eCommerce & Merchandising

Boosting Online Retail Sales with Artificial Intelligence

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Globally, top internet players have captured 50% of the eCommerce marketplace. The “secret” contributing to their growth is digital intelligence from millions of customer interactions and transactions.

The Digital consumerization has fundamentally changed consumer behaviors across the globe:

  • There are 2.5 billion active Facebook, Twitter and YouTube accounts that are being constantly used by consumers to share their views and feedback on the numerous numbers of brands they interact every day.
  • The top two influencers for any buying decisions are friend’s posts and pins on social networks.
  • Every day, we create 2.5 quintillion bytes of data and 90% of world’s data generated over the last two years, out of which 80% of such data is invisible to the business.

For example, Wal-Mart alone generates 2.5 peta bytes of data every hour for every one million customer interactions.

Today’s consumers are highly instrumented and socially connected – 65% of online shoppers spend 15+ minutes comparing products on shopping engines. Per eMarketer forecast, total worldwide retail sales across all channels will reach nearly $28 trillion by 2019. Worldwide B2C e-commerce sales reached $1.7 trillion in 2015, and it is estimated to reach $2.35 trillion by 2018. Mobile commerce will jump from $204B in 2014 to $626B in 2018, representing nearly half of e-commerce by 2018. This growth is mainly fueled by sales in China, India, the US and developing countries in the Middle East and Africa. One of the key segments of the commerce growth is millennials. The convenience that technology provides is the key for millennials. They have grown comfortable with a world that delivers instant results and gratification and expect it in every sliver of their lives.

While convenience is key, speed is paramount; 83% of millennials are more likely to make impulse purchases on payday or while shopping online than any other age group. Today, 72% of the millennials research online before purchasing in a store. At the same time, research shows 70% of the consumers have stopped doing business with a brand following a poor customer experience irrespective of the touchpoints they interact with the brand.

So the impact of data and channel proliferation is huge for retailers today. It’s next to impossible for any traditional merchandising and replenishment systems to analyze such a huge volume of unstructured data, or even identify hidden trends and product attributes dynamically and real-time. Only an artificial intelligence driven system like IBM Watson can help to correlate between structured and unstructured data, tell what brands or products to order and when to discount or replenish them. It can analyze consumer data to learn which colors or materials customers in a specific region or product category are buying. This insight will help marketers to have fewer markdowns or discounting, increasing overall profit. These insights could help brands be first to market with styles that are likely to become mainstream trends in short term or medium term. Even designers, merchandisers and buyers could all use this artificial intelligence based insight to predict what customers want to wear, before they even know themselves.

The research shows that personalized recommendations can increase conversion rates by up to 5.5 times. The AI based solution can help significantly to personalize offerings. For example, AI based solutions can be used by eCommerce players, where the shopper describes the dress of their dreams and in seconds, the (AI powered) search engine in the eCommerce site tracks down the closest match. Even eCommerce players can use AI powered chat bots that guides shoppers online to decide their gifts or products as per their need instead searching through thousands of products.

For example, 1-800-Flowers used IBM Watson-powered digital gift concierge uses cognitive capabilities to tailor product suggestions for shoppers. Dubbed as “GWYN” (Gifts When You Need), the concierge will engage consumers in conversation on the company’s desktop and mobile web sites. Shoppers, rather than browse the company’s inventory in search of the right bouquet or gift basket, will be able to tell GWYN what they are looking for, then select and order the product from inside the conversational interface. Similarly North Face uses IBM Watson as an online recommendation engine, a “personal shopper” that let’s the customers describe their needs and the tool quickly provides the exact product they desire.

So the biggest competitive differentiators for retailers today will be their customer data—be it inside or outside their firewall. The secret to faster growth and profitability lies in how soon retailers adopt cognitive and artificial-intelligence-based marketing, and efficient commerce and supply chain solutions to unleash the hidden business insights from their data.

To learn more how other retailers and consumer product companies are leveraging cognitive solutions, I would recommend you attend IBM World of Watson 2016 at the Mandalay Bay hotel in Las Vegas, October 24­—27, 2016. You can also connect me through my twitter id @pk_mohapatra for updates.

Worldwide Product Marketing Lead, Watson Commerce Insights

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