For a few years now, the use of Artificial Intelligence and Machine Learning in online Commerce has steadily increased. The early adopters and retail’s big players have primarily led in this area due to the high cost. 2018 could be the year this starts to change. Machine Learning is becoming more affordable and widely obtainable for businesses outside of the Commerce giants and this shift will influence the future of commerce search.
At the recent Coveo Impact 2018 conference, there was an almost palpable sense that the future of Search must also include Artificial Intelligence (AI) and Machine Learning (ML). These are closely related subjects that are gaining wider acceptance in a number of areas, including search context, personalization and marketing technology. There are so many exciting developments set to be released to the market soon, including the latest development from Coveo. I’m really looking forward to seeing how these take shape and specifically impact the future of Commerce Search.
Impact of AI for Merchandisers and Product Content Managers
Business Tools that are enhanced with Artificial Intelligence can help Commerce teams (merchandisers, product line managers) make the vast amounts of data within their platform work for them thereby converting it into a valuable resource. The task of optimizing search in Commerce scenarios is normally a manual one. For example – building synonym dictionaries normally involves an analysis of lengthy search logs and search result reports to identify the search terms. AI-enhanced Business Tools can surface these terms without lengthy analysis and suggest exactly which synonym dictionary they should be added to. The merchandisers and product line managers see the immediate benefit, and the site user ends up seeing much better search results with fewer “no results” pages.
AI-Infused Search and Recommendations
Consumers’ expectation of search is changing in the Commerce space. The importance of the search bar has shifted. It is now more important to present the shopper with the right product at the right time, regardless of how the search takes place. This concept of transactional experience is blending search functionality into a contextual presentation. Search solutions such as Coveo are taking this change to heart and positioning their platform to leverage AI and ML. Search platforms are no longer just utilized to crawl content and present relevant search results. They are positioned to be a critical part of the enterprise which can consume data from multiple sources and provide recommendations and decisioning tools.
Businesses can utilize AI and ML to make search even better by utilizing it to power personalized and contextual recommendations for the shopper. Based on site awareness, before a shopper starts typing a single letter into the search bar, they can be presented with search recommendations or create a widget in the presentation which offers personalized recommendations based on prior activity. As the level of experience expectation from shoppers increases, businesses will be forced to adapt and will have to leverage more AI and ML to respond.
As search platforms adapt their mindset and offerings to reflect “more than search,” we will start to see the impact across the enterprise. Search technologies will be leverage to mine and process data from various sources. AI and ML will be the engine that drives processing and interpretation of data. We are already seeing some of the impacts in this space with the advances in automated bots within Commerce storefronts. These bots derive intelligence based on the data that has been harvested and processed within search platforms. Soon the same changes will be coming to the AR/VR and IoT applications for Commerce scenarios. I am excited about the future of Commerce Search as we start to see the advanced application of AI and ML within the traditional search space.