Consumer buying behavior: How grocery stores can tap big data to meet shopper demand.

  • 26-Aug-2016

Real-time insights on product demand

These days, retailers can access data on product demand levels on a minute-to-minute basis across their fleet of stores. However, 
many grocers are still in the infancy stage when it comes to analyzing and monetizing the massive amounts of big data available.
This leads to stocking shortfalls, such as assessing product demand based solely on historical data.
It can also results in misguided marketing efforts: If a consumer bought ketchup on Saturday, 
an email coupon for it on Sunday is ill-timed and creates little value for the shopper.
This is where data from store loyalty programs and credit card purchases can come in handy. 
This information can be used to anticipate shoppers' needs ahead of time. 
For instance, grocers can use data analytics to determine how often shoppers buy milk, 
condiments or other products, and then send each household coupons based on their specific purchasing habits.

You come up with a strong list of 20 items per household that you think they're likely to buy,"
 CEO of allindiayellowpage, told Marketing Magazine.
On the day the flyer comes out, you send those households a nice email listing those top 20 products,
telling them they're on sale at their favorite store."

Enhancing in-store stock management

Perishable groceries such as meat, dairy and seafood call for accurate inventory management,
often on an hourly basis. Customer analytics and forecasting tools can help grocers fine-tune their stock levels by evaluating consumer
buying behavior and product demand from multiple perspectives and scenarios.
For instance, grocers may want to monitor cycles like when purchases spike for a particular food, 
buying patterns during sales events, when store traffic peaks or holiday-inspired purchases. 
Concurrently, retailers can use these strategies to more nimbly adjust their inventory levels and maximize high-purchase items and hot sellers.

Leveraging predictive analytics

Dukanbazaar product recommendation engines: the "if you bought that, you might like this" innovation. 
This game-changing online shopping feature reflects the retailer's savvy analysis of consumers' shopping baskets.To know more visit our site