- Inventory Management
AI in retail is creating better demand forecasting. By mining insights from
marketplace, consumer, and competitor data, AI business intelligence tools
forecast industry shifts and make proactive changes to a company’s
marketing, merchandising, and business strategies. This also impacts supply
chain planning, as well as pricing and promotional planning. - Adaptive Homepage –
Mobile and digital portals are recognizing customers and customizing the e-
retail experience to reflect their current context, previous purchases, and
shopping behavior. AI systems constantly evolve a user’s digital experience
to create hyper-relevant displays for every interaction.
- Dynamic Outreach
Advanced CRM and marketing systems learn a consumer’s behaviors and
preferences through repeated interactions to develop a detailed shopper
profile and utilize this information to deliver proactive and personalized
outbound marketing — tailored recommendations, rewards, or content. - Interactive Chat
Building interactive chat programs is a great way to utilize AI technologies
while improving customer service and engagement in the retail industry.
These bots use AI and machine learning to converse with customers,
answer common questions, and direct them to helpful answers and
outcomes. In turn, these bots collect valuable customer data that can be
used to inform future business decisions. - Visual Curation
Algorithmic engines translate real-world browsing behaviors into digital
retail opportunities by allowing customers to discover new or related
products using image-based search and analysis — curating
recommendations based on aesthetics and similarity. - Guided Discovery
As customers look to build confidence in a purchase decision, automated
assistants can help narrow down the selection by recommending products
based on shoppers’ needs, preferences, and fit. - Conversational Support
AI-supported conversational assistants use natural language processing to
help shoppers effortlessly navigate questions, FAQs, or troubleshooting and
redirect to a human expert when necessary — improving the customer
experience by offering on-demand, always-available support while
streamlining staffing.
- Personalization & Customer Insights
Intelligent retail spaces recognize shoppers and adapt in-store product
displays, pricing, and service through biometric recognition to reflect
customer profiles, loyalty accounts, or unlocked rewards and promotions —
creating a custom shopping experience for each visitor, at scale. Stores are
also using AI and advanced algorithms to understand what a customer
might be interested in based on things like demographic data, social media
behavior, and purchase patterns. Using this data, they can further improve
the shopping experience and personalized service, both online and in
stores. - Emotional Response
By recognizing and interpreting facial, biometric, and audio cues, AI
interfaces can identify shoppers’ in-the-moment emotions, reactions, or
mindset and deliver appropriate products, recommendations, or support —
ensuring that a retail engagement doesn’t miss its mark.
10.Customer Engagement
Using IoT-enabled technologies to interact with customers, retailers can
gain valuable insights into consumer behavior preferences without ever
directly interacting with them. Take the Kodi soft interactive tablet for
example – Kodi soft developed a tablet to be used in the restaurant setting
for customers to use to browse menus, order, and play games. Supported by
the IoT Hub and machine learning, this tablet has leveraged consumer data
and behavior trends, allowing companies to increase engagement and
success with customers.
11.Operational Optimization
AI-supported logistics management systems adjust a retailer’s inventory,
staffing, distribution, and delivery schemes in real-time to create the most
efficient supply and fulfillment chains, while meeting customers’
expectations for high-quality, immediate access and support.
12.Responsive R&D
Deep learning algorithms collect and interpret customer feedback and
sentiment, as well as purchasing data, to support next-generation product
and service designs that better satisfy customer preferences or fulfill unmet
needs in the marketplace.
13.Demand Forecasting
Mining insights from marketplace, consumer, and competitor data, AI
business intelligence tools forecast industry shifts and make proactive
changes to a company’s marketing, merchandising, and business strategies.
14.Customized Selections
Taking customer service to the next level, many retailers are using AI to help
them provide unique, personalized experiences for customers. And, there’s
big money in providing such services. “Brands that create personalized
experiences by integrating advanced digital technologies and proprietary
data for customers are seeing revenue increase by 6% to 10% — two to
three times faster than those who don’t,” according to a study by the
Boston Consulting Group.
