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 instead. While merging these two might not have made the least bit of sense until a few decades ago, using AI in retail has emerged to be a prevalent practice for large and small businesses alike!
Using automated systems or AI in retail to run a business has proven to bring the best of machine and man together, making way for endless possibilities of use. Assimilating AI in retail has:
- Decreased error margins
- Better customer experiences
- Data analysis
- Trend forecasting
- Purchase decisions
- Reduced clerical workload
- A smaller workload also enables you to repurpose resources on other important things (strategizing, expansion, etc.)
- Increased efficiency, thereby enabling larger business opportunities
- Easier gateway to expansion
The list goes on as retail AI use cases keep evolving by the day.
With artificial intelligence changing the game for businesses and services across the globe, Qalara identified a few AI systems that prove to be highly effective for retail businesses. The list includes several applications and a bevy of possibilities they come with.
1. Predictive analysis tools
Information is an important asset in today’s time. This AI tool analyzes information and gives output about demographics and choices. Gathering data points from consumer choices, trend shifts, seasons, and a lot of other crucial factors, predictive analysis tools help forecast market behaviors for the business.
This data might be easily available to retailers in terms of customer transactions, sales percentages, and purchase aggregates. The predictive analytics system makes good use of all such digital exhaust data points to give stores 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 gauged 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 stocked up, Inventory management AI tools gather data that can 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 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 experience systems
These tools benefit the most important stakeholders of your business. The customers. Generative AI in retail can better the customer experience facet of your business and efficiently eradicate all the factors in retail that customers today might consider as discomfort.
As businesses expand, manual grievance support becomes far more impractical. So, such generative AI in retail enables businesses to grow without having to lose out on customer relations which is integral to retail store models.
⬝ 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. So, such generative AI in retail enables 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
5. Conclusion
AI in retail now simply means adapting 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.
Through educative blogs such as this, Qalara aims to educate and inform retail store owners on market shifts, hacks, tips & tricks, and newer trends, that can maximize business.
Click here, to browse through our well-researched blog content on the same, and let us know what other topics we can cover that could help you in the comments below!
Leave a Reply