According to The Demand Institute, omnichannel consumers, or the so-called economically active consumers who have access to the internet and manage free cash, are responsible for one third of all consumer spending in the world, and by 2025 this figure will exceed 50%. Changing the habits and demands of the buyer with a smartphone in hand is one of the forces that adjusts the strategies of retailers and manufacturers of consumer goods.
Over the next five years, $6 trillion will be spent on the purchase of Internet of Things technologies (according to Forbes), and 10 million self-driving cars will be assembled (according to Business Insider).
Among all the relevant trends, four will have the most noticeable impact on consumer markets in the next five years: accelerating the penetration of the existing technological infrastructure (internet, smartphones), the development of artificial intelligence based on big data, machine learning, and innovation in the forms of payment.
Accelerating the penetration of the existing infrastructure sets the stage for technology development in the consumer sector. Today, the Internet covers 47% of the world’s population, and just three years ago, this figure was at 40%. The LTE network covers almost 4 billion people (53% of the global population), and the prices for mobile internet, as well as for smartphones, are declining in all regions of the world, especially in less developed countries with growing consumer potential.
The UK’s leading online retailer, Shop Direct, uses the power of artificial intelligence to select the most effective frequency and channel of communication with the consumer, as well as predictive modeling of when and for what reasons a particular person will stop contacting that store. Tesco also relies on the analysis of a huge array of data about its customers. It studies customer behavior before visiting the point of sale of the network and the influence of this factor on the choice of specific products. Moreover, the insights received are available to all Tesco units in the world.
Another area of application for AI by retailers and manufacturers is marketing analytics. Already today, experts are increasingly using autonomous virtual analytics. For example, the Wizer platform (one of the startups funded by the Nielsen Innovate — Forbes venture capital fund) is able to provide an answer to any marketer’s question in 48 hours, analyzing both the company’s own data and external sources. Another example of service capabilities is the use of artificial intelligence in assessing the effectiveness of sports sponsorship. With the help of algorithms, the system independently detects brands entering the television broadcast field, adjusting the values in accordance with the screen from which the content is consumed (television transmission is perceived differently than the online broadcast on Facebook). Thus, sponsors get real-time data in real time, how much more efficient it is to place a logo on a player’s t-shirt compared to a banner on the field.
Machine learning will also be optimizing human labor. For example, when researching the purchase history of individual households within the framework of consumer panels, it helps analyze checks faster and in much larger volumes than if this work was done manually. Over time, the machine learns and becomes able to identify the name of the store, its address, the list of purchased items and other information from the check with a minimum error.
In some states, a non-cash form of payment already prevails over cash. The growing penetration of smartphones will turn these devices into universal payment tools. On the other hand, the concept of stores also has its effect on the development of forms of payment, where customers leave the point of sale bypassing the cash register, and information on purchased products is read out automatically. This approach also has significant chances to turn into a sustainable business model when finalizing the technical side.
The Ubex project applies all of the technologies that retailers need in their strive to better reach customers and does it through the use of programmatic algorithms, which are more efficient and effective than any other form of advertising. With the help of its machine learning and consumer analysis tools, Ubex is determined to become the next generation of reliable advertising instruments that retailers will be turning to in their search for customers.