To meet customers’ retail needs, retailers must make a concerted effort to understand, and even anticipate, how they think and act. One way of doing this is to tap into the power of retail data and analytics. From predicting trends to forecasting demand for a product, Retail Analytics is invaluable for any retailer. It can even help you to optimise your pricing.
What is retail analytics?
The Collins English Dictionary defines Retail Analytics as “any information that allows retailers to make smarter decisions and manage their businesses more effectively”.
This information can include anything from your inventory levels to supply chain movement to sales figures or even your customers’ demands. If compiled correctly, the information acquired through the data will allow you as a retailer to make better decisions around your business.
Then there is the fact that Retail Analytics can help you identify who your best customers are, where they live, and even predict how they will be spending their money going forward. From a consumer point of view, access to that sort of information may sound unsettling. However, with this information, as a retailer, you can personalise the shopping experience, leading to happier, more satisfied customers.
It’s a win-win situation for both yourselves as a retailer and your customers. While they get what they want, where they want it and when they want it, your business can maximise sales and profit margin.
There is also the added boon of further entrenching any reputation that you may have as the go-to retailer for a product or products.
Why is retail analytics so important for retailers?
Considering the influence that data has had on businesses in general – it has revolutionised old-school industries and given birth to a new industry to name just two reasons – the impact it has had on the retail industry to date is vast. And it’s just the beginning.
In a space such as retail where competition is fierce, any possibility of a competitive edge should be welcomed with open arms. That is why Retail Analytics is so powerful. It allows you the opportunity to place yourself in the marketplace strategically.
It also helps you to understand the sales contribution of all categories and products in the business so that you can identify opportunity gaps to see what stock to discontinue or to add to the range. Then there is the units contribution, where you can see which categories, sub-categories, segments and/or SKU’s are performing in terms of volume.
Now, instead of making decisions based on your gut feel or customer intelligence that isn’t grounded in data, you’ll have the ability to anticipate what your customers need or want. This customer demand will, in turn, inform your assortment planning to ensure that the correct or most valued SKUs or items are listed and placed in an easy to find location.
As stated in a previous blog article, product assortment carries an enormous impact on your sales and gross margin. It can also be complicated and time-consuming. But with the help of Retail Analytics, your whole assortment planning process is streamlined, saving you time to focus on other parts of your business.
How can retail analytics be used to achieve better price points?
Besides giving you the ability to understand consumer behaviour so that you can adjust your business accordingly, Retail Analytics can also be used to help you to achieve better price points.
One way of doing that is by comparing all data sets that are available, which will give you a bigger picture view of product prices within the marketplace.
In understanding your price points, you will also know what your category role should be. Considering that shoppers are price sensitive, they will know if your pricing is competitive so you need to have the best prices.
Then there is the fact that with Big Data on your side, the uncertainty about pricing disappears. As a retailer, it will allow you to determine when to drop pricing, a point which Bernard Marr, author of books such as Big Data in Practice and Data Strategy makes in an article on Forbes.com.
“Prior to the age of analytics, most retailers would just reduce prices at the end of the buying season for a particular product line, when demand was almost gone.”
This ability to know what the shopper is looking for will allow you to understand the price elasticity of a product, which means you know which products can get a price increase and which should be regularly offered on promotion to sustain loyalty.
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Conclusion
The introduction of analytics has given any retailer the opportunity to become that much more competitive. And it’s not just you, the retailer, who will be happy. Your customer will be too.
