Data science is playing an increasingly bigger role in how businesses utilize technology in strategy, planning, and operations. Everyone is trying to collect data, analyze it and apply the intelligence learned into optimizing business activities.
One area where the value of data – particularly in predictive analytics – has been making its mark is in retail. This is a tough sector to be in, especially with brick and mortar taking a beating from e-commerce. With a record $3 billion in digital sales revenue, the most recent Black Friday sales event indicates that customers like to avoid the shopping rush, opting instead to order through web and their mobile devices.
These trends are prompting retailers, especially physical stores, to apply digital technologies in order to better compete against pure-play digital retailers. So-called online-to-offline or O2O endeavors can help bridge the gap between digital and traditional operations to ensure that even offline businesses can gain benefits from online applications.
Data and analytics promise deeper insights that these businesses can use to make better-informed decisions and possibly even steer their business toward more profitable directions.
For brick and mortar retailers, a key challenge in using analytics is data collection. Unlike with an online store setup, where analytics platforms can be easily deployed, physical stores have to use smart beacons and sensors, such as those offered by Euclid, in order to gather data on customer behavior. For smaller players that do not have the option of deploying sensors across their premises, a good alternative that can help better manage data would be to digitize the retail workflow. This can be done through retail management applications like Vend, which extend the point-of-sale (POS) system to also function as an analytics tool.
With these options now available, more businesses can leverage the benefits of data gathering and analytics in improving their own retail activities.
Here are four reasons why predictive customer analytics, and using platforms that leverage this will benefit your business:
1 – Manage Stock and Supply Better
One of the silent killers of retail is the fact that stocks sit idle in warehouses and backrooms for too long. The traditional solution to determining stocks and inventory used to be historical sales data, although this can only do so much in terms of determining future movement of the goods.
Predictive analytics enhances this by creating accurate demand forecasts so that businesses can manage inventory better. For example, Vend integrates inventory management with your POS, which readily provides a detailed look into inventory data — which products sell more and when.
With the rise of omni-channel approaches to doing e-commerce and retail, it is even more critical to keep integrated inventories to eliminate the need to track separate stocks for physical and online stores. Such systems can even automatically generate stock orders when inventory dips, based on customizable conditions so that you don’t run out. This way, businesses can optimize the flow of products in and out of warehouses and stockrooms.
2 – Handle Work and Workers More Efficiently
Operations is another aspect where analytics can help run a retail business. Even with products from inventory that are in high demand, you run the risk of inefficiencies or even failure if your store isn’t operated well.
Take staffing, for example. Do you have enough employees to service the ebb and flow of customers on a seasonal basis? Face-to-face interactions continue to be important in building lasting relationships with loyal customers. Based on your sales data, the proper use of analytics will allow you to go over the exact days and times when business tends to pick up.
Based on this, you can anticipate the headcount you need at any given time, and you can configure worker schedule accordingly. This way, you only pay for the hours that are profitable. By tagging sales facilitated by particular staff members, analytics can also track who among them are performing well.
3 – Respond to Customer Needs as They Happen
Beyond products, service and after-sales are critical parts of the value chain where analytics can help shine a light on opportunities. The rise in popularity of smart devices can be quite disruptive.
One area of opportunity here is the Internet-of-Things (IoT). Connected devices can provide information if products or their parts would be needing replacement or servicing. Such data can guide retailers to anticipate demand and even act proactively by initiating contact to customers.
Another advanced application of big data for larger ventures is geo-targeting. This can include factoring in online searches from the immediate vicinity of stores so that they can stock up on needed products just at the time there is demand. These can even enable better collaboration among suppliers and manufacturers and retailers on how sharing their data and insights can help everyone do better business.
4 – Deliver Enhanced Customer Experiences
Delivering excellent customer experience counts, and this is where personalization can be a game changer. Analytics can track preferences and habits of particular customers through their individual sales and interaction data. While others may find tracking individual customer behavior and preferences intrusive, using the information to delight customers through personal interactions make customers appreciate such personalized gestures.
This goes beyond the usual customer loyalty programs, wherein customers simply earn points from their purchases. A more data-driven approach here would be to turn such customer interactions into more proactive and personal ways to engage by making suggestions for products that they would actually consider. This can both in either online or offline approaches. Knowing what your customer wants before they even know it is one of the major benefits of data.
On the business end, this is a great way to cross-sell, upsell or, at the very least, secure repeat business. Customers will get better satisfaction with your brand’s ability to anticipate their needs and wants.
Forrester actually calls it a shift toward the “age of the customer,” with 2017 becoming the so-called “Year of Action,” because data is expected to have an increasing impact on how businesses engage with customers.
Essentially: A Better Bottom Line
There are many more aspects of a business where predictive analytics can be applied. Smaller ventures can benefit from using analytics to make more focused and anchored decisions. Thanks to technology, these are cost-efficient ways to get the benefits of big data without having to make substantial investments. Using data to streamline your product lines and optimize operations can increase efficiency and sales. Essentially, all of these lead to a better bottom line.
Oren Rofman is a senior technology writer. He’s particularly interested in information technology, big data and the cloud.
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