Artificial intelligence (AI) systems have been developing quickly in the past period. One of the most prominent sectors that benefit from this development is e-commerce, specifically marketing. In fact, according to many e-marketing experts, the coming few years will see an integrated AI system replacing traditional marketing as we know it today.
AI applications have become a core part in the e-commerce sector. Companies that want to stay in competition must grasp a better understanding of AI applications and use them across their businesses.
Given the importance of AI-based systems, e-commerce companies have initiated working on tools to introduce AI in their strategies. This means that marketing campaigns will become more efficient, less costly, and highly profitable.
A report by Payfort listed six ways AI can help your e-commerce marketing.
Making programmatic advertising even smarter
The world of digital advertising has seen a massive expansion over the last few years, and the major reason for this growth is data, data, data. Companies are now offering advertisers a limitless combination of behaviours, interests, and consumer profiles to make every advertising dollar count.
All this data comes with its own challenges; however, companies today often struggle to identify the marketing strategies that are right for their business. This is where AI can pick up the slack. Today, there are several platforms that can simplify paid marketing campaigns, identify top performing campaigns, and automate campaign management without any human intervention.
Smarter messenger bots
Pretty much every messaging platform on the market is experimenting with messenger bots. Several social platforms have their own messenger bots that let users engage with a brand using natural language on a comfortable platform.
These bots are quickly starting to take over traditional customer service roles, such as sales and customer support. For businesses that are tight on capital, integrating a messenger bot can be a great way to add a personal touch and engage with you customers at a low cost.
Voice AI
In addition to messenger bots on their favourite social networks, customers are quickly getting accustomed to using personal assistants in their homes. These new tools allow users to communicate with web services using only their voice.
The technology can be integrated into smartphones or smart speakers designed specifically for voice communication, and just as with website optimisation, expect businesses to jump on the trend of voice optimisation in the coming years.
Automated writing bots
Believe it or not, a large portion of the content uploaded every day to blogs and news sites is written by AI. Companies, such as the Associated Press (AP) and Reuters, have been using automated writing bots successfully for the last several years.
Many of these news-writing bots are starting to be adapted to writing descriptions for e-commerce stores and are proving to be very successful. When compared with their human counterparts, the AI writing bots are identical grammatically and considerably cheaper.
Improving decisions with auto traffic analysis
Widely used analytics platforms are also getting in on the AI action and are now providing businesses with AI tools to analyse website traffic. These tools automatically send in-depth reports that highlight performance and even suggest ways to improve traffic on your website.
One company has even taken this idea further by recently integrating an AI powered, text-based query feature that allows users to get accurate answers about their site directly from an analytics platform. For example, a user can ask, “what is the total number of visits to the accessories page of my e-commerce over the last week?” and it will provide the requested data and show a graph of the exact timeframe.
Increasing conversions autonomously
Big companies like the Wall Street Journal and Pandora are already using AI-powered software to increase conversions and improve the sales funnels on their platforms. Their software recognises distinct patterns in user behaviour and collects data on what behaviour leads to conversions.
The AI then analyses the data and makes minor alterations to the website layout and evaluates whether conversions improve or get worse. Over time, the AI learns what alterations are most effective and applies those optimisations site wide.
