The crisis caused by Covid-19 has also engulfed the retail world already challenged by significant changes such as the increase in online sales and the shift to mobile.
In a short time, the pandemic has amplified the gap between retail leaders and those in delay with digital transformation. Indeed, the latter have tried to embark on new strategies to survive in this new reorganization.
Think of how many people do not yet have a eCommerce or an omnichannel approach to offer a better customer experience to their customers.
Naturally, these needs will continue to have a significant fallout in the coming years, which is why the decisions of those in retail will have to be made even faster.
To generate value, those working in this sector will need to leverage new tools and business models to increase efficiency and anticipate sudden changes in the future as well.
Retailing will undoubtedly be increasingly digital, shaped by the adoption of better tools that will help make important and timely decisions, which is why today we want to talk to you about Artificial Intelligence and Machine Learning (AI/ML).
What can they offer those working in the retail world? These tools, for some as yet little known, can improve user engagement, offer personalized experiencesand foster better conversions, as we'll explain below.
In the past decade, we have witnessed an increasing use of Artificial Intelligence and Machine Learning in retail.
The use of these solutions has enabled increasingly efficient data management andexponential advances in computing power.
Core functionality to transform simple data into useful and predictive information for retail businesses, with a significant return on investment (ROI).
Retailers who adopt Artificial Intelligence and Machine Learning to solve their most critical and persistent business problems will continue to reap benefits, particularly when it comes to forecasting.
In comparison with traditional approaches these investments offerrepeated value over time. Why? They help to address in an agile way such vital aspects for retailers as optimization of merchandising and assortment, product lifecycle management, logistics, and many other processes.
In the next article we will delve into the new initiative launched by Google these days with the Product Discovery Solutions for Retail.
A suite of services created to improve eCommerce capabilities and help those in the industry deliver personalized experiences.
Product Discovery Solutions for Retail in fact combines Artificial Intelligence algorithms and Cloud Search for Retail that leverages Google technology to enhance retailers' product search tools.
"As the shift to online continues, smarter and more personalized shopping experiences will be key to winning the competition," said Carrie Tharp, VP retail and consumer at Google Cloud.
"To meet the needs of the industry, retail is in desperate need of agile operating models, powered by cloud infrastructure and technologies such as Artificial Intelligence and Machine Learning (AI / ML). We are proud to partner with retailers around the world and bring forward Product Discovery offerings to help them succeed."
But let's take a step back. What is Artificial Intelligence? It is the development of a system capable of performing human-like tasks and adapting to information received.
Machine Learning is an analytical method that automates the construction of analytical models. Using data, it autonomously provides useful models for making time-performing decisions with minimal human intervention.
The predictions can be diverse, ranging from the simple ones like "What is the product in front of the check out camera?" or "How many team members should I have in the distribution center on Thursday morning?" to the more complex and forward-looking "How many of these clothes should I have in Store X next October?"
Artificial Intelligence and Machine Learning can provide more accurate answers and those answers will improve over time.
More data and the "formation" of system logic will, in fact, offer progressively detailed returns with increasingly effective forecasts.
This opens up a new range of opportunities for all retailers who are continually looking for useful forecasts to better serve their customers and adopt more sustainable and profitable ways.
Even if you have a well-structured IT department, you will know that there are many investments you need to comply with in order to develop a solution with your team that is always up-to-date, secure, and performant.
Google is on the cutting edge and is also able to offer Artificial Intelligence and Machine Learning with its solutions, helping solve the most difficult problems and suggesting compelling opportunities even for those in retail.
power2Cloud, as a Google Cloud Partner in Italy, can provide you with the right support and insights to start using Google infrastructure in your business. A technology that serves multinational corporations as well as medium or small businesses, so it is flexible and adaptable to everyone's needs.
Retailers today must cultivate more profitable relationships with customers in order to retain them. To do so, they need to invest in and strengthen theiromnichannel experience, developing customized products and promotional suggestions.
They need to create new dynamic demand models that can use all signals coming from the market for better demand forecasting.
How can they do this? Using Artificial Intelligence and Machine Learning, they can perform many necessary tasks that are difficult for humans, especially if they are repetitive or require speed.
The data speaks for itself, companies using Artificial Intelligence and Machine Learning can drive 2x data-driven decisions, 5x faster decision making, and 3x faster execution.
Google's goal is to help make Artificial Intelligence and Machine Learning accessible for Retail in three key ways:
Pre-built solutions
Google is pursuing retail-specific solutions across the value chain to solve specific cases. With Recommendations AI for example, it is able to provide highly personalized product recommendations at scale.
Building Blocks
Google's Cloud AI Building Blocks enables developers to easily use Artificial Intelligence in existing applications or allows them to build new ones across a broad spectrum of use cases with or without knowledge of ML.
There are two types of building blocks: AutoMl for custom models and API for pre-formed models. You can use them individually or in combination depending on the use case.
AI platform
If you have the data science and ML knowledge, you can leverage Google's robust AI platform to build your applications and meet the
unique needs of your business.
In the meantime, what are you waiting for? Share your challenges with the power2Cloud team.