Product Intelligence is the New Wave in Retail Analytics
The massive shift to ecommerce in 2020 has been met with increasing consumer demands. Coupled with this are increasing data protection laws online. How do retailers cope? The next evolution in retail analytics will be creating product-driven customer experiences online. Let's take a look at why this is the case, and how it can be done.
There are about 2.14 billion people who shop online. By 2040, 95% of all purchases ever are expected to be through ecommerce. There are more retailers in the market than ever, which means consumers can shop for whatever they want, anywhere, and from anyone. This massive growth and competition within retail comes coupled with ever-increasing data regulations.
More than this, consumer demands are changing. Shoppers want personalization, speed, and convenience. They seek products that are in line with their values, interests, and desires.
To cope with these growing trends, there is a new wave in retail analytics that:
- Analyzes product and contextual data rather than relying on shoppers’ personal data
- Generates actionable insights to personalize product messages in line with the psychology of the individual shopper
This new wave is called “product intelligence”. For retail analytics, this is key to staying on top of the customer-driven market. Product intelligence uses both of the above to cater to the growing demand of digital buyers, whilst at the same time using customer data in a transparent way.
Product-Centric vs. Customer-Centric
Product intelligence is the result of bringing product and customer-centricity together to gain actionable insights about how customers interact with your products.
It’s a necessary step into a not-so-distant future where products are personalized in relation to each individual webshop visitor.
So why is this necessary?
At the dawn of advertising, products were sold based on their unique selling points (USPs). Crayola, for example, sold their colored pencils as “waterproof”, “will not rub off”, and “waxy”. Fast forward fifty years later and Crayola ads now focus on what the product means to the customer. Crayola: a girl dreams of becoming a ballerina, or a boy dreams of becoming a detective.
In effect, this shift shows an evolution from product-centric to customer-centric. The reason for this switch happened as we became more aware of consumers and their psychology. Marketers realized that products are only half of the story. The other half is the person buying the product. When you sell products for what they represent to the person, this becomes a customer-centric approach.
Customer Data is Becoming Harder to Access
Furthermore, data regulations are becoming more rigorous. Google, for example, has recently gotten rid of cookies. The GDPR in Europe already creates protective barriers like cookie consent and sensitive data, and more stringent national legislation is pushing data protection to the forefront of policy-making (Inmoment). Read about how to cope with intelligent tracking prevention as an ecommerce store here.
81% of consumers make a purchase based on a “brand they trust” (Edelman Trust Barometer 2020), and companies that are notorious for data misuse are falling behind.
When it comes to product intelligence, the product data belongs to the retailer, and yet provides endless possibilities for segmentation and optimization. Product intelligence goes the extra mile by using product data to enhance the customer experience.
According to Acquia, 61% of customers feel that brands that are supposed to know them don’t, even at a basic level. Product intelligence personalizes products based on the individual and, in the long run, creates brand equity. It’s a feedback loop between the product and customer that hyper-targets campaigns, whilst giving customers a chance to control which products they want to see in the market.
Product Intelligence is the Future of Ecommerce and Retail
In this way, product intelligence completes your product information management (PIM) systems and customer data platforms (CDP) with rich data sets. It generates data and fuels this product-to-customer feedback loop.
For example, imagine you’re selling a running shoe. You have product labels that show the shoe’s attributes, e.g., “water-resistant”, “extra grip”, “cushioning”, “running cadence 80”. If your customers convert based on these product attributes, then you know to segment those customers into regular runners who seek quality in their products.
(A lot can be said about your customers in how they choose products: maybe they’ve answered a quiz wizard about their running cadence. Maybe they’ve been directed to your website via an ad about marathon running. In each case, the different qualities of a product will be relevant to different shoppers and should be highlighted accordingly. Understanding the differing needs of your customers starts by understanding the qualities of your products, and then making these visible in your product descriptions, or with product labels).
With this data, you can then deliver more relevant campaigns and communication to your specific segments. From these product attributes (and coupled with your other customer data points) you can infer a lot about who your customers are as people.
Product Intelligence Requires an Un-Siloed Approach
Product intelligence is the new way forward to customer-centricity. However, this requires an un-siloed approach so that everyone has access to the data and insights can be reused across the company. For ecommerce teams, product data should be made available in order for them to push a product’s qualities, optimize product descriptions, or recommend similar products for upselling.
For your merchandising teams, understanding what your customers love about your products will help develop future lines and how products are placed on-site. And marketing will leverage product intelligence to optimize segmentation, targeting, and overall campaign messages.
Breaking down departmental silos is something that ecommerce behemoths like Amazon and Zappos are already implementing, whilst always putting the customer first.
Conclusion: It’s Still All About Your Customers
Product intelligence bridges the gap between consumer psychology and data. It’s about unifying the two approaches of product and customer-centricity to stay ahead of your competition.
By promoting the product attributes that your shoppers are looking for, you will make it easier for them to find the products they want in the first place. Product intelligence is a customer-centric product experience that will pave the way forward for ecommerce and retail analytics. This is an important way retailers can stay competitive in a digital market, and relevant to a consumer that is shopping more and more online.