Omnichannels During The Pandemic
The Covid-19 Pandemic has changed the way businesses function worldwide. Where to advertise? What content to push? What to market? When to publicize? And most importantly, how does one engage with customers? The answers to each of these questions have changed since the pandemic started.
Customers have become accustomed to making all their purchases from fresh vegetables to high-end electronics online. In-store visits were drastically reduced during the pandemic. Advertising through billboards might no longer be effective. Just a simple Facebook page is not interactive, either. Push-marketing online that happens too often ends up being a let-down. Products without recent decent reviews are not preferred.
In order to survive the pandemic wave, enterprises must be willing to go all out and engage with their customers across various channels. They should be able to link the customer’s in-store and online behaviors together. They should have an online or contact-less method of making purchases and introduce curb-side pick-ups and last mile delivery.
A McKinsey study states that 56% of consumers would prefer the omnichannel route. In order to grow the omnichannel method, it would be beneficial to explore engagement over IoT-Connected Devices.
Outlook For Omnichannels
Creating websites and having social media pages is the basic requirement. Apps, Chatbots and Augmented Reality integration makes customer engagement more relevant. Augmented reality (AR) technology would enable a buyer to use the camera on their smart device to superimpose digital elements onto their physical surroundings.
Having in-store and contactless payment options will help convert the sale lead, regardless of the platform. By 2023, contactless technologies are projected to generate over 220 billion U.S. dollars in transaction value in the US alone.
Data mining and data analysis can be used to identify recommendations. Additionally, a reminder service for repeat buyers will go a long way to ensure a personalized experience. Recommendation engines use algorithms, A/B testing, and sometimes artificial intelligence-powered machine learning to predict and recommend products.
The customer’s timeline of making a choice happens over various platforms. A lead would come from an influencer’s post. The interested buyer will immediately check the website. After consuming information, they would continue without making any actions.
A few days later, an Instagram advertisement in line with the website gets pushed to the buyer. They would then check out competition products or the cost of the same product on a site like Amazon. They might add it to the cart and forget to complete the transaction. A few days later, the same customer would pass a physical store, and it would add to the trust factor. They might follow up by reading reviews (influenced by Search Engine Optimization), before finally converting their order.