Product intelligence bridges the gap between consumer psychology and data because it helps to unites product and customer-centricity to stay ahead of the competition.
FREMONT, CA: Nearly 2.14 billion people do online shopping. By 2040, ecommerce is expected to account for 95 percent of all purchases. There are many more retailers on the market than ever before, which means consumers can shop for anything they want, whenever they want, and from whoever they want. Ever-increasing data regulations are accompanying this rapid expansion and competition in retail.
Consumer preferences are shifting. They prefer customization, speed, and convenience and are looking for products that align with their values, interests, and desires.
This new trend is known as "product intelligence." This is critical for retail analytics to stay ahead of the customer-driven market. Product intelligence makes use of the above to meet the increasing demands of digital buyers while also making transparent use of customer data.
Product-Centric vs. Customer-Centric
Product intelligence is the result of combining product and customer-centricity to gain actionable insights into how customers interact with the products.
It's a necessary step toward a not-too-distant future in which products are personalized for each webshop visitor.
Customer Data is Becoming Harder to Access
In addition, data regulations are becoming more stringent. Google, for example, recently removed cookies. The GDPR has already established safeguards such as cookie consent and sensitive data, and stricter national legislation pushes data protection to the frontline of policymaking.
When it is about product intelligence, the retailer owns the product data, but it offers limitless opportunities for segmentation and optimization. In addition, product intelligence goes above and beyond by utilizing product data to improve the customer experience.
Product Intelligence is the ecommerce and retail Future
In such methods, product intelligence adds valuable data sets to the product information management (PIM) systems and customer data platforms (CDP). It generates data, which feeds into the product-to-customer feedback loop.
Users can then use this data to provide more relevant campaigns and communication to the particular parts. In addition, they can learn a lot about the customers' personalities from these product attributes (when combined with other customer data points).
Product Intelligence Requires an Un-Siloed Approach
The new path to customer-centricity is through product intelligence. This necessitates a decentralized approach so that everyone has access to the data and insights that can be shared across the organization. Product data must be made available to ecommerce teams to promote a product's qualities, optimize product descriptions, or suggest similar products for upselling.
Realizing what the customers love about the products will help the merchandising teams develop future lines and how products are placed on-site.
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