The retail industry has undergone many changes over the years. E-commerce stores have drawn a lot of focus; retailers have leaned towards inbound marketing; social media has become a crucial part of a retail store’s consumer analysis; however, there is one thing that has not really changed. The retail industry is customer-centric – it is dependent on the habitual patterns of the customers. Hence, understanding consumers has always been and will always be the key to building a successful and sustainable business. The story of Target, one of the largest American retail corporations, will establish this fact.
Target and the expectant mothers
Back in 2002 Target started a marketing drive that has become a phenomenon of sorts. Their marketing team had analyzed customer data to discover that new parents are more likely to buy everything from one place, and they are also very loyal customers. A lot of retailers had similar insights and they tracked publicly available birth records to find out and target new parents. Target took a different path. They dived deep into purchase data to find out what expectant mothers and fathers buy. People buying things like maternity clothes and prenatal vitamins were identified. The theory was that if they could get hold of customers in their third trimester, they would be able to turn them into long term loyal buyers.
This theory worked wonders and Target started sending coupons for baby products to expectant mothers. And just so their data collection methods do not creep the customers out – because pregnancy is a pretty personal issue – they started putting those ads alongside ads for random products.
Where does machine learning come in?
What Target did in 2002 was nothing short of brilliant. The entire programme was based on human brilliance and the analytical prowess of the marketers. As USA’s 8th largest retail corporation, Target could afford all that. Machine learning democratizes the same strategy. Every enterprise today has large data assets. Machine learning makes it possible to use computers to find patterns in data. While it is not possible to replace human analysts in terms of developing data strategies and implementing machine learning algorithms, AI based solutions can be used to lift a lot of burden off the shoulders of the knowledge workers. Machine learning has effectively revolutionized marketing strategy. And retailers around the world are reaping its benefits.
The benefits of machine learning enjoyed by retailers
Automation and AI augmented decision making has changed many industries. Retailers have enjoyed their unique set of benefits.
SKU assortment optimization
SKU stands for stock-keeping units. These are alphanumeric codes attached to a certain type of product to internally keep track of inventory. This is a major part of inventory management. Assorting the SKU is an important and time-consuming task required for optimizing local inventories based on consumer metrics.
Machine learning algorithms can be trained to factor in customer details, purchase history and other features to optimize SKU assortment, thus freeing up a lot of knowledge workers.
As more and more retailers move to online mediums, product recommendations keep growing in importance. The automated product recommendations found on Amazon are pretty accurate and similar systems are adopted by major retail corporations around the world.
With major strides in natural language processing it is now possible to assess customer sentiments from reviews, social media content, and forum discussions. This assists product recommendations, marketing campaigns, and sales drives.
The fierce competition in the retail industry dictates that the product prices be optimized to create an edge over the rivals. Machine learning helps retailers factor in a number of different metrics to achieve optimal pricing for products.
It takes only one mistake to wrought a disaster when it comes to outbound marketing. Putting the right ads on the right screens at the right time is of the essence. Doing this at a large scale is an even bigger challenge. Machine learning algorithms can be used to segment large consumer bases depending on data. Marketing campaigns can then be targeted for specific consumer belts. This includes optimizing offers, composing emails, etc.
Also Read: How Machine Learning Will Shape the Future?
These are just some of the many benefits of machine learning in the retail industry. It can really work as a trump card for retail players to form a competitive edge. The growing dependence on machine learning has also created a sizable demand for personnel with machine learning training. People with machine learning skills are, therefore, highly sought after.