rtificial intelligence (AI) and retail have conventionally been quite contradictory concepts. One flaunts a world replete with unreal possibilities while the other is firmly rooted in reality. Artificial intelligence is the way of the future, taking us closer to a digital world. Retail stores challenge this very notion, valuing real experiences and human contact.
While merging these two might not have made the least bit of sense until a few decades ago, AI in retail has emerged to be a prevalent practice for large and small businesses alike!
Using automated systems in retail to run a business has proven to bring the best of machine and man together, making way for endless possibilities:
- Decreased error margins
- Better customer experiences
- Data analysis
- Trend forecasting
- Informed purchase decisions
- Reduced clerical workload
- Efficient resource management (A reduced workload enables you to repurpose resources, focusing on on areas like strategizing, expansion, etc.)
- Increased efficiency, thereby enabling larger business opportunities
- Easier gateway to expansion
The list goes on as retail AI technology keeps evolving by the day.
With artificial intelligence changing the game for businesses and services across the globe, Qalara identified a few AI systems that have proven to be highly effective for retailers. The list includes several applications and a bevy of possibilities they come with…
1. Predictive analysis
Information is an important asset in today’s time. AI tools focusing on predictive analysis dissect information related to demographics and buyer choices. Gathering data points from consumer choices, trend shifts, seasons, and a lot of other crucial factors, predictive analysis technology helps forecast market behaviors for the business.
This data might be easily available to retailers in terms of customer transactions, sales percentages, and purchase aggregates. Predictive analytics systems make good use of all such digital data points to give businesses a complete context of how the market is and the way your business is reacting to it.
Major factors like sales, inventory, and high-performing SKUs can be assessed and adjusted accordingly.
Applications of predictive analysis-centric AI:
- Forecasting consumer demand
- Sales maximization
- Trend-based purchasing
- Cost adjustments
- Loss minimization
- Marketing strategies
- Cost cutting
- Effective inventory management
2. Inventory management
How you manage your inventory is a major factor in maximizing profits in a retail business. While sales are unpredictable, and stores are expected to be well stocked up all year round, Inventory management AI tools gather data that can help you decide how to efficiently manage a finite storage space and plan purchases accordingly.
Inventory management systems also use a lot of data analytics among other tools. These include maximum automation of inventory and digitized accounts of products.
As it is a highly clerical task, AI ensures that the margin of error is kept near zero. Hence, a large number of retail businesses including the likes of Walmart use such systems for efficient inventory handling.
Applications of inventory management-centric AI:
- Inventory waste minimization
- Anticipating supply chain disruptions
- Scheduling purchases according to predictive sold-out timelines
- Reduced manpower in storehouses
3. Customer service systems
These tools benefit the most important stakeholders of your business – the customers. AI tools can minimize all the factors in retail that customers today might consider as discomfort.
From completely automated customer transactions to reserving purchases online, businesses are happily adapting to tools that contribute to an easier shopping experience.
Applications of customer service-centric systems:
- Cashier-less technology
- Virtual product trials from digital applications (the fashion and beauty industry are known to use such systems)
- Customization facility by taking accurate measurements digitally
- Vibrant & exciting presentation
4. Feedback analysis
Another key customer-relevant tool is the one based on consumer feedback. AI tools that gauge and analyze client feedback help brands and businesses document a plethora of factors that can influence the clients’ buying decisions. They can use this data later to optimize the gaps in their processes that can fetch better conversion rates. The necessary AI tools include virtual assistants and feedback-based digital services.
As businesses expand, manual grievance support becomes far more impractical. Such AI tools enable businesses to grow without having to lose out on customer relations which is integral to retail store models.
Applications of feedback analysis-AI tools
- Effective and faster issue resolution
- Restrategizing marketing & sales
AI in retail now simply means to adapt to the changing world that is advancing towards the digital mode of conducting business and fine-tuning operations. Its foray into the retail world enables businesses to garner insights and get competitive advantages that can help them succeed globally!
The challenge today is not about guessing what to do to make your store stand out, but to invest in the right tools that will help you achieve your end goals faster.
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