5 Ways Retailers Increase Revenue With Location

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Automation is rapidly catching up with retailers, and the next year will be a key year for them in this direction. Radical optimization of store management is the only way that retailers can operate at a lower cost.

Over the past decade, retailers have been addressing the challenges and opportunities posed by the rapid adoption of smart mobile devices by consumers since the launch of the Apple iPhone in 2007. Today, tech-savvy consumers regularly shop digitally, beyond the traditional store. The new consumer behavior has led retailers to redesign their retail space to blend a digital and physical experience that is pleasing and relevant to consumers and that strengthens each retailer's brand.

While these changes are beneficial to consumers, they are at odds with the concept of "self-service" in the operating model of the 20th-century store. In order to serve consumers who start their purchases outside the store but finish them in the store or deliver them directly to the consumer, retailers have to bear new costs that cannot simply be reimbursed at high prices.

As the industry enters the new year, retailers face the challenge of rethinking how their operating processes and systems will support the new sales environment. This is where automation comes into retail.

A combination of IoT (Internet of Things), AI (Artificial Intelligence), ML (Machine Learning) and robotics will be used more often in distribution centers, order management systems, and in stores to perform a wide variety of tasks, from order picking to inventory management and cashier-less store management. In addition, retailers will increasingly use AI/ML "algorithmic" data analysis to automate decision making for routine operating processes.

Some analysts predict the automation of direct delivery of "last mile" orders - from flying drones to automatic vehicles. Although these technologies are being tested in the UK and the US, retailers have many opportunities to optimize processes in traditional stores to operate at higher speeds and at lower costs and to provide the level of service required by today's experienced in-store customers. 

The search behavior of users changes and their expectations grow 

Today's users need immediate answers in situations where they want to know, do, buy or go somewhere else. The concept of micro-moment has enabled marketers to obtain reliable, measurable, and relevant information about consumer behavior.

Analysis of consumer behavior and expectations has proven very useful to marketers. Many companies used the concept of micro-moment as the basis for a strategic plan to work with mobile technologies. This allowed marketers to highlight the most important moments in communication with users and to promptly respond to their requests. In addition, traditional models and approaches were re-evaluated: from determining the share of advertising impact and analysis of business results to ensuring the convenience and usefulness of the content. 

New behaviors and expectations 

Today's consumers are used to getting what they need, here and now. They take constant access to information in a way that is convenient for them for granted. The person always strives for more. It is obvious that the requirements for the volume of useful information, the level of personalization, and the speed of obtaining results will grow. 

Making informed decisions 

Remember the last time you used your phone to find information or make a decision. This could be something important, such as finding a family car or planning a trip. Or there could be something simpler: a choice of pens for a kitchen set, a search for folk bee stings or hiking socks.

People want to make informed decisions, and they are increasingly using phones to find the information they need. This is also clearly visible in the statistics. The number of mobile search queries with the word "best" has grown by 80% in the last two years. This is not only true for over-the-top solutions. People use phones to search for information on virtually any issue. Thus, over the past two years, the number of requests for toothpaste from mobile devices has increased by more than 80%, and requests containing the phrase "the best toothpaste" - by more than 100%. Prior to the advent of smartphones, the search for information required more effort from users. The process is now much simpler and faster, and on any issue, from the most important to almost insignificant, you can weigh the pros and cons and make an informed decision. 

Location accounting 

People expect digital content to be adapted specifically for them, including their location. A few years ago, it was supposed that such information was provided by users themselves. For example, in order to find a sushi restaurant nearby, the user had to specify a city or district or enter the word "nearby". Now it is expected that the system will collect all the necessary data on its own and offer suitable options simply on request "sushi".

And that's not all. Over the past year, smartphone users have become much more likely to buy goods on mobile sites and in applications that adapt the information to the location. People expect that offers will be picked up automatically on the basis of geodata. 

Prompt access to information 

Did you ever need to make a last-minute reservation at a restaurant? Or a hotel room? People are increasingly relying on mobile devices. Every day they shop at the last minute and make spontaneous decisions based on the information they get from their smartphones. Today, users are 50% more likely to buy immediately with a smartphone than they were a year ago.

Mobile technologies significantly expand the possibilities of users. People spend less time on preparations because the smartphone is always with them. And they expect companies to understand their needs and offer only what they really need. 


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Retailers benefit from a very dynamic and flexible response to changes in customer demand, location, and competitor activity. The potential for geodata is enormous as evidenced by the success of Amazon, Walmart, DNS-shop, and other major retailers.

Soon the market will change radically: those who can apply geodata correctly will win the race. If you don't do it now, in 3 years the struggle for the buyer will be lost.

The only difficulty is the availability of quality data. If the store does not have them, it is necessary to start collecting and processing them now, and it will be possible to return to the question of optimization in a year when there will be a sufficient amount of accumulated data.


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