Automation has been the X-factor behind crucial business processes for about 91% of global organizations. A recent survey suggests that 93% of companies believe automation forms the fulcrum of their digital transformation initiatives. That being said, over 73% companies have been entirely satisfied with the business benefits reaped from Robotic Process Automation (RPA). With several senior executives shedding light on implementing automation technologies, we are witnessing a surge in Chief Automation Officers and automation committees. Over the years, robotic process automation has been implemented only in processes involving unstructured data such as finance, human resources, and other back-office operations.
But with the introduction of artificial intelligence and machine learning, marketing teams are leveraging cognitive automation to digitize their marketing service chain by automating processes that involve voluminous data as well. Retail marketers can overcome several challenges in RPA such as automating mainstream processes, lack of executive buy-in, unrealistic goals, missed ROI, infrastructure constraints, and much more. As marketers feel the need to innovate ahead of the curve, cognitive automation drives marketing strategies to derive best-in-class results.
1. Launching New Products
A retail provider’s best bet depends hugely on introducing new product categories and merchandise options to the stores to attract a larger scale of customers and retain existing ones. However, there is more to it than just picking up the product and placing it in the aisles. The introduction of a new product in a store involves higher investment costs and building close relations between R&D, manufacturing, and marketing. While product roll-outs are created, there are several criteria to be considered such as geographic and demographic variables.
Cognitive automation can be very trustworthy in this respect. By ensuring fruitful collaboration between departments, cognitive automation promises to enhance decision making by automating the process and making product launches more effective. With the help of real-time sales data, retailers have the luxury of adjusting pricing, inventory, and production based on customer demands.
2. Trade Promotions
Regardless of the size and scale of the firm, marketing and promotions are a huge cost today. For a CPG firm, trade promotions are an integral part of marketing as it involves a lot of data gathering and strategies to increase demand for products at the retail level. The best example of trade promotion is the concept of rebate management. In order to offer discounts, the retailers will have to keep asking themselves, “What’s enough to attract the customer, but at the same time stay within the threshold?”
The use of artificial intelligence and machine learning will negate the entire process of creating manual data and over-reliance of spreadsheet data. Cognitive automation creates real-time data that automatically translates to visual insights while factoring in exceptions and variables. Eventually, marketers can come up with unique offers and schemes to constantly entice the customers.
3. Customer Engagement and Service
CMO’s today want to engage more with their customers for obvious reasons. Marketing professionals make the best use of available data to improve the accuracy and target a real audience to gain relevance of the content they prepare.
The best scenario is the use of a software bot at an industry event to quickly browse the Salesforce application of an organization and determine the account owner based on a spreadsheet provided at the venue.
The other important example is the use of chatbots to serve customers better. Chatbots allow the organizations to engage with the customers 24/7, while also cutting costs on the manual customer support.
Success Story of a Fashion Store
The fashion store employs a part-time associate in the fashion store’s casual merchandise section. The store is virtually run by cognitive automation, allowing the associate to trade his shifts whenever he wants to go to the university or any other errands he has to run. Due to the automation technology in place, the fashion store rarely needs a person at the store at all times. However, this part-time associate loves working in the store for his keen interest in merchandise. Although, his work includes manual tasks like stocking and picking for online orders, his workload is very light. Due to the sensors deployed in the shelves in each aisle, the items are automatically taken away by smart carts.
Cognitive automation allows the associate to spend most of his time interacting with customers, educating them on new arrivals and latest fashion statements. In case the customer is unable to find the desired merchandise, he will be able to pinpoint the exact location with the help of cognitive automation based on the customer’s shopping habits.
Meanwhile, the store manager is planning a huge promotional event that involves significant changes to the range of items on display along with launching new products in the men’s apparel area. However, there is no major effort going into this due to the artificial intelligence tools in the store. Any change in the inventory and product placement is automatically detected by the bots. The store manager only devotes time on real-time situations when her phone is alerted on a promotion that’s not working as good as the other stores. This allows her to focus more on service improvements and tweaking an offer’s presentation to boost sales.
Although, the store of the future is still in its early stages, retail leaders must start practicing cognitive automation too serve customers better especially in the post-pandemic world. Marketing professionals must think more creatively in today’s hyper-competitive business world to stand out from the crowd. Our advice would be to demand a prototype or a proof-of-concept based on your organization’s requirements before initiating an intelligent automation project.