Profit margins are known to be slim in the retail sector. So, companies must be keenly aware of customers’ demands or jeopardize sending their business to the tech-savvy competition. Retailers can lean on data analytics to communicate efficiently with customers via new channels. Rather than sending customers spam, retailers can send targeted marketing messages based on specific purchasing habits or interests. Store remodels can benefit from data indicating locations that customers visit most frequently so that customers keep coming back.
AI can source more in-depth information from more digital source materials. AI and the Internet of Things (IoT) are the forces behind the next evolution of data insights, ranging from advancements in inventory assessment and evaluation and video content analysis to targeted marketing based on consumer location.
It is more critical today than ever for retailers to communicate with their customers and develop customized experiences to keep them loyal.
Are data analytics essential to the retail industry?
Today’s consumer expects more. They also tend to be short on patience. Customers want to communicate with retailers using their preferred platforms, including apps, chat, text, and voice calls. They also expect communication to go smoothly regardless of which platform they select.
For retailers, offering consumers their pick of communication channels also means acquiring data points that number in the billions. Big data analytics and AI can distill all those data points into practical intelligence. In short, data analytics combined with AI eliminates the need for estimates on the operations side of the retail industry.
The retail data analytics glossary
AI analytics can leverage generative AI and big data to ascertain challenges and their underlying cause before suggesting solutions. AI analytics is among the most cutting-edge forms of data analytics.
Diagnostic analytics can review data from various sources, such as customer reviews, financial data, and payment transaction devices, allowing retailers to identify business issues and what caused them.
Descriptive analytics can analyze historical data using statistics to identify patterns, relationships, and operational changes. Descriptive analytics can help interpret changes in sales and inventory.
Predictive analytics can help predict future outlooks like sales forecasts so that retailers can plan for inventory changes and time promotions in response to anticipated customer demand.
Can data analytics give retailers more customer insight?
Customers love complimentary Wi-Fi. If free Wi-Fi access means answering a simple question or two, they’re generally willing to participate. A grocery store might ask which of three options is the customer’s favorite dish for Thanksgiving dinner. On subsequent store visits during the holiday season, the customer might be asked if they prefer pumpkin, apple, or cherry pie and if they identify as the head of household. Collectively, all data points will become part of a consumer profile.
Other communication channels, such as apps and e-mail, are vital to better understanding customers. Both platforms can also give retailers visibility into in-store customer locations and spending habits. Additional data can be gleaned from IoT devices like sensors and cameras. Cameras are most commonly a security tool; however, they can also indicate areas of a store that most attract customers via heat maps. Location beacons can also gauge consumer interest by measuring the length of time their device is in-network.
Another benefit of beaconing is delivering customized promotions directly to the consumer’s device, using past purchases to inform the offer. So, a shopper who often buys cookies could receive a discounted offer via text while in the snack aisle.
Learn more: Enhance retail customer analytics with geospatial intelligence marketing technology
How can retailers access data analytics relevant to customer purchasing habits?
An analytics and location engine (ALE) can easily provide retailers with data from consumer mobile devices near or accessing their in-store Wi-Fi network. Simply put, this AI tool can provide an open rate on messages sent by the retailer. The newest AI technology can also communicate suggestions to marketing teams that could improve open rates. This data is also employed by predictive analytics to estimate open rates for future promotions.
These technology tools allow retailers to create customer profiles based on metrics such as how often they visit or their average spending per visit. Retailers could potentially identify a customer who habitually spends $1,000 during each visit or who shopped multiple times in a week but not again for several months.
This technology can arm retailers with valuable insights that have future applications. For instance, location data shows that the dress section of a women’s clothing boutique is attracting a lot of foot traffic. That information could be used to draw parallels to a sizable new dress display or a prominently placed dress display in the front of the store.
Actionable data analytics give retailers insights into why customers are interested in your business, why they keep coming to the store, and their buying habits.
What are the possible drawbacks that retailers should be aware of?
Consumers will readily provide brief snapshots of personal data in exchange for a seamless Wi-Fi connection with a single authentication. But most customers aren’t willing to answer more than two questions for Wi-Fi access. Developing an accurate customer profile will take time as the data accumulates. Along with the power to create customer profiles, AI can also suggest personalized promotions based on the customer’s past purchases.
Retailers who do not invest in AI run the risk of lagging behind competition that is already accessing the technology.
Learn more: AI technology amplifies IT efficiency and customer experience
How OnX can design solutions specifically for retailers and their consumers
OnX has a long history of guiding clients through various iterations of different technologies. Today, customers are turning to us to assist with one of the most cutting-edge technology tools to date: AI. The team at OnX can put your retail organization on the right track and help determine which tech investments will most benefit your business.
The primary objective is to deliver consumer loyalty. AI, IoT, Wi-Fi, and data analytics are essential for gaining deeper customer insights. IoT and Wi-Fi are necessary for gathering channel data. Data analytics produced by AI configures the collected data to make recommendations that can strengthen your business.
Contact an OnX AI professional to learn how your retail business can keep in lockstep with the latest developments in AI.