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Pervasive CommerceHow Product Intelligence is Enabling

Shopping Experiences Tailored for You

Pervasive CommerceHow Product Intelligence is Enabling Shopping Experiences Tailored for You

By the year 2020, the next generation of the Internet, connected devices, and machine learning technologies will transform the way we live. Every digital experience will be contextual and individually tailored to people’s needs and wants. Highly personalized experiences will be delivered everywhere, and the economic impact of these advancements will be staggering. Commerce, in particular how people buy and sell goods and services, will be revolutionized. Machine learning technologies that anticipate, guide, and help people decide will be a driving force in this evolution.

Indix aims to enable a critical part of this change by building the world’s largest Product Intelligence Platform. Product Intelligence is going to be the catalyst for the personal shopping experiences mentioned above. It will usher in the era of Pervasive Commerce, where shopping is pervasive and you are at the center. Every interaction with a consumer in the physical world or online will be an opportunity to sell goods and services. With access to Indix’s comprehensive catalog that provides product information in real time and at scale, businesses will be able to deliver the right product, to the right customer, at the right time, at the right place. Every time.

Momentum is Building

Online commerce has grown steadily since Amazon and eBay pioneered this movement almost two decades ago. First, people gained the ability to find and buy things on the Internet, accelerating a radical shift in how we seek, discover, and buy products. Then, Web 2.0 enabled an explosion of user-generated content through social media, blogs, reviews, and other community-oriented services, altering the way brands and retailers engage with and

market to consumers. Subsequent generations of the Internet will synthesize these advances and those to come to generate a new wave of rich, targeted experiences.

The next iteration of the Internet will create a harmonious confluence of people and context. Mass marketing will adopt context-driven personalization at a massive scale. Independent of the device being used, Web interactions will be tailored to each person’s preferences, browsing behavior, and intent, with customized context as the norm1.

An early sign of this can be seen in the current growth of social commerce. Whether it is Twitter or Facebook’s “Buy” button, or a social shopping site such as Wanelo, businesses are focusing on bringing products to consumers, and not the other way around.

A recent online retail forecast report from Forrester Research projects that online retail sales will grow 57 percent, from $263 billion in 2013 to an estimated $414 billion in 20182. While many physical stores are closing, companies are investing more money into digital strategies. For instance, while Staples had to close physical stores because of poor sales, its online growth was noteworthy and led to a logical redirection of investment toward Staples.com3.

Commerce is no longer destination-based. It is quickly becoming pervasive. Rather than have consumers visit physical stores, product offers are now presented to them on the devices that they use. Products are discoverable and purchasable on devices such as smartphones, tablets, and PCs. Two thirds of Americans now own smartphones,

Online retail sales will grow 57 percent, from $263 billion in 2013 to an estimated $414 billion in 20182

Commerce, in particular how people buy and sell goods and services, will be revolutionized.

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according to Nielsen’s recent Digital Consumer Report, and that number continues to grow4. A brand or retailer’s website isn’t the only place where product search, discovery, and purchase occurs. Online marketplaces, social media platforms, social shopping sites, blogs, and articles are adding to the channels that facilitate interaction with products. Soon, these devices will include wearables, interactive storefronts, and other technological advancements that transcend omni-channel to an infinite-channel world full of product-aware apps and websites.

But, as consumers share more personal data, they expect more customized shopping experiences. A Monetate survey states that 75 percent of consumers don’t mind

sharing personal information if they get a tailored and relevant experience5.

These factors illustrate the complex nature of the consumer journey. It is no longer defined by the want or desire for something, followed by going to a store to look for it, getting help from a store assistant, and completing the purchase. Consumer-centric commerce has replaced the bygone seller-centric era. Today, consumers expect the perfect product offering to be delivered to them intuitively, no matter where they are.

But, what is the perfect product offering? What are its defining elements? A perfect product offering is delivered to the right person, at the right time, at the right price, at the right place, through the right channel. Every time. Such an offering is perfected at the intersection of Customer Intelligence, Business Intelligence, and Product Intelligence. Companies must build a deep understanding of each:

• Customer Intelligence: browsing habits, buying habits, and social affinities.

• Business Intelligence: the company’s own business and their surrounding ecosystem.

• Product Intelligence: the company’s products, those of their competitors, and how both are presented in the marketplace.

Customer Intelligence and Business Intelligence have been an area of massive investment by merchants of all size. But, Product Intelligence is the new investment area – when all three forms of intelligence come together within a

Product-Aware Apps and Websites

Product awareness is the capability to access rich, deep, and comprehensive product information in real time from the Web, sensors, and smart wearable devices.

