An electronics store featured a TV on their website, offering a $100 discount to customers who made a purchase in the two-week period before the championship game. The promotion had been successful in previous years, but to the retailer’s disappointment, this time the TVs didn’t sell. A month later, after analyzing a sales report and researching the promotion, the retailer realized that a competitor had a similar offer that included free shipping.
Real time information matters, especially for retailers. Despite a heavy investment in both inventory and promotion, most of the TVs remained unsold, causing a jam up in the warehouse and tying up capital. The opportunity was lost, and the retailer was stuck looking for ways to get the TVs out of the warehouse.
If the retailer had real-time information on hand, they would have been aware that a competitor had a more compelling offer. They could have reacted, either by offering free shipping, bundling different offers with the TV to make it more attractive, or further lowering the price of the TV.
Here are other situations where real-time really matters:
Cost and Inventory Changes
Inventory changes can have different impacts on price. For merchandise that is nearing an expiration date, or a holiday item that will be worth much less after the holiday, real-time inventory data can help you set a reduced price to make sure you aren’t left holding unsellable merchandise.
On the other hand, if a product is selling fast, you want real-time inventory data to guide you on raising your prices. With demand peaking, if your available inventory is running low it may be the right time to raise prices.
Both these inventory scenarios only work when you have real time inventory available to you, to help you guide your prices.
You and your competitor both sell the same turkey fryer on the homepage of your ecommerce store. At the beginning of the week you were both selling it for a 10% discount, but as Thanksgiving got closer, your competitor reduced prices by another 15%.
With real-time information, you have a few options. First, you could match the discount. However, you can also make a decision to cancel the discount and feature another product. Alternatively, you can raise the price of your turkey fryer, and when the competitor sells out, you can go back to featuring your turkey fryer at a higher price.
Regardless of the strategy employed, it can only be employed if you have real-time retail information.
User Behavior Analytics
Every October, as you read through the Q3 sales reports, you notice surprising sales trends relating to some back to school items. However, by the time you read the report it’s too late to take advantage of the trend, and with the big holiday season just ahead, August and September sales simply aren’t that important.
By the time August comes around the following year, you’ve already forgotten about the trends, and don’t prepare for similar results. However, with real time sales retail information, you would be alerted to those trends in real time. Armed with information, you could use those trends to create more compelling offers, which would increase sales and profits.
Collecting Data in Real Time
Today’s dynamic pricing engines use artificial intelligence to scour the market and track trends, note prices, and see what products competitors are out of. Using that information would allow retailers to take advantage of opportunities, and turn real-time data into profitable business opportunities.