Smart Retailing
Traditional retail is currently undergoing a seismic shift. One of the fastest evolving competitive markets, it has already witnessed one groundbreaking change - a global move toward digital shopping. The ever-changing sentiments of highly-informed consumers are now forcing a new perspective in the industry.
Manufacturers, distributors, mediators and retailers, across the globe, are adopting AI. Machine Learning, Probabilistic Machine Learning, Clustering, Reinforcement Learning, Collaborative Filtering, Supervised Learning or Neural Networks, etc. are but a few functions of AI that have found applications across various aspects of retail like customer experience (CX), optimizing supply chain, ‘Extreme Personalization’, Planograms, and Micro-targeting/Pricing.
By 2020, 85% of all customer relations will be managed by AI
88% consumers say personally relevant content improves how they feel about the brand.
91% of customers unsubscribe from emails, 44% of direct mail is never opened, 60% of us opt out of mobile push notifications.
Over $280 billion is abandoned in digital shopping carts, every year.
Top 1% your customers are worth 18 times more, than the average customer.
Source - Gartner, Marketing Insider Group, Salesforce, NewsCred, Kahuna, Google, RJ Metrics
Data insights are critical for any successful retail operation. Customer and operational datasets are massive, messy and do not necessarily have a pattern (customer behavior, for instance). The rules are undefined and the success criteria are ambiguous.
Salespeople, call center agents and employees in other customer-facing roles cannot be expected to understand a customer’s entire history and derive their own insights from it in real time.
Automated systems cannot be hand-programmed with rules to handle every conceivable customer history. Delivering a coherent experience across all enterprise touchpoints requires finding patterns across an overwhelming number of data points. This is a prime stomping ground for AI.
AI solutions have found applications in many fronts
Business to Business, Business to Customer, Online Shopping Establishments, Brick & Mortar stores.
Clearly, there are a number of uses of AI and ML solutions that can be leveraged to improve the retail business. Whether your objective is to improve your customer experience, manage your own operations efficiently or upgrade the effectiveness of your marketing, Quadratyx can help build a customized solution, tailored to your specific needs. With our cross-vertical experience, we provide out of the box solutions that could be a game changer for your business.
A detailed description of AI applications and our related services:
-
Customer Experience -
Marketing -
Operations
-
EXTREME PERSONALIZATION
AI-powered personalization will aid in moving from segments to 'audiences of one'- the top 1%, that are worth 18x more than the average. Transitioning from multi-channel to truly cross-channel engagement - the right message on the right channel and on the right path and pace of conversion is assured.
-
CHATBOTS
Chatbots can play the role of personal shopping assistants, helping locate items and additionally provide recommendations based on preferences. Messaging bots can replace the telephone as a media for promotions and information on offers and sale. Chatbots find applications in brick and mortar stores too. They can seamlessly replace the traditional counters.
-
VISUAL SEARCH
Visual commerce provides a quantifiable edge over legacy text based search. AI assisted visual searches have resulted in increased conversion rates (30-50%). Visual searches have applications in B2C & B2B, store-front/user facing interfaces and background operations. AI-powered visual searching can tag, categorize and provide recommendations too, increasing significantly - the overall size of each sale.
-
CUSTOM OFFERS
AI techniques can generate personalized offers that are based on unique interest, history and preference. Analytics can further hone and optimize offers, specific to the high churn customers. Offer optimization ensures increased revenue generation. Optimization is achieved by building a reliable and scalable big data infrastructure and developing sophisticated machine learning models that personalize to each user.
-
real-time pricing analysis
AI-powered personalization will aid in moving from segments to 'audiences of one'- the top 1%, that are worth 18x more than the average. Transitioning from multi-channel to truly cross-channel engagement - the right message on the right channel and on the right path and pace of conversion is assured.
-
INFORMED TARGETING
AI and ML models can focus further on a target group, providing insights such as ‘which stage each buyer is in’, scoring the interest level, based on interaction. Overlaying social media activities provides a section of only high interest customers. Analytics-driven targeted marketing initiatives provide better customer experience through advanced segmentation and predictive modelling techniques.
-
RECOMMENDATION ENGINES
Recommendation systems like PRE-B & PRE-C use machine learning models to record, store and analyze consumer data from a variety of channels like social media, e-commerce websites and internal CRM websites. They function in both B2B and B2C environments and create cross-selling and up-selling opportunities. Solutions are dynamic, configurable, scalable and mobile-enabled.
-
OMNI-CHANNEL AT FULL CAPACITY
AI tools help maximize omnichannel fulfilment capacity by creating a strategy that is flexible enough to meet any customer mix, while controlling the costto-serve. Solutions with real-time sourcing can move returns and at-risk inventory, scale product quickly to meet increased demand. Dynamic solutions can meet any change with immediate scenario planning and map out the fastest, most cost-efficient option in the face of current constraints.
-
EFFICIENCY AT LEAST COST & LABOUR
AI can be leveraged to perform mundane tasks like monitoring void spaces and stock availability. Data transfer activities between retailers, dealers and vendors can also be automated and streamlined. This translates to reduced manual labour and cost benefiting through efficient use of staff time.
-
WAREHOUSING AND INVENTORY
Intelligent forecasting systems can predict demand and supply metrics and assist in data-driven decisions on stocking and product movement. With accuracy levels as high as 90%, models can assist circumvent surplus stocking issues.
-
PLANOGRAMS
AI solutions provide insights into on-floor availability and planogram compliance. Threshold limits for each parameter initiates action from staff. Optimized shelf spacing, based on bestseller products is done in real time.
-
ROUTE OPTIMIZATION
Intelligent planning and route optimization assistants like ARRO ensure on-time deliveries, with minimum to no disruptions. Analytics are handled in real-time and they result in efficient movement of goods with least resource allotment, throughout the supply chain.