A perfect product offering is delivered to the right person, at the right time, at the right price, at the right place, through the right channel. Every time.

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single system, the “perfect product offer” can be realized. And this new wave is coming fast. In fact, by the end of 2016, IDC predicts, product intelligence will determine 80 percent of the top 10 ecommerce retailers’ pricing decisions6. By 2020, product intelligence will influence $3.7 trillion in U.S. retail sales, 18 percent of the GDP7.

The Future of Commerce

By 2020, personalized and enhanced shopping experiences will become a reality attainable by those with smart devices. Imagine the presence of a super-concierge attending to our product needs and wants. This concierge, an Ambient Shopping Assistant (ASHA), might bear a likeness to digital assistants used today, such as Siri and Cortana, but it will offer much more customized and intuitive services. Here’s a scenario that ASHA could enable:

You tell it: “It’s my friend Megan’s birthday tonight. What gift should I bring, and where can I find a good bottle of champagne on my way?” As your super-concierge, ASHA has access to your contacts, your calendar, your address, and other personal data. It also knows Megan’s address, her likes, dislikes, and other details from her social profile. ASHA will find the appropriate gift at the right price, get your approval on the purchase, and place the order on your behalf. Enhanced supply chain logistics will ensure that the gift is waiting on your doorstep by the time you return from work, and ASHA will map your trip, leaving you time to pick up a bottle of champagne from a store near Megan’s house. ASHA also might remind you that the cast-iron skillet that you were looking at on a cooking blog a few weeks ago is on sale at a store adjacent to the wine shop.

Such a system is based on product data science and machine learning. Over time, based on what the consumer chooses to share, ASHA will generate increasingly refined product offers. The system will have access to near infinite amounts of data and will be trained by, and learn from the user regularly for improved relevance.

The main challenges inhibiting this scenario are the access, accuracy, and security of consumer personal data—customer intelligence—and the lack of a universal product catalog that provides information at scale and in real time—product intelligence.

This scenario will be permission-based—people will get to opt in and out of services as they desire. Imagine the existence of a personal data bank. We trust banks to store our financial assets and then selectively grant permission to certain entities, such as our employer or our gym, to access our information and retrieve what they need, while we can add or revoke access with relative ease. Similarly, by 2020, there will be interoperable services that talk to each other and use consumer data in a transparent yet protected manner. Giving consumers absolute control over their information and empowering them to choose to grant access to different services will ease anxiety over the use of personal data. Issues of intrusion will diminish as there will be full disclosure about which services are chosen and how personal data is being used.

The other critical piece of this puzzle is product intelligence, the force multiplying technology foundation that enables businesses to deliver the right product, to the right customer, at the right price, at the right place. Every time. Currently, product information exists in fragments all over the Internet. This scattered, inconsistent information inhibits the development of product-aware applications at scale. Truly product-aware apps must have real-time access to product information—product intelligence—to help consumers make the most informed choice.

Ambient Shopping Assistant (ASHA), might bear a likeness to digital assistants used today.

Truly product-aware apps must have real-time access to product information.

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Deeper View of Product Intelligence

What does product intelligence encompass? At a high level, it puts product information into two categories—offers and catalog. Offers intelligence includes dynamic information related to the sale of a product—the stores at which it is sold, price history, promotions, channels, availability, and shipping. Catalog intelligence comprises relatively unchanging product information, such as brand, images, descriptions, specifications, attributes, tags, and facets.

We envision a product intelligence system as robust and powerful as GPS coordinates for a physical location. Like a fingerprint, each product in the world will have a unique identifier that surpasses the limitations of today’s UPC. All of the product information mentioned above would be accessible through this one, unique ID—think of it as a Product GPS.

At Indix, we are creating this Product GPS by building the world’s broadest and deepest product database. When every product in the world is assigned a unique ID, all of the rich information associated with it will sit in one database, and every service offering product information will access it from this one place, ensuring a consistent view to the end user, every time. So whether you are walking by a store or reading a blog at home, the information that you are served as a consumer will be precise and comprehensive.

What it all Means

Product intelligence will enable a wide range of capabilities for both consumers and businesses. It will provide easy access to all the offers and catalog data associated with a particular product, thereby empowering ASHA to serve context-relevant and personalized product information. What does this mean? Let’s return to the example of Megan’s birthday and see how Product Intelligence makes this happen.

