Automating and Personalizing Using Data
Every year retailers adjust their strategy to strengthen their position in the market. The use of data is evermore becoming the center of this strategy. Data helps retail organizations to predict trends, identify opportunities and gain competitive advantage over their competitors. With real-time data, organizations can begin to predict consumer behavior and market trends before they actually happen.
In this blog we will discuss three data trends which are leading the retail industry:
- The development of automated and dynamic pricing models
- Data led personalized marketing and inventory management
- Predicting spend and forecasting demand
1. Automated and dynamic pricing models
To stay competitive, retailers need to ensure their pricing model is dynamic, reflecting the transitional market. Retailers must pay close attention across their full portfolio, particularly Key Value Items (KVIs). They are constantly balancing their pricing models, placing their KVIs next to their higher value products in order to drive sales and compensate for the low margin KVIs.
However, in order to manage and successfully maintain a dynamic pricing model, leading retail organizations are investing in data management to automate this process. Dynamic pricing models enable organizations to assure they are best placed in the market, maximizing sales and driving overall revenue. Dynamic pricing models also make suggestions on ideal costs which allows businesses to make better and more informed decisions within their marketplace, while minimizing manual administration costs.
The use of intelligent data solutions powered by artificial intelligence are crucial to retail organizations to maintain their competitive position. These tools allow organizations to not only produce dynamic pricing intelligence, but also calculate demand for individual items in a range and help create solutions for the organization's business goals, cycles and customer base.
2. Personalized Marketing
Personalized marketing is one of the most common uses of data in retail. Customers nowadays are choosing brands that they feel listen to them, understand them and focus on their specific wants and needs. That’s where personalization comes in. Personalized marketing is driving increased and repeat engagement and loyalty from customers over time.
Retailers are getting data from more sources than ever before, including mobile apps, online/in store point of sale systems (POS), surveys, browsing data, and more. But how do you manage that data, to create a complete picture across all platforms and ultimately, extract value from it? Trying to draw insights from a messy excel spreadsheet is challenging, costly and time consuming, resulting in important data being hidden away in silos. Data silos occur when businesses fail to centralize their data. In order to create more focussed marketing campaigns, optimize advertising efforts and deliver a greater brand experience, data must be centralized and transformed into one coherent language.
3. Inventory Management - Predict spending and forecast demand
Inventory management is a crucial part of the retail industry. Stock must be managed in a way to assure the correct quantities are ordered, at the right time. Without access to the correct data, retailers are making uninformed decisions. For example, without a holistic view from all platforms and locations of trends across seasons and specific product lines, stock may be over-ordered, negatively affecting working capital and incurring high inventory storage costs. This leads to further costly promotional activities to sell-through the excess inventory. Likewise, real-time insight to sales and successes can speed decision making to get the right products to consumers, when they want them.
A unified future for retail data
Having your data sources combined into one place, and translated into one language is crucial for the retail industry. Transforming and organizing retail inventory data allows retailers to enhance their inventory management, predict spend and forecast future demand. It removes the guesswork, enabling better decision making. Kleene picks up the data topic for you. We combine all data sources in one place, translate them into one language, and organize everything to make it easier for your teams to work with. Kleene does this at pace, smoothly and with future-proofed technology.
