How AI-ready is your business?

To answer this question, let’s take a quick look at the Data Science Hierarchy of Needs.

There are six levels to it:

Data Collection + Raw Storage: The first point data that you receive from various sources that get stored in multiple systems, including your point of sale, eCommerce, loyalty, merchandising, marketing, and other systems. Storage of this disparate data is ideally in the cloud.
Data Cleaning + Structured Data Storage: This is where data scientists clean that data, remove junk, and structure it as a strong fundamental for future use. The vast majority of this can be automated with Automatic Machine Learning (AutoML).
Descriptive Analytics: The part of data science that uses the above data to answer the question, “What happened?” This includes standard reports, KPIs, scorecards, and ad-hoc reports. More rudimentary forms of descriptive analytics have been around for some time in legacy business intelligence systems such a reporting or visualization tools. These same systems tend to fall short on diagnostic, predictive, and prescriptive capabilities described below.
Diagnostic Analytics: This is when you go one step further to understand “why it happened.” This includes self-service analytics, causation, segments, aggregates, strategy, and A/B tests.
Predictive Modeling: AI-powered Predictive Modelling allows you to more accurately predict what will happen over a time horizon. This is where Machine Learning and data science contribute.

With all of your various data sources tied to a unified source, you can produce accurate Demand Forecasts and answer questions like “What will be my revenues be in a given category or store location next quarter?” or “What will be my best selling items this year?” Instead of having your analysts build complex algorithms that take hours or days, you can get accurate predictions now in seconds.

Prescriptive Optimization: This is the zenith for businesses. Using AI technologies like AutoML, retailers can get answers to complex questions and obtain insights into the best possible outcomes. What “may or may not” happen with the help of a team of data scientists can be accurately accomplished with Machine Learning.

Say your sales of cheese can increase dramatically when placed with a given bottle of wine..wouldn’t you rather have these insights automatically by having an AI-powered system instantly analyze potentially millions of data points including past customer behavior?

With powerful recommendations and insights just seconds away, you won’t just optimize your resources and maximize your company’s revenue potential – you’ll always be a step ahead.

Data, Data, Data

One key takeaway from the Data Science Hierarchy of Needs is that data is at the heart of everything. When considering the use of AI in retail, you need a solid foundation of data that is cleansed, structured and effectively tracked across different channels.

With great AI, comes great responsibility. Once you’re AI-ready, it’s essential to start on the right foot by ensuring that your business needs and data integrate together seamlessly to produce intelligent insights – transforming your decision-making with the power of data in your hands.

Harness the power of AI-driven decision-making

Instead of the old model where you spend days (or even weeks) waiting for insights from a team of time-starved analysts, consider using a state-of-the-art AI-powered analytics platform like Hypersonix that can empower you with autonomous, predictive and prescriptive insights.

You can reap the following benefits:

Unify data sources into one platform. Using AutoML (Automated Machine Learning), the AI-enabled analytics system can ingest, cleanse, validate, and structure data from various sources in a highly automated fashion.
Discover untapped opportunities with intelligent recommendations. An AI-powered analytics system will not only tell you what happened, but also what you should do about it.
Speed up data processing time from days to seconds. Your AI-Analytics software can put data together in seconds, as compared to days of back-and-forth with your data analytics team.
Save $$$ with an AI-powered analytics software solution that has the equivalent power of scores of data scientists behind every insight. Reduce investment of money, time and effort and optimize your workforce.
Converse with your personal assistant! Powered by billions of data points, your virtual assistant can read and understand human language to engage in a natural conversation with you.

Meet the World’s First AI-Driven Autonomous Analytics Platform

Powering your business decisions with Hypersonix gives you an exceptionally simple and fast and “Google-like” text and voice search experience for your business that is augmented by Jarvix – an embedded virtual decision assistant. Hypersonix helps users measure results, understand root cause on why results are positive or negative, and what to do next.

Since Hypersonix is autonomous, it’s always learning and self-improving by ingesting and processing millions of various data points to deliver better and better recommendations in seconds.

Your next decision can be seamlessly backed by the intelligence you need in seconds, allowing your retail business to deliver personalization and retain customers like never before.