15.Store Layout & Merchandising Optimization-
Planning your store layout and then optimizing it for the best customer
experience and most sales is an important task for everyone starting a retail
business. AI can help in that aspect.
Rather than simply relying on intuition or your own strategies, you can take
a data-informed approach to your retail store design and setup. Foot traffic
counters and analytics platforms monitor not only how many people enter
your shop but also where and how they move around within it. Placer.ai,
which we include in our guide to determining foot traffic, is one example of
such a tool, but there are many out there that also use predictive analytics
to help you plan your layout and identify upselling opportunities.
16.Staffing & Scheduling
Setting an effective staff schedule is important. You want to ensure you
always have enough personnel to maintain the store and help customers,
but you don’t want to overstaff to the point where employees have nothing
to do or, worse, you’re losing money.
Predictive analytics and AI can help optimize employee scheduling and take
some of the tedious manual processes out of it. When you look for
powerful retail scheduling software, identify options that leverage AI
technology.
Humanity, for example, has two AI features: Auto-Fill Schedule and
Location-Based Break Rules. The former allows retailers to quickly assign
shifts and fill empty slots using custom-built rules to avoid scheduling
conflicts. The latter automatically adds breaks to shifts while maintaining
compliance with state-mandated labor regulations. Find out more about
the platform and its offerings in our in-depth Humanity review.
17.Forecasting & Purchasing
On the note of inventory management, AI is also helpful for improving the
accuracy of a retailer’s forecasting and purchasing. Annual spend on AI
software for demand forecasting is expected to increase significantly, from
$760 million in 2019 to $3 billion by 2023.
More accurate demand forecasting leads to improved purchasing, so you
can maintain optimal inventory levels.
18.Self-checkout & Loss Prevention
Retailers are constantly improving the checkout experience both for the
customer and for loss prevention. AI in self-checkout monitors shopper
activity and alerts staff to cases of suspected theft. The value of
transactions processed by smart checkout technologies will increase from
just $2 billion in 2020 to $387 billion in 2025, Juniper Research estimates.
19.Retail Marketing
AI is also prevalent in retail marketing, especially as it relates to automation.
In fact, AI technologies for marketing campaign personalization grew
114.5% in one year—the fastest-growing use case. Marketing automation
includes email sequences, social media advertising optimization, customer
segmentation, and even personalized promotions and campaigns, among
many other things.
20.Virtual Fitting Rooms
Virtual fitting rooms are creating a footprint in the retail landscape as more
and more businesses adopt the technology. Many of these platforms
include some sort of AI technology. This technology tracks user behavior,
notes which products customers like, and makes predictions and
recommendations based on those data inputs.
21.Sustainability
AI technology can help businesses operate more sustainably in a number of
ways, including:
- Monitoring, controlling, and optimizing energy consumption levels
- Accurately forecast demand for products to eliminate expired inventory
and waste - Reduce emissions through automated supply chain optimization
- Cost Efficiency
Optimized inventory levels reduce carrying costs. AI reduces the need for
costly human labor and allows people to focus on more impactful tasks. On
top of that, automation improves accuracy while mitigating costly errors.
It also provides a rich amount of data that businesses can use to make
better, more informed decisions—with less financial risk. These are just a
few of the ways AI helps retail businesses become more cost-efficient in
their operations.
23.Customer Satisfaction
AI also automates and impacts a lot of customer-facing interactions. Marketing
campaigns, automated email sequences, personalized ads, customer service—
these all stand to benefit from AI, and when the customer wins, so does your
business. - Supply Chain Management
Because supply chain management touches so many areas of the business, there
are many ways you can use AI. You might rely on ordering and routing
automations, or use AI in analytics reporting to see which suppliers are high
performers and which ones could use improvement. - Cross-selling Techniques for Retailers
Find your flagship products or big-ticket items and pair them with directly related
products. These include items that your customers need to enhance the features
they are looking for in your main product. Once you have your list, you can decide
how to place them.
