Smart data tailors a new ‘customer-retailer’ relationship
In the era of growing digitalization, today’s customers are more empowered and connected than ever before. They anticipate seamless shopping experience across all channels that would reflect their unique personal preferences and interests. Today’s customer doesn’t have time to mess around and wants to buy anything anytime from any place with just a few mobile clicks. Modern customers are constantly online and are willing to access any information – anytime, anywhere.
Retailers are changing the ways they focus on their customers.
It’s crucial for retailers to continuously adapt how they understand and connect with their customers across all channels in order to provide real added value at the point-of-sale via existing and new distribution channels, relying on data-driven insights.
The new challenge is to really focus on the customers and to understand their needs and wishes – by knowing their preferred time for shopping, their brand preferences and favourite payment methods.
Smart Data comes into play
Retailers need to cluster the retail data sets along the customer journey. In order to ensure that the offer matches the demand and to increase the chances of the customers re-purchasing a product/service, retailers have to start analyzing customer segments and selecting relevant characteristics by offering customers their targeted promotional measures in terms of product availability, pricing strategy and dedicated loyalty and couponing programs, based on the data already collected before.
Hence, with an aim to successfully compete against harsh retail competition online and to provide a pleasant shopping experience, retailers should make use of the full potential of smart data.
How to attract more customers?
Retailers are doing great by offering different kinds of awards for purchases and by offering personalized discounts and recommendations to their customers. Even more, seamless shopping experience across all channels is completed by an easy-to-handle mobile payment system in the eyes of customers.
By doing this, retailers now can get answers to the following questions: “Where do our most profitable customers live?” “How much did they spend this month compared to the last month?” “What is the most likely item they will buy next, considering their history and preferences?” In such a way, a business can be more flexible and react quicker to the ever growing customer expectations.
So, what are the key advantages of smart data use in retail sector?
Customer analysis – it allows learning about what makes your clients convert from casual to regular, finding out what they really want as a reward for their loyalty and driving retention.
Inventory analysis – unutilized stocks are some of the most significant sources of waste for a company. Get all the data about inventory, best/worst performing products and plan for success by looking at trends.
Predictive models – in the light of constantly changing customer demands, you need to know what your customers are going to buy and in what quantities.
Price optimization – price is no longer the reason to choose a specific retailer, but dynamic optimization can make a difference if the displayed value is just a bit less than what you saw on the competitor’s website.
Marketing – looking at data provided by free platforms (Google Analytics or Facebook Insights) can give you an overview of your clients, their behaviours, and their preferences.
What’s the role of technology in all these transformations?
Technology helps extract and analyse data more effectively and assist with new product innovation and portfolio optimisation. Thus, retailers might benefit from automatically loading, integrating and augmenting data from their stores to create an up-to-date single view of customers. The process involves analysing everything from POS, CRM and loyalty card data, as well as inventory and consumer panel information.
When these retail data sets are coupled with analytics for price, promotions and assortment analysis, retailers get a better understanding of how they and their suppliers can best target shoppers. Better data analysis certainly means more effective targeting when spending money on promotions.
As a result, smart data will reveal what is working best in which store in which region and with which consumer segment. Hence, the businesses might be more sensitive to promotions in some areas than in others, for smart data allows brands and retailers to be sensitive to these differences and react accordingly.
Challenges of using smart data for retail
Despite the immense success of smart data use in retail, it’s still rather problematic to select the right metrics from the tons of information and to create a coherent narrative. In other words, it’s all about structuring all the available records in a unitary dashboard that can be subsequently used by non-technical specialists to answer daily questions about stock, distribution or pricing.
Apart from that, accuracy and cleanliness of data represent another challenge for the experts, for various sets or types of data extracted from various sources need to be transformed to be technically viable. Moreover, security remains a main issue when it comes to manipulating customer data that could include personal data (e.g., banking transactions). The systems aiming to use these sets to provide a personalized experience should use the latest advancements in encryption and data protection.
When a customer returns, it’s a real victory for a retailer. From now on, the customer’s actions can be analyzed in order to continue to target behaviour that will lead to a stronger customer-retailer relationship. Smart data thus takes data that has proven to be successful and feeds it back into the system in order to create more promotions, pricing, rewards, discounts, and ultimately loyalty.
Today’s retailers have to use smart data to focus on all aspects of their relationship to the customer. It’s no longer a simple act of buying - it’s about maintaining and sustaining at every point of contact, whether it is before, during, or after purchase.