Top 10 AI-Driven Strategies for Omnichannel Success
AI integration calls for an adaptive and flexible approach in crafting omnichannel experiences. Each AI application requires a tailored strategy that aligns with its target audience across various channels and platforms.
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In the rapidly advancing technology landscape, there is little scope to draft a concrete strategy for scripting omnichannel success stories. The challenge gets even more pronounced when you try to replicate the famous John Lewis omnichannel strategy in a dynamic domain such as artificial intelligence (AI).
AI, coupled with changing customer preferences, calls for an adaptive and flexible approach, in curating omnichannel experiences. Every use case of AI will have to adopt a unique strategy, aligning with its target audience across all channels and platforms.
Let’s delve into some AI use cases within the consumer business sector to gain deeper insights into the strategies that resonate with the target audience
1. Smart Inventory Movement
Retail store and inventory optimisation, and predictive movement of inventory from warehouses to stores, based on consumption within a pin code, should become BAU (business as usual) for retailers and brands. AI algorithms could predict inventory movement within warehouse management systems and store order management systems and send updates accordingly. The predictive nature of accurately pinning down inventory availability is the key to a retailer’s omnichannel success.
2. Core-Neural Personalisation and Recommendation
In the ecommerce sphere, recommendation and personalisation algorithms have been the key to enhancing customer experiences and driving sales for the last two decades. Of late, video-on-demand consumption and short-form content like reels have almost perfected personalisation algorithms to cater to individual preferences. That said, video commerce is yet to adopt neural models on product detail pages and services detail pages. Core neural models of personalisation for ‘AI on video commerce’ are the way forward.
3. Immersive Reality for Virtual Stores
Omnichannel for consumer businesses has created a new vista for customer experience touch points. Thanks to immersive reality, ‘pick-up’ stores have given way to virtual stores, opening up huge opportunities for AI recommendations.
4. Voice-Powered Purchases
The era of conversational AI, championed by Alexa, Google Home and Siri, has unveiled a true omnichannel use case for voice-based purchases and for organising our daily living in BAU mode. From checking out your work calendar via your voice assistants to booking your flight tickets to ordering your groceries, voice-powered AI has emerged as a prime example of omnichannel adoption, changing the way we interact with technology in our daily lives.
5. Mood Monitors and Sentiment Scanners
Customer feedback is no longer enough; aggregated insights now reveal their mood and sentiments during the purchase process. Monitoring offline and online chatter to augment CSAT (customer satisfaction) and NPS (net promoter score) has now started to emerge as a huge omnichannel AI use case. Neural models of behavioural AI continuously analyse a customer during doorstep deliveries, in-store searches and through sentiments voiced over a phone call.
Leveraging AI-driven omnichannel customer experience (CX), insights has enhanced omnichannel service quality, cross-selling, upselling, and process enhancements, making it an essential game changer in modern business strategies.
6. Digital Signages
The marketing world has been driven by OOH, ATL, BTL and performance marketing in the past two decades. Today, the landscape has transformed with the integration of massive digital signages, which is dynamically adjusted to reflect seasonality, festive periods, and national sentiment through deep tech applications.
AI is trying to track the reach of these signages delivering aggregated insights to the marketeers’ desk. It’s a true offline-to-online play where AI sits at the centre of omnichannel strategy for ATL use cases.
7. Spend Analysers
AI for home communities has started to emerge as a great omnichannel tool. Today, thanks to e-billing, your digital consumption is exposed owing to the consumption of utility services such as gas, electricity and water. Current neural models can predict your consumption patterns and every utility provider can now give you spend analysers which allow the consumers to be aware of their spend patterns.
8. Purchase Affinity Trackers
Today, any brand can analyse your wallet affinity, purchase affinity, and consumption category affinity based on your debit or credit card usage, thanks to core data science-driven AI algorithms. These algorithms have started leading to more curated offerings for every customer.
9. Entertainment-Driven AI Hacks
When you watched a movie at a theatre a musical or a play near you, it didn’t get measured by others. So offline entertainment was purely ringfenced. However, with the adoption of booking apps such as Ticketmaster, lastminute and BookMyShow, the aggregators are using pure AI algorithms to recommend your entertainment affinity and genre affinity. These result in a huge uplift of various content consumption offline purely triggered by online AI models.
10. Ride-hailing persona analysis
Ride-hailing communities of BOLT, Lyft, Uber and OLA have now transcended an offline ride augmented by AI-generated recommendations. It creates a great arcade for omnichannel business. You can order an Uber to the airport and order food from UberEats to ensure that you have your appetite met before you catch a flight. Based on millions of such transactions, a persona and targeted segmentation strategy gets prepared by AI to create accurate recommendations for food and gifts.
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