Since the past 4-5 years, we have seen a change in the shopping behavior of users, both online as well as offline. It has resulted from user’s reviews and recommendations about the products ranging from fashion to home to technology, all thanks to social websites like Facebook, Pinterest, Instagram and many other global as well as regional social sites. Social commerce is a term, coined by Yahoo in 2005, as a set of online shopping tools that take into account the user liking patterns, sharing reviews, information and advices on products, as per their usages, thus affecting the sales of those products.
There are two types of social commerce strategies — one is offsite where the e-retailer brings in the social angle from external social platforms, separate from their own websites, thus enhancing the sales and second is onsite social commerce platform where the website/platform uses its own channel to enhance sales based on content, context, and reviews etc. AI and ML Tech comes into play after these reviews and recommendations have been provided by the users and then placing the same in front of potential buyers for better decision making.
Artificial and machine learning technologies have been used by giants like Google, Microsoft, Facebook, and Apple for more than a decade to enhance their platforms for better user experience which can now be seen to be mandatory adaptation for most of the internet based businesses, not only as it shows better ROI, but also open countless doors for future digital opportunities.
Let’s take a look at how AI and deep learning are helpful across social commerce startups.
Finding relevant content or product faster
This is also perceived as personalization when a user logs on to the platform. There can be few questions/preferences asked and accordingly the landing page can be customized or if the same is skipped then based on the search keywords and time spent on the pages, recommendations can be proposed for the relevant products based on what other users have liked, shared, commented or purchased, who visited the same pages or searched for the same product.
Customer engagement
Through website and app based chatbots, armed with witty answers and fed with as much data as possible, customer engagement can become easy — customer queries can be resolved without deploying a forced sales approach. Automated “contact us” forms understanding the context of the dispute and routing them to the concerned department can save a lot of time and resources as well.
Reminders and Remarketing for re-engagement
Once a user has visited the platform, sending regular relevant product and content reminders/emails will get the users engaged with your platform and one can play with prices as well while sending the reminders. Be cautious to the frequency of these reminders to save you from spamming. Remarketing is widely used for the users to see branding ads on Facebook, Google etc. giants related to the pages visited on the social commerce platform which is also possible through deep learning algorithms.
Based on followings
Social commerce platforms focus on community building for its users to take informed and better decisions based on the user followings, followers, likes, shares, comments, reviews etc. about a particular content or product. Through deep learning, recommendations and push messages are kept in front of the users while browsing the platform which again results in better purchases.
Image Recognition and visual search
Facebook has invested heavily on image recognition for its tools to detect the faces and suggest tags while uploading or viewing an image. Image recognition is not new in AI, but there are still a lot of advancements that need to happen in the field. Image recognition uses machine learning on the basis of data, where the user can upload an image on a social commerce platform and similar suggestions of products can be presented based on the color, texture and patterns of the image uploaded.
Voice Recognition
With Amazon Echo and Google home assistants available in the market based on AI and ML for best suggestions converting speech to text format, many are betting big on speech recognition as a tool to help consumers get best out of their product. Recently Mark Zuckerberg’s year long hard work on Jarvis came into light with its product named “Jarvis” for controlling/connecting home appliances for regular updates and what not! The same way, social commerce startups can integrate voice recognition in their mobile apps for understating human behavior and showing results.
Tech juggernauts across the world are betting big on AI and ML technologies to shape the buyer’s market andinvestors as well are looking for startups based on these technologies for a better future and cutting edge results. With more than 3.5 billion online users in the world (approx. 48% penetration already), one can really expect to get into tapping endless possibilities by understanding user behavior and get into the business with artificial intelligence and machine learning implemented for time saving, accurate results and better decision for their users.
The author is Founder & CEO of Helpmebuild