Not unlike the way in which the internet swept the world over in the 1980s, artificial intelligence seems to be the next big thing, soon to take over several spheres of our lives. Among others, it has already made significant advances in the field of retail business. Where implemented, AI has made shopping experiences more personalised and efficient, from helping people find the ideal product for their needs to checking and maintaining stocks behind the scenes.
It’s rather interesting to understand how AI is used to help owners of retail stores provide a better experience to their customers while also increasing revenue. AI basically involves taking a set of big data along a specific line of inquiry and running it through algorithms to develop a model. This model can provide the business owner with information that would otherwise not be obvious, regarding the business itself, the customers, inventory, or any other useful field, and help him/her identify scopes for improvement.
However, rudimentary chatbots may prove to be ineffectual and irritating for customers to deal with. According to a 2018 Logmein Consumer survey, 46% of customers still rely on the familiarity of telephonic conversations to interact with brands.
Dynamic pricing has been an invaluable strategy for scores of retail companies looking to manipulate prices based on demand and ultimately drive sales and build profits. This is done by tracking trends and analysing data patterns using machine learning algorithms in order to get the optimum price.
McKinsey statistics indicate that dynamic pricing strategies, if properly refined, can result in a sales growth of 2-5% and a margin growth of 5-10%.
Another hot topic lately has been around Personalisation. Personalised product recommendations and offers promise us higher conversion rates and CTRs, because naturally shoppers will be more interested to click and buy products relevant to their tastes. According to a study conducted by BCG and commissioned by Google, customers increasingly prefer a shopping experience that’s easy and fast and that helps them make purchase decisions.
But developing a unique experience for every customer at every step of the way can be very costly. Rather, the goal for leaders should be to use technology to personalise critical touch points in a way that best drives value for the customer and retailer.
Artificial Intelligence has been touted as a messiah for companies, as it aims to streamline marketing efforts based on consumer demographics and ultimately improve sales statistics. However, the fact remains that although an AI system can complement a human sales team, it is yet to reach the level of becoming a worthy substitute to them. Also, AI systems are still mostly proprietary, and only major franchises with a large budget for technology can make effective use of them.
AI in online retail is still in its early stages, and it cannot yet understand the intricacies of a company or come up with creative sales tactics and make client-related decisions.
Logistical complications aside, AI is indeed a boon for online retailers, especially considering the doors that could be opened by predictive analysis and AI-aided forecasting. Automating and optimising repetitive tasks, accelerating troubleshooting operations, and assistance in guided sales are other areas where AI has proven itself to be invaluable. A resource with such potential cannot stay untapped for very long. A Gartner report predicted that by 2020, AI would be used to improve some aspect of sales in 30% of B2B companies, and its use will only increase from there.
Amazon & ASOS are investing heavily in AI
Amazon has tapped into German talent for their AI research. Their Berlin office has around 800 employees, most of whom are working on innovations in the Amazon marketplace. They are automating the process of translating product descriptions and trying to predict the demand for certain products. For its Prime members, Amazon is trying to employ AI algorithms to correlate the content one sees with the products one purchases, further tailoring the website to the customer’s needs.
ASOS is investing heavily in voice recognition, image recognition and virtual assistants to influence consumer behaviour. Their Fit Assistant uses machine learning to provide personalised recommendations while selecting outfits. They also possess a visual search feature which matches the photos of the user with clothes being sold online.
In the future, virtual racks, mirrors and trial rooms may revolutionise retail with the product selection. Chatbots will efficiently increase engagement with customers and provide optimised support for all kinds of problems. Watching this space will be quite interesting in the coming years, as one can expect the technology to spread rapidly and become accessible to even smaller retailers. By helping the company provide customers with prompt and personalised attention, AI will help improve brand loyalty.