Meet Mandy, a hyper-connected consumer who expects a seamless shopping experience every time she shops. Mandy loves online shopping, but for her day-to-day grocery needs, she still visits her local supermarket.
In the town where Mandy lives, she has a choice between three different grocery stores, all in different areas, and even though there is a grocery store right around the corner from Mandy's home, she drives all the way to the other side of town to visit one specific store.
You see, this store has shifted from being a product-centric store that focuses on the products it brings to the market, to a consumer-centric organisation that rather focuses on providing solutions to local shoppers and consumers. Mandy knows that if she drives all the way to this store, she will find exactly what she is looking for, and her needs will be met.
This store has a thorough understanding of the type of consumer that walks through their doors. So what exactly does this store do differently? The store that won Mandy over probably took the below into account during their assortment planning process:
- Location: Is the store in a busy city or a quieter town? Is it a tourist area? Is it close to a school or is it close to a university? This will have an impact on the needs and wants of local shoppers and consumers.
- Demographic factors: Some of the demographic factors that will also have an influence include income, ethnicity, age, number and age of dependents etc
- Internal POS data: By analysing internal sales data, stores can see which products are popular and which ones are really just using up space for no reason.
- External Market Data: External market data is used to spot products that are performing well in the market but aren't included in their assortments. Poor performing products are then replaced with the more popular products as identified by the external market data.
Mandy's store targets assortments more intelligently. This allows the right assortment and the right inventory to be placed where consumers are most likely to buy. This approach helps retailers create optimised localised assortments, resulting in lower costs, increased sales, and an improved in-store experience for shoppers.
Approaching assortment planning in this way may sound like a major challenge when you look at each store individually, but leading retailers "cluster" their stores into a number of groups and manage the whole process using assortment planning software. Each group will have stores with similarities including demographics and buying patterns. Assortment plans are then developed for each cluster.
Conclusion
Mandy left the store with everything she needed feeling fully satisfied. She even made a few impulse purchases. To her, her shopping experience felt like a break from her busy life having a full-time job and managing her family. In her eyes, this grocery store "gets" her.