Customer intelligence enables ASHA to understand and analyze Megan’s shopping history, browsing history, and social profiles. Say Megan mentions on social media that she is headed for a hiking trip to Mount Rainier. Her browsing history might reveal that she has been looking at hiking hats and that she has shown preference for a particular color. Catalog intelligence ensures that products are tagged with hundreds of relevant attributes, such as brand, size, color, material, type of hat (skull cap, beanie, rain hat), use (backpacking, cycling, camping, casual), and features (moisture-resistant, insect-repellent, quick-drying, earflaps). Offers intelligence ensures that you get the best deal for the product based on different parameters – the price of the product at different stores, promotions, availability, shipping information etc. By matching consumer preferences and interests with rich product data (product intelligence), ASHA will generate the most relevant and customized product offering.

In the big picture, this implies that never again will you see a Web ad that doesn’t meet your interests. Whether you are seeking a product or being presented with ads for one,

Categories of Product Intelligence

Offers intelligence includes dynamic information related to the sale of a product—the stores at which it is sold, price history, promotions, channels, availability, and shipping.

Catalog intelligence comprises relatively unchanging product information, such as brand, images, descriptions, specifications, attributes, tags, and facets.

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product data science and machine learning services are ushering in a seamless, delightful new era of shopping.

Netflix and Product Intelligence

One of the first companies to practice and implement product intelligence effectively is Netflix, owner of the broadest, deepest database of films and television shows in the world. Netflix not only built the database, but also made it actionable by tagging each piece of content with a vast library of attributes, resulting in the formation of 76,897 micro-genres8. Such a rich database enables Netflix to make personalized recommendations, and at the same time, it allows subscribers to look up movies using a combination of attributes.

Netflix epitomizes how combining customer, business, and product intelligence can be a game-changer. The company has transformed how people think about access to entertainment by putting power in the hands of the consumer. You can watch whatever you want, whenever you want, however it is convenient to you. Personalization is powered by learning algorithms. The more Netflix learns about you (customer intelligence), the better it gets at making movie recommendations (product intelligence), a practice that helps retain viewership.

Opportunity for Transformation

Netflix’s success in revolutionizing the field of home entertainment validates how other consumer-facing fields are ripe for change as well. Commerce companies must strive to achieve the same level of personalization, instant gratification, and innovation. Big data and machine learning will play a pivotal role in this transformation by helping to build solutions that scale.

Brands and retailers must become technology companies in the business of selling products. Technology is not just something that companies deploy. It powers what they offer and what defines them. Companies that don’t adapt will perish, just as Blockbuster did in the entertainment industry. By granting businesses access to real-time product information at scale, product intelligence will provide critical capability to brands and retailers in their quest to become technology leaders.

At Indix, we are building the world’s largest Product Intelligence Platform. With the application of patented machine learning algorithms and domain expertise, we collect, normalize, analyze, organize, and visualize the world’s product information. By building a universal

Is Netflix a sleeping ecommerce giant?

Is Netflix capable of venturing into full-blown ecommerce, for instance through shoppable video? It’s not too hard to imagine that with the press of a button a subscriber could save items to be bought later. Just as Amazon followed Netflix with a streaming entertainment service, will Netflix now compete with Amazon in reverse and become a channel for commerce?

Pervasive Commerce, where the experience of shopping is all about you.

Companies that don’t adapt will perish.

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product catalog, we are creating the world’s most comprehensive Product Intelligence Platform that will enable businesses to build product-aware applications, websites, and services, such as ASHA.

Today, Indix has more than 600 million products in its database. We are building a standardized and structured catalog with the application of product data science and machine learning algorithms. When our Product Intelligence Platform powers a consumer application, the perfect product offer can be presented to, or easily discovered by, the end user.

We are entering the age of Pervasive Commerce, where the experience of shopping is all about you, the consumer. By 2020, traditional advertising as we know it will be dead. If you don’t own a car, you will never see a commercial for car wax. Products finally will be delivered to the right person, at the right time, at the right price, at the right place. Every time.

Sources

1 www.wired.com/2014/09/e-commerce-to-web-3-0/2 www.internetretailer.com/2014/05/12/us-online-retail-sales-will-grow-57-20183 www.businessinsider.com/staples-strategy-to-improve-business-2014-34 mashable.com/2014/02/13/smartphone-us-adoption/5 content.monetate.com/h/i/12311823-mass-marketing-versus-personalization6 www.idc.com/getdoc.jsp?containerId=prUS252335147 www.idc.com/getdoc.jsp?containerId=2523278 www.theatlantic.com/technology/archive/2014/01/how-netflix-reverse-engineered-

hollywood/282679

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