Shoppers’ eager anticipation of Black Friday and Cyber Monday (BFCM) deals for big purchases has become an annual ritual. Not long ago, most of the Christmas shopping was done in physical stores, malls and supermarkets. But with the rapid boom of e-commerce, things have changed drastically.
BFCM has already set a new milestone for online shopping in 2020, with a 22% increase (YoY), equivalent to $9 billion. And despite the reopening of physical stores, 2021 seems to have been no different when it comes to online shopping. Seventy-four percent of shoppers expect to shop online this year, according to a survey by Publicis Sapient.
A survey by the website Black Friday suggests that 52% of customers are willing to take advantage of special offers and discounts on this day. In addition, it is predicted that internet purchases on Cyber Monday will increase by 61% this year.
AI can be groundbreaking during the BFCM
Retail businesses are experiencing a strong digital transformation, especially after the pandemic-induced lockdowns. Machine learning (ML) based on big data can help companies predict demand and personalize services by using artificial intelligence (AI).
As an e-commerce business, whatsapp france numéro you can benefit from propensity models that help predict consumer behavior based on the data you have about past purchases. Since ML engines are built on artificial neural networks and can mimic the learning process in the human brain, they achieve higher and higher levels of accuracy as their use increases.
AI can also help estimate the number of products and inventory you need to have “on hand” to account for upselling and cross-selling. In addition, it allows you to efficiently plan and manage pricing, logistics and distribution during BCFM selling.
With the why behind using AI, it’s time to find out how you can leverage this BFCM’s AI for ecommerce success. Check out these smart ways to use AI and outrun the competition.
Personalized recommendations
Online stores witness a 220% increase in traffic on Black Friday, according to data from Adthena. One way to make the most of this is to use AI that optimizes conversion. This is where recommendation systems pay off.
Recommendation algorithms developed by social alternatives: convert traffic faster Amazon have redefined the e-commerce market, as almost every online store now uses them. Many e-commerce companies are increasingly using data from various third-party resources to estimate what a customer will buy next based on their recent purchases.
Product personalization is possible when you know what your customers have recently purchased. For example, if your customer bought a new smartphone during the Black Friday sale, use AI to offer an extended warranty and screen protection plan under the “usually bought together” suggestions. This way, you can use AI to both upsell and cross-sell products through product suggestions.
AI-powered e-commerce tools Like Dialog can deliver personalized product recommendations along with tailored messaging. Its #Recommender automatically displays related product suggestions on the product page, collection pages, aero leads homepage.
Ultimately, you benefit from analyzing the purchasing behavior of your customers who keep coming back to your store. Machine learning tools can help you predict your customers’ repurchase habits and preferences.
Moreover, if you use proper data labeling techniques and high-quality annotations, the AI model can easily learn them and complete the tasks properly. This will help you provide a more personalized experience to your customers by leveraging the right data for remarketing.