Column: How brands, etailers can leverage AI, ML to optimise festive sales
Diwali is one of the biggest festivals in India and apart from the rituals and traditions associated with it, shopping, either to decorate homes or to get gifts for loved ones, sends people into a frenzy of sorts during this period. But for consumers to buy, brands must sell what appeals to them.
The festive season, which generally sees a 40% jump in consumer traffic, is amongst the most competitive yet lucrative times for retailers to put themselves out there and claim their glory. Online retail has surely eased the stress of having to wait in line and drive around to places, but the challenge of being visible amidst the clutter still remains. As highlighted by Flipkart’s recent association with Zee TV to create QR-based interactive ads for television, retailers must bring their A-game this season in order to stand out.
For most, artificial intelligence (AI) is proving to be just the ingredient they need to augment existing roles and processes.
With so many variables at play, brands are increasingly turning to AI to keep track of consumer behavior, personalize their offerings, and significantly reduce human error. According to a report by Salesforce, in 2018, buyers that engaged with AI-driven product recommendations had a 26% higher average order value compared to consumers who didn’t. Given that the Diwali season is when shoppers are already willing to spend more, using AI can help retailers maximize their revenues, cut down operational costs and greatly improve customer retention for the future.
Let us look into how they can achieve this:
Elevating consumer engagement
AI-backed systems are ‘smart’ and once programmed with the relevant information, can learn independently with every new piece of data they process. The resulting impact is two-fold – retailers have access to more detailed, granular insights with time, and customers have a more personalized and hence, enhanced buying experience. Of all the options available, chatbots have emerged as a top choice for retailers around the world as the first point of contact for customers, thus reimagining multifaceted brand representatives. As per a report by Gartner, AI is likely to manage 85% of customer-facing interactions by 2020.
Powered by machine learning (ML), chatbots are available 24x7 and can communicate with customers in a human-like manner via chat. Based on what they are programmed for, they can answer various brand and product-related questions, record feedback, and present relevant offers and recommendations. These are personalized based on the way a particular customer interacts with the bot and can be done for thousands of people at a time, making it all the more useful in the lead-up to the festive season.
They can be used with the most popular messaging platforms such as Facebook, WhatsApp and Kik, making them even more accessible to customers who tend to use these platforms daily anyway. For instance, Levi’s has created a bot used to help users find a pair of jeans which is perfect for them, by eliminating the need to browse through several options or going to a physical store. The bot is deployed via Facebook Messenger and Levi’s website, and asks users a few questions such as style, fit and wash. Based on the user’s chat answers, it filters down the jeans to present a single pair that accurately meets the consumer’s requirements.
Effective targeting through automated insights
AI has the power to deliver real-time insights and recommendations not only for customers but for brands in their planning processes. Through machine learning and predictive analytics, brands can map customer preferences and behavior from their first browsing session to the completion of a purchase and post-purchase follow-ups.
According to a report by Forbes, AI-backed approaches for demand projection can reduce errors in forecasting by close to 50%.
By studying several data points, AI can identify dominant and recurring patterns and help retailers to present offers, discounts and promotions that are tailor-made for various consumer segments. These are categorized based on how likely it is for a particular set of customers to make a purchase, thereby targeting each consumer at the right time and via the right channel.
This is why you may have noticed that when you search for a product on Amazon, even if you don’t buy it, its ads begin popping up on your Instagram and Facebook feeds, prompting you to make a purchase or continue looking for what you want.
Using historical data to enhance present strategies
To enhance the current year’s sales strategies, retailers must take into account the activities and factors that showed promising results in the previous year – from promotions and offers to ads that appealed to most customers and clicks that led to positive conversions.
Using AI makes it easier not only to process a large amount of data that is presented here, but to compare several data points and unearth crucial insights in an instant. This is something that is beyond the capabilities of even experienced sales professionals, given the complexity. With the information garnered, retailers can realign their strategies to eliminate the redundant bits and only use what is most likely to appeal to their target audiences for their present plan.
At any given time, businesses in the retail space are dealing with thousands of customer-centric data points, be it purchases, queries, feedback or website traffic. These increase manifold during the Diwali season, along with other variables that the festive season brings with it.
By strategically employing AI tools and systems, retailers can effectively gather and utilize valuable information from each data-point in real-time. Through this, they can lead, as well as be with, every customer throughout the purchase cycle as well as provide them with personalized incentives and higher engagement. This leads to greater customer satisfaction, positive sales conversions and higher retention for the festive season and beyond.
Suhale Kapoor is co-founder and executive vice president of Absolutdata, a San Francisco based marketing analytics firm that offers and AI and ML based solutions and services.