6 MINS READ
Retail faces great macroeconomic pressures
Stockouts, price bumps, and delayed fulfillment.
Every holiday season, we hear the same stories. Clearly, innovations at the front side of sales, like same-day delivery and faster site performance, are not adequately supported by behind-the-scenes retail operations.
Retail is facing greater macroeconomic pressures now than ever before. With inflation in the UK and the US touching a 40-year high, shoppers are becoming careful about spending. As a result, demand levels have become unpredictable, margins are under threat, and businesses face the risk of losing customers to competitors. Business leaders are, therefore, focusing on recalibrating cost structures to maintain profit margins this holiday season.
Retailers need to shift from XLS and email-driven core business workflows (with 30-50% processing taking place outside IT systems) to automated and intelligent workflows. They should integrate functional silos and create a unified value chain and data foundation and reimagine core retail processes to offer better experience, not just for consumers but also for business teams and store associates.
With intelligent process automation (IPA), the gains will be big—30-50% increase in operational efficiency besides reduced costs, improved customer service and experience, and higher sales.
Intelligent automation: A strategic lever
IPA can build enterprise agility and help retailers respond in real time to consumer trends by quickly onboarding suppliers and products or renegotiating vendor contracts when cost increases.
Retailers can shape demand with promotions to take advantage of their inventory. Further, if they anticipate a delay in delivery, they can proactively inform customers and send offers to avoid a negative experience. End-to-end automated workflows will simplify tracking and compliance, while AI-ML will offer immense potential to predict and respond to emerging scenarios, consumer trends, and competitor moves in real time.
Six key areas for operating the intelligent way
With IPA, retailers can maximize sales and profit margins by turning core operations from mundane to magical.
Pricing and promotions
With a pricing cycle of 40 days and promotion cycle of 20 weeks, it’s impossible to respond to market shifts and competitor moves in real time. However, with AI, retailers can respond with agility. Pricing managers have access to dashboards that provide real-time and historical views of price changes, competitor prices, and margin impact due to changes in cost price. Before rolling out price changes, AI validates them for pricing policy compliance such as floor pricing, spiral pricing, and minimum or maximum margins required. Retailers can also set better initial prices for newly sourced items. More significantly, it frees up time for experimenting with different pricing strategies.
About 72% of promotional campaigns fail due to lack of real-time data integration. AI enables end-to-end omnichannel promotion, supplier-inclusive promotions planning, and automated price reverts. Retailers can also run short-term and short-turnaround promotions to drive demand for products with high inventory.
Product and supplier onboarding
As retailers diversify sourcing, they not only have to onboard suppliers quickly, but also make them visible across the enterprise. The only way to achieve this is with a single-window application that can liaise with the multitude of apps it abstracts. This also makes a great case for AI to be meshed with everyday merchandising operations such as product onboarding. AI models available today can extract a lot of metadata, along with peripheral information, from a single image. For example, an image of a model wearing a garment, and a product title is all that is required for AI to generate alternative colors of the garment, search tags, a clean background image, and product description. This can be seamlessly integrated into the product onboarding workflow, which can drastically reduce the time to market.
Digital experience management
A broken link or long image loading time is enough to deflect customer interest. With AI, retailers can be custodians of customer experience all the way from awareness to advocacy. AI can improve product discovery through better site search with product enrichment, keyword extraction, contextualizing faceted search, and real-time SEO calibration. For CXOs and digital marketing officers dealing with several moving parts at once, a digital command center can provide a dashboard view of critical digital operations such as automated alerts on high bounce rates, low traffic, failed orders, fraud, and fulfillment delays.
With retailers vying with each other to discover Google’s secret sauce, SEO is an area that is ripe for automation opportunities to manage meta tags and deploy AI for content tagging and indexing. Quality content (both product and non-product) is, in fact, a big driver in the customer decision-making process.
Partnering with influencers is already a big trend in mainland China, and the rest of the world is expected to catch up in time for the holidays. Brands usually engage with influencers for social media posts, video reviews, and live shopping events. Marketing by association is, however, not necessarily a good thing, as the organizers of the ill-fated Fyre festival found out. The event lacked planning and transparency, resulting in a huge lawsuit against the organizers. The message is clear. Brands need to go beyond followers or views and look at user engagement and conversions.
A vast majority of customers admit holiday gift shopping is stressful. Virtual agents can help last-minute shoppers or those facing choice paralysis by providing personalized recommendations. Retailers will also get a lot of customer calls and queries as shopping is expected to reach an all-time high this holiday season; what customers expect is immediacy and empathy. Chatbots can also inform customer service by not only informing customers about potential delays in shipment but also by proactively sending a gift coupon or an offer to compensate for a bad experience such as a wrong delivery. From generating content such as how-to guides for installation of electronics, to interfacing with customers based on a human agent’s step-by-step instructions, AI can take after-sales service levels a notch up. Further, with natural language processing (NLP), retailers can leverage sentiment analytics to analyze customer comments on social media and prevent irate customers from churning.
The interspersion of conversational AI and analytics has led to a new era of augmented analytics where executives across functions will be able to consume data and insights without having to navigate through a labyrinth of screens and systems. AI that can understand the context and intent of business questions can mine data and give conversational reports proactively or on demand. Picture this. You can simply ask questions and get answers along with automated visualization in seconds. For example: What’s the return rate on a specific category? How many customers have subscribed to newsletters? What is the most sold item this season? Which category has the highest conversion?